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Identification and characterization of
aryl hydrocarbon receptor (AHR) as a suppressor
of non-small-cell lung cancer metastasis
Inaugural-Dissertation
zur
Erlangung des Doktorgrades
Dr. rer. nat.
der Fakultät für Biologie
an der Universität Duisburg-Essen
vorgelegt von
Silke Nothdurft
aus Aschaffenburg
Oktober 2019
Die der vorliegenden Arbeit zugrunde liegenden Experimente wurden im Labor für
Molekulare Onkologie der Inneren Klinik (Tumorforschung) am Universitätsklinikum
Essen durchgeführt.
1. Gutachter: Prof. Dr. med. Martin Schuler
2. Gutachter: Prof. Dr. rer. nat. Markus Kaiser
3. Gutachter: Prof. Dr. med. Guido Reifenberger
Vorsitzender des Prüfungsausschusses: Prof. Dr. rer. nat. Ralf Küppers
Tag der mündlichen Prüfung: 23.03.2020
Diese Dissertation wird via DuEPublico, dem Dokumenten- und Publikationsserver derUniversität Duisburg-Essen, zur Verfügung gestellt und liegt auch als Print-Version vor.
DOI:URN:
10.17185/duepublico/71562urn:nbn:de:hbz:464-20210817-104321-6
Alle Rechte vorbehalten.
3
Table of contents
A part of the results in this thesis have been included
in a manuscript to be submitted for publication.
4
Table of contents
TABLE OF CONTENTS
Table of contents ........................................................................................................... 4
1 Abstract ...................................................................................................................... 8
1.1 English .................................................................................................................. 8
1.2 German ................................................................................................................. 9
2 Introduction ............................................................................................................. 11
2.1 Lung cancer: clinical features and treatment options .......................................... 11
2.1.1 Staging and survival rates ...................................................................... 11
2.1.2 Current treatment modalities .................................................................. 12
2.2 Factors governing cancer metastasis and the role of the epithelial-mesenchymal
transition (EMT) ......................................................................................................... 16
2.2.1 Transitions between epithelial and mesenchymal phenotypes (EMT/MET)
............................................................................................................... 19
2.2.2 Emerging roles of the microenvironment in cancer metastasis .............. 22
2.2.3 Metabolic dependencies and reprogramming ......................................... 23
2.3 Aryl hydrocarbon receptor: a sensor of xenobiotics and its potential role in tumor
progression ................................................................................................................ 24
3 Aim of the study ...................................................................................................... 25
4 Methods .................................................................................................................... 26
4.1 Cell Biology Methods .......................................................................................... 26
4.1.1 Cell culture ............................................................................................. 26
4.1.2 Freezing and thawing of cells ................................................................. 26
4.1.3 Spheroid formation assay ....................................................................... 26
4.2 Generation of stable transgenic cell models ....................................................... 26
4.2.1 Generation of lentiviral and retroviral particles ....................................... 26
4.2.2 Lentiviral and retroviral transduction of lung adenocarcinoma cell lines . 27
4.2.3 Small hairpin ribonucleic acid (shRNA)-mediated knockdown ................ 27
4.2.4 Reintroduction of shRNA-resistant AHR into AHR knockdown cell lines 28
4.3 siRNA mediated knockdown ............................................................................... 30
4.4 Proliferation assays ............................................................................................. 30
5
Table of contents
4.5 Cell competition assay ........................................................................................ 30
4.6 Transwell migration invasion assay..................................................................... 31
4.7 T-HUVEC adhesion assay .................................................................................. 31
4.8 Biochemical methods .......................................................................................... 31
4.8.1 Preparation of whole cell extracts ........................................................... 31
4.8.2 Measurement of protein concentrations ................................................. 32
4.8.3 SDS-PAGE, protein transfer and staining............................................... 32
4.8.4 Gelatine zymography ............................................................................. 33
4.9 Molecular Biology Methods ................................................................................. 33
4.9.1 Plasmid isolation from bacterial cultures ................................................ 33
4.9.2 Transformation of competent bacteria .................................................... 33
4.9.3 Site-directed mutagenesis ...................................................................... 33
4.9.4 Agarose gel electrophoresis and gel extraction ...................................... 34
4.9.5 Restriction digest .................................................................................... 34
4.9.6 RNA isolation and cDNA synthesis ........................................................ 34
4.9.7 Quantitative real-time PCR (qRT-PCR) .................................................. 35
4.10 Flow cytometry .................................................................................................. 35
4.11 RNA-Sequencing .............................................................................................. 36
4.12 Gene set enrichment analysis (GSEA) ............................................................. 36
4.13 In vivo experiments ........................................................................................... 36
4.13.1 Orthotopic lung xenografts ..................................................................... 36
4.13.2 In vivo and ex vivo bioluminescence imaging ......................................... 37
4.13.3 In vivo shRNA screen using orthotopic lung cancer model..................... 37
4.13.4 In vivo stress assay ................................................................................ 38
4.14 Statistics ........................................................................................................... 38
5 Results ..................................................................................................................... 39
5.1 Unbiased shRNA screen in an orthotopic mouse model of lung cancer reveals
potential metastasis genes ........................................................................................ 39
5.2 Suppression of endogenous AHR increases metastatic potential of H1975 cells
in vitro ........................................................................................................................ 41
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Table of contents
5.3 Reconstitution of AHR expression by introduction of shAHR-resistant AHR in
H1975 AHR-knockdown cells partially reverses the pro-metastatic phenotype ......... 44
5.4 Depletion of AHR favors metastatic spread in vivo ............................................. 47
5.5 RNA sequencing experiment identifies candidate targets of AHR involved in
stress responses and metastasis .............................................................................. 49
5.5.1 AHR activation and expression negatively correlates with genes
associated with matrix remodeling and EMT .................................................... 54
5.5.2 AHR activation regulates cellular stress responses in H1975 ................ 56
5.5.3 ASNS and ATF4 are confirmed AHR targets in colorectal cancer cells .. 59
5.6 AHR is involved in metabolic reprogramming ..................................................... 60
5.7 In vivo stress assay ............................................................................................. 66
6 Discussion ............................................................................................................... 70
6.1 AHR as a suppressor of lung cancer metastasis ................................................ 70
6.2 Mechanistic insights to AHR-regulated metastatic pathways .............................. 72
6.3 AHR-regulated pathways as a target in anti-metastatic therapy of lung cancer .. 78
6.4 Conclusion and outlook ....................................................................................... 80
7 References ............................................................................................................... 81
8 Appendix ................................................................................................................ 101
8.1 Supplementary figures ...................................................................................... 101
8.2 Materials and reagents ...................................................................................... 102
8.2.1 Eukaryotic cell lines .............................................................................. 102
8.2.2 Plasmids and primers ........................................................................... 104
8.2.3 Antibodies ............................................................................................. 106
8.2.4 Commercial kits .................................................................................... 106
8.2.5 Chemicals ............................................................................................. 107
8.2.6 Media, reagents and commercial buffers ............................................. 108
8.2.7 Buffers and solutions ............................................................................ 109
8.2.8 Restriction enzymes and buffers .......................................................... 111
8.2.9 Consumables ....................................................................................... 111
8.2.10 Technical equipment ............................................................................ 112
8.2.11 Software ............................................................................................... 113
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Table of contents
8.3 List of figures ..................................................................................................... 113
8.4 List of tables ...................................................................................................... 115
8.5 List of abbreviations .......................................................................................... 116
9 Acknowledgements ............................................................................................... 120
10 Curriculum Vitae .................................................................................................... 122
11 Declarations ........................................................................................................... 124
8
Abstract
1 ABSTRACT
1.1 English
Lung cancer is the leading cause of cancer-related deaths worldwide. Lung cancer mor-
tality is mainly caused from metastatic progression. The majority of patients presents with
metastatic disease at primary diagnosis. In addition, a substantial fraction of patients
comes down with metastatic relapse despite potentially curative treatment of localized
disease. Lung cancers are histologically classified as small cell (SCLC) and non-small-
cell lung cancers (NSCLC). Adenocarcinomas and squamous cell carcinomas are the
largest subgroups of NSCLC. Current strategies to reduce the risk of metastatic relapse
in early stage NSCLC rely on adjuvant cisplatin-based chemotherapy and radiation though
having only modest activity. There are no therapeutic or preventive approaches
specifically tailored to modulation of metastasis. This is in part due to still limited
understanding of the metastatic process itself and the lack of defined molecular targets
for anti-metastatic interventions.
Against this background, we used an in vivo shRNA screening platform in an orthotopic
mouse model of lung cancer to identify candidate metastasis-modulators. Among these,
aryl hydrocarbon receptor (AHR), a ligand-regulated transcription factor and sensor of
xenobiotics, was prioritized and subjected to functional and mechanistic validation in this
thesis.
In the NCI-H1975 lung adenocarcinoma model, shRNA-mediated suppression of AHR
expression increased metastatic potential in vitro and promoted metastases formation in
an orthotopic lung cancer model in vivo. Importantly, low intratumoral AHR expression
correlated with inferior survival and decreased time to progression in patients with locally
or locally advanced lung cancer. Analysis of constitutive and AHR-ligand activated RNA
expression profiles revealed a negative correlation of AHR expression and EMT signa-
tures including several genes encoding matrix-metalloproteases. Activation of AHR by its
ligand omeprazole induced expression of ASNS and ATF4, both encoding gene products
that are involved in the cellular stress response. Interestingly, ASNS induction was ATF4-
dependent and attenuated in AHR-deficient NCI-H1975 exhibiting increased metastatic
9
Abstract
potential. Moreover, AHR knockdown conferred increased resistance to glutamine-
depleted growth conditions.
These findings identify AHR and AHR-regulated pathways as promising targets for
rational anti-metastatic interventions in NSCLC.
1.2 German
Lungenkarzinome sind weltweit die Hauptursache der Krebs-assoziierten Todesfälle. Die
hohe Mortalität bei Lungenkrebs wird hauptsächlich durch metastasierendes Fortschrei-
ten der Krankheit verursacht. Die Mehrheit der Patienten weist bei der Erstdiagnose
bereits ein Krankheitsstadium mit ausgebildeten Metastasen auf. Des Weiteren erleidet
ein erheblicher Teil der Patienten mit lokalisiertem Tumor trotz potenziell kurativer
Behandlung ein Rezidiv durch das Auftreten von Metastasen. Histologisch wird
Lungenkrebs in das kleinzellige (SCLC) und das nicht-kleinzellige Lungenkarzinom
(NSCLC) eingeteilt. Adenokarzinome und Plattenepithelkarzinome sind die größten
Untergruppen des NSCLC. Gegenwärtige Strategien, um das Risiko eines Rezidivs durch
Metastasierung bei Patienten in einem frühem Krankheitsstadium zu verringern, beruhen
auf adjuvanter Cisplatin-basierter Chemotherapie und Strahlentherapie, welche
dahingehend aber nur moderate Wirksamkeit aufweisen. Es gibt keine therapeutischen
oder präventiven Ansätze, die speziell auf die Modulation der Metastasierung abzielen.
Dies ist teilweise auf das noch immer eingeschränkte Verständnis des
Metastasierungsprozesses sowie das Fehlen von spezifischen molekularen
Ansatzpunkten für anti-metastatische Interventionen zurückzuführen.
Vor diesem Hintergrund haben wir eine in vivo shRNA-Screening-Plattform in einem
orthotopen Mausmodell des Lungenkarzinoms genutzt, um potentielle Metastasierungs-
modulatoren zu identifizieren. Von diesen wurde der Aryl-Hydrocarbon-Rezeptor (AHR),
ein Liganden-regulierter Transkriptionsfaktor und Sensor von Xenobiotika, priorisiert und
im Zuge dieser Arbeit einer funktionellen und mechanistischen Validierung unterzogen.
In dem Lungenadenokarzinom-Modell NCI-H1975 erhöhte die shRNA-vermittelte
Suppression der AHR-Expression das Metastasierungspotential in vitro und förderte die
Metastasenbildung in einem orthotopen Lungenkrebs-Modell in vivo. Bei Patienten mit
lokalem oder lokal fortgeschrittenem Lungenkrebs korreliert eine niedrige
10
Abstract
AHR-Expression im Tumorgewebe mit einer verkürzten Zeit bis zur Progression. Die Ana-
lyse von konstitutiven und AHR-Liganden-aktivierten RNA-Expressionsprofilen ergab eine
negative Korrelation zwischen AHR-Expression und EMT-Gensignaturen. Darunter
befanden sich mehrere Gene, die für Matrix-Metalloproteasen kodieren. Die Aktivierung
von AHR durch seinen Liganden Omeprazol induzierte die Expression von ASNS und
ATF4, welche für Genprodukte codieren, die an der zellulären Stressantwort beteiligt sind.
Interessanterweise war die ASNS-Induktion abhängig von ATF4 und war in AHR-
defizienten NCI-H1975, die ein erhöhtes metastatisches Potential aufwiesen, vermindert.
Darüber hinaus vermittelte die Herabregulation von AHR eine erhöhte Resistenz
hinsichtlich Wachstum unter Glutaminentzug.
Diese Ergebnisse identifizieren AHR und AHR-regulierte Signalwege als vielverspre-
chende Ansatzpunkte für zielgerichtete, anti-metastatische Interventionen bei NSCLC.
11
Introduction
2 INTRODUCTION
2.1 Lung cancer: clinical features and treatment options
Lung cancer is the most commonly diagnosed cancer type worldwide and leading cause
of cancer-related deaths accounting for 1.8 million deaths estimated in 2018 (American
Cancer Society 2019, Bray et al. 2018). Besides smoking being the main risk factor for
lung cancer, several other causal components including asbestos, radon and genetic pre-
disposition have been described (Field et al. 2000 , Hodgson, Darnton 2000 , Matakidou
et al. 2005, McGuire 2016). As more than 80 % of lung cancer cases in Western
populations are attributed to smoking, prevention of cigarette smoke exposure is of utmost
importance (Bray et al. 2018 , Goeckenjan et al. 2011). Nevertheless, never smokers
should not be neglected. Further, inhalation of environmental pollutants such as
carcinogenic particles, volatile substances and xenobiotic chemicals is much more
challenging to avoid and its role in lung cancer prevention is less understood.
Based on histological and clinical characteristics, lung cancer is divided into small-cell
lung cancer (SCLC) and non-small-cell lung cancer (NSCLC). With approximately 85 %,
the majority of lung cancer patients is diagnosed with NSCLC, which comprises adeno-
carcinoma, squamous carcinoma, large cell carcinoma, mixed types and lung cancer not
otherwise specified. Adenocarcinomas are the most common form of lung cancer
amounting approximately 50 % of all cases (American Cancer Society 2019 , Zappa,
Mousa 2016).
2.1.1 Staging and survival rates
Anatomical staging of lung cancer is based on the size and invasion of neighboring struc-
tures of the primary tumor, lymph node involvement and distant metastasis. This is sum-
marized by the TNM staging system, which determines assignment to four UICC/IASCL
stages (Detterbeck et al. 2017). Stage I comprises locally (IA) and locally advanced
tumors (IB) with lymph nodes being unaffected. In stages II and III patients show large
and/or locally invasive primary tumors, ipsilateral lung metastases and/or local and medi-
astinal lymph node metastases. Stage IV is defined by the occurrence of distant metasta-
ses either in the contralateral lung, pleura or single extrathoracic site (IVA) or multiple
metastatic sites (IVB). Importantly, both clinical prognosis and treatment decisions are
12
Introduction
highly dependent on the stage at diagnosis (American Cancer Society 2019 , Detterbeck
et al. 2017, Goeckenjan et al. 2011 , Zappa, Mousa 2016).
Today, lung cancer is still among the cancer types with the lowest survival rates with an
estimated 5-year survival rate of 18 % for all stages. In NSCLC, 5-year survival estimates
show immense differences with regard to TNM staging ranging from 73 % in stage IA to
13 % in stage IV (American Cancer Society 2019 , Woodard et al. 2016). Despite improve-
ment of clinical detection methods, the majority of patients (about 40 %) is diagnosed with
stage IV lung cancer and therefore facing a very poor prognosis. Approximately 16 % of
lung cancers are detected at a non-metastatic stage (IA and IB) with a 5-year survival rate
of 56 % (American Cancer Society 2019 , Zappa, Mousa 2016). Further, screening by low-
dose computed tomography (CT) scanning has recently led to improved outcomes in high-
risk populations due to early detection of lung cancers. Its implementation effectively pre-
vented deaths in high-risk populations (Aberle et al. 2011). Therefore, increasing numbers
of lung cancer patients with localized disease are expected from national screening pro-
grams using this technology. Hence, there is a high need in developing treatment options
effectively reducing the risk of metastasis in this patient group to improve clinical
outcomes.
2.1.2 Current treatment modalities
In early stages of NSCLC (I, II and IIIA), patients amenable to surgery usually undergo
surgical resection of tumors and systemic lymph node dissection. For stages II and III,
adjuvant therapy including chemotherapy and in case of mediastinal lymph node involve-
ment radiotherapy aims to reduce the risk of lung cancer relapse (Zappa, Mousa 2016).
For patients with inoperable tumors or refusing surgery, radiation or combined chemo-
radiotherapy is currently the recommended treatment option (Lemjabbar-Alaoui
et al. 2015). In advanced NSCLC, including stage III patients with severe comorbidities
and stage IV patients, the standard of care is palliative treatment with systemic
chemotherapy and local radiotherapy (Goeckenjan et al. 2011 , Ramalingam,
Belani 2008). More recently, chemotherapy is combined with antibodies targeting the
programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) immune
checkpoint molecules (Zappa, Mousa 2016). Moreover, genomically defined subgroups
of stage IV NSCLC receive targeted therapies with small molecules inhibiting oncogenic
13
Introduction
kinases, such as epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase
(ALK), proto-oncogene tyrosine-protein kinase ROS (ROS1), serine/threonine-protein
kinase B-raf (BRAF), proto-oncogene tyrosine-protein kinase receptor Ret (RET),
neurothrophic tropomyosin receptor kinases (NTRK) or hepatocyte growth factor receptor
(Boolell et al. 2015, The Cancer Genome Atlas Research Network 2014).
Radiotherapy is applied to a large part of lung cancer patients upon their treatment course
either as first-line therapy or combination therapy in adjuvant, neoadjuvant or palliative
settings (Goeckenjan et al. 2011, Mohiuddin, Choi 2005). In general, radiotherapy applies
high-energy radiation to induce cell death in tumor cells by directly damaging the deoxy-
ribonucleic acid (DNA) and by indirect effects conferred by free radicals deriving from
ionization (Baskar et al. 2012 , Baskar et al. 2014). During conventional radiotherapy,
fractionated regimes are used to deliver the highest possible dose while limiting
detrimental effects to adjacent non-tumorous tissue (Baskar et al. 2014). Optimal dosing
and scheduling have been intensively studied and are depending on disease stage and
the physical condition of the patient (Goeckenjan et al. 2011 , Lindblom et al. 2015 , Roach
et al. 2018, Saunders et al. 1999). Improvement in imaging modalities and implementation
of software-supported approaches such as intensity modulated radiation therapy (IMRT)
or cone-beam computed tomography (CBCT) has highly improved localized application of
radiation (Baskar et al. 2012 , Jaksic et al. 2018 , Wang-Chesebro et al. 2006). In non-
resected early stage NSCLC, stereotactic body radiation therapy (SBRT) has been shown
to confer superior survival benefits compared to conventionally fractionated radiation
therapy (CFRT) (Abel et al. 2019 , Baumann et al. 2009 , Nyman et al. 2006) and suggested
to result in potentially comparable clinical outcomes as after resection (Chang et al. 2015 ,
Onishi et al. 2011). Radiosensitizers such as platin-based chemotherapy are commonly
applied in combination with radiation to improve treatment effects by sensitizing the tumor
(Sause et al. 1995 , Schaake-Koning et al. 1992). More recently, the integration of targeted
approaches in radiotherapy has been subject to intense research aiming to further
increase radiation efficacy and precision (Dumont et al. 2009 , Wang et al. 2017 , Zhuang
et al. 2014).
In the past 15 years, identification of several oncogenic drivers including EGFR and ALK
has led to the development of targeted therapy approaches exploiting these molecular
14
Introduction
dependencies in respective patient subgroups (Boolell et al. 2015 , The Cancer Genome
Atlas Research Network 2014 , Zappa, Mousa 2016). The use of targeted therapies is
clinically active by inducing remission, delaying cancer progression, and improving sur-
vival (Camidge et al. 2012 , Maemondo et al. 2010 , Mok et al. 2009). Further, these drivers
or their mutational status were successfully used as biomarkers to predict therapy
responses of certain patient cohorts (Lynch et al. 2004 , Mok et al. 2009 , Paez et al. 2004).
