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Long-term expansion of human alveolar epithelial cells as a novel model system to study lung disease progression in vitro

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Long-term expansion of human alveolar epithelial cells as a novel model system to study lung disease progression in vitro

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Content 1 Long-term expansion of human alveolar epithelial cells as a novel model system to study lung disease progression in vitro. By Evelyn Tran _____________________________________________________ A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirement for the Degree DOCTOR OF PHILOSOPHY GENETIC, MOLECULAR, AND CELLULAR BIOLOGY August 2019 Copyright 2019 Evelyn Tran 2 To Evelyn: Because I never thought you could, … But you did, … And here you are. With love from Evelyn 3 Acknowledgements I am inclined to list out every single person who has meant something to me over the past eight years of my time at USC as a graduate student –but I will not. As I look forward to a new chapter in my professional and personal career, I want to embrace change. So, in light of making a change in myself, I want to keep my words of gratitude short, so that the feelings associated with it may shine through. Thank you, Committee Members, Dr. Beiyun Zhou, Dr. Ram Subramanyan, and Dr. Ite Offringa for your patience and support of my project. I greatly appreciate you taking time to meet for my ARAs and for my defense. Your comments and criticisms are invaluable. Thank you, Ite, for teaching me how to do science the right way – by doing it all the wrong way, learning to pick myself back up, then doing it the right way. Thank you for encouraging me, even when I don’t readily accept the encouragement. Thank you to the Offringa Lab members for tolerating my chattiness, my need to take pictures of everything, and my overall weirdness. Thank you for making me laugh and engaging in after-hours talks (even at 11 am). Thank you to the Marconett Lab for being respectful neighbors and, again, tolerating my chattiness. Thank you to the Borok Lab for sharing protocols and reagents (antibodies!) and offering advice and criticism on my experimental designs and overall project goal. Thank you to the Minoo Lab for housing much needed Core equipment. I know it is awkward to have outside lab members share your lab space, so for being so patient with me in particular, I am grateful. Thank you to Dr. Changgong Li and Dr. Fremont Gao for helpful discussions on my project. Thank you, Sophia Petraki and Jing Gao of the Ryan (Firth) Lab for introducing me to the Echo Revolve microscope – what a game changer for my project! Thank you to Yibu Chen and Meng Li of the USC NML Bioinformatics Core for helping me process all my RNA-seq data, introducing me to the wonders of Partek Flow, and helping me through interface with USC’s HPCC server. Thank you for taking time out to respond to me numerous emails. Thank you to the Hastings Center for Pulmonary Research Core for providing access to microscopes and tissue embedding equipment. Thank you to Bernadette Masinsin and Jeff Boyd of the USC Stem Cell Flow Cytometry Core for help with FACS. Thank you, Rose Hills Foundation for awarding me a fellowship for my first 3 years in the PhD program. I never thought I would receive such an award during my time as a grad student, much less before I joined! I am grateful to the members for believing in my potential. I am also extremely grateful to whoever nominated me for this fellowship! Lastly, I want to thank everyone who has interacted with me throughout my near decade-long PhD experience. I will not list each person here because you all know who you are: If I have conversed, laughed, cried, thrown a tantrum, shared my personal stories, vented, or complained to you at any point, yes, you are a part of this long list. Edder, if it weren’t for you, I would not be here at USC. Also, to my fur-babies – thank you for teaching me how to love unconditionally! Woof to you guys, too! 4 Table of Contents Dedication ………………………………………………………………………………………...2 Acknowledgements ……………………………………………………………………………….3 Table of Contents …………………………………………………………………………………4 List of Figures …………………………………………………………………………………….6 List of Tables ……………………………………………………………………………………..7 Abbreviations ……………………………………………………………………………………..8 Chapter 1: INTRODUCTION ……………………………………………………………………9 A Brief Overview of the Lung …………………………………………………………..10 Lung Cancer: Statistics and Subtypes …………………………………………………...11 Mutational Landscape of Lung Cancer ………………………………………………….15 Methods for Studying Lung Cancer ……………………………………………………..19 Non-cancer Cell Models for Studying Lung Cancer ……………………………………25 Generating a Refined Cell Model to Study Lung Adenocarcinoma …………………….33 Chapter 2: MATERIALS AND METHODS ……………………………………………………36 Ethics Statement …………………………………………………………………………37 Isolation and culture of primary human alveolar epithelial cells Mycoplasma and rodent pathogens testing Derivation of human alveolar epithelial cell lines ………………………………………39 Construction of lentiviral plasmids and production of viral particles Lentiviral transduction of human alveolar epithelial cells ………………………………40 Proliferation assay ……………………………………………………………………….41 Anchorage-independent growth assay Quantitative PCR ………………………………………………………………………..42 Karyotyping Three-dimensional co-culture Treatment with Wnt agonist or FGF cocktail Histological Processing ………………………………………………………………….44 Immunofluorescence staining Statistical Analyses ……………………………………………………………………...45 RNA-seq Analyses ………………………………………………………………………46 Chapter 3: RESULTS …………………………………………………………………………...49 Direct transduction results in ineffective immortalization ………………………………49 Optimization of culture media conditions ………………………………………………53 Derivation of a collection of proliferative AEC cell lines ………………………………57 Characterization of the transformation state of AEC cell lines …………………………60 5 Derivation of additional AEC cell lines from two normal lungs ………………………..66 AEC cell lines are transcriptionally distinct …………………………………………….71 AEC-LT cells exhibit expression features of lung progenitor cells …………………….80 AEC-LT cells retain the ability to form lung spheroids ………………………………...83 AEC-LT spheroids robustly express alveolar epithelial markers ……………………….91 Activation of WNT or FGF signaling on AEC-LT spheroids …………………………..98 CONCLUSIONS ………………………………………………………………………102 Chapter 4: DISCUSSION ……………………………………………………………………...103 Chapter 5: FUTURE DIRECTIONS …………………………………………………………..114 Transcriptomically profile AEC-LT-derived spheres at the single-cell level …………115 Investigate AT1 plasticity ……………………………………………………………...117 Investigate epithelial-mesenchymal interactions ………………………………………118 Track stepwise molecular alterations during lung carcinogenesis ……………………..118 Investigate differences in intrinsic cell susceptibility to genetic alterations .…………..120 Screen novel chemotherapeutic drugs …………………………………………………121 Investigate the effects of environmental exposures ……………………………………122 Investigate the effect of ethnic/racial diversity in lung cancer ………………………...122 REFERENCES ………………………….……………………………………………………..124 Chapter 1: Introduction References ……………………………………………………125 Chapter 2: Materials and Methods References ………………………………………...136 Chapter 3: Results References …………………………………………………………136 Chapter 4: Discussion References ……………………………………………………..139 Chapter 5: Future Directions References ………………………………………………143 6 List of Figures Figure 1. Cell types of the lung ………………………………………………………………….11 Figure 2. Estimated cases and deaths for lung cancer for 2019 …………………………………12 Figure 3. Percent of lung cancer cases by stage and 5-year survival rate ……………………….12 Figure 4. Lung cancer mutational burden ……………………………………………………….16 Figure 5. Lung Adenocarcinoma and Lung Squamous Cell Carcinoma driver genes …………..18 Figure 6. Cell cycle regulation …………………………………………………………………..27 Figure 7. Schematic of lentiviral plasmids ……………………………………………………...51 Figure 8. Morphologies of AECs following different transduction methods …………………...52 Figure 9. Relative expression of AEC markers in new AEC-ROCKinh cells …………………..55 Figure 10. Representative fluorescent images of transduced AEC-ROCKinh cells …………….58 Figure 11. Alveolar epithelial cell line derivation scheme ……………………………………...59 Figure 12. Proliferation assay on AEC cell lines ………………………………………………..61 Figure 13. Proliferation assay at higher density …………………………………………………61 Figure 14. Proliferation assay of AEC-ROCKinh cells at P4 vs P6 …………………………… 63 Figure 15. Anchorage-independent growth assays on AEC cell lines …………………………..64 Figure 16. Derivation scheme for two additional AEC-LT cell lines …………………………...68 Figure 17. Proliferation assay on AEC-LT biological replicate cell lines ………………………69 Figure 18. Anchorage-independent growth assays on AEC-LT replicates ……………………...70 Figure 19. Sample-sample distance matrix of AEC cell lines compared to other cells …………74 Figure 20. PCA plot of AEC cell lines and other cell samples ………………………………….75 Figure 21. Unsupervised hierarchical clustering of top 500 most variable genes ………………76 Figure 22. Heatmap of 75 lung-related genes ………………………………………………..77-79 Figure 23. Box-and-whiskers plot of SOX2 and SOX9 expression in AEC cell lines ………….81 Figure 24. Immunofluorescence staining for SOX2 and SOX9 ………………………………...82 Figure 25. Illustration of three-dimensional co-culture set up …………………………………..84 Figure 26. Optimization of MLgs in three-dimensional co-culture system ……………………..85 Figure 27. AEC-LT-derived spheres form from a single-cell suspension ………………………86 Figure 28. Time course growth images of AEC-LT-derived sphere ……………………………87 Figure 29. Quantitation of sphere size and percent formation efficiency ………………….........89 Figure 30. Phase contrast images of spheres showing diverse shapes …………………………..91 Figure 31. Composite DAPI-stained images of sphere sections showing lumen structure ….93-94 Figure 32. Immunofluorescence staining of sphere sections for AEC markers ……………..95-96 Figure 33. Additional staining images for AQP5 ……………………………………………97-98 Figure 34. Treatment of three-dimensional co-cultures with CHIR and FGF cocktail ………..101 Figure 35. Comparison of AEC-ON-LT12E4 sphere shape to published organoid …………...111 Figure 36. Representative images of AEC-ON-LT12E4 spheres collected for single-cell seq ..116 7 List of Tables Table 1. List of mycoplasma test primers ……………………………………………………….38 Table 2. List of RNA-seq data from ENCODE and DBTSS …………………………….