One prime example routinely being used in treatment of lung cancer is EGFR. Activating
mutations in EGFR lead to uncontrolled cancer cell proliferation and survival and can be
detected in up to 10-15 % of NSCLC patients. Most commonly these are deletions in
exon 19 or a single point mutation giving rise to the L858R variant in exon 21 (Lynch
et al. 2004, Pao et al. 2004 , The Cancer Genome Atlas Research Network 2014 , Zappa,
Mousa 2016). Targeting of EGFR with tyrosine kinase inhibitors (TKIs) improves the clin-
ical outcome and quality of life also in late stage disease (Mok et al. 2009 , Zhou
et al. 2011). First generation TKIs, namely gefitinib and erlotinib, are small molecules
reversibly binding to EGFR and are approved for EGFR-mutated NSCLC stage IV patients
(Morgillo et al. 2016). Unfortunately, the majority of patients acquire resistance upon TKI
treatment leading to recurrent disease. The emergence of secondary resistance mutations
such as T790M occurring in about 60 % of NSCLC patients has further guided the devel-
opment of second and third generation TKIs (Balak et al. 2006 , Socinski et al. 2013 , Yu
et al. 2013). Afatinib, a second generation EGFR TKI covalently binding to EGFR, human
epidermal growth factor 2 (HER2) and 4 (HER4), significantly improved clinical outcome
compared to gefitinib and chemotherapy in EGFR-mutant patient cohorts (Park
et al. 2016, Sequist et al. 2013). Specifically designed to target mutant EGFR T790M, the
third-generation TKI osimertinib exhibited improved activity in T790M-positive NSCLC
patients progressing upon or after EGFR-TKI therapy (Cross et al. 2014). Further,
osimertinib demonstrated superior clinical outcomes and superior central nervous system
(CNS) efficacy as compared to chemotherapy (Mok et al. 2016) and to first generation
EGFR-TKIs (Soria et al. 2018). Despite being clinically effective, the absence of clinically
targetable oncogenic driver mutations in the majority of lung cancer patients limits the
applicability of tailored therapies to certain patient subgroups. Further, acquisition of
resistance commonly occurs along therapy leading to cancer recurrence or metastatic
15
Introduction
relapse also in initially responding patients (Balak et al. 2006, Morgillo et al. 2016 , Zappa,
Mousa 2016).
More recently, immunotherapy has been implemented in lung cancer treatment (reviewed
in (Zappa, Mousa 2016)). Here, different approaches are used to target immuno-
modulating mechanisms aiming to accelerate the immune system’s anti-tumor activity.
Previous approaches used cytokines such as interleukin-2 (IL-2) or interferon (IFN) to
systemically activate the host’s immune system with modest effect (reviewed in
(Berraondo et al. 2019)). For lung cancer, immunostimulating cytokines failed to
consistently improve clinical outcomes while causing partially severe side effects (Ridolfi
et al. 2011, Yang et al. 2016). Recently developed strategies comprise the blockade of
tumor-mediated immune suppression and thereby enhancing immunosurveillance of the
tumor. Here, the inhibition of immune checkpoints by monoclonal antibodies has shown
promising results (Pardoll 2012 , Zappa, Mousa 2016). Mechanistically, tumor cells are
able to avoid immune clearance by expressing immune-suppressive surface markers
such as PD-L1. Binding of PD-L1 to PD-1 expressed on T-cells leads to suppression of
T-cell proliferation and activity (Keir et al. 2006 , Santini, Hellmann 2018 , Yang et al. 2016).
This negative feedback can be abrogated by antibody-mediated blockade of the
PD-1/PD-L1 interaction. In lung cancer, antibodies targeting PD-1 or PD-L1 were superior
to second-line chemotherapy (Borghaei et al. 2015 , Carbone et al. 2017 , Herbst
et al. 2016). In NSCLC patients with high PD-L1 expression, pembrolizumab alone was
more efficacious than platinum-based first-line chemotherapy (Reck et al. 2016). In
NSCLC patients with low or absent PD-L1 expression, anti-PD-1/PD-L1 antibodies are
combined with platinum-based chemotherapy (Gandhi et al. 2018 , Paz-Ares et al. 2018 ,
West et al. 2019).
Currently, two anti-PD-1 antibodies (nivolumab and pembrolizumab) and two anti-PD-L1
antibodies (atezolizumab and durvalumab) are globally approved for second-line treat-
ment of recurrent NSCLC (Lu, Su 2019). Further, combination treatment with anti-PD-1
and anti-CTLA4 (cytotoxic T-lymphocyte antigen-4) antibodies has been suggested to
increase clinical activity and improve survival rates (Hellmann et al. 2017 , Ready
et al. 2019). An additional field of research has led to the application of acellular or cellular
vaccines designed to prime tumor cells for tumor-associated antigens (TAA) which are
16
Introduction
currently under clinical investigation (García et al. 2008 , Gonzalez et al. 2003 , Lu,
Su 2019, Parikh et al. 2011 , Ramalingam et al. 2013 , Yang et al. 2013 , 2013, Yang
et al. 2016).
Despite improvement among NSCLC treatment modalities, metastatic relapse remains
the foremost cause of cancer-related death displaying a great challenge in the treatment
of lung cancer (Anderson et al. 2019 , Herbst et al. 2018 , Lambert et al. 2017). Intense
research on the mechanistic principles of cancer metastasis during the last decades could
not yet overcome the lack of therapies specifically targeting metastatic spread which
largely determines the clinical outcome of cancer patients. Although adjuvant chemo-
therapy (Arriagada et al. 2004 , Douillard et al. 2006 , Winton et al. 2005) or chemoradio-
therapy (Douillard et al. 2008 , Eberhardt et al. 2015) was shown to improve survival of
patients with localized lung cancer, curative treatments are not available for the majority
of NSCLC patients. Recently, durvalumab has been demonstrated to increase overall
survival and decrease the risk of metastatic progression in stage III NSCLC patients
treated with simultaneous radiochemotherapy (Antonia et al. 2018). However, its impact
in resected lung cancer has not yet been evaluated.
The development of anti-metastatic drugs has several obstacles to overcome due to the
complexity of the metastatic process, the biological difference of primary tumors and
metastatic cells and the translation of preclinical data into clinical application (Anderson
et al. 2019). Valid preclinical models and molecular dissection of metastasis are the
prerequisite for clinically active therapies capable of delaying or even preventing
metastatic progression.
2.2 Factors governing cancer metastasis and the role of the epithelial-
mesenchymal transition (EMT)
Cancer metastasis is a multistep cascade (Figure 1) including the invasion of cancer cells
from a locally growing primary tumor and dissemination via the circulatory system to form
secondary lesions at distant sites (Brabletz 2012 , Chaffer, Weinberg 2011 , Lambert
et al. 2017). Given the small proportion of disseminated tumor cells (DTCs) successfully
forming metastases, cancer metastasis can be considered a highly ineffective process
upon which many metastasizing cells die (Luzzi et al. 1998). Still, metastatic relapse
commonly occurs among all tumor types and remains the major challenge in the curative
17
Introduction
treatment of cancer patients (Anderson et al. 2019 , Lambert et al. 2017). However, the
biological obstacles that tumor cells have to overcome during metastasis might constitute
promising targets for anti-metastatic therapies (Anderson et al. 2019). Intensive research
in evaluating the biological and molecular mechanisms of cancer metastasis has led to a
better but still incomplete understanding of this complex process.
Figure 1: Overview of the metastatic cascade. The multistep process of cancer metastasis comprises tumor cell
invasion into the adjacent microenvironment to enable intravasation into blood or lymphatic vessels and transit of tumor cells through the circulation before extravasation in order to form metastasis. Tumor-derived factors secreted from the primary tumor lead to the formation of pre-metastatic niches which facilitate survival and growth of micrometastases at the secondary site which is required for metastatic colonization. Acquisition of dormant phenotypes in disseminated tumor cells or micrometastases enables escape from cell death. MDSC: myeoloid-derived suppressor cells (Anderson et al. 2019).
In the initial step of metastasis, primary tumor cells need to acquire an invasive phenotype
in order to locally invade the adjacent tumor microenvironment and to intravasate into
blood or lymphatic circulation (Chaffer, Weinberg 2011). Epithelial tumors such as adeno-
carcinomas are mainly consisting of highly differentiated cells with strong intercellular
junctions and are bordered by basement membranes (Brabletz 2012 , Chaffer,
18
Introduction
Weinberg 2011). Upon tumor progression, accumulation of genetic and epigenetic
alterations increase tumor heterogeneity which leads to locally invasive and metastatic
tumors characterized by increased dedifferentiation especially at the invasive front
(Brabletz 2012, Marusyk et al. 2012). Hallmarks of epithelial-mesenchymal transition
(EMT) including activation of EMT transcription factors (EMT-TF), notably Snail, Slug,
Twist and Zeb1, and loss of epithelial markers such as E-cadherin are commonly
associated with this dedifferentiation (Lambert et al. 2017 , Nieto et al. 2016 , Polyak,
Weinberg 2009). Furthermore, invasive tumor cells show increased secretion of matrix-
metalloproteases (MMPs) and thus induce the degradation of the surrounding
extracellular matrix (ECM) facilitating tumor cell invasion (Conlon, Murray 2019 , Radisky,
Radisky 2010). Certain MMPs including MMP2, MMP9 and MMP28 were implicated in
promotion of EMT pathways and phenotype (Illman et al. 2006 , Radisky, Radisky 2010).
Generally, induction of EMT or EMT-like processes is considered to be highly
advantageous for cancer cell invasion and dissemination (Chaffer, Weinberg 2011 ,
Lambert et al. 2017 , Spaderna et al. 2008). Mechanistically, mesenchymal-like cells show
increased invasiveness, anchorage-independent growth and stemness-like character-
istics, all of which support cancer metastasis (Guadamillas et al. 2011 , Mani et al. 2008 ,
Polyak, Weinberg 2009 , Singla et al. 2018). However, the necessity of EMT induction for
metastasis is recently controversially discussed as the importance of re-differentiation of
disseminated tumor cells by mesenchymal-epithelial transition (MET) is increasingly
recognized as a crucial step for outgrowth of metastatic lesions (Brabletz et al. 2018 ,
Chaffer et al. 2006 , Chu et al. 2013).
Traditional models of tumorigenesis claim metastatic spread to occur as a late event of
tumor progression, though there now has been experimental evidence demonstrating the
occurrence of early dissemination (Harper et al. 2016, Hüsemann et al. 2008 , Rhim
et al. 2012, Talmadge, Fidler 2010). Further, different forms of dissemination have been
described so far. Besides the classical view of single disseminating cells that have gained
invasive capacity and spread from the tumor, recent studies using intravital microscopy or
tumor spheroid models have demonstrated the collective migration of tumor cell clusters
(Friedl et al. 2012 , Konen et al. 2017 , Lambert et al. 2017).
19
Introduction
Notably, trans-endothelial migration (TEM) during intra- and extravasation requires the
tumor cells to endure mechanical deformation. Here, low cellular stiffness has been
suggested to be advantageous for metastatic cells (Cross et al. 2007 , Wirtz et al. 2011).
After entry into the circulation, immunogenicity as well as mechanical and oxidative stress
display major challenges for the survival of circulating tumor cells (CTCs) or multicellular
CTC clusters (Headley et al. 2016 , Lambert et al. 2017 , Wirtz et al. 2011). Importantly, the
generation of a viable metastatic niche is considered the critical if not rate-limiting step of
metastasis in order for the disseminated tumor cells to survive and regain proliferative
functions (Chambers et al. 1995 , Luzzi et al. 1998). As the microenvironment of the
secondary site is markedly different from the primary tumor site, the translocated tumor
cells have to substantially adapt to the new environment to allow for metastatic coloni-
zation (Anderson et al. 2019 , Lambert et al. 2017). Acquisition of temporary dormant
states are described to facilitate survival of DTCs until cellular pathways are sufficiently
remodeled to cope with the conditions at the secondary site (Lambert et al. 2017 , Senft,
Ronai 2016). Furthermore, dormancy of DTCs potentially explains the clinical occurrence
of metastatic relapse after a period of latency with no clinical manifestation of residual
disease (Meng et al. 2004 , Senft, Ronai 2016). Accumulating evidence suggests a com-
bination of EMT characteristics and stemness features as prerequisite for metastasis in a
concept of migrating cancer stem cells (Brabletz et al. 2005). Cancer stem cells (CSCs)
endow the ability to regain a proliferative state and give rise to differentiated cell types,
thus being qualified to represent the founders of metastatic colonies (Ayob,
Ramasamy 2018, Lambert et al. 2017 , Mani et al. 2008). However, preservation of a
mesenchymal cell state has been shown to limit tumor cell proliferation and thereby inhibit
metastatic colonization (Brabletz et al. 2001 , Tsai et al. 2012 , Vega et al. 2004). Thus,
re-differentiation via MET after dissemination is frequently observed in metastases that
recapitulate the main histological and genetic characteristics of the primary tumor at dif-
ferent secondary sites (Brabletz 2012, Liu et al. 2017 , Tsai et al. 2012).
2.2.1 Transitions between epithelial and mesenchymal phenotypes (EMT/MET)
EMT has first been described in physiological conditions occurring successively upon the
formation of embryonic layers and the generation of internal organs during embryonic
development (Acloque et al. 2009). During tumor progression, tumor cells appear to hijack
20
Introduction
parts of these transcriptomic programs to gain metastatic capacity (Brabletz et al. 2018 ,
Lambert et al. 2017 , Nieto et al. 2016). EMT and MET have therefore been object of
numerous investigations revealing molecular mediators and signaling pathways.
EMT can be induced by various external triggers including soluble factors, such as
transforming growth factor-β (TGF-β), hepatocyte growth factor (HGF), fibroblast growth
factor (FGF) as well as Wnt, Notch and hedgehog proteins (Thiery, Sleeman 2006 , Xiao,
He 2010). Furthermore, hypoxic conditions and interactions with components of the ECM,
such as collagen and hyaluronic acid, are described to induce EMT in cancer cells (Choi
et al. 2017, Yang et al. 2008 , Zoltan-Jones et al. 2003). Subsequent activation of signaling
cascades orchestrated by a network of EMT-TFs provoke alterations in proteins regulating
cell polarity, adhesion, cytoskeleton and ECM degradation (Polyak, Weinberg 2009 ,
Puisieux et al. 2014 , Thiery, Sleeman 2006). Generally, EMT activation leads to
decreased abundance of epithelial and increased abundance or activation of mesen-
chymal markers (Lee et al. 2006). Loss of E-cadherin as epithelial marker is regarded to
be crucial for EMT induction and commonly described to be downregulated during tumor
progression (Polyak, Weinberg 2009 , Puisieux et al. 2014 , Wirtz et al. 2011). However,
recent studies showed controversial results in which E-cadherin is required for the for-
mation of metastases (Chu et al. 2013). Still, loss in adhesion appears necessary for
adenocarcinoma cells in order to dissociate from the primary tumor (Cavallaro,
Christofori 2004, Nieto et al. 2016 , Puisieux et al. 2014). Several mesenchymal markers
including Zeb1, Zeb2, Snail, Slug, and Twist are either direct or indirect repressors of
E-cadherin (Polyak, Weinberg 2009). In many epithelial cancer types, loss of E-cadherin
is accompanied by induction of mesenchymal cadherins including N-cadherin and
cadherin-11 (Cavallaro, Christofori 2004). Moreover, β-catenin, usually part of adherens
junctions when binding cadherins, is translocating into the nucleus as a transcriptional co-
activator of EMT-related genes (Lee et al. 2006).
21
Introduction
Figure 2: Model of cellular plasticity through transitional EMT/MET states. During tumor progression, transition
between epithelial (E) and mesenchymal (M) phenotypes is considered as a continuum with several intermediate (EM) cell states. Upon transition, cells sequentially lose their polarity and cell-adhesions (TJ - tight junction, AJ - adherens junction, DS - desmosome). Several transcription factors (SNAI1/2, ZEB, TWIST1, GRHL2, OVOL1/2 and PRRX1), miRNAs and epigenetic factors have been described to be involved in a regulatory network conferring this phenotypic plasticity. The existence of stable and metastable EM states is predicted but not yet proven. ECM: extracellular matrix (Nieto et al. 2016).
During developmental programs, complete transitions from epithelial to mesenchymal cell
states occur, whereas cancer cells rather show transient and partial EMT upon metastatic
progression (Brabletz 2012 , Lambert et al. 2017). Multiple intermediate cell states
exhibiting some mesenchymal traits while retaining other epithelial features were demon-
strated to exist during the course of the metastatic cascade (Figure 2) (Lambert
et al. 2017, Nieto et al. 2016 , Pastushenko et al. 2018). Here, reciprocal feedback loops
between classical EMT-TFs and microRNAs (miRs) such as miR-200 as well as epi-
genetic regulations are suggested to allow for reversible and transient molecular changes
and phenotypic plasticity (Brabletz 2012, Nieto et al. 2016 , Wellner et al. 2009). Further,
this model of cellular plasticity is able to explain the switch to re-differentiation via MET in
order to form macrometastases (Chaffer et al. 2006 , Nieto et al. 2016).
Additionally, EMT-TFs are discussed to affect stemness, DNA repair and survival path-
ways, which are advantageous for metastatic cells by increasing therapy resistance and
cell survival (Brabletz et al. 2018 , Puisieux et al. 2014 , Shibue, Weinberg 2017).
22
Introduction
2.2.2 Emerging roles of the microenvironment in cancer metastasis
Recently, the tumor microenvironment (TME) has been increasingly recognized as an
important factor for cancer metastasis as well as a potential therapeutic target for the
suppression of metastatic progression (Altorki et al. 2019 , Anderson et al. 2019 , Hanahan,
Coussens 2012, Hanahan, Weinberg 2011 , 2011). Because of its close proximity and
reciprocal interaction with tumor and host cells, the TME highly influences the survival and
signaling pathways of tumor cells (Peng et al. 2017). Thus, the TME has been considered
as an emerging hallmark of cancer (Hanahan, Weinberg 2011).
A supportive microenvironment is both important for primary tumor growth and metastasis
to establish viable premalignant and metastatic niches (Zhang, Xiang 2019). This com-
prises recruitment of associated stromal cells, ECM remodeling including stimulation of
angiogenesis, induction of malignant features such as invasion and EMT, immuno-
suppression as well as alteration in metabolism (De Palma et al. 2017 , Hanahan,
Coussens 2012, Liu et al. 2014). In order to improve blood supply of the tumor, tumor cells
initiate secretion of vascular endothelial growth factor (VEGF) under hypoxic conditions
thus inducing angiogenesis by engaging VEGF receptor 2 (VEGFR2) on endothelial cells
(LaGory, Giaccia 2016 , Potente et al. 2011). Moreover, direct interaction of tumor cells
with ECM proteins such as collagen I via integrins leads to activation of internal signaling
pathways and has been demonstrated to promote tumor growth as well as establishment
of metastatic niches (Navab et al. 2016 , Peng et al. 2017 , Wu et al. 2019b). Further, the
development of pre-metastatic niches is suggested to occur even prior to tumor cell dis-
semination. Here, the microenvironment at prospective metastatic sites is actively modi-
fied by systemic secretion of regulating factors from the primary tumor (Liu et al. 2014 ,
Peinado et al. 2017, Zhang, Xiang 2019). Moreover, homing of disseminated cancer cells
appears in an organ-specific manner as many cancer types display preferred secondary
sites (Langley, Fidler 2011). Common metastatic sites for lung cancer are the contralateral
lung, lymph nodes, liver, adrenal glands, bones, and brain (Milovanovic et al. 2017).
Several therapeutic strategies targeting the tumor or metastatic microenvironment are
currently under clinical investigation. With regard to immunotherapy and angiogenesis,
various approaches have already been approved and implemented in cancer treatment
(Lu, Su 2019, Potente et al. 2011).
23
Introduction
2.2.3 Metabolic dependencies and reprogramming
Major remodeling of the primary metabolism in cancer cells has been defined as one of
the emerging cancer hallmarks (Hanahan, Weinberg 2011). During tumor initiation and
metastatic colonization, the survival and sustained proliferation of cancer cells at hypoxic
and nutrient-poor environments demand for alternative routes of nutrient supply. In the
absence of sufficient supply with metabolites, micro- and macropinocytosis of extracellular
proteins, entosis of living cells or phagocytosis of apoptotic bodies have been described
to fuel tumor cell metabolism (Krajcovic et al. 2013 , Pavlova, Thompson 2016 , Stolzing,
Grune 2004). Besides opportunistic routes of nutrient utilization, the rewiring of intrinsic
metabolic pathways leads to alterations in metabolite dependencies enabling uncontrolled
cell proliferation under limiting growth conditions (Hanahan, Weinberg 2011).
Glucose and glutamine are two principal nutrients supporting proliferation and bio-
synthesis of cells. Their catabolism provides cells with essential components including
carbon intermediates, source of reducing agents nicotinamide adenine dinucleotide
hydrogen (NADH) and flavin adenine dinucleotide dihydrogen (FADH2) as well as equiva-
lents such as adenosine triphosphate (ATP) (Pavlova, Thompson 2016). Various cancer
cells exhibit high levels of glycolysis also in presence of oxygen (aerobic glycolysis, also
termed Warburg effect) thus generating ATP at a lower efficiency compared to oxidative
phosphorylation on which normal cells rely for energy production (Fouad, Aanei 2017 ,
WARBURG 1956). Further, upregulation of glucose transporters such as GLUT1 has
been demonstrated in many cancer types as means to enhance cellular glucose uptake
(Gonzalez-Menendez et al. 2018 , Hanahan, Weinberg 2011). Glutamine is the most abun-
dant amino acid and constitutes not only a source of carbon but also of nitrogen for
de novo biosynthesis (Altman et al. 2016 , Pavlova, Thompson 2016). Due to the increased
catabolism in tumor cells, glutamine and glucose are commonly used as isotope-labeled
clinical tracers during tumor imaging and suggested as therapeutic target to exhaust tumor
metabolism (Almuhaideb et al. 2011 , Altman et al. 2016 , Hamanaka, Chandel 2012 ,
Lieberman et al. 2011 , Venneti et al. 2015). More recently, the availability of other amino
acids such as asparagine and aspartate has been controversially discussed to affect
tumor growth under limited nutrient and oxygen conditions (Garcia-Bermudez et al. 2018 ,
Pavlova et al. 2018 , Sullivan et al. 2018). Although much of metabolic reprogramming is
24
Introduction
considered cell intrinsic, increasing evidence indicates reciprocal feedback from the
microenvironment (Pavlova, Thompson 2016). Upon metastatic progression, DTCs need
to adapt their metabolic pathways according to the nutrient environment at a specific
metastatic site leading to altered metabolism also between primary tumor and metastases
(Christen et al. 2016 , Elia et al. 2018). Further, CTCs rely on antioxidant metabolism
during loss of adhesion and transit in circulation in order to circumvent reactive oxygen
species (ROS)-mediated cell death (Elia et al. 2018 , Hawk, Schafer 2018 , Piskounova
et al. 2015).
2.3 Aryl hydrocarbon receptor: a sensor of xenobiotics and its potential role in
tumor progression
Aryl hydrocarbon receptor (AHR) is a ligand-regulated transcription factor sensing xeno-
biotic and endogenous factors leading to the modulation of highly complex regulation pat-
terns (Esser et al. 2018 , Murray et al. 2014). Here, a variety of exogenous factors including
2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and benzo[a]pyrene (BaP) as well as some
endogenous ligands such as kynurenine and indoxyl sulfate have been identified as acti-
vating ligands of AHR (Murray et al. 2014). Upon ligand binding, AHR translocates into
the nucleus, dissociates from its cytosolic complex and regulates target genes of xeno-
biotic responsive elements (XRE) upon heterodimerization with aryl hydrocarbon receptor
nuclear translocator (ARNT). In response to xenobiotic stimuli, AHR induces the transcrip-
tion of several cytochrome P450 (CYP) enzymes that are important in the metabolism and
bioactivation of carcinogens (Li et al. 1998 , Murray et al. 2014 , Whitlock 1999). Besides
its transcriptional activity, ligand-independent regulation of AHR was suggested to be
mediated by nucleo-cytoplasmatic shuttling in AHR high expressing cells (Chang
et al. 2007, Ikuta et al. 2000 , Murray et al. 2014).
As a transcription factor, AHR modulates a variety of physiological as well as pathological
pathways and processes (Esser et al. 2018 , Larigot et al. 2018). Important roles of AHR
in embryonic development and homeostasis of organs such as heart, liver and skin as
well as in the function of the immune system were demonstrated by the developmental
defects observed in transgenic mouse models (Fernandez-Salguero et al. 1997 , Schmidt
et al. 1996). However, AHR-deficient mice are viable and fertile. With regard to patho-
logical processes, AHR-mediated activity has been linked to response to environmental
25
Aim of the study
factors, autoimmunity, imbalance in metabolism and carcinogenesis (Esser et al. 2018 ,
Fingerhut et al. 1991 , Rothhammer, Quintana 2019 , Whitlock 1999).
First, AHR was discovered as the receptor of TCDD, a high-affinity ligand that mediated
immunosuppression and tumor promotion by sustained activation of its receptor (Knerr,
Schrenk 2006, Rothhammer, Quintana 2019). Further, pro-tumorigenic functions of AHR
were demonstrated in numerous other studies (D'Amato et al. 2015 , Murray et al. 2014 ,
Opitz et al. 2011). However, AHR displayed tumor and metastasis suppressive activity in
certain entities including Ewing sarcoma, neuroblastoma as well as lung and breast
cancer (Jin et al. 2014 , Mutz et al. 2016, Wu et al. 2019a). Hence, the controversial results
of AHR functions in tumor initiation and progression suggests a ligand- and tissue-specific
role that might be depending on disease stage.
3 AIM OF THE STUDY
This work was based on the hypothesis that a better understanding of the molecular
mechanisms of cancer metastasis will guide the development of treatment options specif-
ically targeting metastatic progression in lung cancer patients. In order to identify factors
crucial in the metastatic cascade, a shRNA screen in an orthotopic lung cancer mouse
model has been conducted in a collaborative project of our group and the group of
Dr. Trever G. Bivona at the Department of Medicine of the UCSF Cancer Center prior to
this work.
This thesis aimed to validate and characterize AHR as a putative metastasis-modulating
factor and identify novel insights into the metastatic process in lung cancer. NCI-H1975
cells with stable shRNA-mediated AHR suppression were generated to provide reliable
cell models to investigate the impact of AHR on the metastatic potential of adeno-
carcinomas. Those were used for validation of AHR as a suppressor of lung cancer
metastasis using the established orthotopic mouse model recapitulating the complete
metastatic cascade. Mechanistic studies of AHR-regulated pathways could then provide
promising targets to develop pharmacological strategies to prevent metastatic progres-
sion. Further, publicly available databases were mined to correlate the expression of AHR
with clinical outcomes in lung cancer patients.
26
Methods
4 METHODS
4.1 Cell Biology Methods
4.1.1 Cell culture
HEK293FT, Phoenix (FNX), SW480 and SW620 cells were cultivated in DMEM,
NCI-H1975 (hereinafter referred to as H1975), A549 and NCI-H1299 (hereinafter referred
to as H1299) cells in RMPI 1640, each supplemented with 10 % heat-inactivated FBS,
100 U/ml penicillin, 100 μg/ml streptomycin, and 2 mM L-glutamine, in a humidified
atmosphere at 37 °C and 5 % CO2. Passaging of cells was performed at 80-90 % conflu-
ency using 0.05 % trypsin-EDTA. Cells were discarded at passages higher than 30. If not
stated otherwise, cells were pelleted by centrifugation at room temperature (RT) and
300 x g for 5 min. Treatment with omeprazole (Sigma-Aldrich) was conducted for 48-72 h.
All cell lines were authenticated using short tandem repeat (STR) analysis and absence
of mycoplasma contamination was confirmed by regular testing.
4.1.2 Freezing and thawing of cells
All cell lines were frozen in early passages using FBS supplemented with 10 % DMSO
and stored short-term at -80 °C and long-term in liquid nitrogen. Frozen cells were shortly
thawed at 37 °C, centrifuged and transferred to culture dishes with warm culture medium.
Cells were passaged at least once after thawing before being used for experiments.
4.1.3 Spheroid formation assay
In order to initiate formation of spheroids, cells were seeded into commercially available
cell culture plates with cell-repellent surface. Spheroids were grown for up to 72 h and
pictures taken every 24 h using Primovert microscope (Zeiss).
4.2 Generation of stable transgenic cell models
Note that viral particles are handled at BSL-2.
4.2.1 Generation of lentiviral and retroviral particles
For generation of lentiviral particles, HEK293FT cells were transfected at 50 % confluency
in fibronectin-coated 10 cm dishes with lentiviral packaging plasmids pMD2, pSPAX and
the plasmid of interest (1.5, 3 and 3 µg, respectively) using FuGENE HD transfection
reagent (Promega) according to the manufacturer’s recommendations. Fresh medium
27
Methods
was added after 24 h and viral supernatants collected 72 h post transfection. Remaining
packaging cells were removed from the supernatants using 0.45 µm filters to avoid cross-
contamination. For generation of retroviral particles, FNX cells were transfected as
described above only that retroviral packaging plasmids Hit60 (MLV gag-pol) and
pCMV.VSV-G were used.
4.2.2 Lentiviral and retroviral transduction of lung adenocarcinoma cell lines
Human cell lines were infected with lentiviral or retroviral constructs by addition of viral
supernatant from packaging cells diluted 1:2 in culture medium and 1 µg/ml polybrene for
24 h. After 48 h, H1975 cells were selected with 0.5 µg/ml puromycin and A549 as well as
H1299 were selected with 1 µg/ml puromycin for 7 days. In the rescue approach, selection
of H1975 cell clones expressing shAHR or control shRNA (shScr) was carried out in the
presence of 1 mg/ml neomycin.
4.2.3 Small hairpin ribonucleic acid (shRNA)-mediated knockdown
Lentiviral shRNA targeting AHR (shAHR) and retroviral shRNAs targeting ASNS
(shASNS) were purchased as bacterial stocks from Sigma-Aldrich and OriGene,
respectively (Table 1). Plasmid DNA was prepared as described in chapter 4.9.1. Viral
supernatants were generated (4.2.1) and used to stably integrate shRNAs into human
adenocarcinoma cell lines by viral transduction (4.2.2).
Table 1: Sequences for shRNAs targeting AHR or ASNS.
target sequence (5’ - 3’)
lentiviral (pLKO.1 backbone)
non-mammalian
target (Scr)
CCGGCAACAAGATGAAGAGCACCAACTCGAGTTGGTGCTCT
TCATCTTGTTGTTTTT
AHR CCGGCGGCATAGAGACCGACTTAATCTCGAGATTAAGTCGG
TCTCTATGCCGTTTTT
retroviral (pGFP-V-RS backbone)
scrambled negative
control n/a
ASNS A) AAGGTCTTGTTACATTGAAGCACTCCGCG
B) ATTCGGAAGAACACAGATAGCGTGGTGAT
28
Methods
In order to enhance stability of target gene suppression, clonal cell lines were established
from the transgenic cell lines using limiting dilution after antibiotic selection. Briefly, cells
were seeded at 0.5 cells/well in a 96-well plate and proliferating colonies from single cells
were expanded for experiments and long-term storage in liquid nitrogen.
4.2.4 Reintroduction of shRNA-resistant AHR into AHR knockdown cell lines
In order to reconstitute AHR expression in the shAHR harboring H1975 cell lines, rescue
vectors encoding for shRNA-resistant AHR were established.
As the shRNA carrying cells were already puromycin resistant due to stable integration of
the pLKO.1-shRNA vector, a retroviral MSCV backbone mediating neomycin resistance
was chosen for rescue vector generation. MSCV-tdTomato-PGK-Neo was kindly provided
by Dr. Barbara M. Grüner, which was used by Dr. Sophie Kalmbach to generate a
tdTomate-truncated MSCV backbone (hereinafter referred to as MSCV vector).
The full-length coding sequence (CDS) of AHR was generated in a single polymerase
chain reaction (PCR) (Table 2) using high fidelity AccuPrime Polymerase (invitrogen)
according to the manufacturer’s guidelines. cDNA transcribed from 2 µg of RNA from
parental H1975 was diluted 1:5 and used as a template.
Table 2: PCR program for generation of full-length CDS of AHR.
procedure period [min] temperature [°C] # of cycles
initialization 2:00 95 1x
denaturation 0:15 95 35x
annealing 0:30 64
elongation 3:00 68
final elongation 2:00 68 1x
cooling ∞ 4 1x
Primers were designed to result in a PCR product consisting of the CDS of AHR flanked
by restriction sites for FspAI at the 5’ end and BglII at the 3’ end (Table 3).
29
Methods
Table 3: Primer sequences for cloning of rescue vector.
primer sequence (5’ - 3’)
AHR FspAI For ATTGTGCGCATCCACCATGAACAGCAGCAGCGCC
AHR BglII Rev CGGCGAGATCTCCGTTACAGGAATCCACTGGATGTCAA
After purification of the PCR product using PCR Purification Kit (Qiagen) according to the
manufacturer’s manual, the PCR product as well as the MSCV vector were digested with
FspAI and BglII restriction enzymes for 3 h at 37 °C (Table 4).
Table 4: Reaction mixes for restriction digest of MSCV backbone and AHR PCR product.
procedure MSCV PCR product
amount DNA 4 µg total amount from
purification
restriction
enzyme
15 U FspAI
20 U BglII
15 U FspAI
20 U BglII
10x O puffer 5 µl 5 µl
aqua ad 50 µl
DNA fragments of interest were separated using agarose gel electrophoresis and isolated
from the gel with QIAquick Gel Extraction Kit (Qiagen) according to the manufacturer’s
protocol (4.9.4). DNA was eluted in 30 µl A. dest.
Backbone and insert were used for ligation at a molar ratio of 1:6 using T4 DNA ligase
(New England Biolabs) overnight at 16 °C in a total volume of 10 µl. All steps were
conducted referring to the manufacturer’s recommendations.
Ligation products (3 µl of reaction mix) were introduced into One ShotTM Stbl3TM E. coli
(invitrogen) by transformation according to the manufacturer’s protocol. Integration of the
CDS of AHR into the MSCV backbone was confirmed by PCR and Sanger sequencing
(Microsynth Seqlab) using AHR Primers (Table 3). Plasmid DNA was isolated from bac-
terial cultures (4.9.1). Silent point mutations were introduced into the shRNA-binding site
of the CDS using site-directed mutagenesis (4.9.3) in order to confer resistance to shAHR.
30
Methods
The sequence of the resulting vector (AHR rescue vector) was again confirmed using
Sanger sequencing. Finally, the AHR rescue vector was introduced into H1975 expressing
shAHR (K1-K3) or shScr by retroviral transduction as described before (4.2.2). Further,
respective cell lines transduced with the empty MSCV vector were generated to serve as
controls.
4.3 siRNA mediated knockdown
Transient introduction of siRNA into adenocarcinoma cell lines was conducted using
Lipofectamine® RNAiMAX reagent (Thermo Fischer Scientific) according to the manufac-
turer’s protocol. 30 pmol and 150 pmol of siRNA were used for transfection of 6-well or
10 cm dish, respectively. During siRNA studies, treatment with omeprazole was started
24 h post transfection to ensure suppression of target mRNA at the time of treatment.
MISSION® esiRNA targeting human ATF4 as well as MISSION® siRNA Universal
Negative Control were purchased from Sigma-Aldrich.
4.4 Proliferation assays
Cell proliferation was analyzed using 3-(4,5-Dimethylthiazole-2-yl)-2,5-diphenyl-2H-
tetrazolium bromide (MTT) in 96-well plates after 48-72 h. Briefly, 10 µl of MTT solution
was added per well. After 4 h of incubation, cells were lysed with 100 µl MTT solubilization
buffer overnight. The absorption was measured with a spectrophotometer plate reader at
570-595 nm and at 655 nm as reference wavelength. For L-glutamine and serum
starvation studies, cells were directly seeded into different starvation media and incubated
for 72 h before addition of MTT. Omeprazole treatment was conducted by addition of
treatment as a twofold concentrated solution to cells seeded in culture medium 4 h before.
For all assays, 5 x 104 cells were seeded per well.
4.5 Cell competition assay
H1975 cells expressing AHR-specific or control shRNAs were mixed in equal ratios and
co-cultivated in culture medium with or without addition of L-glutamine. H1975 shScr
control cells or H1975 shAHR-K2 expressing green fluorescent protein (GFP) were mixed
with their non-labeled counterparts and vice versa. The proportion of fluorescent cells in
the cell mixtures was determined by flow cytometry at the day of seeding and after two
weeks of culture. Cells were passaged every 3-5 days.
31
Methods
4.6 Transwell migration invasion assay
The transwell migration invasion assay was conducted using BioCoatTM GFR Matrigel and
control inserts for 24-well plate (Corning) according to the manufacturer’s protocol. Briefly,
cells were seeded at 6 x 105 on 10 cm dishes. The next day, cells were starved with low-
serum (0.5 % FBS) medium for 4 h and then seeded at 1.5 x 104 cells/insert using low-
serum medium. Full-serum (10 % FBS) medium was added to the lower compartment to
serve as chemoattractant. Cells were incubated for 24 h in a humidified incubator at 37 °C
and 5 % CO2. After mechanical removal of cells remaining on the apical side of inserts,
migrated/invaded cells were fixed with 70 % ethanol and stained using 0.1 % crystal violet
solution. Membranes were then cut from the inserts and embedded with entellan. Four
representative pictures were taken per insert using the BIOREVO BZ-9000 microscope
(Keyence). The mean cell number of triplicates was used to calculate the number of
migrated or invaded cell as well as the relative invasion as described in the manual for the
transwell inserts.
4.7 T-HUVEC adhesion assay
hTERT-immortalized HUVEC (human umbilicial vein endothelial cells, hereinafter referred
to as T-HUVECs) were kindly provided by Dr. Barbara M. Grüner and seeded in 24-well
plates to form confluent monolayers. H1975 cells expressing AHR-specific or control
shRNAs were treated with omeprazole or DMSO for 48 h. Treated cells were harvested
using trypsin, washed twice with PBS and resuspended in culture medium. Cell suspen-
sions with 5 x 105 cells/ml were prepared for each treatment group and 5 x 104 cells/well
added to T-HUVECs in duplicates. After incubation for 20 min with agitation, unbound
cells were washed off with PBS twice before remaining cells were harvested and analyzed
by flow cytometry for proportion of GFP-positive (GFP+) cells.
4.8 Biochemical methods
4.8.1 Preparation of whole cell extracts
According to the cellular localization of the target protein, NP40 or RIPA lysis buffer were
applied for cell lysis. RIPA buffer was used for mainly nuclear localized and membrane
proteins whereas NP40 buffer was used for cytosolic proteins.
32
Methods
Cells were harvested using trypsin followed by washing with PBS. Cell pellets were
resuspended in appropriate volumes of cold lysis buffer supplemented with cOmplete
protease inhibitor cocktail (Roche) and phosphatase inhibitors cocktails 2 and 3 (Sigma-
Aldrich). For treatment studies and detection of phosphorylated proteins, cells were
directly scraped off the culture dish on ice after washing with PBS and addition of cold
supplemented lysis buffer. Cell lysis was carried out for 20 min on ice with regular
vortexing. Finally, lysates were snap frozen with liquid nitrogen, thawed on ice and cleared
of cell debris by centrifugation at 18,400 x g at 4 °C for 10 min. Total protein
concentrations were determined as described in 4.8.2 and protein extracts were stored
at -80 °C.
4.8.2 Measurement of protein concentrations
For all protein extracts, total protein concentrations were determined using Bio-Rad
Protein Assay Dye Reagent Concentrate (Bio-Rad). Briefly, Bradford reagent was diluted
1:5 in A. dest and samples were added at a ratio of 1:500. Absorbance was detected at a
wavelength of 595 nm using the Gene Quant Photometer (Amersham). Protein concen-
tration was determined by comparison to a blank value with lysis buffer as reference.
4.8.3 SDS-PAGE, protein transfer and staining
Equal amounts of proteins (range = 20-50 µg) were supplemented with 5X SDS-PAGE
loading buffer, denatured at 95 °C for 5 min and separated at 95-110 V using the Mini-
PROTEAN electrophoresis system (Bio-Rad). Proteins were transferred to nitrocellulose
membranes with the Trans-Blot® TurboTM system (Bio-Rad) and Mini Nitrocellulose
Transfer Kit (Bio-Rad). Membranes were incubated in blocking buffer for at least 1 h and
blotted with primary antibodies overnight at 4 °C (Table 10). After incubation with horse-
radish peroxidase (HRP)-conjugated secondary antibodies (Pierce Antibodies, 1:4000) for
1-3 h at RT, signals were detected with the Super Signal West Pico/Femto system
(Thermo Fisher Scientific) on the ChemiSmart Imaging System (VILBER LOURMAT
Deutschland GmbH). For reprobing with different antibodies, membranes were incubated
in Restore™ Western Blot Stripping Buffer (Thermo Fisher Scientific) according to the
manufacturer’s protocol to remove primary and secondary antibodies prior to blocking and
blotting with the next antibody.
33
Methods
4.8.4 Gelatine zymography
Gelatine zymography to assess activity of MMP2 and MMP9 was adapted from Kleiner
and Stetler-Stevenson (Kleiner, Stetler-Stevenson 1994). Briefly, cells were seeded at
3.5 x 105 in 6-well plates. After adhesion of the cells to the surface, culture medium was
replaced by medium containing 0.5 % FBS. Conditioned medium (CM) was harvested
after 16 h of incubation and centrifuged to remove floating cells. Equal volumes of CM
were supplemented with 5X non-reducing zymography sample buffer, incubated for
15 min at RT and subjected to separation by SDS-PAGE (4.8.3). Subsequently, gels were
successively incubated for 1 h each in 2.5 % triton X-100 and zymography enzyme buffer.
Fresh enzyme buffer was added before the gels were incubated 18-48 h at 37 °C in an
incubator under atmospheric conditions. Staining with 0.5 % coomassie blue in 30 %
methanol and 10 % acetic acid for 1 h and destaining with 30 % methanol and 10 % acetic
acid for 0.5 h plus 1 h were conducted at RT on a rotary shaker. Areas of digestion
displayed as non-stained bands.
4.9 Molecular Biology Methods
4.9.1 Plasmid isolation from bacterial cultures
Bacterial glycerol stocks or bacterial colonies from agar plates were used to inoculate
bacterial cultures in Circlegrow® medium containing 50 µg/ml ampicillin or 25 µl/ml
kanamycin. Bacterial cultures were grown at 37 °C and 225 rpm overnight. For viral
packaging plasmids temperature was reduced to 32 °C. Plasmid DNA from bacteria was
isolated with QIAGEN Plasmid Plus Maxi Kit (Qiagen) or QIAprep Spin Miniprep Kit
(Qiagen) according to the manufacturer’s protocol. DNA concentrations were determined
using the NanoDrop photometer (Peqlab) and DNA samples were stored at -20 °C.
4.9.2 Transformation of competent bacteria
Plasmid DNA was transformed into One Shot® Stbl3TM chemically competent E. coli
(invitrogen) according to the manufacturer`s protocol.
4.9.3 Site-directed mutagenesis
In order to inhibit shRNA-mediated degradation of the ectopically expressed AHR
messenger RNA (mRNA) in H1975 shAHR, five silent point mutations were introduced
into the rescue vector at the shRNA binding site using GeneArt™ Site-Directed
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Methods
Mutagenesis System Kit (Thermo Fisher Scientific) according to the manufacturer’s
instructions.