……...48 Table 3. Summary of growth media tested to expand alveolar epithelial cells …………………56 Table 4. Summary of calculated population doubling times for AEC cell lines ………………..63 Table 5. De-identified lung donor information ………………………………………………….66 Table 6. Summary of cell line derivation strategies …………………………………………….67 Table 7. Calculated population doubling times for AEC-LT replicates ………………………...69 Table 8. List of RNA-seq data sources used in this study ………………………………………73 Table 9. Summary of metrics for AEC-LT-derived spheres …………………………………….88 Table 10. Summary of metrics for treated AEC-LT-derived spheres …..……………………...100 8 Abbreviations PNEC, pulmonary neuroendocrine cell AEC, alveolar epithelial cell AT2, alveolar epithelial type 2 cell AT1, alveolar epithelial type 1 cell IPF, idiopathic pulmonary fibrosis COPD, chronic obstructive pulmonary disease NSCLC, non-small cell lung cancer SCLC, small cell lung cancer LUAD, lung adenocarcinoma LUSQ, lung squamous cell carcinoma NKX2-1, NK2 Homeobox-1 (also known as TTF-1, thyroid transcription factor-1) TP63, tumor protein 63 KRT5, keratin 5 EGFR, epidermal growth factor receptor KRAS, Kirsten rat sarcoma ALK, anaplastic lymphoma kinase receptor PTEN, phosphatase and tensin homolog FGFR1, fibroblast growth factor receptor 1 PIK3CA, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha EML4, Echinoderm microtubule-associated protein-like 4 RB, retinoblastoma protein TCGA, The Cancer Genome Atlas IRES, internal ribosome entry site CDK4, cyclin-dependent kinase 4 hTERT, human telomerase (catalytic subunit) SV40 LgT, Simian virus 40 Large T antigen HBEC, human bronchial epithelial cell SAEC, small airway epithelial cell MLg, mouse neonatal lung fibroblast DAPI, 4′,6-diamidino-2-phenylindole ECAD, E-cadherin AQP5, Aquaporin-5 HOPX, homeodomain-only protein homeobox CSC, cigarette smoke condensate 9 Chapter 1 INTRODUCTION 10 A Brief Overview of the Lung The lung is divided into three general regions: the upper airways, the small airways, and the distal/alveolar space. The lung epithelium is comprised of different cell types with specialized functions. Figure 1 illustrates the different types of cells of the lung with associated gene markers. In the upper airways, the trachea divides into two main bronchi, which then bifurcate into primary bronchi. Along the primary bronchi, basal, secretory (goblet and Clara cells), and ciliated cells predominate, together orchestrating the trapping and removal of inhaled airborne pathogens and particulates [Rackley and Stripp, 2012; Tata and Rajagopal, 2017]. In the small airways where the bronchi branch into increasingly smaller bronchioles, fewer ciliated cells and rare pulmonary neuroendocrine cells (PNECs) are observed. Transitioning towards the alveolar space, there is a noticeable absence of basal cells lining the epithelium [Tata and Rajagopal, 2017]. Alveolar sacs are composed of cuboidal, surfactant-producing type 2 cells (AT2) and large, flattened type 1 cells (AT1) which are sites of gas exchange [Tata and Rajagopal, 2017; Rock and Hogan, 2011; Rackley and Stripp, 2012]. From lung injury studies in mice, basal, Clara, and AT2 cells exhibit stem cell characteristics, possessing the ability to self-renew and transdifferentiate to re-populate the damaged epithelium [Beers and Morrisey, 2011]. Based on the great number of lung cells found to possess some regenerative properties under different conditions, it is easy to think that the lung is resistant to disease. On a day-to-day basis, the lung efficiently and effectively protects us from harmful insults. However, as lung cancer and age- related lung diseases such as idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) remain a prominent health challenge to this day, there is still so much we need to understand about this multifaceted organ in order to develop additional treatments for lung disease. 11 Lung Cancer: Statistics and Subtypes Lung cancer is the leading cause of cancer deaths in the US and worldwide [ACS Facts and Figures; Bray et al 2018]. For the current year, 2019, the incidence of lung cancer in the US among men is predicted to be 116,440 cases and for women, 111,710 cases, of these 76,650 men and 66,020 women will die from this disease (Figure 2) [U.S. Cancer Statistics Working Group]. Compared to other cancers, lung cancer represents 12.9% of all new cancer cases in the US, but 25% of cancer deaths [Howlander et al., 2018]. Trends in lung cancer deaths have steadily decreased by 2.9% per year from years 2007 to 2016. Concurrently, new cases of lung cancer have also decreased steadily. Figure 1. Different cell types along the proximal-distal axis of the lung. [Leeman et al., 2014.] 12 The overall 5-year survival rate increased from 13.9% in 1993 to 19.4% in 2015, with an average survival rate of 19.4% as of 2015. Lung cancer is diagnosed at different stages of disease, which corresponds the where the cancer is found. Lung cancer detected at early stage of disease is typically localized (stage I). Later stages (II, III, IV) reflect regional or distant spreading of disease to different parts of the body and typically display worse patient outcomes. From 2009 to 2015, the average percentage of patients diagnosed with localized disease stage was 16%, for Figure 2. Estimated new cases and deaths for lung cancer for 2019 [SEER Cancer Statistics, 2019]. Figure 3. Percent of lung cancer cases found in different regions and the five-year survival rate based on lung cancer stage as indicated by tumor location [SEER Cancer Statistics, 2019]. 13 regional stage, 22%, and for distant stage, 57%. The corresponding stage-specific 5-year survival rates are 57.4% for localized, 30.8% for regional, and 5.2% for distant (Figure 3) [Howlader et al., 2018]. Lung cancer is subcategorized based on the overall architecture and cytological appearance of cancer cells. There are two main histological subtypes of lung cancer, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). SCLC accounts for approximately 15% of lung cancer cases, while NSCLC accounts for 85% of cases [de Groot, et al., 2018]. Each subtype has a distinct natural history that influences prognosis and treatment options. SCLC is more highly associated with smoking and, without treatment, has the most aggressive clinical course of any type of pulmonary tumor. Median survival rate among untreated patients from diagnoses is 2 to 4 months. Patients with SCLC typically have favorable responses to chemotherapy and radiation therapy, however they usually relapse within a 2 year period. SCLC patients generally do not undergo surgical resection. [PDQ® Adult Treatment Editorial Board]. NSCLC can present in former, current, and never-smokers, and is considered a heterogeneous disease. NSCLC is subdivided into lung adenocarcinoma (LUAD), squamous cell carcinoma (LUSQ), and large cell carcinoma (LULC). LUAD is the most common type comprising approximately 40% of lung cancer cases, LUSQ comprising 30% of cases, and LULC comprising 10% of cases [de Groot et al., 2018]. LUAD generally arises from alveolar epithelial cells of the distal lung, whereas LUSQ arises from basal cells of the proximal airways. LUSQ is more highly associated with smoking and chronic inflammation than LUAD [Chen et al., 2014; Langer et al., 2010; Davidson et al., 2013]. 14 Important to clinical diagnosis, staging, and treatment of lung cancer is distinguishing between LUAD and LUSQ. Both are common NSCLC subtypes but have different histopathologies and disease mechanisms. LUAD often exhibits a glandular histology and upon immunohistological staining is positive for lung lineage marker NKX2-1 (also called Thyroid transcription factor ‐1, TTF ‐1) and Napsin A, an aspartic proteinase involved in maturation of surfactant protein B which is expressed in type 2 alveolar epithelial cells (AT2) [Stoll et al., 2010]. LUSQ exhibits a squamous, pseudostratified columnar histology with positive staining for basal cell markers TP63 and KRT 5/6, and P40 (which is a TP63 isoform truncated at the N-terminus, also designated ΔNp63) [Pelosi et al., 2013; Inamura, 2018]. The International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society (IASLC/ATS/ERS) recently reported additional subtypes within the adenocarcinoma and squamous cell histological classes. Mixed histologies pose a challenge because the panels of adenocarcinoma markers or squamous cell markers are not comprehensive enough to fully characterize the spectrum of NSCLC tumors. Importantly, in advanced-stage NSCLC it is imperative to accurately classify nodules and cytological specimen as LUAD or LUSQ because there are differences in the efficacy and safety of treatment options: 1) LUAD tumors with underlying epidermal growth factor receptor (EGFR) mutations are predicted to respond to current tyrosine kinase inhibitors (TKIs) 2) LUAD treated with the drug pemetrexed has an improved outcome compared to LUSQ 3) potential life-threatening hemorrhaging may occur in patients with LUSQ treated with the antibody bevacizumab, which targets vascular endothelial growth factor (VEGF) [Travis et al., 2011]. 15 Mutational Landscape of Lung Cancer Mutations are a critical feature of cancer. The presence of mutations in all cancers strongly suggests that mutations are potent drivers of carcinogenic progression, enabled by exposure to toxins, genome instability and faulty DNA repair [Loeb and Loeb, 2000]. Advances in and increased accessibility to next-generation sequencing (NGS) platforms and other high- throughput technologies have expanded the collection of known mutations, especially those underlying lung tumors. Lung cancer has a high tumor mutational burden, lagging only behind skin cancer (Figure 4) [Chalmers et al., 2017; Martincorena and Campbell, 2015; Yarchoan et al., 2019]. LUAD and LUSQ have similar tumor mutational burdens measured by percentage of cases with more than 20 mutations per megabase of coding genome (12.3% and 11.3%, respectively) [Chalmers et al., 2017]. However, their underlying mutational landscapes are quite distinct, contributing to differences in patient treatment options. Figure 5 shows the most common activating mutations in LUAD and LUSQ. Common mutations found in LUAD tumors occur in the epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene homologue (KRAS), and anaplastic lymphoma kinase receptor (ALK) genes, whereas common mutations in LUSQ tumors are found in the phosphatase and tensin homolog (PTEN), fibroblast growth factor receptor 1 (FGFR1), and phosphatidyl-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) genes (Figure 5) [Lovly et al., 2018]. 