The forward primer was designed to be complementary to the binding site of the AHR-
targeting shRNA with the exception of five single bases each on the third position of the
codon (Table 5).
Table 5: Primer sequences for AHR mutagenesis. Yellow: shRNA binding site. Red: silent point mutations.
primer sequence (5’ - 3’)
silMut AHR
For ATCCTTCCAAGCGGCACAGGGATCGTCTCAATACAGAGTTGGACC
silMut AHR
Rev GGTCCAACTCTGTATTGAGACGATCCCTGTGCCGCTTGGAAGGAT
4.9.4 Agarose gel electrophoresis and gel extraction
Agarose gels were prepared using 1-2 % agarose in TAE buffer and 0.5 µg/ml ethidium
bromide. Separation of DNA fragments supplemented with 6X DNA loading dye was
achieved by applying 100-120 V for 1-2 h. Isolation of DNA fragments from TAE agarose
gels was achieved using QIAquick Gel Extraction Kit (Qiagen) according to the
manufacturer’s protocol.
4.9.5 Restriction digest
Digestion of plasmid DNA or purified PCR product was carried out using restriction en-
zymes as indicated according to the manufacturer’s protocol. Undigested DNA was used
as negative control and samples were analyzed using agarose gel electrophoresis (4.9.4).
4.9.6 RNA isolation and cDNA synthesis
For qRT-PCR, RNA was isolated and purified using High Pure RNA Isolation Kit (Roche)
and reversely transcribed by Transcriptor High Fidelity cDNA Synthesis Kit (Roche) as per
the manufacturer’s protocols. For mRNA sequencing, RNeasy Mini Kit (Qiagen) was used
to obtain highly enriched mRNA-fractions (4.11).
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Methods
4.9.7 Quantitative real-time PCR (qRT-PCR)
qRT-PCR was conducted using LightCycler® 480 SYBR Green I Master Kit (Roche
Molecular Systems, Inc.) according to the manufacturer’s manual. If not stated otherwise,
primers were designed using Primer3 software and purchased from Thermo Fisher
Scientific, Qiagen or Integrated DNA Technologies (Table 9) and applied at 2 µM final
concentration.
Table 6: Standard protocol for qRT-PCR at LightCycler®480.
procedure period [min] temperature [°C] # of cycles
initialization 5:00 95 1x
denaturation 0:10 95 45x
annealing 0:10 s 57
elongation 0:10s 72
melting curve
0:05 s 95 1x
1:00 65
continuous 97
cooling 0:10 40 1x
Target expression was quantified in duplicates or triplicates on a LightCycler®480 System
(Roche) using the 2-ΔΔCt method and actin beta (ACTB), glyceraldehyde-3-phosphate
dehydrogenase (GAPDH) and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as
internal controls. For a detailed run protocol see Table 6.
4.10 Flow cytometry
Detection of fluorescently labeled cells and analysis of cell viability was conducted using
flow cytometry. If not indicated otherwise, cells were harvested using trypsin, centrifuged
at 300 x g for 5 min and resuspended in FACS buffer. DAPI (5 ng/ml) was supplemented
to allow for discrimination of viable cells.
FACSCelestaTM and FACSDiva™ software (BD Biosciences) were used for all analyses.
Data from the in vivo stress experiment were re-analyzed using FlowJo software due to
file sizes.
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Methods
4.11 RNA-Sequencing
RNA was isolated from cells after 48 h of treatment with 200 µM omeprazole using
RNeasy Mini Kit (Qiagen) according to the manufacturer’s recommendations. RNA
integrity was confirmed using Screen Tape Kit (Agilent) and Screen Tape Station (Agilent).
3’UTR mRNA-Seq library preparation and analysis on an Illumina HiSeq2500 was
performed by the working group of Prof. Dr. Michael Hölzel as described previously (Layer
et al. 2017).
Transcript-level quantification was performed using salmon version 0.11 with the Ensembl
GRCh38 assembly as reference genome. Resulting count estimates were then merged
above all samples and transformed to gene-level using tximport version 0.16. Differential
expression analysis was performed on the resulting gene-counts table using Deseq2
version 1.18. Data processing from quantification to differential expression analysis was
kindly conducted by Jan Forster.
Expression changes were considered significant with Padj < 0.05 and log2-fold change
(log2FC) <-1 or <1. Principal component analysis and heat map clustering was performed
using Perseus software (Max Planck Institute for Biochemistry, Martinsried, Ver-
sion 1.5.5.3). Among all groups, Euclidean clustering was carried out for differential ex-
pression data for genes being significantly altered between experimental groups A and B.
4.12 Gene set enrichment analysis (GSEA)
Gene count matrix file from RNA-Seq was used for gene set enrichment analysis (GSEA)
using java-based GSEA software v3.0 and the curated hallmark gene set collection
(Mootha et al. 2003 , Subramanian et al. 2005). Parameters were set to 1,000
permutations and gene-set permutation mode.
4.13 In vivo experiments
4.13.1 Orthotopic lung xenografts
Orthotopic transplantation as well as subsequent bioluminescence imaging (BLI) was con-
ducted at the University of California, San Francisco (UCSF) by Dr. Ross A. Okimoto or
Dr. Frank Breitenbücher. Human adenocarcinoma cell lines were orthotopically implanted
into immunocompromised mice as described previously (Okimoto et al. 2017). Briefly, cell
suspensions were prepared with Matrigel at a final concentration of 105 cells/µl. Six- to
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Methods
eight-week-old female SCID CB.17 mice (purchased form Taconic, Germantown, NY)
were anesthetized with 2.5 % inhaled isoflurane and the left thorax was surgically opened
to access the lateral ribs. 10 µl of cell suspension (106 cells) were injected into lung
parenchyma of the left lung lobe through the intercostal space using a 30-gauge hypo-
dermic needle. Mice were observed for pneumothorax before primary wound closure and
allowed to recover for one week prior to imaging.
4.13.2 In vivo and ex vivo bioluminescence imaging
Transgenic cell lines used for the orthotopic mouse model were further engineered by
lentiviral transduction to express GFP and Luciferase (Luc) from an EGFP-ffluc epHIV7
vector (kindly provided by Dr. Michael Jensen, Seattle). Isolation of GFP+ cells was con-
ducted by Klaus Lennartz using a BD FACSVantage SE with BD FACSDiVA Option (BD
Biosciences) modified by addition of a S2 bench (Lennartz et al. 2005).
Mice were imaged at the UCSF Preclinical Therapeutics Core with Xenogen IVIS 100
bioluminescence imaging as described previously (Okimoto et al. 2017). For in vivo imag-
ing, mice were anesthetized and injected IP with 200 µl (150 mg/kg) D-Luciferin and bio-
luminescence intensity of tumors was monitored once weekly until week five. After five
weeks, D-Luciferin was injected and mice euthanized to resect organs for ex vivo imaging.
4.13.3 In vivo shRNA screen using orthotopic lung cancer model
The shRNA library screen was performed by Dr. Frank Breitenbücher and Dr. Ross
A. Okimoto prior to this thesis. To this end, a lentiviral pooled barcoded shRNA library was
generated using DECIPHER shRNA Library Human Module 1 (Cellecta Inc.) following the
manufacturer’s protocol. Briefly, HEK293FT cells were transfected with shRNA library
DNA using FuGENE (Promega) and viral supernatants were collected 72 h post trans-
fection. GFP and Luciferase expressing H1975 and A549 cells were transduced with the
shRNA library-containing supernatant. Transduction efficacy was set to 25 % to ensure
that total cell number would exceed the library’s complexity by 1,000-fold. After puromycin
selection, cell populations were orthotopically implanted in the left lungs of CB-17 SCID
mice. Tumor growth was monitored using bioluminescent in vivo imaging until metastases
were detectable. To identify representation of the library’s shRNAs in metastases and
primary tumors, harvested tissues were subjected to parallel sequencing of barcoded
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Methods
regions as previously described (Okimoto et al. 2017). Statistical analyses were
performed by Dr. Saurabh Asthana.
4.13.4 In vivo stress assay
C57BL/6 mice were kindly provided by the working group of Prof. Dr. Jens Siveke and
were 12 months old on average. Prior to tail vein injection, transgenic H1975 cells
expressing AHR-specific or control shRNAs were treated in vitro with omeprazole or
DMSO as control for 48 h. Subsequently, cell suspensions at 106 cells/100 µl PBS were
prepared for all treatment groups and kept on ice until injection. Per mouse, 100 µl of cell
suspension were transplanted intravenously. After 5 min, mice were sacrificed to collect
0.5-1 ml of cardiac blood as well as lung and spleen.
Blood was collected in tubes with 3 µl of 0.5 M EDTA and directly subjected to red blood
cell lysis. To this end, 4 ml of ACK buffer was added and samples were incubated for
10 min at RT. After centrifugation, incubation in ACK buffer was repeated. Finally, cells
were pelleted, resuspended in FACS buffer and stored on ice until flow cytometry analysis.
Lung lobes (n = 3 per mouse) were subjected to tissue digestion as described in
Grüner et al. (Grüner et al. 2016). Briefly, lung tissues were minced with scissors and
incubated in digestion medium for 1 h at 37 °C. Digest was stopped with quenching solu-
tion and cell suspension was filtered through 40 µm mesh, centrifuged and subjected to
red blood cell lysis as described above.
Spleens were filtered through 40 µm mesh and subjected to red blood cell lysis as
described above.
For all samples, cells were pelleted by centrifugation and resuspended in FACS buffer
supplemented with 5 µg/ml DAPI to detect living and GFP+ cells using flow cytometry.
4.14 Statistics
Significance was assessed for all experiments with three biological replicates by statistical
analysis using GraphPad Prism 6. As applicable, either student’s t-test or one-way
analysis of variance (ANOVA) was used.
In graphs, P-values are indicated as following:
ns (not significant), P > 0.05, * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001,**** P ≤ 0.0001
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Results
5 RESULTS
Due to the complexity of the metastatic process comprising sequential adaptation of
cancer cells during its different steps, the implementation of legit in vivo models for the
preclinical investigation of the underlying molecular mechanisms is of utmost importance.
While several modulators of metastatic processes have been identified, unbiased in vivo
screens reflecting the entire metastatic cascade have the potential to uncover important
genes in this complex biological phenomenon. For this purpose, shRNA libraries targeting
multiple genes have already proven their value for revealing factors involved in
tumorigenesis (Berns et al. 2004 , Gargiulo et al. 2014 , Sims et al. 2011).
5.1 Unbiased shRNA screen in an orthotopic mouse model of lung cancer reveals
potential metastasis genes
In order to identify novel modulators of metastasis in NSCLC, Dr. Frank Breitenbücher
and Dr. Ross A. Okimoto performed an unbiased in vivo shRNA library screen using an
orthotopic mouse model of lung cancer prior to this work. Importantly, this approach
incorporates all sequential steps of the metastatic process thereby constituting a legit
model for factors crucial in lung cancer metastasis. The screen was based on two NSCLC
cell lines, NCI-H1975 (subsequently referred to as H1975), which have low endogenous
metastatic potential, and A549 endogenously capable to form metastases in this ortho-
topic model. A barcoded shRNA library was lentivirally introduced under single hit condi-
tions into A549 and H1975, which were engineered to express Luciferase (Luc) and green
fluorescent protein (GFP) reporters (Figure 3A). Library-expressing A549 and H1975 cell
populations were orthotopically transplanted into immunocompromised mice as described
previously (Okimoto et al., 2017). Bioluminescent imaging (BLI) revealed mainly local
tumor growth of parental H1975, whereas metastatic spread was induced in shRNA-
library transduced H1975 (Figure 3B). Deep sequencing of metastases, primary tumors
and a reference sample from the initial cell population allowed evaluation of barcode
representation of the shRNAs by bioinformatic analyses which were conducted by
Dr. Saurabh Asthana from the UCSF (Figure 3C). A list of 69 putative metastasis-
modulating target genes was identified including aryl hydrocarbon receptor (AHR,
Figure 3C) that has been subjected to profound characterization and validation
experiments during this thesis.
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Figure 3: Unbiased in vivo shRNA screen using an orthotopic mouse model of lung cancer. A) Schematic over-view of experimental layout. B) Bioluminescence images of SCID CB.17 mice transplanted with GFP-Luc+ H1975 expressing shRNA library or parental GFP-Luc+ H1975. C) Statistic analysis for one mouse (m3) displaying shRNA
representation in primary tumor and metastases normalized to shRNA representation in the initial cell population. Aryl hydrocarbon receptor (AHR, red circle) was selected for further characterization as a potential metastasis modulator. These experiments were performed by Dr. Breitenbücher and Dr. Okimoto. Statistical analyses were conducted by Dr. Asthana.
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Results
AHR is a ligand-activated transcription factor, which is involved in many cellular processes
including responses to xenobiotic stimuli, autoimmunity, metabolic imbalance and inflam-
matory diseases (reviewed in Esser et al. 2018, Larigot et al. 2018). Further, a role of AHR
has been controversially discussed with regard to cancer initiation and progression
(D'Amato et al. 2015 , Jin et al. 2014 , Murray et al. 2014 , Opitz et al. 2011).
5.2 Suppression of endogenous AHR increases metastatic potential of H1975
cells in vitro
In order to investigate the role of AHR in the metastatic process of NSCLC, we established
stable cell models by introduction of a shRNA targeting AHR (shAHR) into H1975 using
lentiviral transduction. H1975 stably expressing a non-mammalian target control
shRNA (shScr) were generated as control. As target gene suppression was not detectable
in the bulk population of H1975 shAHR cells (Figure 4A), clonal cell lines (K1, K2 and K3)
were established using limiting dilution to exclude the impact of heterogeneity in the
studied cell population. Expression of AHR was significantly reduced on protein and
mRNA level in H1975 shAHR-K1 and -K2 compared to shScr control cells analyzed by
immunoblotting (Figure 4A) and qRT-PCR (Figure 4B). Suppression of AHR did not affect
proliferation of H1975 in a short term MTT assay (Figure 4C).
Figure 4: Suppression of endogenous AHR by stable integration of shAHR into H1975 cells. AHR protein and mRNA levels in shScr control and shAHR cell clones were assessed by immunoblotting (A) and qRT-PCR (B). A) Actin was used as control. B) Expression was normalized to ACTB and GAPDH relative to the shScr control. Mean ± SD of the two house keeping genes (HKG) is displayed. C) Proliferation was analyzed after 72 h using MTT assay. Data are
shown as mean ± SD relative to the shScr control. n = 3 for all experiments. Significance was assessed using one-way ANOVA.
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Results
In order to functionally characterize AHR as a modulator of lung cancer metastasis, we
used established in vitro platforms to assess the migratory and invasive capacity of H1975
with regard to AHR expression. In concordance with the results from the in vivo screen,
suppression of AHR significantly increased the invasion of H1975 cells in a transwell
migration invasion assay (Figure 5A-C) though migration was reduced (Figure 5A+C)
compared to controls.
Figure 5: shRNA-mediated suppression of AHR increases metastatic potential of H1975 cells in vitro. A) Number
of migrating and invading H1975 cells expressing shAHR or shScr were assessd using a transwell migration invasion assay. B) Relative invasion was calculated by dividing the mean number of invading by the mean number of migrating cells. C) Representative pictures from transwell inserts. Scale bar 200 µm. D)+E) MMP2 and MMP9 activity were
assessed using gelatine zymography. Relative intensities of gelatinolytic bands from MMP9 were quantified using ImageJ. For A, B and D, data are shown as mean ± SD. n = 3 for all experiments. Significance was assessed using one-way ANOVA (A+D) or student’s t-test (B).
As knockdown of AHR increased the invasion through the matrigel-covered inserts, we
hypothesized that AHR may regulate the activity of matrix-metalloproteases (MMPs)
which are known to be involved in matrix remodeling and metastatic progression (Conlon,
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Murray 2019). Gelatine zymography was applied to assess the activity of the gelatinases
MMP2 and MMP9 using conditioned medium of H1975 shScr cells or H1975 cell clones
expressing shAHR. H1975 shAHR-K2 cells with the most efficient suppression of AHR
expression displayed high MMP9 activity, while MMP2 activity was unaltered irrespective
of AHR expression levels (Figure 5D+E). However, MMP9 activity was not increased in
the other two clonal cell lines expressing shAHR.
Figure 6: Intercellular adhesion is altered upon suppression of AHR in H1975 cells. A) Representative pictures of spheroids formed by GFP-Luc+ H1975 shAHR-K2 and shScr control cells. Scale bar 200 µm. B) CDH1 (E-cadherin) and CDH2 (N-cadherin) mRNA levels in H1975 shScr control and shAHR cell clone K2 were assessed by qRT-PCR. Expression was normalized to ACTB and GAPDH relative to the shScr control. Mean ± SD of the two house keeping genes (HKG) is displayed. Significance was assessed using student’s t-test. n = 3 for all experiments.
To assess the impact of AHR expression on cell growth in three dimensions, which is
important to assess the metastatic and invasive capabilities, cells were plated on repellent
culture surfaces provoking formation of tumor cell spheroids. Increased cell scattering was
observed in GFP-Luc-expressing H1975 shAHR-K2 cells compared to AHR-proficient
cells (Figure 6A), which is described to be associated with increased migratory and inva-
sive capacity (Stadler et al. 2018). Upon metastatic progression of epithelial tumors a
switch from epithelial adhesion molecules, most prominently E-cadherin, to mesenchymal
markers such as N-cadherin is commonly observed in epithelial-mesenchymal transition
(EMT) (Nieto et al. 2016). Interestingly, CDH1 (E-cadherin) expression was sustained
upon shRNA-mediated suppression of AHR while expression of CDH2 (N-cadherin) was
increased (Figure 6B).
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Overall, suppression of AHR in H1975 cells was sufficient to enhance their invasive
capacity in our experimental conditions in vitro.
5.3 Reconstitution of AHR expression by introduction of shAHR-resistant AHR in
H1975 AHR-knockdown cells partially reverses the pro-metastatic phenotype
In order to exclude cell clone specific effects and to confirm the impact of AHR on the
metastatic ability of H1975 cells, we re-expressed AHR in our knockdown cell models by
introduction of shRNA-resistant AHR cDNA. To this end, mutant AHR cDNA harboring
five silent point mutations that abolish shRNA binding efficacy was stably introduced into
the three clonal H1975 shAHR cell lines as well as the shScr control by retroviral trans-
duction. The empty MSCV vector (EV) was transduced to generate the appropriate con-
trols (Figure 7A). By this, AHR mRNA levels were partially increased in H1975 cell clones
expressing shAHR as analyzed by qRT-PCR (Figure 7B), whereas protein levels were not
detectably changed (Figure 7C).
To demonstrate functionality of exogenous AHR in the generated rescue cell models, we
used the AHR agonist omeprazole to examine the induction of the AHR target gene
Cytochrome P450 Family 1 Subfamily A Member 1 (CYP1A1) (Figure 7D). Indeed, acti-
vation of AHR by omeprazole led to a significant increase (200-fold) of CYP1A1 expres-
sion in AHR-proficient H1975 shScr cells, which was significantly dampened in H1975
expressing shAHR (Figure 7E). Partial reconstitution of AHR by stable introduction of
shRNA-resistant AHR cDNA in part restored omeprazole-mediated induction of CYP1A1
expression (Figure 7E). Hence, the rescue cell models were subjected to characterization
of altered metastatic capacity.
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Figure 7: AHR cDNA resistant to shAHR was successfully introduced into H1975 cell models expressing shAHR or shScr. A) Schematic overview of generation of rescue cell models. B) Expression of AHR was assessed using qRT-PCR. GAPDH was used as reference gene. C) AHR protein levels were analyzed using immunoblotting. Actin was used as control (n = 1). D+E) Expression of the AHR target CYP1A1 in the absence and presence of the AHR agonist
omeprazole (omep, 200 µM, 72 h) was analyzed using qRT-PCR. Expression was normalized to GAPDH. n = 3 for all experiments if not indicated otherwise. For B and E, data are shown as mean ± SD normalized to control. Significance
was assessed using one-way ANOVA.
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Results
Here, H1975 cells with suppressed AHR expression (H1975 shAHR-K2 EV) consistently
showed increased invasive abilities in both the transwell migration invasion assay
(Figure 8A+B) and gelatine zymography (Figure 8C+D). Further, reintroduction of AHR in
H1975 shAHR-K2 cells moderately dampened this increase in relative invasion as well as
MMP9 activity suggesting the observed effects to be AHR specific. In conclusion, restoring
of endogenous AHR expression in H1975 shAHR-K2 cells by introducing a shRNA-
resistant AHR partially reversed the metastatic phenotype in vitro.
Figure 8: Reconstitution of AHR expression in H1975 with shRNA-mediated AHR suppression partially rescued metastatic phenotype observed in vitro. A) Evaluation of invasive capability of cells with partially reconstituted AHR
expression using transwell migration invasion assay. Relative invasion was calculated by dividing the mean number of invading by the mean number of migrating cells. Data are shown as mean ± SD. B) Representantive pictures from transwell inserts. Scale bar 200 µm. C)+D): Gelatine zymography was used to determine MMP2 and MMP9 activity of
rescue cell models. Relative intensities of gelatinolytic bands from MMP9 were quantified using ImageJ. Data are shown as mean ± SD normalized to control. n = 3 for all experiments. Significance was assessed using one-way ANOVA.
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Results
5.4 Depletion of AHR favors metastatic spread in vivo
As the metastatic cascade involves multiple steps which cannot completely be recapitu-
lated in vitro, we performed an in vivo validation experiment. Here, metastatic spread of
H1975 expressing shAHR and shScr control was investigated using the orthotopic mouse
model of lung cancer (Figure 9A), which was already applied in the initial shRNA screen.