16 Molecular genotyping has greatly improved patient care, especially for those with LUAD. Targeted therapies against EGFR mutations or ALK fusions, in particular, are far more efficacious than standard platinum-based doublet therapies [Hirsch et al., 2016; Huang et al., 2017]. Treatment with tyrosine kinase inhibitors (TKIs) such as erlotinib and gefitinib for EGFR mutations results in progression-free survival by 11-12 months [Kuan et al., 2017]. Treatment of advanced stage adenocarcinoma with EML4-ALK fusion gene with ALK inhibitors, such as crizotinib, yields an overall response rate of 74% and progression-free survival of 10.9 months [Shaw et al., 2013]. Several groups have employed genome-wide sequencing approaches to further characterize and refine the mutational landscape of LUAD by comparing more than 150 matched tumor and normal tissues in each study. These studies found high rates of somatic mutations with a mean exonic mutational rate of 10 to 12 events per megabase of coding genome, indicating a generally Figure 4. Lung cancer has one of the highest mutational burdens among other cancers. It is only second to melanoma [Campbell et al.,2016]. 17 high tumor burden [Imielinski et al., 2012; Lawrence et al., 2014; Hellman et al., 2018]. The majority of these mutations lie in TP53, KRAS, EGFR, BRAF, and STK11 genes. Additional mutations were found in driver oncogenes NRAS, ERBB2/HER2, RIT1, and MET, and tumor suppressor genes KEAP1 and NF1. Enriched pathways were those corresponding to RTK/RAS/RET pathway, PI3K-mTOR pathway, TP53 signaling, and cell cycle pathway led by CDKN2A. Copy number variations were commonly detected as copy gains in EGFR, KRAS, TERT, NKX2-1, MDM2, and MYC, and as copy losses in TP53 and CDKN2A [TCGA, 2014; Imielinski et al., 2012; Ding et al., 2008]. NGS studies also show that the LUAD mutational landscape is rich in genomic rearrangements, indicated by high frequencies of intra- and inter- chromosomal rearrangements, genic rearrangements (where breakpoints are located in promoters, untranslated regions, introns, or exons of a gene), and intergenic rearrangements [Imielinski et al 2012]. The mutational frequency is higher in heavy smokers than in light or never smokers. KRAS mutations are more prevalent among smokers, whereas EGFR mutations are more common among never-smokers and female patients [TCGA 2014; Imielinski et al., 2012; Ding et al., 2008; Tokumo et al., 2005]. 18 Unlike for LUAD, current treatment options for LUSQ are limited to the standard of care which are surgery, radiation therapy, platinum-based doublet therapy, angiogenesis inhibitor chemotherapy, or immunotherapy; targeted therapies for LUSQ are actively under investigation [Derman et al., 2015]. Molecular profiling of LUSQ continues to uncover genetic alterations with the promise of turning some of these into clinically actionable mutations. Comprehensive characterization of 178 LUSQ samples by the TCGA Consortium (2012), found a mean exonic mutation frequency of 360 events per tumor, genomic rearrangement frequency of 165 events per tumor, and copy number alteration frequency of 323 per tumor. The mean somatic mutation rate was 8.1 events per megabase of coding genome. Significant genes harboring exonic mutations were TP53 (81% of cases), MLL2 (20%), PIK3CA (16%), CDKN2A (15%), NFE2L2 (15%), KEAP1 (12%), PTEN (8%), NOTCH1 (8%), RB1 (7%), and HLA-A (3%). The EGFR mutation (L861Q) previously found to be sensitizing to afatinib [Saxton et al., 2017], and only mildly to erlotinib and gefitinib [Watanabe et al., 2014] was present in a small proportion of LUSQ cases. EGFR L858R and in-frame deletions in exon19, found in LUAD, were completely absent from this Figure 5. Common driver gene mutations found in lung adenocarcinoma and lung squamous cell carcinoma tumors. Adapted from Lovly, et al. (2018). Graphs published by Lungevity Foundation. 19 tumor cohort. Copy number alterations in LUSQ were both focal and broad (as defined by a segment spanning >= 50% of the chromosomal arm). Amplification of the chromosomal arm 3q containing SOX2, PDGFRA, EGFR, FGFR1, CCND1, CDKN2A genes was a distinct characteristic of LUSQ compared to LUAD. Tumor suppressor gene inactivation by intra- and inter-chromosomal rearrangements was detected in PTEN, NOTCH1, ARID1A, and NF1. The frequency of gene fusions was not remarkable in LUSQ, except for a singular case where exon 18 of KIAA1797 was fused to the p16INK4 gene in the CDKN2A locus. Although many of the significantly mutated genes found in LUSQ have also been identified in mutational analyses of LUAD, the mutational frequency of these particular genes is much higher in LUSQ than in LUAD, suggesting they have a stronger driver role in squamous cell lung disease. Notably, results from the TCGA study (2012) and one conducted by Campbell et al (2016) implicate the PI3K/RTK/RAS signaling pathway and associated genes PI3K, PTEN, and FGFR1 in driving LUSQ. Methods for Studying Lung Cancer Given the complex landscape of lung cancer tumors, there are several different ways researchers study lung cancer development and progression. One of the most physiological approaches is to use mouse models. Most mouse models developed have been used to study LUAD. Initial experiments assessed spontaneous generation of lung tumors from susceptible mouse strains such as A/J and SWR [Shimkin and Stoner, 1975]. Susceptible mouse strains were generally found to have a polymorphism in intron 2 of Kras thereby affecting Kras expression, [Chen et al., 1994] or in the locus containing Cdkn2a, as is the case for BALB/cj and A/J strains [Manenti et al., 1997; Zhang et al., 2002, Herzog et al., 1999]. Induction of lung tumors with chemical 20 carcinogens has also been used to study sporadic cancer. Potent carcinogens such as polycyclic aromatic hydrocarbons and nitrosamines from tobacco, and urethane have reproducibly resulted in pulmonary adenomas and adenocarcinomas [Shimkin and Stonerm 1975; Malkinson, 1989]. Tumor number and latency depended on the baseline susceptibility of the mouse strain. The histology of adenomas and adenocarcinomas was generally of a papillary or solid subtype, as observed in humans. Interestingly, if benign adenomas were present, they rarely progressed to adenocarcinoma; if malignant adenocarcinomas were detected, they rarely metastasized [Malkinson, 2001]. Spontaneous and carcinogen-induced tumors generally harbored activating mutations in Kras early in progression, in hyperplastic lesions. Overexpression of Kras and c- Myc, and inactivation of Tp53, Apc, Rb1, and Cdkn2a were commonly detected in tumors. Mutations in Tp53 were never found in hyperplasia, but more frequently in adenocarcinomas To investigate specific genetic drivers of lung cancer, transgenic and knockout mouse models were developed. Unlike the sporadic and chemically-induced models, transgenic models allow for spatial and temporal control over engineered genetic alterations. Several NSCLC models have been generated for Kras, Egfr, Eml4-Alk, and Pten, among other genes [Meuwissen and Berns, 2005; Safari and Meuwissen, 2015]. Special attention has been given to Kras mutant-driven tumorigenesis since the early years of genetically engineered mouse models. Using a latent germline allele of oncogenic Kras G12D such that expression occurs only after spontaneous recombination, Johnson et al (2001) found nodules at 1 week of age and eventual development of pulmonary adenocarcinomas, skin papillomas, and aberrant intestinal crypt foci, indicating that tissues other than the lung are sensitive to Kras 21 mutation. Pulmonary lesions seemed to progress through a series of morphological stages from hyperplasia to overt carcinoma, reminiscent of human NSCLC. Interestingly, no metastases were detected in these mice. Similar findings were reported by systemic activation of conditional Kras G12D but with a longer latency of about 8 months [Guerra et al., 2003]. Only a subset of bronchiolar and alveolar epithelial cells exhibited hyperplasia, and within that subset, only a fraction progressed to adenocarcinoma. No metastatic spread was detected. Cell-specific inducible models limiting expression of Kras G12D to alveolar and bronchioalveolar cells yielded adenomas and adenocarcinomas within 2 months of induction [Fisher et al., 2001]. When Kras activation is combined with a second alteration, for example Tp53, p19, Pten, or Lkb11 deficiency, tumorigenesis is accelerated, and a more malignant or advanced histology is observed in lung tumors [Riccardo et al., 2014; Fisher et al., 2001; Iwanaga et al., 2008; Ji et al., 2007]. When Kras activation was halted by doxycycline withdrawal, tumors regressed, even in the absence of tumor suppressor genes [Fisher et al., 2001], suggesting that Kras is not only important for tumor initiation but also for maintenance. Also well-studied in mice models is the second most common oncogene in LUAD, Egfr. Egfr signaling occurs independently and upstream of Kras. Mutations are frequently found in the tyrosine kinase domain between exons 18 and 21, with the most prevalent being L858R and in- frame deletion of exon 20 (DEL) [Shigematsu and Gazdar, 2006]. When expressed in the alveolar region under doxycycline-inducible conditions, Egfr L858R or Egfr DEL mutants gave rise to bronchioloalveolar carcinomas initially. With continued doxycycline administration, tumors progressed to invasive adenocarcinomas. These tumors were positive for downstream effectors of Egfr signaling: phosphorylated Erk, phosphorylated Akt, and phosphorylated Stat3. Of note, 22 Egfr L858R tumors formed faster and were more aggressive than Egfr DEL tumors. Similar to reports on Kras-driven tumor formation, upon withdrawal of doxycycline, Egfr mutant tumors quickly regressed [Ji et al., 2006; Politi et al., 2006]. Treatment of these Egfr mutant tumors with erlotinib resulted in regression, while long-term treatment led to the emergence of erlotinib- resistant tumors driven by the secondary Egfr mutation T790M and focal amplification of the Met gene [Politi et al., 2010]. These results were strikingly similar to reports in human patients with EGFR mutations. Two mouse models for the Eml4-Alk fusion gene were generated. One transgenic model by Soda et al. (2008) expressed Eml4-Alk specifically in Spc + alveolar epithelial type 2 cells. A second model by Pyo et al. (2018) used the Cre/loxP-STOP-loxP inducible system for targeted expression of Eml4-Alk in Spc + type 2 cells. In both models, rapid development of multiple adenocarcinoma nodules was observed and confirmed by CT scan. Treatment with ALK inhibitors greatly reduced the tumor burden to near undetectable levels after about 2 weeks. In the case reported by Soda et al, there was no report of drug resistance or tumor relapse in mice treated with the ALK inhibitor for 25 days. In contrast, Pyo et al. using the specific ALK inhibitor crizotinib, reported acquired resistance after continuous treatment for 4 weeks and eventual tumor regrowth after 12 to 14 weeks. Sequencing the kinase domain of Alk in these lung tumors revealed a secondary mutation Alk G1202R , previously identified in patients with acquired resistance to crizotinib [Doebele et al., 2012]. PTEN is a tumor suppressor that is commonly mutated in early-stage LUSQ [Xu et al., 2014]. It is a negative regulator of the PI3K/AKT cell survival pathway [Wu et al., 1998]. A doxycycline- inducible mouse model of Pten knockout specifically in SPC + alveolar epithelial type 2 cells 23 showed dual functions of Pten in lung morphogenesis during embryonic lung development and prevention of lung carcinogenesis [Yanagi et al., 2007]. Histologically, lungs of E10-E16 mice lacking Pten showed notable bronchiolar and alveolar septal hyperplasia. Around 18 months after birth, lung tumors of adenocarcinoma histology were detected, except for one specimen which exhibited squamous cell carcinoma histology. Lungs of postnatal mice formed spontaneous lung adenocarcinoma tumors within a 10 - 18 month observation period. These tumors showed elevated levels of phosphorylated Akt, increased expression of c-Myc, Bcl-2, Shh, and frequent mutations in Kras at codon 61. Compared to Kras G12D , Egfr mutant, and Eml4-Alk transgenic mice, inactivation of Pten seems to promote lung tumors with long latency. Interestingly, Pten inactivation in a Kras G12D background accelerated tumorigenesis and lethality. Lung tumors displayed cytological atypia and invasive features indicative of a more advanced histology [Iwanaga et al., 2008]. Although mouse models are valuable in vivo systems to study cancer initiation and progression, there are differences between mouse and human physiologies that can influence the clinical applicability of using transgenic models to assess or screen for drugs. Patient-derived xenograft (PDX) models are fast becoming a model of choice for their predictive value of therapeutic activity and response in the clinic. PDX models are generated by transplantation of primary tumor cells from patients into immunodeficient mice, such as athymic nude mice, SCID, or NOD-SCID. The cells are allowed to engraft and grow, then harvested and transplanted into a new immunodeficient mouse for expansion. The advantage of this system over common cell culture methods is retention of the parental tumor's histomorphological characteristics and natural course of clonal selection. If propagated under standard culture conditions, over time 24 these primary tumor cells will acquire major genetic and phenotypic changes that diverges them from the original tumor they were meant to represent, compromising their value as a screening tool [Morgan et al., 2017; Lai et al., 2017]. NSCLC PDX models harboring genetic mutations in EGFR, KRAS, and FGFR1 have been used to evaluate the range of responses to gefitinib; results from the PDX model were consistent with those of clinical trials [Zhang et al., 2013]. The disadvantage of PDX models is the variability in engraftment success [Morgan et al., 2017], cost, and feasibility of xenotransplantation for labs not versed in this technique. PDX models hold great promise as a near-human model to ascertain chemoresistance and risk of treatment failure, however, they remain out-of-reach for the general research community as a common tool. Another method for studying lung cancer is to use cell lines. Cell models have afforded researchers a tractable and simplistic, yet powerful system in which to study mechanisms controlling normal lung and diseased states. In the US beginning around the 1970s, large collections of lung cancer cell lines were established and made available to the research community. Two of the most common collections were established by Gazdar and Minna at the National Cancer Institute ("NCI-" strains) and at UT Southwestern Medical Center ("HCC-" strains) [Gazdar et al., 2010]. Cell lines generated in these collections came from a diverse population of lung cancer patients, and each cell line was accompanied by documentation of its histological origin. Since then, extensive studies have been conducted to characterize the cell lines' expression signatures [Gandhi et al., 2009], allelic profiles [Virmani et al., 1998], and similarity to primary tumors [Wistuba et al., 1999; Wang et al., 2006]. A subset of this cell line collection has also been used as a drug screening model for anticancer drugs [Shoemaker, 2006]. Internationally, similar efforts to characterize these lung cancer cell lines have been conducted. 25 Multi-omics data are available through the DBTSS database (Database of Transcriptional Start Sites <https://dbtss.hgc.jp/>) which includes transcriptomic, epigenomic, and single nucleotide variation (SNV) data, providing a rich resource to investigate transcriptional deregulation across a diverse set of representative tumor contexts [Suzuki et al., 2015; Suzuki et al., 2015; Suzuki et al., 2017]. For example, lung cancer PC9 and PC3 cells are derived from Asian patients and can be used to identify underlying ethnic contributions to disease progression. Undoubtedly, these lung cancer cell line collections, as well as cell lines available through American Type Culture Collection (ATCC), are valuable tools to investigate lung cancer mechanisms. However, since these cell lines were derived from patients with varying stages of lung cancer, they are not suitable models to study early events in carcinogenesis. To address this shortcoming, several labs have generated immortalized normal lung cells from primary cell populations. Non-cancer Cell Models for Studying Lung Cancer A challenge in generating normal cell models has been the general intractability of primary human cells in culture. In order to survive under ex vivo conditions, cells must overcome cellular senescence and telomeric attrition, two key events that preclude cellular immortalization. Under normal conditions, cells divide only in response to external cues, such as growth factors. Entry into the cell cycle is exquisitely controlled. When stimulated to divide cells progress from G0 to G1 phase, from G1 to S phase, S phase to G2, then onto mitosis. One of the most critical checkpoints occurs at the G1 to S phase. This transition is controlled by cyclin D and its cognate cyclin-dependent kinases, CDK4 and CDK6 (CDK4/6) (Figure 6). Under nondividing conditions, when cyclin D is absent, CDK4/6 is inactive and its immediate downstream target the 26 retinoblastoma protein, pRB binds E2F transcription factor preventing E2F-mediated expression of mitogenic genes. When cell cycle progression is permitted, the activated cyclin D-CDK4/6 complex phosphorylates pRB, inhibiting pRB sequestration of E2F, thereby allowing E2F binding to promoters controlling DNA replication and cell cycling genes such as DNA polymerase alpha, CDC2, and cyclins A and E [Hateboer et al., 1998; Zou et al., 2002]. Subsequent activation of CDK2 in complex with cyclin E in late G1 initiates entry into S phase [Zou et al., 2002]. The activities of CDK4/6 are specifically regulated by the INK4-type inhibitors p16 INK4A , p15 INK4B , p18 INK4C , and p19 INK4D . In many cancers, mutations in either CDK4 or p16 mark an initiating event that primes cells for subsequent transformation. In melanoma-prone families, the germline mutation at Arg24 of CDK4 (R24C) renders the protein resistant to INK4-type inhibition [Chin et al., 2006]. In human mammary epithelial cells (HMECs), promoter DNA methylation silences p16 expression allowing for deregulated activation of CDK4/6 and progression into the cell cycle [Garbe et al., 2014]. 27 Cellular senescence is a state in which cells are semi-irreversibly growth arrested, but metabolically active. Intrinsic and extrinsic stressors, such as oncogenic activation, genomic instability, chemotherapeutic drugs, and suboptimal culture conditions can induce senescence [Harranz and Gil, 2018; Kuilman et al., 2010]. Cellular senescence is thought to be an evolutionary protective mechanism to prevent cancer by stringently initiating growth arrest before further cellular damage is incurred [Campisi, 2013]. Transient induction of senescence can also function as a way to give cells time to recover from injury [Demaria et al., 2014]. Senescent cells secrete a variety of molecules such as cytokines, chemokines, and growth factors, to either suppress cancer initiation or promote tissue repair and regeneration upon injury. Two key regulators of establishing and maintaining senescence are p53/p21 and p16 INK4A /pRB pathways. Figure 6. Cell cycle regulation in mammalian cells [Lapenna and Giordano., 2009]. 28 Cell immortalization is akin to the initiating steps in cancer development [Hahn and Weinberg 2002]. Cells must acquire alterations in cell cycle control to overcome replicative senescence and keep dividing. As cells undergo multiple rounds of cell division, their telomeres, a highly repetitive DNA sequence of TTAGGG capping the ends of chromosomes, shorten. This process, called telomere attrition, eventually leads to another bout of cellular senescence due to activation of DNA damage responses at critically short or uncapped telomeres. DNA damage response factors such as gammaH2AX and 53BP1 accumulate at telomeric ends that are now recognized as double-stranded breaks. Eventually, cells enter a state of cellular "crisis", characterized by extensive chromosomal fusions and cell death. Within this apoptotic population, rare surviving cells can arise, having spontaneously acquired the ability to maintain their telomere length by reactivation of telomerase or an alternative pathway [Yang et al 2016; Muraki et al. 2012]. These surviving cells possess genomic rearrangements due to DNA damage repair at unprotected chromosomes and widespread gene expression alterations resulting secondarily from cellular responses triggered by telomere attrition [Platt et al., 2013; Shah et al., 2013; Ye et al., 2014]. Consequently, these cells give rise to diseases not limited to cancer [Kong et al 2013]. In the lung, idiopathic pulmonary fibrosis (IPF) is characterized by genetic defects in telomerase genes hTERT, encoding the enzymatic reverse transcriptase, and hTR, the template RNA for telomere repeat addition, resulting in accelerated telomere shortening [Armanios 2012; McDonough et al 2018]. Loss of telomere function in alveolar epithelial cells results in failure to self-renew and induction of senescence [Alder et al 2015]. Patients with IPF are extremely sensitive to pulmonary-toxic drugs and typically exhibit widespread airspace destruction brought about by alveolar epithelial cell damage [Armanios 2012]. 