Figure 9: Targeted suppression of AHR increases metastatic spread of H1975 in an orthotopic lung cancer mouse model. A) Schematic overview of in vivo validation experiment. B) AHR expression was assessed by immuno-blotting. Actin was used as control. C) BLI images of SCID CB.17 mice transplanted with either GFP-Luc+ H1975 shScr or GFP-Luc+ H1975 shAHR-K2. D) Ex vivo bioluminescent imaging of explanted lung lobes. E) Metastasis-free survival of SCID CB.17 mice bearing GFP-Luc+ H1975 expressing shAHR (K2) or shScr. P-value, log-rank. In vivo experiments were conducted by Dr. Okimoto at the UCSF.
In order to enable in vivo bioluminescent imaging (BLI), the clonal H1975 cell line with the
most effective AHR knockdown (shAHR-K2) and shScr control cells were engineered to
stably express GFP and Luc. Persistence of AHR knockdown was confirmed using
immunoblotting (Figure 9B). These GFP-Luc+ H1975 shAHR-K2 cells as well as control
cells were orthotopically implanted into the left lung of immunocompromised mice. Tumor
growth and metastasis formation were monitored for four weeks. Luciferase-based imag-
ing revealed metastatic spread of shAHR-K2 cells compared to mainly localized tumor
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Results
growth of the control cell lines (Figure 7C). Importantly, shRNA-mediated suppression of
AHR significantly increased the metastatic ability of H1975 cells in vivo as displayed by
decreased metastasis-free survival of mice implanted with shAHR-K2 compared to the
control tumors (Figure 9C-E).
Figure 10: Impact of endogenous AHR expression in lung adenocarcinoma on patient outcomes following resection. Kaplan-Meier plots displaying overall survival (OS) and time to first progression (FP) for patients with stage I lung adenocarcinomas with high or low AHR expression (20820_at) (Győrffy et al. 2013). Cutoff median.
To further corroborate the role of AHR as a suppressor of lung cancer metastasis we
analyzed publicly available RNA expression data from patient cohorts with early stage and
locally advanced lung adenocarcinoma (Győrffy et al. 2013). Interestingly, overall survival
(Figure 10A) and time to first progression (Figure 10B) were significantly reduced in
patients with tumors exhibiting low AHR expression.
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Figure 11: Impact of endogenous AHR expression in lung adenocarcinoma on patient outcomes among all disease stages. Kaplan-Meier plots showing overall survival (OS) and time to first progression (FP) for patients with lung adenocarcinomas among all stages with high or low AHR expression (20820_at) (Győrffy et al. 2013). Cutoff median.
Analyzing cohorts of patients with adenocarcinoma among all disease stages, this corre-
lation was less profound for overall survival (Figure 11A) and non-significant regarding
time to first progression (Figure 11B).
5.5 RNA sequencing experiment identifies candidate targets of AHR involved in
stress responses and metastasis
A variety of endogenous and exogenous ligands of AHR have been described (Larigot
et al. 2018, Murray et al. 2014). Although our previous results suggested that suppression
of endogenous AHR was sufficient to impact the metastatic potential of H1975 cells, we
also wanted to consider the impact of AHR activation on the transcriptional response of
target cells. Thus, we included an experimental group in which the AHR-activating ligand
omeprazole was added to the cells prior to RNA sequencing as omeprazole had pre-
viously been linked to reduced metastasis in breast cancer models (Jin et al. 2014).
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Figure 12: Omeprazole inhibits growth of H1975 cells in an AHR-dependent manner. Proliferation and metabolic viability of H1975 shScr and shAHR-K2 upon omeprazole (omep) treatment was studied after 48 h (A) and 72 h (B)
using MTT assay. Data are shown as mean ± SD normalized to respective DMSO control. Significance was assessed using one-way ANOVA.
First, we analyzed the impact of omeprazole on H1975 with regard to AHR expression in
an MTT assay. Proliferation and metabolic activity of AHR-proficient H1975 cells was sig-
nificantly inhibited by treatment with omeprazole in a dose-dependent manner, which was
significantly attenuated in H1975 expressing shAHR (K2) (Figure 12).
In addition to the functional assays performed earlier, we aimed to identify those AHR
effectors involved in regulating lung cancer metastasis. To this end we subjected H1975
with and without shRNA-mediated suppression of endogenous AHR to mRNA
sequencing. Further, we included treatment with omeprazole to discriminate between con-
stitutive and induced expression profiles (Figure 13A). To confirm validity of our experi-
mental settings, expression of the AHR target CYP1A1 was analyzed for all samples prior
to RNA sequencing using reverse transcription to cDNA and qRT-PCR. Indeed, CYP1A1
expression was strongly elevated by the activation of AHR upon omeprazole treatment
(Figure 13B). Moreover, CYP1A1 induction was significantly blunted in H1975 with
shRNA-mediated suppression of AHR. RNA sequencing and initial data preparation were
performed by the group of our collaborator, Prof. Dr. Michael Hölzel, University of Bonn,
and by Jan Forster, M.Sc., Institute of Genetics, respectively. Principal component analy-
sis confirmed reproducibility of gene expression across biological replicates (Figure 13C).
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Results
Figure 13: Constitutive and induced expression signatures of H1975 shAHR cell models were identified using mRNA sequencing. A) Schematic overview of experimental settings for RNA sequencing experiment. B) CYP1A1
expression was analyzed for all RNA sequencing samples after generation of cDNA using qRT-PCR. Omeprazole (omep) was used at 200 µM for 48 h. Expression was normalized to GAPDH. Data are shown as mean ± SD normalized to control. n = 3. C) Principal component analysis recovered clustering of experimental groups. D) Venn diagram of differential gene expression analysis. E) Euclidean clustering was used to generate a heat map displaying gene patterns
for genes that were differentially expressed upon omeprazole treatment. Changes with p < 0.05 were considered significant.
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Differential gene expression analysis was performed among all treatment groups to
determine AHR-dependent expression profiles. Comparing the effect of omeprazole in
AHR-proficient and AHR-suppressed H1975 cells revealed an overlap of 281 regulated
genes (Figure 13D). Moreover, we identified genes being differentially expressed upon
omeprazole treatment in H1975 shScr cells. Clustering of RNA data according to the
Euclidean distance revealed that AHR-proficient cells and shAHR-K2 cells showed com-
parable gene expression patterns upon omeprazole treatment while the amplitude of
target gene regulation was dampened in shAHR-K2 cells (Figure 13E).
To identify transcriptomic programs that are particularly altered upon activation of AHR by
omeprazole or shRNA-mediated suppression of AHR, gene set enrichment analysis
(GSEA) was performed using the ‘Hallmarks of Cancer’ gene set collection (Mootha
et al. 2003, Subramanian et al. 2005).
Here, AHR activation by omeprazole was positively correlated with the unfolded protein
response (UPR) and xenobiotic metabolism (Figure 14A+C). Interestingly, knockdown of
AHR was significantly correlated with increased expression of EMT genes
(Figure 14B+D). Additionally, this gene set was found to be significantly less represented
upon activation of AHR by omeprazole in both H1975 cells with and without suppression
of AHR (Figure 14A, Supplementary Figure 1).
Moreover, inspection of these gene sets associated with AHR expression and activity
revealed several target genes implicated in cancer progression, including several mem-
bers of the matrix metalloprotease family (MMPs, most prominently MMP24), asparagine
synthetase (ASNS) and activating transcription factor 4 (ATF4). Those have been
subjected to further investigation.
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Figure 14: Gene set enrichment analysis links AHR expression and activation to several cancer hallmarks. A) Gene sets differentially represented in H1975 shScr omep (group B) compared to H1975 shScr DMSO (group A). B) Gene sets differentially represented in H1975 shAHR-K2 DMSO (group C) compared to H1975 shScr DMSO (group A). C) Enrichment plot for the gene set ‘Unfolded Protein Response’ enriched in omeprazole treated H1975 shScr (shScr +) compared to the DMSO treated control (shScr -). D) Enrichment plot for gene set ‘Epithelial-Mesenchymal-Transition’ enriched in H1975 shAHR-K2 (shAHR -) compared to the shScr control (shScr -). For A and B, treshhold for significant gene set enrichment was set to FDR < 0.1. Biological replicates are indicated with I, II
and III.
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5.5.1 AHR activation and expression negatively correlates with genes associated
with matrix remodeling and EMT
Matrix-metalloproteases (MMPs) are known to contribute to matrix degradation during
invasion of tumor cells and are associated with enhanced invasiveness of tumor cells and
inferior survival prognosis (El-Badrawy et al. 2014 , Wang et al. 2019). In order to confirm
findings from the mRNA sequencing approach, expression levels of several MMPs were
analyzed for three independent H1975 cell clones expressing shAHR (K1, K2 and K3)
with and without treatment with omeprazole compared to the H1975 shScr control.
Figure 15: AHR regulates expression of matrix-metalloproteases (MMPs) in H1975. Expression of MMPs in H1975
cell clones expressing shAHR (K1-K3) and shScr control was analyzed after treatment with omeprazole (omep, 200 µM, 48 h) or DMSO (-). MMP24 expression was assessed by qRT-PCR (A) and immunoblotting (B). C)+D) qRT-PCR analysis of MMP19 and MMP9 mRNA levels is shown. For A, target gene expression was normalized to ACTB, GAPDH and HPRT1 relative to the shScr control. Mean ± SD of the three house keeping genes (HKG) is displayed. For C and D, target gene expression was normalized to ACTB and GAPDH relative to the shScr control. Data are shown as mean ± SD of the two house keeping genes (HKG). n = 3 for all experiments, excluding D for which n = 2.
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Expression of MMP24 mRNA was highly increased in all three H1975 cell clones express-
ing shAHR, which was significantly attenuated upon omeprazole treatment (Figure 15A).
These findings were confirmed by immunoblotting (Figure 15B). Furthermore, MMP19
expression was elevated in H1975 cell clones shAHR-K2 and shAHR-K3 (Figure 15C).
As we already demonstrated increased MMP9 activity in H1975 shAHR-K2 cells using
gelatine zymography (Figure 5D+E), we also investigated MMP9 expression using
qRT-PCR. MMP9 expression was moderately increased in H1975 shAHR-K2 compared
to shScr cells (Figure 15D). Importantly, in AHR-proficient cells (shScr) MMP9 expression
was repressed upon activation of AHR by omeprazole. This suggests an AHR-dependent
regulation despite the fact that MMP9 expression was not regulated in the two other cell
clones expressing shAHR.
Figure 16: RNA sequencing results suggest a role of AHR in the regulation of collagen expression. Normalized
counts from RNA sequencing for several collagens found to be differentially expressed with regard to AHR expression and activation. Data are shown as mean ± SD.
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Moreover, inspection of the list of EMT genes upregulated in AHR-deficient H1975 cells
in the GSEA (Figure 14D) revealed overexpression of several members of the collagen
family. Collagen is the major structural protein of the extracellular matrix and has been
linked to cancer progression and metastasis (Lee et al. 2019 , Liu et al. 2018 , Nerenberg
et al. 2007). H1975 cell clone K2 expressing shAHR showed high expression of COL12A1,
COL1A1, COL1A2, COL5A1, COL6A2 and COL7A1 as compared to the shScr control
(Figure 16). Additionally, expression of collagens was decreased by omeprazole treat-
ment in H1975 shAHR-K2 cells. Interestingly, collagen-crosslinking genes of the lysyl
oxidase family (LOX, LOXL1 and LOXL2) were positively correlated with AHR suppres-
sion (Figure 14D). These findings are to be validated using qRT-PCR and immunoblotting
as well as functional assays.
5.5.2 AHR activation regulates cellular stress responses in H1975
In contrast to the examined EMT markers being negatively regulated by AHR, results from
the GSEA suggested induction of cellular stress responses such as UPR upon activation
of AHR. In concordance with these results, expression of ASNS was strongly induced by
treatment with omeprazole as validated using qRT-PCR and immunoblotting. Here, treat-
ment with omeprazole elevated both mRNA and protein levels of ASNS, which was sig-
nificantly attenuated in all three H1975 shAHR cell clones (Figure 17A+B). Further,
activation of AHR by omeprazole induced expression of ATF4 and DNA damage inducible
transcript 3 (DDIT3 also known as CHOP), which are part of the UPR signaling cascade
(Figure 17C-E). Comparable to regulation patterns observed for ASNS, omeprazole-
mediated induction of ATF4 expression was dampened in shAHR-expressing H1975 cell
clones K1 and K2 (Figure 17C).
As ASNS has been suggested as direct target of ATF4 under nutritional stress conditions
(Ameri et al. 2010, Chen et al. 2004), we hypothesized that AHR-dependent regulation of
ASNS was mediated by ATF4 in our H1975 cell models. First, we demonstrated that acti-
vation of AHR by omeprazole not only induced expression of ASNS and ATF4 in H1975
but also in two other lung adenocarcinoma cell lines, H1299 and A549 (Figure 18A+B). In
addition, siRNA-mediated suppression of ATF4 completely blocked omeprazole-mediated
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induction of ASNS confirming the suggested regulatory axis (Figure 18A+B). The induc-
tion of ASNS and ATF4 was less profound in A549 compared to H1975 and H1299
cells (Figure 18B).
Figure 17: Suppression of AHR attenuates omeprazole-mediated induction of UPR signaling genes ASNS, ATF4 and CHOP. Expression of potential AHR targets in H1975 cell clones expressing shAHR (K1-K3) and shShr control was analyzed after treatment with omeprazole (omep, 200 µM, 48 h) or DMSO (-). A) ASNS expression assessed by qRT-pCR. Significance was evaluated by one-way ANOVA. B) ASNS protein levels assessed by immunoblotting. C) ATF4 protein levels assessed by immunoblotting. D)+E) ATF4 and CHOP expression was analyzed using qRT-PCR. For A, target gene expression was normalized to ACTB, GAPDH and HPRT1 relative to the shScr control. Mean ± SD of the three house keeping genes (HKG) is displayed. For D and E, target gene expression was normalized to ACTB and GAPDH relative to the shScr control. Mean ± SD of the two house keeping genes (HKG) is displayed. A-C n = 3, D und E n = 1 (indicated by #) or n = 2.
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Figure 18: AHR regulates ASNS expression in an ATF4-dependent manner. Prior to treatment with omeprazole (omep, 200 µM, 48 h), H1975, A549 and H1299 were transfected with siRNAs targeting ATF4 or a non-targeting control (siCtrl). A) Expression of ASNS and ATF4 was assessed using immunoblotting. Actin was used as control. B) qRT-PCR analysis of ASNS and ATF4 mRNA levels normalized to ACTB and GAPDH relative to the respective,
untreated siCtrl control. Mean ± SD of the two house keeping genes (HKG) is displayed. Significance was assessed using one-way ANOVA.
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Taken together, the findings from the GSEA (Figure 14) and the identification of an
AHR-ATF4-ASNS axis in lung adenocarcinoma (Figure 18) suggest that AHR interferes
with mediators of cellular stress responses as well as classical metastasis genes such
as MMPs.
5.5.3 ASNS and ATF4 are confirmed AHR targets in colorectal cancer cells
Regarding tumor initiation and progression, AHR has been controversially discussed
among different entities (D'Amato et al. 2015 , Jin et al. 2014 , Murray et al. 2014) raising
the question whether the regulatory axis of AHR with its targets ATF4 and ASNS could
also be validated in other entities.
To this end, we used two established colorectal cancer (CRC) cell lines that have been
derived from the primary tumor (SW480) and a metastatic lesion at a lymph node (SW620)
of the same patient (Leibovitz et al. 1976). Interestingly, AHR mRNA and protein expres-
sion was significantly reduced in SW620 compared to SW480 cells supporting our
hypothesis of AHR as a metastasis suppressor (Figure 19A+B). Further, ATF4 and ASNS
expression were induced upon omeprazole treatment in both CRC cell lines as demon-
strated by immunoblotting (Figure 19A) and qRT-PCR (Figure 19C+D). Omeprazole-
mediated induction of ASNS expression was attenuated in the metastatic cell line SW620
comparable to our findings in H1975 expressing shAHR (Figure 17A+B). In contrast to the
lung adenocarcinoma cell line, ATF4 expression was not decreased but increased in the
metastatic CRC cell line (Figure 19A+D).
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Figure 19: AHR and its targets ASNS and ATF4 are differentially regulated in a metastatic colorectal cell line compared to the corresponding primary, non-metastatic cells. A) Expression of AHR, ASNS and ATF4 was
detected in SW480 and SW620 cells with or without treatment with omeprazole (omep; 200 µM, 48 h) by immuno-blotting. Actin was used as a control. B-D) AHR, ASNS and ATF4 mRNA expression was assessed by qRT-PCR. Expression was normalized to the two house keeping genes (HKG) ACTB and GAPDH. Mean ± SD of the two HKG is
displayed relative to untreated SW480 cells. n = 3 for all experiments. Significance was assessed using one-way ANOVA.
5.6 AHR is involved in metabolic reprogramming
For metastasizing cancer cells, adaptation to metabolic stresses is of particular
importance during extravasation and metastatic seeding to survive and regain a prolif-
erative state in limiting nutrient conditions at a secondary site (Lambert et al. 2017 , Senft,
Ronai 2016). To investigate the impact of AHR on metabolic stress resistance, we mim-
icked these metabolic challenges by limiting cell culture conditions. Here, FBS and/or
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L-glutamine (L-Gln) was omitted from the culture medium or supplied at limiting concen-
trations. In an MTT assay, the proliferation of three independent H1975 cell clones ex-
pressing shAHR cells was significantly increased under L-Gln starvation and serum star-
vation as compared to H1975 shScr control (Figure 20A). To further confirm this response,
we performed a cell competition experiment in which either fluorescently labelled cell
clone H1975 shAHR-K2 or shScr control cells were mixed with their unlabeled counter-
parts (Mix A and Mix B, respectively, Figure 20B) and co-cultured for two weeks in the
absence or presence of L-Gln. Under normal cell culture conditions, H1975 shAHR-K2
cells were outcompeted by AHR-proficient cells (Figure 20C). However, depletion of L-Gln
resulted in significant enrichment of H1975 shAHR-K2 cells in the mixed cell population
(Figure 20C). These findings indicate that suppression of AHR enhances adaptation to
metabolic stress of lung adenocarcinoma cells.
Figure 20: Depletion of AHR increases resistance to L-glutamine withdrawal. A) Proliferation and metabolic via-
bility of H1975 expressing shAHR (K1-K3) or shScr depending on FBS and L-glutamine (L-Gln) levels was studied using MTT assay. Data are shown as mean ± SD normalized to respective control. Significance was assessed using one-way ANOVA. B) Schematic view of the mixing experiment. C) Relative amount of H1975 shScr and shAHR-K2 was
re-assessed after two weeks of co-cultivation in glutamine-deprived or normal culture settings during the mixing experiment using flow cytometry. n = 3 for all experiments.
Furthermore, we tested the effect of treatment with the glutaminase (GLS) inhibitor
CB-839 thereby limiting the supply of L-glutamate as an intermediate of the tricarboxylic
acid cycle (TCA) cycle. GLS inhibition significantly reduced proliferation of both
H1975 shAHR-K2 and shScr cells at a concentration of 10 µM, however, there was no
difference in sensitivity to CB-839 attributable to AHR expression levels (Figure 21).
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Figure 21: Suppression of AHR does not influence sensitivity to CB-839. MTT assay was used to assess prolif-
eration and metabolic activity of H1975 shScr and H1975 shAHR-K2 upon CB-839 treatment (72 ؘ h). Data are shown as mean ± SD normalized to respective control. Significance compared to respective control was assessed using one-way ANOVA.
Interestingly, parental H1975 cells were less sensitive to CB-839 treatment and L-Gln
withdrawal compared to A549 and H1299 cells as assessed by MTT assay
(Figure 22A+B). However, H1975 also showed decreased proliferation upon serum
reduction.
Figure 22: H1975 are less sensitive to CB-839 treatment and L-glutamine withdrawal compared to A549 and H1299. A) Effects of CB-839 on parental NSCLC cells was assessed after 72 h using MTT assay. B) Proliferation and
metabolic viability of parental NSCLC cells depending on FBS and L-glutamine (L-Gln) levels was studied using MTT assay. n = 3 for all experiments. Significance was assessed using one-way ANOVA. * display significance compared to respective control. # show significance between samples as indicated.
Nutrient supply is well known to limit tumor growth and in particular asparagine availability
mediated by ASNS was previously linked to metastasis (Knott et al. 2018). As we linked
suppression of AHR to both increased resistance to metabolic stress and dampened
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induction of ASNS upon AHR activation, we investigated whether the metabolic pheno-
type of AHR knockdown could be recapitulated by suppression of endogenous ASNS. To
this end, we generated H1975 cell clones with stable shRNA-mediated suppression of
ASNS expression. Knockdown of ASNS was confirmed by western blot analysis
(Figure 23A) and qRT-PCR (Figure 23B) for three cell clones (H1975 shASNS-K1, -K2
and -K3) expressing two distinct shRNAs (shASNS-A for K1 + K2, shASNS-B for K3,
Table 1 in 4.2.3).
Figure 23: Suppression of endogenous ASNS by stable integration of shASNS into H1975. ASNS protein and mRNA levels in H1975 shScr control and shASNS cell clones (K1-K3) were assessed by immunoblotting (A) and qRT-PCR (B). n = 3 for all experiments. For B, data are shown as mean ± SD. Significance was assessed using one-way
ANOVA.