29 Experimentally, researchers have employed two different methods to generate immortalized cell lines. The classical approach is to use viral oncogenes, such as HPV E6/E7 and SV40 T antigens to deregulate cell cycle checkpoints allowing for continued proliferation and the rise of spontaneously immortalized cell populations. HPV E7 protein binds cellular pRB releasing bound E2F transcription factor permitting S phase entry, while E6 targets p53 for degradation and induces telomerase activation [Dyson et al 1989; Klingelhutz et al 1996]. SV40 tumor virus was used to generate the first untransformed, post-crisis cell line, NIH 3T3 mouse fibroblast line. SV40 large T antigen in particular can transform cells by abrogating pRB-E2F complex formation and preventing p53 from binding to promoters of its target genes [Jha et al 1998; Pipas 2009]. Non-viral methods, such as ectopic expression of CDK4 or cyclin D1 and hTERT, have also been shown to deregulate the cell cycle similar to viral approaches, however, with minimal additional genomic perturbations. Both methods have successfully yielded immortalized cell lines to study cellular transformation and carcinogenesis in different tissue types. Normal human lung cell lines from the airways have been reported. In 1988, Reddel et al. generated a bronchial epithelial cell line (BEAS-2B) by infection with an Adenovirus 12-Simian virus 40 large-tumor antigen hybrid virus (Ad12-SV40 LgT) [Reddel et al., 1988]. This new line exhibited unlimited proliferative potential, while maintaining near diploid karyotype. BEAS-2B cells also retained the ability to undergo squamous cell differentiation as observed in the parental normal bronchial epithelial cells, despite transformation with Ad12-SV40 LgT [Ke et al., 1988; Ke et al., 1990]. When low passage cells were injected into athymic nude mice, no tumors formed. However, at higher passages (>= 32) [Reddel et al., 1993] or when mutated p53 was ectopically expressed, BEAS-2Bs formed tumors [Gerwin et al., 1992]. Interestingly, the most 30 tumorigenic BEAS-2B tumor-derived cell line from nude mouse experiments contained loss of chromosome 3p, a common genetic alteration observed in LUSQ [Reddel et al., 1993]. Since their establishment, BEAS-2B cells have been used in studies of neoplastic transformation, inflammatory response, and carcinogen exposure [Reddel et al., 1995; De Silva et al., 1994; Jang et al., 2017; Pratheeshkumar et al., 2016]. In 2004, Ramirez et al. immortalized normal human bronchial epithelial cells (HBEC) with mouse Cdk4 and the catalytic subunit of human telomerase (hTERT) to avoid potential genomic instability brought about by transduction of viral oncogenes [Ramirez et al., 2004]. These cells exhibited insensitivity to p16 inhibition conferred by ectopic expression of Cdk4, telomerase activity, and an intact Tp53 pathway. Chromosomal analyses by aCGH array revealed multiple regional amplifications and deletions across several chromosomes which were not observed in parental bronchial epithelial cells, but were present in HPV16 E6/7-transformed HBECs and BEAS-2Bs. Gene expression profiling showed HBECs immortalized with CDK4 and hTERT clustering more closely to, but still distinct from, HPV16 E6/7-transformed HBECs and clustering further away from BEAS-2B cells. In soft agar, HBECs immortalized with Cdk4 and hTERT did not form anchorage-independent colonies, nor did they give rise to tumors when injected subcutaneously into nude mice. In addition, HBECs exhibited differentiation and morphogenic capabilities. When grown on collagen I matrix in the presence of fibroblast feeders, HBECs differentiated into ciliated and goblet cells of the airway [Vaughan et al. 2006]. When grown on Matrigel overlaying fibroblast feeders, HBECs formed branching tubular structures which were positive for markers of airway and distal lung cells [Kaisani et al., 2014]. 31 Since these immortalized HBECs retained characteristics of normal human bronchial epithelial cells, they have been used as a model for investigating lung carcinogenesis. Sato et al [2006] tested whether TP53 knockdown, KRAS G12V expression, or EGFR mutant expression in various combinations was able to confer a malignant phenotype to HBECs. The authors found that TP53 knockdown, KRAS G12V expression, and both TP53 knockdown plus KRAS G12V (TP53 KD +KRAS) significantly increased formation of anchorage-independent growth colonies in soft agar. In organotypic culture, TP53 KD +KRAS HBECs exhibited dysplastic growth and invasion into the bottom matrix layer. However, when these cells were injected into athymic nude mice, no tumors were formed. Ectopic expression of mutant EGFR delE746-A760 in HBECs increased soft agar colony formation, whereas expression of the more clinically common EGFR L858R mutant did not confer anchorage-independent growth. In a follow up study, Sato et al. (2013) found that additional overexpression of MYC (TP53 KD +KRAS+MYC) significantly increased colony forming efficiency in soft agar, but was only slightly more tumorigenic than TP53 KD +KRAS cells injected into nude mice. Histologies of tumors arising from injected TP53 KD +KRAS or TP53 KD +KRAS+MYC cells varied widely, showing predominantly poorly differentiated large cell/giant cell carcinoma, but also adenosquamous, adenocarcinoma, and squamous cell carcinoma morphologies. Interestingly, in this study the authors detected tumor formation following injection of TP53 KD +KRAS into nude mice, whereas their previous study [Sato et al., 2006] reported no tumor formation, a discrepancy that could be attributed to sample size differences (Sato et al 2006 used 5 mice per condition; Sato et al 2013 used on average 10 mice) or differences in type of immunodeficient mice used (Sato et al 2006 used nude mice; Sato et al 2013 used NOD/SCID mice). Moreover, the authors 32 found significant differences in tumorigenicity among transformed HBEC clones derived from the same donor, as well as differences between HBEC cell lines derived from separate donors. Taken together, these results reveal the complexities of oncogene-induced malignant transformation and the importance of ex vivo and in vivo conditions on cellular behavior. Additional immortalized cell lines derived from human airways were established by Piao et al. (2005) and Sasai et al. (2011), who used small airway epithelial cells (SAEC) and Lundberg et al. (2002) (who used tracheal epithelial cells, hTBE). Piao et al. generated immortalized SAECs by ectopic expression of TERT alone, while Sasai et al. further introduced expression of CDK4 and a dominant-negative form of TP53 which results in accumulation of inactive TP53 protein (SAEC-CTdn53). Both methods resulted in immortalized SAECs with near diploid karyotype that are unable to form colonies in soft agar nor tumors in immunodeficient mice. Sasai et al. found that additional expression of either KRAS G12V or MYC, a potent oncogene [Gabay et al., 2014], in SAEC-CTdn53 cells was not sufficient to promote anchorage-independent growth nor tumor formation in nude mice. The combination of KRAS G12V and MYC facilitated significant colony formation in soft agar, but only a low incidence of tumor formation in nude mice. Interestingly, further expression of BCL2, an anti-apoptotic regulator, dramatically increased tumor incidence with only a modest effect on increasing soft agar colony growth. Tumors detected in immunodeficient mice were all poorly differentiated. Lundberg et al. generated immortalized tracheobronchial epithelial cells by retroviral transduction of TERT and SV40 early region (SV40 ER) containing both large and small T antigens. These cells exhibited enhanced proliferative properties in the absence of malignant 33 transformation, failing to form colonies in soft agar and tumors in nude mice. The authors also derived immortalized small airway epithelial cells (SA) from primary tissue by the same method. Both hTBE and SA immortalized cells formed soft agar colonies and tumors in nude mice when either KRAS G12V or HRAS G12V was ectopically expressed. Unlike previous findings of generally poorly differentiated tumors arising from RAS-transformed airway cells [Sato et al., 2013; Sato et al., 2006], tumors formed by injection of SA+RAS exhibited only squamous cell carcinoma histologies - no tumors were of adenocarcinoma histology. In contrast, Sasai et al. (2011) found that SAEC-CTdn53 expressing KRAS G12V with either PIK3CA, CYCLIN D1 (CCND1), or LKB1 (STK11) formed predominantly tumors with adenocarcinoma-like histologies, some even reminiscent of papillary or acinar subtypes. Most of these tumors stained positive for the alveolar epithelial cell marker NKX2-1. All of the discussed models above were derived using airway cells, thus potentially yielding LUSQ models. There is a notable absence of immortalized alveolar epithelial cells. As mentioned previously, LUAD and LUSQ arise from distinct cell types of the lung. Immortalized alveolar epithelial cells are thus needed to model LUAD development. In the next section, I will discuss the current status of alveolar epithelial cell models for the study of lung cancer. Generating a Refined Cell Model to Study Lung Adenocarcinoma As LUAD arises from alveolar epithelial cells, development of a cell model derived from these cells would greatly aid in understanding the specific genetic alterations driving this common lung cancer subtype. 34 As discussed in earlier sections, non-malignant, immortalized lung cells have been primarily derived from the upper and small airways (hTBE, SAEC, BEAS-2B, and HBEC). Models of alveolar epithelial cells (AECs) are limited. Methods for isolating alveolar epithelial cells, particularly surfactant-producing type 2 cells (AT2), have been published extensively for both rodent and human lungs. Unlike airway epithelial cells, human alveolar epithelial cells have been reported to be difficult to maintain in culture. Purified type 2 cells spontaneously transdifferentiate into flattened, type 1 (AT1)-like cells [Dobbs et al., 1985; Danto et al.., 1995], especially when grown on filter membranes or plastic tissue culture dishes, even in the presence of feeder cells [Bove et al., 2014]. AT2 cells, following isolation and purification from tissue, highly express surfactants such as surfactant protein C (SFTPC) and B (SFTPB) and the ATP binding transporter A3 protein, ABCA3, which is expressed in lamellar bodies where surfactants are produced. When cultured, isolated AT2 cells quickly lose expression of surfactants and steadily begin expressing markers of type 1 cells such as the water channel protein aquaporin-5 (AQP5), podoplanin (PDPN/T1alpha), caveolin-1 (CAV1), and receptor for advanced glycation of end products (RAGE) [Wang et al., 2007]. These AT1-like cells also exhibit transepithelial membrane resistance [Elbert et al., 1988]. Since AT2 cells are the primary players in regenerating the alveolar epithelium upon injury, much attention has been dedicated to optimizing type 2 culture conditions. A recent report by Sucre et al. (2018) found that the AT2 phenotype can be maintained when the cells are grown on top of a sandwich comprising the Engelbreth-Holm-Swarm extracellular matrix, Matrigel, layered on top of primary fetal lung fibroblasts. 35 Despite the difficulty in maintaining primary human alveolar epithelial cells in culture, several labs have derived alveolar epithelial-like cell lines to study transport mechanisms. Kemp et al. generated an immortalized human AT1-like cell line by retroviral transduction of hTERT and temperature sensitive SV40 LgT (U19tsA58 LT). These cells formed monolayers exhibiting membrane resistance and were capable of nanoparticle uptake and transport [Kemp et al., 2008; Thorley et al., 2014]. Kuehn et al. used a proprietary cocktail of 33 'immortalizing' genes to generate an alveolar epithelial cell line showing transepithelial electrical resistance to investigate alveolar barrier function [Kuehn et al., 2016]. Although these new immortalized lung cell lines approximate several normal AEC characteristics, morphogenic and differentiation capabilities have not been assessed. The focus of my thesis study is to develop an alveolar epithelial cell system that can be used to recapitulate LUAD-specific cancer events. The study builds upon published culture conditions found to promote proliferation of primary human cells [Liu et al., 2012; Bove et al., 2014] and Weinberg's two-hit model of cell immortalization to generate a collection of novel cell lines derived from adult human alveolar epithelial cells. My results address these key challenges: 1) alveolar epithelial cell growth arrest upon isolation from human lung tissue 2) optimal immortalization conditions have not been reported for adult alveolar epithelial cells and 3) primary epithelial cells tend to lose their cell-type specific characteristics after long-term expansion in culture. 36 Chapter 2 MATERIALS AND METHODS 37 Ethics statement Remnant human transplant lungs were obtained in compliance with the University of Southern California Institutional Review Board-approved protocols for the use of human source material in research and processed within 3 days of death. All donors were de-identified according USC HIPAA regulations. Isolation and culture of primary human alveolar epithelial cells Lung tissue was collected from several donors at different times for this study. Cell lines were successfully derived from these particular lungs: Lung 3: 25-year-old Caucasian, male. Lung 4: 66-year-old Caucasian, female. Lung 5: 62-year-old Caucasian, male (see Tables 5 and 6). Human alveolar epithelial cells (AECs) were isolated and purified as previously described (Ballard et al., 2010) using anti-EpCAM beads. Cells were resuspended in 50:50 medium (50% DME-F12 (Sigma Aldrich D64421), 50% DMEM High glucose (Gibco 21063) supplemented with 10% FBS, Pen/Strep, Gentamycin, and Amphotericin B). Differentiation to AT1-like cells was assessed by SFTPC and AQP5 expression by qPCR and Western blot analyses as described in Marconett et al. (2013). Remaining purified cells that were not plated in media were frozen in cryovials at 1-2 X10 6 cells/mL and stored in liquid nitrogen. Mycoplasma and rodent pathogens testing Cells were routinely tested for mycoplasma using an in house qPCR-based method adapted from Ishikawa et al. (2006). Briefly, cells to be tested were passaged two times in antibiotic- and antimycotic-free media, then collected for genomic DNA (gDNA) extraction using Qiagen DNeasy Blood and Tissue kit (Qiagen #69504) following the manufacturer's instructions until the last step, instead, eluting in DNase-RNase-free water. Genomic DNA was diluted to a 38 concentration of 10 ng/uL in water, then 50 ng gDNA was used per qPCR reaction using iQ SYBR Green Supermix (Bio-Rad #1708880). Each assayed primer set was tested in technical triplicates. Per 50 ng gDNA (5 uL) 0.375 uL 3 uM forward primer, 0.375 uL 3 uM reverse primer, and 6.25 uL SYBR Supermix was combined, mixed gently, then run on MJ DNA Engine Opticon 2 Research thermocycler. Primer sequences are listed in Table 1. Cycling conditions: Initial 94C, 3 min, followed by 40 cycles of: (i) 94C for 15 s; (ii) 65C for 30 s, (ii) 72C for 30 seconds, followed by final extension at 72C for 10 min. A melt curve (55C to 95C) is performed at the end of the PCR to confirm the identity of each product and verify controls. Results were considered negative if Ct values were above 30 cycles. Negative controls are usually at Ct of 35- 40, positive controls fall around Ct of 15-20. In cases where Ct values were not clear, samples were sent to the Norris Cancer Center Bioreagent and Cell Culture Core for additional testing. Rodent pathogen testing was managed through the USC Department of Animal Resources. Samples were tested by Charles River Laboratories. 39 Derivation of human alveolar epithelial cell lines Previously frozen purified AECs were quick-thawed in 37°C water bath, spun down to remove freezing medium, and resuspended in Fmed+ROCKinh media [3:1 (v/v) DMEM/F12 (Corning 10-090-CV) to DMEM (Gibco 21063-029), 5% FBS (Omega Scientific FB-11), 0.4 µg/mL hydrocortisone (Sigma Aldrich H0888), 5 µg/mL insulin (Sigma Aldrich I0516), 8.4 ng/mL cholera toxin (Sigma Aldrich C8052), 10 ng/mL hEGF (Gemini Bio-Products 300-110P), Antibiotic-Antimycotic (Gibco 15240-062), (10 µM Y-27632 (Enzo Life Sciences 270-333)] (modified from Liu et al., 2012). Resuspended AECs were plated in 96-well Primaria culture plate (BD Falcon 3872), ~6250 cells/well and allowed to attach for 2 days. On the second day, Fmed+ROCKinh media was completely replaced. Wells were monitored every day for surviving cells and outgrowth. Media was changed every 2-3 days. Once wells reached 90-100% confluency, cells were detached with Accutase (Innovative Cell Technologies AT-104) and replated onto 48-well culture plate ("Passage 1"), then 24-well culture plate ("Passage 2"), then 12-well culture plate (Passage 3"), then 6-well culture plate ("Passage 4"). Stocks of cells were frozen down starting at passages 3 and 4 (10% DMSO in 0.22 µm filtered FBS). Construction of lentiviral plasmids and production of viral particles LeGO iG and LeGO iT plasmids (http://www.lentigo-vectors.de/) were a kind gift from Dr. Kate Lawrenson (Cedars Sinai Medical Center, Los Angeles, CA). CDK4 R24C CDS was subcloned from pBABE-hygro-CDK4 R24C plasmid (Addgene 11254) by PCR amplification into LeGO iG vector between BamHI and SbfI sites. hTERT CDS was subcloned from pBABE-puro- hTERT plasmid (Addgene 1771) into LeGO iT vector between BglII and EcoRI sites. SV40 40 Large T antigen CDS was subcloned from pBABE-puro SV40 LT plasmid (Addgene 13970) into LeGO iG vector between BamHI and EcoRI sites. Plasmids were propagated in Stbl3 chemically competent E.coli (ThermoFisher C737303). Plasmid sequences were verified by Sanger sequencing (GENEWIZ Inc). Third generation lentiviral particles were produced in low passage 293T cells by transfection. Per 10 cm dish of 4-5 X 10 6 293T cells: 15 uL BioT (BioLand LLC B01-00), 2 µg pMD2.G-VSVG (courtesy of Dr. Beiyun Zhou), 2 µg pMDLg/pRRE (Addgene 12251), 2 µg pRSV-Rev (Addgene 12253), and 2 µg lentiviral plasmid carrying transgene (LeGO iG-CDK4 R24C, LeGO iT-hTERT, LeGO iG-SV40 LgT). Viral supernatant was collected at 48- and 72-hours post- transfection, pooled, spun down at 300 g to remove cell debris, filtered through 0.45 µm PES filter, and concentrated using Lenti-X Concentrator (Takara Bio 631231). Lentiviral pellets were resuspended in DMEM, aliquoted and stored at -80°C. Viral infectivity was tested empirically on 293T cells. Lentiviral transduction of human alveolar epithelial cells AEC-ROCKinh cells (passage 4) were plated onto 96-well culture plate in Fmed+ROCKinh media. The following day when cells were at 40-50% confluency, different amounts of LeGO iG-CDK4 R24C, LeGO iT-hTERT, and LeGO iG-SV40 LgT viruses, singly or in combination, were mixed with 8 µg/mL polybrene in Fmed+ROCKinh media. Amounts of virus used were determined empirically based on 293T test infection. Two days post-transduction, when wells were 90-100% confluent, cells were detached with Accutase and replated onto 48-well culture plate. At four days post-transduction, expression of CDK4 R24C, hTERT, and SV40 LgT was checked by fluorescence microscopy (Nikon Eclipse Ti-U inverted fluorescence microscope). 