As with the shAHR models, in vitro assays were used to assess the invasive capacity and
metabolic stress resistance of H1975 expressing shASNS or shScr. In contrast to AHR
knockdown, suppression of ASNS expression did not increase relative invasion in a
transwell migration invasion assay (Figure 24A+B), though migration of
H1975 shASNS-K2 was increased compared to shScr control (Figure 24A). MMP9 activity
was not elevated but even reduced in two cell clones expressing shASNS (Figure 24C+D).
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Figure 24: Suppression of ASNS does not result in increased invasiveness of H1975 cells in vitro. A) Number of
migrating and invading H1975 cells expressing shASNS or shScr were assessd using a transwell migration invasion assay. B) Relative invasion was calculated by dividing the mean number of invading by the mean number of migrating cells. C) MMP2 and MMP9 activity were assessed using gelatine zymography. D) Relative intensities of gelatinolytic
bands from MMP9 were quantified using ImageJ. n = 3 for all experiments. Data are shown as mean ± SD. Significance was assessed using one-way ANOVA.
ASNS is a metabolic enzyme converting aspartate and glutamine to asparagine and
glutamate (Andrulis et al. 1987 , Krall et al. 2016). Thus, we hypothesized that attenuation
of omeprazole-mediated induction of ASNS in AHR-deficient H1975 might rather affect
the metabolic reprogramming than alter the invasive capacity of cells. Indeed, two H1975
clones expressing shASNS showed moderately increased proliferation upon L-Gln
withdrawal in an MTT assay when compared to shScr control, though changes did not
reach significance (Figure 25). Taken together, ASNS knockdown was not sufficient to
fully phenocopy the effects of AHR knockdown.
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Figure 25: Suppression of ASNS does not significantly alter L-glutamine dependency. Proliferation and metabolic
viability of H1975 expressing shASNS (K1-K3) or shScr with regard to FBS and L-glutamine (L-Gln) levels was studied using MTT assay. Data are shown as mean ± SD normalized to respective control. Significance was assessed using one-way ANOVA.
Still, patient outcomes in cohorts with stage I adenocarcinomas showed correlation of high
ASNS expression with superior overall survival (Figure 26A) and lower likelihood of
progression (Figure 26B), suggesting a role of ASNS in the progression of early stage
NSCLC.
Figure 26: Impact of endogenous ASNS expression in lung adenocarcinoma on patient outcomes following resection. Overall survival (OS) and time to first progression (FP) of patients with stage I lung adenocarcinomas was
analyzed with regard to ASNS expression (205047_at) using the publicly available KM plotter tool (Győrffy et al. 2013). Cutoff lower tertile.
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5.7 In vivo stress assay
During metastatic progression, tumor cells accomplishing invasion of the microenviron-
ment surrounding the primary tumor and intravasation into the blood stream face unfavor-
able conditions during the transit in the circulation. Further, circulating tumor cells (CTCs)
need to extravasate to access secondary sites while being exposed to immune cells as
well as oxidative, nutritional and mechanical stress (Lambert et al. 2017).
Figure 27: Schematic overview of in vivo stress assay. Briefly, GFP-Luc+ H1975 shAHR-K2 and GFP-Luc+
H1975 shScr were pretreated with omeprazole (omep, 200 µM) or DMSO for 48 h and injected intravenously into C57BL/6 mice. Lungs, spleens and blood samples were collected from sacrificed mice after 5 min of incubation and subjected to analysis for GFP+ cells using flow cytometry.
In order to mimic mechanical and environmental stress during dissemination of tumor
cells, we performed an in vivo stress assay in which GFP-Luc+ AHR knockdown and
control cells were pretreated with omeprazole or DMSO and injected intravenously into
C57BL/6 mice. After 5 min, mice were sacrificed and blood, lung and spleen subjected to
further analysis for GFP+ cells (Figure 27).
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Figure 28: Effect of AHR expression and activation on environmental stress resistance and adhesion to the lung in vivo. GFP-Luc+ H1975 cells expressing shAHR (K2) or shScr were pretreated with omeprazole (omep, 200 µM,
48 h) or DMSO and then subjected to an in vivo stress assay. GFP+ cells in the blood and lung tissue were analyzed using flow cytometry. Absolute (A) and relative (B) number of GFP+ cells detected in blood samples is shown. C) Viability of GFP+ cells collected from blood samples was determined by DAPI exclusion. D) Relative amount of GFP+
cells deteced in lung samples after digestion. Data are shown as mean ± SD.
Interestingly, total numbers of detected GFP+ cells in the blood samples were rather low
among all treatment groups despite the short period of incubation (Figure 28A+B). Thus,
interpretation of the following survival analysis is limited due to low cell numbers. Never-
theless, neither suppression of AHR expression nor omeprazole treatment seemed to
confer a benefit for the survival of H1975 cells in the blood stream under these short-term
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stress conditions in vivo (Figure 28C). However, this finding has to be additionally vali-
dated. In order to investigate adhesion of H1975 shAHR-K2 and shScr cells to secondary
tissues, three lung lobes as well as the spleen from each mouse were processed for
detection of GFP+ cells by flow cytometry. In cell populations isolated from the spleens,
no GFP+ cells were detectable. Regarding tumor cell adhesion to the lung, no significant
difference could be concluded regarding AHR expression or activation due to high vari-
ance within the treatment groups (Figure 28D).
Figure 29: Effect of AHR expression and activation on adhesion to T-HUVEC cells in vitro. GFP-Luc+ H1975
shScr and GFP-Luc+ H1975 shAHR-K2 pretreated with omeprazole (omep, 48 h, 200 µM) or DMSO were added to a confluent monolayer of T-HUVEC and adhesion was analyzed after 20 min of incubation. Relative number of GFP+ cells was determined using flow cytometry. Data are shown as mean ± SD relative to untreated H1975 shScr control. n = 2.
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During metastatic dissemination, tumor cells face the challenge of extravasation initially
requiring adhesion to the endothelial cells of lymph or blood vessels. In order to further
investigate the impact of AHR on the adhesion of H1975 cells, we performed an in vitro
adhesion assay using immortalized human umbilical vein endothelial cells (T-HUVECs).
GFP-Luc+ H1975 cells expressing shAHR (K2) or shScr were pretreated with omeprazole
or DMSO and seeded on confluent monolayers of T-HUVECs. GFP+ cells adherent after
20 min were quantified by flow cytometry. Here, we did not detect any significant differ-
ence in the adhesion capacity of H1975 with regard to AHR expression or activation
(Figure 29), suggesting that AHR is not crucially involved in facilitating homing to second-
ary sites during metastasis of H1975 cells.
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Discussion
6 DISCUSSION
Curative treatment with long-term eradication of the tumor is the ultimate goal of cancer
therapy. However, despite major improvements in treatment and detection modalities,
curing cancer remains an unmet goal for the majority of patients with the exception of few
entities (Robert Koch-Institut 2016). Still, lung cancer shows one of the poorest clinical
outcomes not exceeding 20 % overall survival at five years which is mainly due to late
detection of disease, acquisition of therapy resistance and metastatic relapse (Herbst
et al. 2018, Robert Koch-Institut 2016). Although detection of lung cancer at early stage
was improved using low-dose CT scans, highly effective risk reduction therapies that
enhance curative potential of surgery are missing for patients with local or locally
advanced disease (Aberle et al. 2011 , Anderson et al. 2019 , Zhong et al. 2018). The
development of cancer therapies specifically targeting and preventing metastatic
progression would potentially increase curative capacity of treatment modalities.
6.1 AHR as a suppressor of lung cancer metastasis
Though several potential targets for anti-metastatic treatment approaches have been sug-
gested including but not limited to transforming growth factor-β (TGF-β) signaling, matrix-
metalloproteases (MMPs) and angiogenesis (Anderson et al. 2019 , Padua,
Massagué 2009), there is still no clinically approved treatment specifically targeting
cancer metastasis. This might be due to the fact that many of the preclinical models that
have been used to identify those targets do not reflect the complexity of the metastatic
disease. We hypothesized that identification and mechanistic evaluation of surrogates of
the metastatic process in lung cancer would be fundamental for the development of novel
anti-metastatic interventions.
Against this background, our group in collaboration with scientists from the UCSF Cancer
Center has performed an unbiased shRNA screen using an orthotopic mouse model of
lung cancer in order to identify putative modulators of non-small-cell lung cancer (NSCLC)
metastasis. Notably, this in vivo model comprises all stages of cancer metastasis including
dissemination, intra- and extravasation as well as metastatic colonization. Previously, we
have demonstrated that this model is qualified for the investigation of crucial factors in the
metastatic process (Okimoto et al. 2017). For the in vivo screen, the two NSCLC cell lines
H1975 and A549 were used that display low and high metastatic potential, respectively.
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Discussion
Further, H1975 cells exhibit constitutively activated epidermal growth factor receptor
(EGFR) signaling due to two mutations L858R and T790M, and are thus commonly used
as a model for EGFR-mutant lung cancer (Sordella et al. 2004). Implementation of non-
metastatic H1975 allowed for the identification of metastatic modulators initiating lung
cancer metastasis when suppressed by specific shRNAs from a barcoded shRNA library.
Among others, we here identified aryl hydrocarbon receptor (AHR) as a significantly
overrepresented shRNA target in metastases compared to primary tumors suggesting
metastasis-suppressing functions for AHR (5.1).
AHR is a ligand-regulated transcription factor involved in numerous signaling pathways
mediated by both endogenous and xenobiotic ligands (Esser et al. 2018 , Murray
et al. 2014). Due to the direct exposure of the lung to cigarette smoke and environmental
pollutants, initially, AHR and its activation by xenobiotics has been mainly considered to
promote tumorigenesis in lung cancer (Guerrina et al. 2018 , Tsay et al. 2013). Further,
immunohistochemistry demonstrated elevated expression of AHR in lung carcinomas
compared to healthy tissue supporting the impact of AHR in tumorigenesis (Lin
et al. 2003). Although being previously described as pro-tumorigenic factor (D'Amato
et al. 2015, Murray et al. 2014, Opitz et al. 2011 , Shimizu et al. 2000), emerging evidence
suggests a more complex role for AHR in carcinogenesis and tumor progression in which
AHR functions are regulated in an entity-, stage- and ligand-dependent manner (Murray
et al. 2014). Analyses of the impact of AHR on triple-negative breast cancer (TNBC)
showed conflicting results regarding the formation of metastases. While AHR activation
by omeprazole reduced metastatic spread in a mouse model of breast cancer, tryptophan
2,3-dioxygenase (TDO2)-mediated production of kynurenine was shown to activate AHR
which in turn enhanced invasive and metastatic capacity of TNBC cells (D'Amato et al.
2015, Jin et al. 2014). Moreover, kynurenine-mediated activation of AHR suppressed
tumor immunity and increased cancer cell motility in malignant brain tumors (Opitz et al.
2011). Most recently, treatment with kynurenine has also been demonstrated to impair
metastatic spread of subcutaneously transplanted neuroblastoma cells in an in vivo
mouse model (Wu et al. 2019a). However, the role of AHR in lung cancer metastasis has
not yet been functionally and mechanistically confirmed in an orthotopic model of lung
cancer.
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Discussion
To the best of our knowledge, we here validated AHR for the first time as a suppressor of
metastasis in a legit in vivo model of metastasis in EGFR-mutant lung cancer (5.4). By
allowing for orthotopic tumor growth and spontaneous formation of metastases from the
primary tumor site, the sequential cascade of metastasis is fully recapitulated. Here,
targeted suppression of AHR enabled metastatic spread of non-metastatic H1975 cells.
Importantly, low intratumoral AHR expression was associated with inferior clinical out-
comes of patients harboring early stage adenocarcinomas supporting our findings (5.4).
6.2 Mechanistic insights to AHR-regulated metastatic pathways
Despite intensive research in the field of cancer metastasis, the picture of its molecular
mechanisms is not yet completely understood and further exhibits stage- and entity-
dependent differences.
Within this thesis, we uncovered AHR-mediated regulation of metastatic programs in
ligand-induced and constitutive expression patterns using functional and mechanistic
studies (5.5, 5.6). Acquisition of mesenchymal features by tumor cells via epithelial-
mesenchymal transition (EMT)-like processes increases tumor cell invasiveness facili-
tating evasion from the primary tumor site (Chaffer, Weinberg 2011 , Lambert et al. 2017).
Using RNA sequencing technology, we demonstrated that higher AHR expression as well
as omeprazole-mediated activation of AHR decreased EMT signatures in H1975 shScr
cells compared to AHR-deficient cells, thus suggesting a negative correlation between
AHR and EMT (5.5.1). Hence, silencing of AHR expression during cancer progression
might endow tumor cells with increased invasive capacity allowing for local invasion of the
surrounding tumor microenvironment.
The loss of epithelial adhesion molecules such as E-cadherin has been demonstrated to
occur in cells undergoing EMT and was suggested to be advantageous for the process of
metastatic progression (Polyak, Weinberg 2009 , Wirtz et al. 2011). In this work, suppres-
sion of AHR expression in H1975 cells increased cell scattering in tumor cell spheroids
indicating alteration in intercellular adhesion (5.2). Further, colorectal cancer cells
excluded form tumor spheroids showed increased invasiveness (Stadler et al. 2018) and
the loss of E-cadherin was associated with decreased density of spheroids (Ivascu,
Kubbies 2007 , Stadler et al. 2018). As E-cadherin expression was sustained in our H1975
AHR knockdown model, altered spheroid formation ability was not caused by loss of
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Discussion
E-cadherin. However, targeted suppression of AHR increased N-cadherin expression
suggesting a potential role for AHR in the regulation of adhesion molecules (5.2).
Recently, Beerling at al. demonstrated epithelial-mesenchymal plasticity in metastasizing
cells of mammary tumors without exogenous EMT inducers in a mouse model using intra
vital microscopy (Beerling et al. 2016). Additionally, sustained E-cadherin expression dur-
ing metastatic progression has been suggested to be crucial for tumor growth upon
hypoxia (Chu et al. 2013). Interestingly, suppression of E-cadherin was observed during
collective invasion of breast cancer cells allowing for partial perpetuation of intercellular
cohesion whereas its complete loss blocked cell tether formation and ultimately sup-
pressed metastasis formation in vivo (Elisha et al. 2018). In our RNA sequencing analysis,
not only AHR expression but also its ligand-mediated activation affected expression of
EMT gene sets (5.5, 8.1, Supplementary Figure 1). Thus, AHR could potentially mediate
temporary transition between epithelial and mesenchymal cell states depending on the
presence or absence of endogenous ligands. The interplay between EMT-activating
endogenous factors such as TGF-β or hypoxia and AHR expression and activation seems
a promising field to investigate. Interestingly, AHR expression was described to attenuate
basal and TGF-β-induced EMT in murine keratinocytes and epithelial NMuMG cells (Rico-
Leo et al. 2013).
In order to enter the circulation, disseminating tumor cells have to overcome and degrade
the extracellular matrix (ECM) as well as the basement membrane (BM) surrounding the
primary tumor. Degradation of ECM molecules facilitates tumor cell invasion and migration
(Conlon, Murray 2019). In H1975, targeted suppression of AHR was associated with ele-
vated expression of several MMPs including MMP9, MMP19 and MMP24 stressing a role
of AHR in acquisition of invasive phenotypes in EGFR-mutant adenocarcinomas (5.5.1).
In concordance with our results from the AHR knockdown model, Okimoto et al. demon-
strated MMP24-dependent gain of metastatic competence in H1975 cells after genomic
loss of Capicua (CIC) (Okimoto et al. 2017). Importantly, CIC knockout was excluded to
be present in our AHR-deficient cells suggesting an alternative mechanism for MMP
induction (8.1, Supplementary Figure 2). However, the possibility of a post-transcriptional
suppression of CIC mediated by MAPK-ERK signaling as proposed by Okimoto et al. has
not yet been investigated in our AHR knockdown cells. As MMPs are usually secreted as
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Discussion
inactive precursors, we analyzed MMP9 and MMP2 activity using gelatine zymography
(Kleiner, Stetler-Stevenson 1994). Indeed, MMP9 activity was increased in H1975 with
pronounced AHR suppression (5.2). Interestingly, El-Badrawy et al. demonstrated
increased MMP9 expression and activity in NSCLC over healthy tissue which was further
associated with late stage disease (El-Badrawy et al. 2014). Additionally, VEGFR1-
dependent induction of MMP9 in lung endothelial cells has been shown to form pre-
metastatic niches for lung-specific metastasis (Hiratsuka et al. 2002). Hence, AHR-
dependent regulation of MMPs might be a promising target to reduce local invasion as
well as formation of pre-metastatic niches induced by secretion of MMPs.
A reciprocal modulation of EMT and ECM has been demonstrated in several studies.
Collagen, as one of the major components of the ECM, has been implicated in tumor
progression and metastatic homing to the lung (Lee et al. 2019, Liu et al. 2018, Nerenberg
et al. 2007). Our RNA sequencing results indicate an upregulation of several types of
collagens and collagen-crosslinking enzymes of the lysyl oxidase family upon suppression
of AHR expression (5.5.1). Interestingly, Peng et al. demonstrated increased collagen
deposition and ZEB1-mediated crosslinking of planar collagen fibers in metastatic tumors
compared to non-metastatic tumors in a mouse model of lung cancer using subcutaneous
transplantation (Peng et al. 2017). Furthermore, signaling via collagen binding receptors
such as discoidin domain-containing receptor 1 (DDR1) was demonstrated to increase
invasiveness and metastatic homing to the lung in bladder cancer models (Lee
et al. 2019). Synthesis of collagen was inhibited upon activation of AHR in a study using
intestinal fibroblasts (Monteleone et al. 2016) further supporting an AHR-mediated
regulation of collagen formation, stabilization and signaling. Collectively, our findings
strongly support an impact of AHR on EMT-mediated matrix remodeling and on the tumor
microenvironment.
During metastatic progression, disseminating tumor cells are exposed to numerous stress
stimuli including oxidative pressure as well as nutrient and oxygen limiting conditions
(Lambert et al. 2017). Interestingly, activation of AHR by omeprazole was associated with
increased unfolded protein response (UPR) signaling as demonstrated in the gene set
enrichment analysis (5.5, 5.5.2). In contrast to exhibiting increased EMT and MMP activity,
AHR-deficient cells appeared to attenuate omeprazole-induced stress response genes
75
Discussion
including activating transcription factor 4 (ATF4), DNA damage inducible transcript 3
(DDIT3 also known as CHOP) and asparagine synthetase (ASNS). Previously, ATF4 has
been demonstrated to induce ASNS in oncogenic KRAS models (Gwinn et al. 2018).
Figure 30: Proposed regulatory AHR-ATF4-ASNS axis. AHR-dependent induction of ASNS expression is ATF4-
dependent and attenuated in H1975 expressing shAHR which exhibit increased metastatic potential.
Using RNAi, we here could demonstrate for the first time that induction of ASNS
expression by activation of AHR via omeprazole is requiring ATF4 in oncogenic EGFR-
and Ras-driven adenocarcinomas (5.5.2). This strongly supports our hypothesis of a
regulatory AHR-ATF4-ASNS axis in lung cancer (Figure 30). Further, omeprazole-
mediated induction of CHOP expression, a key mediator in ER stress-induced apoptosis
that is transcriptionally regulated by ATF4, was attenuated upon AHR knockdown (5.5.2).
The UPR signaling is induced by ER-stress, hypoxia, oxidative stress and nutritional
limitations leading to intrinsic activation of apoptotic pathways in the absence of adaptation
processes (Vandewynckel et al. 2013). Our results demonstrate suppressed induction of
UPR signaling in AHR-deficient H1975 cells which might confer survival advantages upon
exogenous stress stimuli experienced during metastatic dissemination. The impact of
AHR on expression and activation of UPR mediators after exogenous stress remains to
be experimentally determined. Additionally, AHR activation mediated the induction of
ASNS and ATF4 in colorectal cancer (CRC) cells suggesting a potential general validity
also in other entities (5.5.3). Additionally, SW620 cells derived from the metastatic lesion
76
Discussion
of a CRC patient displayed lower AHR expression as well as attenuated ASNS induction
compared to the non-metastatic SW480 cells derived from the primary tumor from the
same patient. Hence, AHR apparently was downregulated before or upon metastatic pro-
gression in this patient-derived CRC model complementing our concept of AHR as
metastatic suppressor.
Once that a growing tumor exceeds two millimeter in diameter, cancer cells start to get
deprived of nutrients and oxygen (Weber 2016). In order to evade apoptosis induced by
persistent nutrient lack or hypoxia, cancer cells exhibit major remodeling of metabolic
dependencies and pathways (Elia et al. 2018 , Vandewynckel et al. 2013). Tumor cells
show increased glucose uptake and catabolism via oxidative glycolysis, also known as
Warburg effect. However, this phenomenon is frequently replaced by alternative routes of
energy supply during metastasis as the lack of cellular adhesion impairs the glucose
metabolism (Celià-Terrassa, Kang 2016 , Elia et al. 2018 , Weber 2016). Thus, the
important role of supply with other metabolites such as amino acids has been discussed
more recently with regard to tumor progression.
Emerging evidence suggests a rate-limiting role for cytosolic aspartate in terms of tumor
growth under glutamine deprived conditions (Alkan et al. 2018). Further, aspartate was
limiting for tumor growth under hypoxic conditions as mimicked by electron transport chain
(ETC) inhibition (Garcia-Bermudez et al. 2018 , Sullivan et al. 2018). Garcia-
Bermudez et al. showed that expression of SLC1A3, an aspartate-glutamate transporter,
can rescue sensitivity to ETC inhibition by enabling the import of aspartate from the extra-
cellular space (Garcia-Bermudez et al. 2018). However, no evidence for SLC1A3 expres-
sion was found in our cell model. In contrast, exogenous supply with asparagine could
rescue growth arrest of cancer cells under glutamine deprivation (Pavlova et al. 2018). In
our AHR knockdown models, ATF4-mediated induction of ASNS was repressed and fur-
ther a decreased sensitivity to glutamine withdrawal was found (5.5.2, 5.6). ASNS is a
metabolic enzyme converting asparagine form aspartate in a glutamine- and ATP-
dependent manner (Andrulis et al. 1987, Krall et al. 2016). Thus, we hypothesize that
blockade of ASNS induction in AHR-deficient cancer cells shifts the equilibrium to
increased cytosolic aspartate levels which in turn might facilitate cancer cell growth under
limiting nutrient and oxygen conditions. Although targeted suppression of ASNS partially
77
Discussion
mimicked the phenotype of AHR-deficient H1975 with regard to glutamine dependency, it
was not sufficient to phenocopy the alterations in the metastatic capacity in terms of
invasion and MMP activity (5.6). Hence, AHR modulates additional, ASNS-independent
programs to suppress lung cancer metastasis.
Taken together, downregulation of endogenous AHR increased metabolic stress
resistance of lung cancer cells suggesting a dynamic role of AHR in metabolic reprogram-
ming potentially regulated by varying exogenous stimuli such as endogenous indole
derivatives including kynurenine. Due to the highly artificial nutrient conditions applied
during in vitro settings, the impact of AHR on metabolic programs in EGFR-mutant lung
cancer needs to be validated using in vivo models.
Upon dissemination, epithelial cancer cells require alteration of their intercellular adhe-
sions in order to overcome their immobility and enable translocation from the primary
tumor. Here, the concept of phenotypic plasticity has been introduced by Nieto et al. sug-
gesting EMT-related phenotypic changes including the regulation of epithelial and
mesenchymal adhesion molecules (Nieto et al. 2016).
Albeit we did see AHR-mediated alterations in spheroid formation capacity and expression
of adhesion molecules, the adhesion of H1975 to endothelial cells was not affected by
AHR expression or activation neither in vitro nor in vivo (5.3, 5.7). However, as tumor cell
transplantation was achieved by intravenous injection in the absence of a primary tumor,
there are some limitations to conclusions drawn from this experiment as this model fails
to recapitulate the complexity of the metastatic cascade. On the other hand, these results
might also imply that the suppression of AHR is more relevant for invasion and/or
metastatic seeding, which are mostly neglected in this experimental setting. As emerging
evidence suggest a crucial role for colonization during the metastatic process, the impact
of AHR expression and activation on metastatic seeding and outgrowth of metastases
should be analyzed in more detail. Further, AHR has been implicated in the regulation of
immune effector cells and suppression of tumor immunity (Gutiérrez-Vázquez,
Quintana 2018, Rothhammer, Quintana 2019). As we here evaluated the impact of
endogenous AHR in human adenocarcinoma models H1975 and A549, our in vivo
experiments were limited to immunocompromised mouse strains. Although the role of
AHR on immune system functions are certainly important, results obtained from
78
Discussion
immunocompetent mouse models will be of limited value due to only 80 % sequence
homology of murine and human AHR. Therefore, humanized mouse model or
retrospective analysis of patient samples should be considered.
6.3 AHR-regulated pathways as a target in anti-metastatic therapy of lung cancer
Current therapies to prevent or target metastases are basically the same as applied for
eradication of the primary tumor disregarding their biological differences. Development of
effective anti-metastatic therapies therefore requires dissection of molecular mechanisms
underlying metastatic progression to identify specific targets that are crucial for the
formation of metastases (Anderson et al. 2019 , Lambert et al. 2017).
Our findings are complemented by clinical data from publicly available databases (5.4,
(Győrffy et al. 2013)), which indicate that evaluation of AHR expression in primary adeno-
carcinomas after resection is promising to identify a subgroup of patients facing a higher
risk to suffer from metastatic relapse. However, the validity of AHR as a clinical biomarker
remains to be determined by additional clinical trials. Further, it is tempting to speculate
that hyperactivation of suppressed AHR and AHR-regulated anti-metastatic programs in
a neoadjuvant or adjuvant setting might prevent metastatic progression in early stage lung
cancer. A variety of xenobiotic as well as some endogenous AHR agonist have been iden-
tified that exhibit different binding affinities and induce tissue- and ligand-specific regula-
tion patterns (Denison, Faber 2017 , Murray et al. 2014). Thus, the complexity of regulatory
networks induced upon AHR activation as well as the evidence for pro-tumorigenic func-
tions of AHR have to be carefully considered in terms of therapeutic interventions targeting
AHR and its downstream effectors. Activation of AHR by its ligand omeprazole has been
suggested to inhibit cancer cell metastasis in preclinical models of breast cancer (Jin
et al. 2014). Interestingly, omeprazole is a proton pump inhibitor (PPI), which is commonly
utilized in the treatment of co-morbidities during the therapy of cancer patients
(Tvingsholm et al. 2018). However, the administration of omeprazole could not yet been
linked to clinical outcomes of cancer patients (An et al. 2018). Further, an accurate evalu-
ation whether PPIs impact clinical outcomes with special regard to metastatic progression
might be challenging due to its frequent application among cancer patients and therefore
lack of control groups. The role of other AHR ligands in the therapy of lung cancer remains
to be investigated.
79
Discussion
With regard to matrix remodeling and invasion, MMP inhibitors were considered as
potential anti-metastatic therapeutics. However, broad spectrum MMP inhibitors such as
marimastat and prinomastat failed to show robust clinical activity until now while showing
serious adverse effects. This might be due to the fact that clinical trials were conducted in
late stage disease in contrast to the preclinical models starting treatment before or soon
after tumor implantation (Anderson et al. 2019 , Overall, Kleifeld 2006 , Zucker et al. 2000).
However, the development of more specific MMP inhibitors might improve safety profiles
and enable their application in adjuvant treatment settings in order to prevent metastasis
in high-risk populations. Further, small molecule inhibitors targeting lysyl oxidases have
demonstrated anti-metastatic effects in preclinical models (Anderson et al. 2019 , Tang
et al. 2017).
In our studies, UPR signaling was significantly attenuated in AHR-deficient H1975 cells
exhibiting gain of metastatic capacity (5.5, 5.5.2). Therefore, reactivation of these path-
ways might be capable to induce UPR-mediated apoptosis in disseminated cancer cells.
However, therapeutic targeting of the UPR remains challenging due to the complexity of
the UPR signaling network including alternative routes of activation that could cause
severe adverse effects (Vandewynckel et al. 2013). Administration of global UPR activa-
tors such as thapsigargin have been demonstrated to provoke acute toxicity, so that tar-
geted strategies are more promising and currently under investigation (Axten et al. 2012).
As we demonstrated suppression of ASNS inducibiltiy in both metastatic H1975 shAHR
and SW620 cells as compared to their non-metastatic controls (5.5.2, 5.5.3), reactivation
of this pathway might present a promising strategy to prevent metastatic seeding.
However, ASNS knockdown was not sufficient to recapitulate the gain in metastatic
capacity as observed in H1975 upon AHR loss. Hence, other AHR-mediated pathways
should be prioritized for therapeutic interventions. Still, a better mechanistic understanding
of metabolic dependencies is of great interest for the diagnosis and therapy of metastases.
In order to investigate the clinical correlation of AHR and its targets identified in this study
including ASNS, ATF4 and MMP24, we are currently establishing protocols for the retro-
spective analysis of tissue from resected lung cancer patients using RNA scope in collab-
oration with the pathology of the University Hospital Essen.
80
Discussion
Stratification of patients by AHR expression and activation signatures should be further
validated. If these findings substantiate, they could complement established treatment
modalities such as adjuvant chemo-, radio- or targeted therapy potentially and ultimately
improve OS and progression free survival (PFS) in patients with lung adenocarcinomas.
6.4 Conclusion and outlook
In summary, our findings strongly support a role for AHR as suppressor of lung cancer
metastasis. Downregulation of endogenous AHR conferred a metastatic phenotype in a
legit in vivo model. AHR is a sensor and regulator of the endogenous defense system
against xenobiotic chemicals being responsible for their decomposition and elimination.
AHR suppression in lung cancer cells correlated with increased metabolic stress
resistance and invasiveness. Intriguingly, we here show that AHR orchestrates anti-
metastatic programs which require suppression in order to enable metastatic progression.
The clinical relevance of our findings is supported by the inferior outcomes of patients with
early stage or advanced lung adenocarcinomas exhibiting low endogenous AHR expres-
sion. Thus, AHR regulated pathways display promising therapeutic targets in the preven-
tion of metastasis in lung cancer. However, the complexity of AHR signaling networks and
pleiotropic effects requires careful study design to achieve the intended clinical outcomes.
Further, AHR has been demonstrated to regulate tumor immunity suggesting a potential
role of AHR for the immune evasion during metastatic progression.
Altogether, our findings validate AHR as suppressor of metastasis of EGFR-mutant lung
cancer and suggest AHR-regulated anti-metastatic programs as potential targets for the
development of novel and specific pharmacologic strategies to prevent metastasis in early
stage lung cancer.
81
References
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Appendix
8 APPENDIX
8.1 Supplementary figures
Supplementary Figure 1: Gene set enrichment analysis links AHR activation to the EMT cancer hallmark. A) Enrichment plot for gene set ‘Epithelial-Mesenchymal-Transition’ (EMT) enriched in H1975 shScr control (shScr -) compared to the shScr omeprazole (shScr +). B) Enrichment plot for gene set ‘Epithelial-Mesenchymal-Transition’
(EMT) enriched in H1975 shAHR-K2 control (shAHR -) compared to the shAHR-K2 omeprazole (shAHR +). Biological replicates are indicated with I, II and III.
Supplementary Figure 2: No genetic loss of Capicua (CIC) was detected in H1975 expressing shAHR. CIC expression in H1975 shScr and H1975 shAHR-K2 (A) and GFP+Luc+ H1975 shScr and H1975 shAHR-K2 cells (B) was assessd by qRT-PCR analysis. mRNA levels were normalized to ACTB and GAPDH relative to the respective control. Mean ± SD of the two house keeping genes (HKG) is displayed. Significance was assessed using student’s t-test.
102
Appendix
8.2 Materials and reagents
8.2.1 Eukaryotic cell lines
Table 7: Cell lines used and established in this project.
cell line tissue properties source
A549 human lung
adenocarcinoma
KRAS Codon 12
mutation (G12S),
EGFR
overexpression
Molecular
Oncology group,
purchased from
ATCC
NCI-H1299 (referred to
as H1299)
human lung
adenocarcinoma
p53 deletion, NRAS
mutation (Q61K)
Molecular
Oncology group,
purchased from
ATCC
NCI-H1975 (referred to
as H1975)
human lung
adenocarcinoma
EGFR double
mutation (L858R,
T790M)
Molecular
Oncology group,
purchased from
ATCC
H1975 shRNA AHR K1 human lung
adenocarcinoma
cell clone K1 stably
transduced with
pLKO.1-shRNA
AHR vector
present work
H1975 shRNA AHR K2 human lung
adenocarcinoma
cell clone K2 stably
transduced with
pLKO.1-shRNA
AHR vector
present work
H1975 shRNA AHR K3 human lung
adenocarcinoma
cell clone K3 stably
transduced with
pLKO.1-shRNA
AHR vector
present work
H1975 shRNA ASNS K1 human lung
adenocarcinoma
cell clone K1 stably
transduced with
pGFP-V-RS -shRNA
ASNS-A vector
present work
H1975 shRNA ASNS K2 human lung
adenocarcinoma
cell clone K2 stably
transduced with
pGFP-V-RS -shRNA
ASNS-A vector
present work
103
Appendix
H1975 shRNA ASNS K3 human lung
adenocarcinoma
cell clone K3 stably
transduced with
pGFP-V-RS -shRNA
ASNS-B vector
present work
H1975 shScr (lenti) human lung
adenocarcinoma
stably transduced
with pLKO.1-non
targeting shRNA
present work
H1975 shScr (retro) human lung
adenocarcinoma
stably transduced
with pGFP-V-RS-
non targeting
shRNA
present work
HEK283FT human embryonic
kidney
viral packaging cells Scholl/Fröhling
group
hTERT-HUVEC
(T-HUVEC)
human umbilical
vein endothelial
cells
immortalized with
expression of
hTERT
Grüner group
Phoenix (FNX) human embryonic
kidney
viral packaging cells Nolan lab,
Stanford
University, USA
SW480 human colorectal
carcinoma
established from
primary tumor
Molecular
Oncology group,
purchased from
ATCC
SW620 human colorectal
carcinoma
established from
metastatic
recurrence in lymph
node from the same
patient as SW480
Molecular
Oncology group,
purchased from
ATCC
104
Appendix
8.2.2 Plasmids and primers
Table 8: Plasmids used and generated in this project.
name properties manufacturer
EGFP-ffluc epHIV7 lentiviral vector encoding
EGFP and Luciferase
Dr. Michael Jensen,
Seattle
Hit60 (MLV gag-pol) retroviral packaging vector
(gag-pol expression)
C. Benedict
MSCV-tdTomato-PGK-
Neo
retroviral vector, neomycin
resistance
Dr. Barbara M.
Grüner
MSCV-PGK-Neo
(referred to as MSCV
vector or empty vector)
MSCV-tdTomato-PGK-Neo
truncated for tdTomato
Dr. Sophie Kalmbach
MSCV-CDS-AHR (AHR
rescue vector)
CDS of AHR with 5 silent
point mutations cloned into
MSCV-PGK-Neo
present work
pCMV.VSV-G retroviral packaging vector
(envelope protein
expression)
W. Nishioka
pGFP-V-RS shRNA scr
retroviral vector with non-
targeting shRNA, puromycin
resistance
OriGene
pGFP-V-RS
shRNA ASNS-A
retroviral vector with shRNA-
A targeting ASNS,
puromycin resistance
OriGene
pGFP-V-RS
shRNA ASNS-B
retroviral vector with shRNA-
B targeting ASNS,
puromycin resistance
OriGene
pLKO.1-shRNA AHR lentiviral vector with shRNA
targeting AHR gene,
puromycin resistance
Sigma-Aldrich
pLKO.1-shRNA scr lentiviral vector with non-
mammilian target shRNA,
puromycin resistance
Sigma-Aldrich
pMD2.VSV-G lentiviral packaging vector
(envelope protein
expression)
Scholl/Fröhling group
pSPAX lentiviral packaging vector
(gag-pol expression)
Scholl/Fröhling group
105
Appendix
Table 9: Oligonucleotide primers used for qRT-PCR. All primers are targeting human genes.
gene sequence (5’ - 3’) comment
ACTB For - GGATTCCTATGTGGGCG
Rev - GGCGTACAGGGATAGC
AHR For - TACCGAAGACCGAGCTGAAT
Rev - GGAGACCAGTGGCTTCTTCA
ATF4 For - n/a Qiagen QuantiTect®
Primer Assay Rev - n/a
ASNS For - TCACTTCCAATATGATCTGCCA IDT RTU mix
Rev - AGTACAGTATCCTCTCCAGACA
CDH1 For - TGCCCAGAAAATGAAAAAGG
Rev - GTGTATGTGGCAATGCGTTC
CDH2 For - ACAGTGGCCACCTACAAAGG
Rev - CCGAGATGGGGTTGATAATG
CHOP For - AGAACCAGGAAACGGAAACAGA
Rev - TCTCCTTCATGCGCTGCTTT
CIC For - TGGAGGGAAAGATGTCTGCA
Rev - ATGACAAGGTGCCATACTCC
CYP1A1 For - CCCAGCTCAGCTCAGTACCT
Rev - AGGCCCTGATTACCCAGAAT
GAPDH For - ATTGCCCTCAACGACCACT
Rev - TCTTCCTCTTGTGCTCTTGCT
HPRT1 For - GCGATGTCAATAGGACTCCAG IDT RTU mix
Rev - TTGTTGTAGGATATGCCCTTGA
MMP9 For - GCACGACGTCTTCCAGTACC (Safranek et al.
2009) Rev - CAGGATGTCATAGGTCACGTAGC
MMP19 For - TTCCGAGTGTCTGCCCTTTG
Rev - ATCCATTGTGTTCGAGGCGA
MMP24 For - GGGGCGAGATGTTTGTCTTT
Rev - TCCCATCGGCCCTTTCATAG
106
Appendix
8.2.3 Antibodies
Table 10: Antibodies used in this project.
antibody source manufacturer
primary antibodies
anti-Actin mouse MP Biomedicals
anti-AHR rabbit Cell Signaling
anti-ASNS rabbit Thermo Fisher Scientific
anti-ATF4 rabbit Cell Signaling
anti-MMP24 rabbit GeneTex
secondary antibodies
anti-mouse (HRP-
conjugated)
goat Pierce Antibodies
anti-rabbit (HRP-
conjugated)
goat Pierce Antibodies
8.2.4 Commercial kits
Table 11: Commercial kits used in this project.
kit manufacturer
GeneArtTM Site-Directed Mutagenesis System
Kit
Thermo Fisher Scientific
LightCycler 480 SYBR Green I Master Roche Molecular Systems, Inc.
PCR Purification Kit Qiagen
High Pure RNA Isolation Kit Roche Molecular Systems, Inc
One ShotTM Stbl3TM E. coli invitrogen
QIAGEN Plasmid Plus Maxi Kit Qiagen
QIAprep Spin Miniprep Kit Qiagen
QIAquick Gel Extraction Kit Qiagen
RNeasy Mini Kit Qiagen
Screen Tape Kit Agilent
Trans-Blot® Turbo™ RTA Mini Nitrocellulose
Transfer Kit
BioRad
Transcriptor High Fidelity cDNA Synthesis Kit Roche Molecular Systems, Inc
107
Appendix
8.2.5 Chemicals
Table 12: Chemicals and reagents used in this project.
chemical/reagent manufacturer
3-(4,5-Dimethylthiazole-2-yl)-2,5-diphenyl-2H-
tetrazolium bromide (MTT)
Carl Roth
acetic acid Carl Roth
acrylamide solution (Rothiphorese Gel 30) Carl Roth
agarose Thermo Fisher Scientific
ammonium persulfate (APS) Merck
ampicillin Sigma-Aldrich
aqua (A. dest) Braun
bromphenol blue Sigma-Aldrich
Circlegrow® (Capsules) MP Biomedicals
collagenase PAN BioTech
comassie Blue Roth
cOmplete protease inhibitor cocktail 25X Roche
4′,6-diamidino-2-phenylindole (DAPI) Carl Roth
dimethylsulfoxid (DMSO) Sigma-Aldrich
DNaseI Sigma-Aldrich
entellan Merck
ethanol absolute Sigma-Aldrich
ethidium bromide solution (0.025%) Carl Roth
ethylenediaminetetraacetic acid (EDTA) Carl Roth
fetal bovine serum (FBS) PAN Biotech
HEPES Carl Roth
gelatine (porcine) Sigma-Aldrich
glyerol Carl Roth
glycine Carl Roth
isopropanol Merck
kanamycin Carl Roth
methanol Fluka
β-mercaptoethanol Carl Roth
Nonidet® P 40 Substitute
[Nonylphenylployethylene glycol] (NP40)
Fluka
O’GeneRulerTM DNA Ladder Mix Fermentas
omeprazole Sigma-Aldrich
Page Ruler Pre-Stained Protein Ladder Fermentas
PBS powder 9.55 g/l, w/o Ca2+, w/o Mg2+ Biochrom
108
Appendix
phosphatase Inhibitor Cocktail 2 Sigma-Aldrich
phosphatase Inhibitor Cocktail 3 Sigma-Aldrich
polybrene Sigma-Aldrich
ponceau S Carl Roth
puromycin, dihydratechloride Calbiochem
sodium chloride Carl Roth
sodium deoxycholate Fluka
sodium dodecyl sulfate (SDS) pellets Carl Roth
T4 DNA ligase New England Biolabs
tetramethylethylenediamine (TEMED) Sigma-Aldrich
TRIS Carl Roth
triton X-100 Carl Roth
tween-20 Carl Roth
8.2.6 Media, reagents and commercial buffers
Table 13: Media, reagents and commercial buffers used in this project.
media/reagent/buffer manufacturer
6X Orange DNA Loading Dye Fermentas
AccuPrime Polymerase invitrogen
bradford reagent BioRad
collagenase IV PAN Biotech
crystal violet solution, 1%, aqueous Sigma-Aldrich
dispase Corning
DMEM gibco
D-PBS, w/o Ca2+, w/o Mg2+ gibco
FuGene HD Transfection Reagent Promega
fibronectin Merck
Leibovitz’s L-15 medium Thermo Fisher Scientific
L-glutamine 200 mM (L-Glu) gibco
Lipofectamine® RNAiMAX Reagent invitrogen
MISSION® esiRNA targeting human ATF4 Sigma-Aldrich
MISSION® siRNA Universal Negative Control Sigma-Aldrich
neomycin (G418) Carl Roth
opti-MEM I Reduced Serum Medium gibco
Penicillin-Streptomycin (Pen/Strep) gibco
Restore™ Western Blot Stripping Buffer Thermo Fisher Scientific
RPMI Medium 1640 gibco
109
Appendix
SuperSignalTM West Pico Chemiluminescence
Substrate
Thermo Fisher Scientific
SuperSignalTM West Femto
Chemiluminescence Substrate
Thermo Fisher Scientific
T4 DNA Ligase Buffer (10X) New England Biolabs
0.05% trypsin-EDTA (1X) gibco
trypan Blue stain 0.4% invitrogen
8.2.7 Buffers and solutions
Table 14: Buffers and solutions used in this project. If not indicated otherwise A. dest was used to prepare buffers.