41 Cells transduced with LeGO iT-hTERT only, LeGO iT-hTERT + LeGO iG-CDK4, or LeGO iT- hTERT + LeGO iG-SV40 LgT were sorted by FACS on eGFP, tdTomato, or dual fluorescence at the USC Flow Cytometry Core Facility (FACS Aria II, BD Biosciences). All cell lines were maintained in Fmed+ROCKinh media. Proliferation assay One thousand cells were plated on a 24-well culture plate in quadruplicates and monitored for seven days. Twenty-four hours post seeding (day 1), cells were detached with Trypsin-EDTA (0.05% Trypsin, 0.02% EDTA) and resuspended in growth media. Cells were counted manually using a hemocytometer. Cell counts are reported as average total cell number ± standard deviation from at least three biological replicates. Population doubling time (PDT) was calculated using the equation [(t2-t1)/3.32] X (log n2 – log n1), based on the linear part of the growth curve. High density proliferation assays were performed in the same manner with the exception of the initial cell seed count being 5000 cells per well. Anchorage-independent growth assay Per well of a 6-well culture plate, 1.5 mL of 0.6% (w/v) Difco Noble Agar (BD Biosciences 214220) in Fmed+ROCKinh media was added to form the bottom layer of the soft agar assay. For the top layer, in 1.5 mL, five thousand cells were mixed with 0.3% Noble Agar in Fmed+ROCKinh media. Top layer was allowed to solidify at room temperature before 1 mL Fmed+ROCKinh media was carefully added. For A549 positive control cells, RPMI 10% FBS was used to set up soft agar layers. Media was changed every 3 days. Colony growth was monitored for 1 month. Colonies were visualized by crystal violet staining (crystal violet 42 dissolved in 10% ethanol) and counted using ImageJ software. Experiments were replicated biologically at least three times, each with six technical replicates. Quantitative PCR Total RNA was isolated and purified using the Illustra Triple Prep kit (GE Healthcare Life Sciences 28-9425-44) and eluted in nuclease-free water. Reverse transcription was performed using 2 µg RNA in 40 µL reaction using iScript cDNA synthesis kit (BioRad 170-8891). Quantitative PCR was performed using SYBR Green (BioRad 170-8886) and relative expression was calculated using 2 -(ΔΔCt) method. Gene expression levels are reported in terms of fold change over whole adult lung RNA. Primer sequences were designed based on Human Genome Assembly hg38 available on the UCSC Genome Browser (Marconett et al., 2013). Karyotyping Cells were seeded in 60 mm culture dishes to reach 60-70% confluency the following day to be treated with 25 ng/mL colcimide in culture media overnight. Cells were visualized under bright field microscope to ensure cells had balled up due to metaphase arrest. Cells were then harvested, washed with PBS, and fixed in methanol:acetone (3:1, v/v), two changes, according to Hsieh CL 1998. Fixed metaphase spreads were then analyzed by Dr. Chih-Lin Hsieh (USC Norris Comprehensive Cancer Center, Los Angeles) using GTW banding method. Three-dimensional co-culture Actively dividing AEC-LT14 cells between passages 6 and 19 were used to set up 3D co-culture with neonatal mouse lung fibroblasts, MLg (ATCC CCL-206). MLgs were cultured in EMEM 10% FBS and maintained at sub-confluence. Noticeable lower sphere formation efficiency was observed when MLgs that had been grown beyond 70% confluence were used in the 3D co- 43 culture. Five thousand AEC-LT14 cells were mixed with 50,000 MLgs in Basic medium (phenol-red free DMEM/F12 (Gibco 11039021), 1X ITS (Gibco 41400-045), 10% FBS, 1X Antibiotic-Antimycotic) with 50% Growth Factor Reduced Matrigel (Corning 47743-720) and plated on Clear Transwell inserts (Corning 3470), 100 µL per insert. Basic medium supplemented with 10 µM SB-431542 (BioVision 1674) was added to the outer chamber and replaced every 2 days. Sphere formation was monitored under bright field microscopy for 1-2 months. Whole well images were captured using Leica MZ16 F fluorescence stereomicroscope and Spot Advanced software (v4.5.8) through the USC Hastings Center for Pulmonary Research Core. Images at 4X bright field and fluorescence magnification were captured using Echo Revolve R4 fluorescence microscope. Treatment with Wnt agonist or FGFs: Three-dimensional co-cultures were set up as described above. Treatment with 1 µM Wnt agonist CHIR99021 (Sigma Aldrich SML1046) dissolved in DMSO or 10 ng/mL FGF7 (Peprotech 100-19) and 10 ng/mL FGF10 (Tonbo Biosciences 21- 7054) dissolved in sterile PBS began two days following culture set up, where SB Basic medium was replaced with fresh SB media containing either CHIR99021 or FGF7+FGF10, or DMSO (vehicle control). Media was changed every two days. Cultures were maintained for two months before sphere size and number were assessed. Whole-well images were captured using Leica MZ16 F fluorescence stereomicroscope. Zoomed images were taken with Echo Revolve R4 fluorescence microscope. Sphere size in microns was measured using the length feature on Echo Revolve R4 microscope; reported sizes are based on the longest diameter. Sphere number was determined using the count feature on Echo Revolve R4 microscope. Values are reported as the mean ± standard deviation. 44 Histological Processing Once spheres have formed, inserts were removed and fixed with room temperature 4% PFA for 30 min. PFA solution was removed by inverting inserts. Inserts were then submerged in 1X PBS for 15 min with two changes and dehydrated in 70% ethanol for 30 min with three changes. Matrigel samples were removed from insert housing by cutting the filter out from the bottom face with a feather razor, then embedded in Histogel (ThermoFisher HG-4000) and equilibrated in 70% ethanol for 1 h room temperature. Histogel "buttons" were further dehydrated using standard methods, then embedded in paraffin wax. Paraffin blocks were sliced to 5 µm sections in-house using Microm HM 314 microtome through the USC Hastings Center for Pulmonary Research Core. Immunofluorescence staining For 2D cultures: Cells were plated on standard multiwell culture plate to reach confluence the following day. Cells were rinsed with filtered 1X PBS, fixed with ice cold methanol for 10 min, washed three times with PBS, blocked with 5% filtered BSA in PBS, then probed overnight at 4C with respective primary antibodies in 5% BSA-PBS solution. The following day, cells were washed with PBS, probed with Biotinylated secondary antibodies in PBS for 1 h, washed, then probed with Streptavidin-Alexa Fluor 647 conjugate (ThermoFisher, S21374). DAPI mounting solution was used as counterstain (Vector Laboratories H-1200). Stained cells were viewed using Nikon Eclipse Ti-U inverted fluorescence microscope and imaging software, NIS-Elements Br (v4.00.12, build 802, 64-bit). Antibodies: Primary: HOPX (SCBT, sc-30216, pro-SPC (Seven Hills Bioreagent, WRAB-9337), SV40 LgT (SCBT, sc-147), AQP5 (Abcam, ab92320), ECAD (BD Biosciences, 610181), 45 NKX2-1 (Leica, NCL-TTF1), Ki67 (Abcam, ab16667), SOX2 (SCBT, sc-365823), SOX9 (ThermoFisher, 14-9765-80). Secondary: Biotinylated horse anti-mouse IgG (Vector Laboratories, BA-2000), Biotinylated goat anti-rabbit IgG (Vector Laboratories, BA-1000). For 3D cultures: Paraffin sections were baked in 60°C oven for 12 hours. Excess paraffin was wiped off using Kimwipes. Slides were then submerged in xylene, two changes, 5 min each, rehydrated through a series of ethanol baths, and rinsed with distilled water. Samples were boiled in Tris-based antigen unmasking solution (Vector Laboratories H-3301) in a standard microwave oven, cooled to room temperature, then permeabilized with 2% Triton X-100 in PBS for 15 min, washed with PBS, then blocked with 5% BSA-PBS for 1 h room temperature. Primary antibodies were diluted in 5% BSA-PBS and probed overnight at 4°C. Subsequently, all washes were with 1X TBST (20 mM Tris, 150 mM NaCl, 0.01% Tween 20, pH 7.5). For single and double stainings, Biotinylated secondary antibodies, Streptavidin-Alexa Fluor 647, Streptavidin-Alexa Fluor 488 (ThermoFisher S11223), and Streptavidin-FITC (ThermoFisher SA-10002) were diluted in PBS and incubated 1 h room temperature each step. Sections were mounted with Prolong Gold antifade reagent with DAPI (Invitrogen P36931), sealed with nail polish, then stored at 4°C. Slides were visualized the following day using Echo Revolve R4 fluorescence microscope. Statistical Analyses No test for normality could be done on the experiments presented in this study, therefore a normal distribution of observations cannot be assumed. Wilcoxon nonparametric rank sum test on independent samples were performed for proliferation assays, anchorage-independent growth assays, and 3D sphere size and percent sphere forming efficiency comparisons. Wilcoxon tests 46 were performed on R programming software using the function wilcox.test() on the appropriate dataset. RNA-seq Analyses RNA-seq analyses comparing derived AEC cell lines with normal lung cells and LUAD cancer cell lines were performed using publicly available data from ENCODE (https://www.encodeproject.org/) and DBTSS (https://dbtss.hgc.jp/) databases (See Table 2 below). For AEC cell lines (AEC-CDK4, AEC-hTERT, AEC-CDK4+hTERT, AEC-FT- LT02A1) and the adult human lung fibroblast cell line (HLF-133), total RNA was isolated from subconfluent, exponentially dividing cells using Illustra TriplePrep kit (GE Healthcare 28-9425- 44) following manufacturer’s instructions. 2 µg of RNA was submitted to the USC Molecular Biology Genomics Core facility for sequencing. RNA quality was assessed on a Bioanalyzer (Agilent) and rRNA depleted (Illumina MRZH11124) before proceeding with library preparation (Illumina TruSeq mRNA Stranded Library preparation kit, Illumina 20020594). These samples were sequenced paired-end 75 bp (PE75), at a depth of ~ 20-30 million reads per sample, on a HiSeq2000/2500 machine (Illumina). For AEC-ON-LT12E4 and AEC-TN-LT10E1 cell lines, total RNA was isolated using the Illustra TriplePrep kit as detailed above. 1 µg of RNA was submitted to the UCLA Technology Center for Genomics and Bioinformatics for sequencing. Samples were rRNA depleted with RiboZero and libraries were prepared at the UCLA facility. Samples were quality-controlled by the UCLA Core using a Bioanalyzer. Libraries were paired- end 75 bp sequenced at a depth of ~ 30 million reads per sample on a NextSeq500 Mid Output machine (Illumina). Raw fastq files were retrieved and processed as follows. 47 Raw fastq files generated from our samples and files taken from ENCODE and DBTSS (Table 2) were uploaded to Partek Flow through the USC Norris Medical Library Bioinformatics Core using the High-Performance Computing nodes. Files were quality-controlled using Partek’s QC tool and trimmed at both ends using Partek default parameters, then aligned using STAR RNA- sequence aligner (v 2.6.1d) and aligned to the Human Genome assembly 38 (hg38) GENCODE Genes, release 29. Raw read counts were generated by quantification to the transcriptome using Partek E/M algorithm under default parameters, again using assembly hg38 GENCODE, release 29. Raw counts were then analyzed and processed in R using the DESeq2 package, as outlined in the Bioconductor Manual Beginner’s Guide to DESeq2 (Love et al., 2014). 