buffer/solution components
10X NET-G 1.5 M NaCl
50 mM EDTA
500 mM Tris-HCl, pH 7.5
0.5 % Tween-20
0.4 % gelatine (porcine)
5X non-reducing zymography
sample buffer
400 mM Tris, pH 6.8,
5 % SDS
20 % gycerol
0.03 % bromphenol blue
5X SDS-PAGE running buffer 125 mM Tris
960 mM glycine
175 mM SDS
5X SDS-PAGE sample buffer 250 mM Tris-HCl (pH 6.8)
8 % SDS
40 % glycerol
200 mM β-Mercaptoethanol
0.2 % bromphenol blue
50X TAE 2 M Tris
250 mM acetic acid
50 mM EDTA
10X ACK buffer 1.5 M NH4Cl
100 mM KHCO3
10 mM EDTA
blocking solution (1X NET-G) 10X NET-G diluted 1:10
digestion medium 1 mg/ml collagenase IV
10 % dispase
10 % trypsin-EDTA (0.05%)
110
Appendix
in HBSS-free (w/o Ca2+ and Mg2+)
FACS buffer 2 % FBS
in D-PBS
FACS buffer (for in vivo stress
assay)
2 % FBS
2 mM EDTA
in D-PBS
MTT solution 5 mg/ml MTT
in D-PBS
MTT solubilization buffer 10% SDS
0.01 M HCl
NP40 lysis buffer 50 mM HEPES
250 mM NaCl
5 mM EDTA
0.1 % NP40
before use complemented with
1:25 cOmplete 25X stock solution,
1:100 Phosphatase Inhibitor Cocktail 2 & 3
ponceau S solution 0.2 % ponceau S
5 % acetic acid
RIPA lysis buffer
150 mM NaCl
50 mM Tris-HCl (pH 8)
1 % triton X-100
0.5 % sodium deoxycholate
0.1 % SDS
before use complemented with
1:25 cOmplete 25X stock solution,
1:100 Phosphatase Inhibitor Cocktail 2 & 3
quench solution 10 % FBS
18.75 mg/ml DNaseI
in L15 medium
SDS-PAGE stacking gel solution 5 % acrylamide
126 mM Tris-HCl, pH 6.8
0.1 % SDS
0.1 % APS
0.1% TEMED
SDS-PAGE resolving gel solution 8-12 % acrylamide
380 mM Tris-HCl, pH 8.8
0.1 % SDS
0.1 % APS
0.04% TEMED
111
Appendix
zymography enzyme buffer 50 mM Tris-HCl, pH 7.5
200 mM NaCl
5 mM CaCl2
1 % Triton X-100
8.2.8 Restriction enzymes and buffers
Table 15: Restriction enzymes and buffers used in this project.
name concentration manufacturer
FspAI 5 U/µl Thermo Fisher Scientific
BglII 10 U/µl Thermo Fisher Scientific
buffer O 10X Thermo Fisher Scientific
8.2.9 Consumables
Table 16: Consumables used in this project.
item manufacturer
0.2 µm filter Sartorius
0.45 µm filter Sartorius
10 cm dishes BD Falcon
6 well plate BD Falcon
12 well plate BD Falcon
15 ml Falcon tubes Greiner bio-one
24 well plate BD Falcon
40 µm cell mesh BD Falcon
50 ml Falcon tubes Greiner bio-one
96 well plate Corning
96 well plate with cell repellent surface Greiner bio-one
BioCoatTM GFR Matrigel Invasion
Chambers (8.0 µm)
Corning
BioCoatTM control inserts (8.0 µm) Corning
CountessTM cell counting chamber slides invitrogen
cuvettes, semi-micro, PS LLG Labware
eppendorf tubes Eppendorf
FACS tubes Greiner bio-one
microscope slides VWR
cover slips VWR
pasteur pipettes Brand
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Appendix
pipette tips Greiner bio-one
serological pipettes Greiner bio-one
8.2.10 Technical equipment
Table 17: Technical equipment used in this project.
device manufacturer
AxioObserver.Z1 Zeiss
BD FACSVantage SE BD Biosciences
BIOREVO BZ-9000 Keyence
centrifuges
SORVALL® RC 6 PLUS
Rotor: SLA-1500
Heraeus MultiFuge 3RS+
Rotor: Swing-out rotor, 4-place
Mikro 200R
Rotor: Angle rotor, 24-place
Thermo Scientific
Thermo Scientific
Thermo Scientific
DJB Labcare
Hettich
Hettich
Chemiluminescence-imager
Chemi Smart 5000
Vilber Lourmat
Countess automated cell counter Invitrogen
FACSCelestaTM BD
Heraeus Function Line Thermo Scientific
Incubator HeraCell 1500 CO2 Thermo Fisher Scientific
LightCycler®480 System Roche
Mini-PROTEAN electrophoresis system Bio-Rad
Orbital shaker Sigma-Aldrich
pH electrode InoLab pH720 WWTW
Photometer Gene Quant pro Amersham
NanoDrop lite spectrophotometer Thermo Fisher Scientific
Power Pac 300 BioRad
Primovert microscope Zeiss
Protein electrophoresis system BioRad
Roller mixer SRT6D stuart
Screen Tape Station Agilent
Thermomixer 5436 Eppendorf
Trans-Blot® Turbo™ Transfer System BioRad
Vortexer Bio Vortex V1 Biosan
Water bath 1013 GFL
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Appendix
8.2.11 Software
BD FACSDiva (BD Biosciences)
FlowJo Software (BD Biosciences)
GraphPad Prism (GraphPad Software, version 6)
GSEA software (Broad Institute, Inc., Massachusetts Institute of Technology, version 3.0)
Perseus software (Max Planck Institute for Biochemistry, Martinsried, version 1.5.5.3)
Primer3 (www.primer3plus.com)
Adobe Illustrator CS3 (Adobe Systems)
Adobe Photoshop CS3 (Adobe Systems)
Affinity Designer (Serif, version 1.7.1.404)
ImageJ (Wayne Rasband, NIH, US)
8.3 List of figures
Figure 1: Overview of the metastatic cascade. .............................................................. 17
Figure 2: Model of cellular plasticity through transitional EMT/MET states. ................... 21
Figure 3: Unbiased in vivo shRNA screen using an orthotopic mouse model of lung
cancer. ........................................................................................................................... 40
Figure 4: Suppression of endogenous AHR by stable integration of shAHR into H1975
cells. .............................................................................................................................. 41
Figure 5: shRNA-mediated suppression of AHR increases metastatic potential of H1975
cells in vitro. ................................................................................................................... 42
Figure 6: Intercellular adhesion is altered upon suppression of AHR in H1975 cells. .... 43
Figure 7: AHR cDNA resistant to shAHR was successfully introduced into H1975 cell
models expressing shAHR or shScr. ............................................................................. 45
Figure 8: Reconstitution of AHR expression in H1975 with shRNA-mediated AHR
suppression partially rescued metastatic phenotype observed in vitro. ......................... 46
Figure 9: Targeted suppression of AHR increases metastatic spread of H1975 in an
orthotopic lung cancer mouse model. ............................................................................ 47
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Appendix
Figure 10: Impact of endogenous AHR expression in lung adenocarcinoma on patient
outcomes following resection. ........................................................................................ 48
Figure 11: Impact of endogenous AHR expression in lung adenocarcinoma on patient
outcomes among all disease stages. ............................................................................. 49
Figure 12: Omeprazole inhibits growth of H1975 cells in an AHR-dependent manner. . 50
Figure 13: Constitutive and induced expression signatures of H1975 shAHR cell models
were identified using mRNA sequencing. ...................................................................... 51
Figure 14: Gene set enrichment analysis links AHR expression and activation to several
cancer hallmarks. .......................................................................................................... 53
Figure 15: AHR regulates expression of matrix-metalloproteases (MMPs) in H1975. ... 54
Figure 16: RNA sequencing results suggest a role of AHR in the regulation of collagen
expression. .................................................................................................................... 55
Figure 17: Suppression of AHR attenuates omeprazole-mediated induction of UPR
signaling genes ASNS, ATF4 and CHOP. ..................................................................... 57
Figure 18: AHR regulates ASNS expression in an ATF4-dependent manner................ 58
Figure 19: AHR and its targets ASNS and ATF4 are differentially regulated in a metastatic
colorectal cell line compared to the corresponding primary, non-metastatic cells. ........ 60
Figure 20: Depletion of AHR increases resistance to L-glutamine withdrawal. .............. 61
Figure 21: Suppression of AHR does not influence sensitivity to CB-839. .................... 62
Figure 22: H1975 are less sensitive to CB-839 treatment and L-glutamine withdrawal
compared to A549 and H1299. ...................................................................................... 62
Figure 23: Suppression of endogenous ASNS by stable integration of shASNS into
H1975. ........................................................................................................................... 63
Figure 24: Suppression of ASNS does not result in increased invasiveness of H1975 cells
in vitro. ........................................................................................................................... 64
Figure 25: Suppression of ASNS does not significantly alter L-glutamine dependency. 65
Figure 26: Impact of endogenous ASNS expression in lung adenocarcinoma on patient
outcomes following resection. ........................................................................................ 65
Figure 27: Schematic overview of in vivo stress assay. ................................................. 66
Figure 28: Effect of AHR expression and activation on environmental stress resistance
and adhesion to the lung in vivo. ................................................................................... 67
115
Appendix
Figure 29: Effect of AHR expression and activation on adhesion to T-HUVEC cells in vitro.
...................................................................................................................................... 68
Figure 30: Proposed regulatory AHR-ATF4-ASNS axis. ............................................... 75
Supplementary Figure 1: Gene set enrichment analysis links AHR activation to the EMT
cancer hallmark. .......................................................................................................... 101
Supplementary Figure 2: No genetic loss of Capicua (CIC) was detected in H1975
expressing shAHR. ...................................................................................................... 101
8.4 List of tables
Table 1: Sequences for shRNAs targeting AHR or ASNS. ............................................ 27
Table 2: PCR program for generation of full-length CDS of AHR. ................................. 28
Table 3: Primer sequences for cloning of rescue vector. ............................................... 29
Table 4: Reaction mixes for restriction digest of MSCV backbone and AHR PCR product.
...................................................................................................................................... 29
Table 5: Primer sequences for AHR mutagenesis. ........................................................ 34
Table 6: Standard protocol for qRT-PCR at LightCycler®480. ...................................... 35
Table 7: Cell lines used and established in this project. .............................................. 102
Table 8: Plasmids used and generated in this project. ................................................ 104
Table 9: Oligonucleotide primers used for qRT-PCR. .................................................. 105
Table 10: Antibodies used in this project. .................................................................... 106
Table 11: Commercial kits used in this project. ........................................................... 106
Table 12: Chemicals and reagents used in this project. .............................................. 107
Table 13: Media, reagents and commercial buffers used in this project. ..................... 108
Table 14: Buffers and solutions used in this project. ................................................... 109
Table 15: Restriction enzymes and buffers used in this project. .................................. 111
Table 16: Consumables used in this project. ............................................................... 111
Table 17: Technical equipment used in this project. .................................................... 112
116
Appendix
8.5 List of abbreviations
ACTB actin beta
AHR aryl hydrocarbon receptor
AJ adherens junction
ANOVA analysis of variance
ALK anaplastic lymphoma kinase
ARNT aryl hydrocarbon receptor nuclear translocator
ASNS asparagine synthetase
ATF4 activating transcription factor 4
ATP adenosine triphosphate
BaP benzo[a]pyrene
BLI bioluminescent imaging
BM basement membrane
BRAF serine/threonine-protein kinase B-raf
BSL-2 biosafety level 2
CBCT cone-beam computed tomography
CDS coding sequence
CFRT conventionally fractionated radiation therapy
CHOP aliase for DDIT3
CM conditioned medium
CNS central nervous system
COL12A1 collagen type XII alpha 1 chain
COL1A1 collagen type I alpha 1 chain
COL1A2 collagen type I alpha 2 chain
COL5A1 collagen type V alpha 1 chain
COL6A2 collagen type VI alpha 2 chain
COL7A1 collagen type VII alpha 1 chain
CRC colorectal cancer
CSC cancer stem cell
CT computed tomography
117
Appendix
CTC circulating tumor cell
CTLA4 cytotoxic T-lymphocyte antigen-4
CYP cytochrome P450
CYP1A1 cytochrome P450 family 1 subfamily A member 1
DDIT3 DNA damage inducible transcript 3
DDR1 discoidin domain-containing receptor 1
DTC disseminated tumor cell
DNA deoxyribonucleic acid
DS desmosome
ECM extracellular matrix
EGFP enhanced green fluorescent protein
EGFR epidermal growth factor receptor
EMT epithelial-mesenchymal transition
EMT-TF epithelial-mesenchymal transition transcription factors
ETC electron transport chain
EV empty vector
FADH2 flavin adenine dinucleotide dihydrogen
FBS fetal bovine serum
FGF fibroblast growth factor
FNX phoenix cells
FP time to first progression
GAPDH glyceraldehyde-3-phosphate dehydrogenase
GFP green fluorescent protein
GFP+ GFP-positive
GLS glutaminase
GLUT1 glucose transporter 1
GSEA gene set enrichment analysis
HER2 human epidermal growth factor 2
HER4 human epidermal growth factor 4
HGF hepatocyte growth factor
118
Appendix
HKG house keeping gene
HPRT1 hypoxanthine phosphoribosyltransferase 1
HRP horseradish peroxidase
HUVEC human umbilicial vein endothelial cells
IL-2 interleukin-2
IMRT intensity modulated radiation therapy
IFN interferon
L-Gln L-glutamine
log2FC log2-fold change
LOX Llysyl oxidase
LOXL1 lysyl oxidase like 1
LOXL2 lysyl oxidase like 2
Luc Luciferase
MET mesenchymal-epithelial transition
miR microRNA
MMP matrix-metalloprotease
mRNA messenger ribonucleic acid
MTT 3-(4,5-Dimethylthiazole-2-yl)-2,5-diphenyl-2H-tetrazolium bromide
NADH nicotinamide adenine dinucleotide hydrogen
ns not significant
NSCLC non-small-cell lung cancer
NTRK neurothrophic tropomyosin receptor kinases
omep omeprazole
OS overall survival
Padj adjusted P-value
PCR polymerase chain reaction
PD-1 programmed cell death-1
PD-L1 programmed cell death ligand-1
PFS progression free survival
PPI proton pump inhibitor
119
Appendix
qRT-PCR quantitative real-time PCR
RET proto-oncogene tyrosine-protein kinase receptor Ret
RNA ribonucleic acid
ROS reactive oxygen species
ROS1 proto-oncogene tyrosine-protein kinase ROS
RT room temperature
SBRT stereotactic body radiation therapy
SCLC small-cell lung cancer
shAHR shRNA targeting AHR
shASNS shRNA targeting ASNS
shRNA small hairpin ribonucleic acid
shScr non-mammalian target shRNA control
STR short tandem repeat
TAA tumor-associated antigens
TCA tricarboxylic acid cycle
TCDD 2,3,7,8-tetrachlorodibenzo-p-dioxin
TEM trans-endothelial migration
TGF-β transforming growth factor-β
T-HUVECs hTERT human umbilicial vein endothelial cells
TJ tight junction
TKI tyrosine kinase inhibitor
TME tumor microenvironment
TNBC triple-negative breast cancer
UCSF University of California, San Francisco
UPR unfolded protein response
VEGF vascular endothelial growth factor
VEGFR2 vascular endothelial growth factor receptor 2
XRE xenobiotic responsive elements
120
Acknowledgements
9 ACKNOWLEDGEMENTS
The work presented in this thesis was supported by funding from the ‘Förderverein Innere
Klinik - Tumorforschung - Essen e.V’ of the University Hospital Essen.
First of all, I would like to thank my supervisor, Prof. Dr. Martin Schuler, for the great
opportunity to perform my PhD project in the Laboratory of Molecular Oncology at the
Department of Medical Oncology of the University Hospital Essen. Further, I would like to
express my deep gratitude for his continuous support, invaluable counsel and guidance.
Special thanks also to Dr. Frank Breitenbücher for the opportunity to be involved in this
interesting and fruitful project as well as for his supervision and all the helpful advice.
Further, I would like to thank him and Dr. Ross A. Okimoto for all their work on the shRNA
screen and the orthotopic mouse model conducted in the group of Dr. Trever G. Bivona
at the UCSF. Additional thanks to Dr. Saurabh Asthana for performing the statistical
analyses of the sequencing data of the shRNA screen.
Many thanks also to Prof. Dr. Alexander Schramm for the supervision and counsel in the
last two years helping to forward the project and prepare the manuscript. Also, I highly
appreciate his rapid proofreading of this thesis.
In addition, I would like to acknowledge the support and advice of Dr. Barbara M. Grüner,
in particular invaluable during the period of lab transitions.
A huge ‘thank you’ to Dr. Sophie Kalmbach for all her support and strength especially
during the times of our ‘two-women lab’. Without you I would not have made it. Further,
I want to thank Jeannette Phasue, Dr. Sarah Wieczorek and Stephanie Meyer for all their
encouragement and the great atmosphere in the ‘AG Schuler lab’. Special thanks also to
Madeleine Dorsch for her scientific input, methodological advice and mental support as
well as to Dr. Marc Schulte for all the productive discussions particularly appreciating his
innovative ideas. Further, I would like to deeply thank Clotilde Thumser-Henner,
Cassandra Ho and Christina Hassiepen not only for their help in the lab but also for their
continuous support and so many fabulous lunch times – of course including Madeleine.
Thank you also to Alicia Tüns, Sabine Dreesmann and Anja Lingott-Frieg for their support
with my experiments and to Sebastian Vogt for solving all sorts of problems occurring in
the lab.
121
Acknowledgements
Moreover, I would like to acknowledge the contribution of the group of Prof. Dr. Michael
Hölzel at the University of Bonn performing the mRNA sequencing and Jan Forster from
the DKTK who conducted the RNA sequencing data preparation. Additional thanks to all
other co-authors that have contributed to this project and provided input for the
manuscript. Further, I would like to thank Prof. Dr. Jens Siveke for providing access to his
laboratory devices as well as Dr. Marija Trajkovic-Arsic, Dr. Sven-Thorsten Liffers and
Konstantinos Savvatakis for their helpful advice. Many thanks also to Prof. Dr. Karl S.
Lang for giving me access to his Keyence microscope. I would like to give credit to the
group of Dr. Alexander Carpinteiro, especially Gabriele Hessler and Melanie Kramer, as
well as to the group of PD Dr. Iris Helfrich, particularly Dr. Stefanie Löffek, for sharing their
methodological and scientific knowledge. Further, I am grateful for the possibility to be
part of the BIOME graduate school and want to thank Delia Cosgrove for the coordination.
Last but not least, I am especially indebted to my family and friends for their unfailing
support and continuous encouragement. Ladies, I am exceptionally grateful for our deep
friendship and want to thank you for all your enduring support and the sorely needed
distractions. Especially, I wish to give thanks to my partner for lovingly bearing with me
also in heavily stressful phases and continuously fostering my confidence. Thank you to
my sister and my brother for providing help and shelter whenever needed. Additional
thanks to my sister and mother for proofreading this thesis. Finally, I am inexpressively
grateful to my parents providing unconditional support, invaluable advice and always
believing in me.
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Curriculum Vitae
10 CURRICULUM VITAE
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123
Curriculum Vitae
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124
Curriculum Vitae
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125
Declarations
11 DECLARATIONS
Erklärung:
Hiermit erkläre ich, gem. § 6 Abs. (2) g) der Promotionsordnung der Fakultät für Biologie
zur Erlangung der Dr. rer. nat., dass ich das Arbeitsgebiet, dem das Thema „Identification
and characterization of aryl hydrocarbon receptor (AHR) as a suppressor of non-small-
cell lung cancer metastasis“ zuzuordnen ist, in Forschung und Lehre vertrete und den
Antrag von Silke Nothdurft befürworte und die Betreuung auch im Falle eines Weggangs,
wenn nicht wichtige Gründe dem entgegenstehen, weiterführen werde.
________________________________________
Name des Mitglieds der Universität Duisburg-Essen in Druckbuchstaben
Essen, den _________________ ________________________________________
Unterschrift eines Mitglieds der Universität Duisburg-Essen
Erklärung:
Hiermit erkläre ich, gem. § 7 Abs. (2) d) + f) der Promotionsordnung der Fakultät für
Biologie zur Erlangung des Dr. rer. nat., dass ich die vorliegende Dissertation selbständig
verfasst und mich keiner anderen als der angegebenen Hilfsmittel bedient, bei der
Abfassung der Dissertation nur die angegeben Hilfsmittel benutzt und alle wörtlich oder
inhaltlich übernommenen Stellen als solche gekennzeichnet habe.
Essen, den _________________ _______________________________________
Unterschrift des/r Doktoranden/in
Erklärung:
Hiermit erkläre ich, gem. § 7 Abs. (2) e) + g) der Promotionsordnung der Fakultät für
Biologie zur Erlangung des Dr. rer. nat., dass ich keine anderen Promotionen bzw.
Promotionsversuche in der Vergangenheit durchgeführt habe und dass diese Arbeit von
keiner anderen Fakultät/Fachbereich abgelehnt worden ist.
Essen, den _________________ _______________________________________
Unterschrift des/r Doktoranden/in