48 49 Chapter 3 RESULTS 50 Direct transduction of adult primary AECs results in ineffective immortalization Primary AT2 cells were isolated as previously reported [Marconett et al., 2013]. Based on the reported immortalization strategy used by Ramirez et al. (2004), I infected freshly isolated primary AT2s from Lung 3 (see Table 6) with lentiviruses carrying genes encoding the catalytic subunit of human telomerase (hTERT) (pLOX-hTERT-TK) and mutant CDK4 (CDK4 R24C ) which has a GFP fluorescent marker (LeGO iG-CDK4 R24C ). I infected cells with increasing amounts of lentivirus based on empirically determined infectivity on 293T cells. Cells were maintained in 50/50 media + 10% FBS. Figure 7 shows a schematic of the lentiviruses used in this study. Five days following infection, many dead and dying cells were observed in all wells containing virus, even in wells containing low titers of virus. Cells that survived were large and flat, with rounded morphologies and prominent lamellopodia. By day 10 post-infection, clusters of green cells were visible along the edges of several wells. Some cell clusters exhibited a fibroblast-like morphology forming foci in the culture dish; other clusters were more epithelial- like, growing in a dense monolayer. One month post-infection, cells maintained green fluorescence and were confluent enough to passage from a 24-well multiwell plate to a 6-well plate. Three weeks later, confluent wells were passaged to T25 flasks (Figure 8A). Transduced cells were maintained in 50/50 media +10% FBS and when confluent, passaged using 0.05% Trypsin-EDTA solution. These cells were maintained for one year in culture, up to six passages, before what appeared to be the onset of cellular senescence. At this point, cells had stopped dividing even when more FBS was added (to final concentration of 20%). Cells were larger and had more prominent nuclei, but there appeared to be no sign of apoptosis based on the observation that growth media was generally free of cellular debris. 51 To determine whether these growth arrested cells could be stimulated to reenter the cell cycle, I tried transducing the cells with lentivirus carrying SV40 Large T antigen (SV40 LgT) (Figure 7). I observed minimal cell death 24 hours following transduction. Three days post-infection, wells were ~ 70% confluent. Surviving cells looked morphologically similar to fibroblasts (Figure 8B) and proliferated rapidly, suggesting that either 1) transduction of SV40 LgT promoted cell proliferation through induction of epithelial-to-mesenchymal transition (EMT) or 2) transduction enriched for contaminating fibroblasts present in the original AT2 cell population, since purification was not 100% efficient. Cells were passaged using Accutase, a gentler detachment solution compared to 0.05% trypsin-EDTA [Bajpai et al., 2008]. These fibroblast-like cells were maintained for at least two months before they were cryogenically frozen and stored for future experimentation. As a second attempt to derive cells, I re-cloned the hTERT gene into a new lentiviral expression vector containing tdTomato fluorescent indicator (LeGO iT-hTERT) (Figure 7). This construct Figure 7. Schematic of lentiviral plasmids used to immortalize primary AECs. A) LeGO iG-CDK4 R24C B) pLOX- hTERT-TK (unmodified from Addgene 12245) C) LeGO iG-SV40 LgT D) LeGO iT-hTERT. Promoters are represented by horizontal arrows. DNA elements are not to size. SFFV, spleen focus-forming virus promoter; CMV, cytomegalovirus promoter; IRES, internal ribosome entry site; TK, thymidine kinase (for negative selection upon treatment with ganciclovir. Not used in this study). 52 combined with the original LeGO iG-CDK4 R24C plasmid (encoding GFP) would allow me to identify proper expression of both genes by fluorescence. Using thawed primary AECs previously frozen and stored in liquid nitrogen, I transduced this new batch of cells with both lentiviruses. Unfortunately, few cells survived the infection even at lower concentrations of virus (Figure 8C). Moreover, of the cells that did survive, none were GFP nor tdTomato positive. These surviving cells eventually apoptosed in culture. AT2 cells spontaneously transdifferentiate into AT1-like cells in culture. These AT1-like cells have attenuated cell bodies and a high overall surface area physiologically facilitating gas exchange. The resulting failure to immortalize primary AECs by direct transduction of "immortalizing" viruses may be because the transdifferentiated AT1-like cells are exquisitely sensitive to external manipulation. Perhaps the intractability of AECs in culture is due to their physiological function of preventing foreign/harmful particles from entering the lung. Indeed, the Figure 8. Morphologies of AECs following different lentiviral transduction strategies. A) Freshly isolated primary AECs were transduced with lentiviruses carrying hTERT (no fluorescence marker) and CDK4 R24C (GFP marker). These cells were eventually growth arrested. B) Growth arrested AECs from (A) were re-transduced with LeGO iG-SV40 LgT lentivirus. Cells adopted a more fibroblast-like morphology. C) Previously cryopreserved AECs were thawed, then transduced with LeGO iG-CDK4 R24C and LeGO iT-hTERT lentiviruses. Transduction efficiency was poor, cells were visibly stressed, and eventually apoptosed. 53 alveolar epithelium is the largest contact surface between the interior and the exterior of the human body (calculated to be about 75 m 2 or half a tennis field in size), and thus must have an elaborate defense against foreign agents and particles. Another reason for failure to immortalize could be that the cells are not molecularly "primed" to respond to mutant CDK4 and hTERT. Looking through the literature, I noticed that successful immortalization seemed to be reported for primary human cells that had at least some proliferative capacity even after isolation and purification [Herbert et al., 2002; O’Hare et al., 2001]. The Ramirez et al. (2004) paper used retroviruses to deliver CDK4 and hTERT, indicating that bronchial epithelial cells were proliferative in culture before immortalization. Moreover, the authors mentioned that HBECs were subcultured first before transduction. I therefore hypothesized that successful immortalization of primary AECs required first stimulating the cells to proliferate in culture, then transducing these dividing cells with immortalizing viruses. Optimization of culture media conditions to propagate adult primary AECs Isolated human AECs spontaneously transdifferentiate in culture and do not proliferate [Dobbs, 1990; Fuchs et al., 2003]. To determine optimal culture conditions in which to maintain primary AECs, I tested media concoctions containing growth factors and small molecules reported to promote cell survival and proliferation of primary epithelial cells. Table 3 lists the media conditions used in this screen. Using thawed primary AECs that were previously frozen following isolation, I plated about 6250 cells per well of a 96-well multiplate in each media condition. Cells were allowed to attach for two days before growth media was replaced with freshly reconstituted media. Wells were monitored for outgrowth every day. In the first two days after plating, most cells did not attach, and growth media contained lots of cellular debris. Wells 54 containing ROCK inhibitor, Y27632, KGF, BIO, and 20% FBS had several cells attached, but not yet flattened. After 3 weeks, only wells containing ROCK inhibitor retained cells. Eventually, only the well containing 10 µM ROCK inhibitor supported cell survival and proliferation. By visual inspection, only 10-20% of the well was populated by cells. About six weeks post-plating, cells were passaged using Accutase to 48-well multiwell plate. From this passage on, cells maintained their proliferative capacity even after detachment and re-plating when grown in media containing ROCK inhibitor. Cells grew as a monolayer and were contact inhibited. Relative expression of common AEC markers was assessed by quantitative PCR (qPCR). AEC-ROCKinh cells were negative for AT2 markers (NKX2-1, SFTPC). Cells moderately expressed AT1 marker, AQP5, and highly expressed the AT1 marker CAV1 compared to whole lung tissue (Figure 9). 55 Figure 9. Relative expression of alveolar epithelial cell markers in AEC cells expanded in ROCK inhibitor media. Previously frozen AEC type 2 cells were plated in media containing ROCK inhibitor, Y27632. Cell outgrowths were passaged using Accutase detachment solution and maintained in ROCK inhibitor media. At passage 6, when cells grown in T25 flask were ~ 70% confluent, cell pellet was collected for RNA isolation and subsequent qPCR analyses. Actin was used for expression normalization. Whole lung RNA was used as a reference. 56 57 Derivation of a collection of proliferative AEC cell lines To ensure that the proliferative capacity of the derived cells was maintained, I transduced these AEC-ROCKinh cells with lentiviruses carrying hTERT, CDK4 R24C , or SV40 LgT in different combinations: hTERT alone, CDK4 mutant alone, hTERT and CDK4 mutant, and SV40 LgT alone. Cells were transduced in 96-well format, with technical triplicates for each viral condition. Infection media was diluted with ROCK inhibitor media 20 hours after the addition of lentivirus; cells were allowed to recover for 2 days post-transduction. Unlike with direct transduction in 50/50 + 10% FBS, transduction of AEC-ROCKinh cells did not yield remarkable amounts of cell death. Cells were still attached and continued proliferating several days post-transduction. When wells became confluent, cells were passaged into a 48-well multiwell plate. GFP and tdTomato fluorescence intensities were still low at this point. At passage 4, about 1 month post- transduction, fluorescence intensities of GFP and tdTomato were well above background (Figure 10). Transduced cells were maintained in media containing ROCK inhibitor. As shown in Figure 11, a polyclonal population of cells resulted following each lentiviral transduction. Cells were proliferative and morphologically large with rounded membrane and bulbous nuclei. At full confluence, cells were contact inhibited, suggesting that these cells maintained their epithelial origin. Interestingly, cells transduced with SV40 LgT were small and compact, and highly migratory at subconfluence based on the observance of filopodia and lamellopodia. 58 Figure 10. Representative fluorescent images of lentivirally transduced AEC-ROCKinh cells at passage 4. A) Initial population of AEC-ROCKinh cells expanded from the previous media optimization experiment. These were used for subsequent transduction with LeGO iG-CDK4 R24C (B), LeGO iT-hTERT (C), CDK4 R24C +hTERT (D), or LeGO iG-SV40 LgT (E). Scale bar, 100 µm. 59 Figure 11. Alveolar epithelial cell line derivation scheme using ROCK inhibitor media. Previously frozen purified alveolar epithelial cells were initially plated in media containing ROCK inhibitor, Y27632. Cell outgrowths were expanded for cryopreservation and subsequent lentiviral transduction. A) Brightfield image of AEC-ROCKinh cells expanded from ROCK inhibitor media only. Resulting transduced cell lines expressing B) hTERT, C) CDK4 R24C , D) CDK4 R24C +hTERT, or E) SV40 LgT. Side panels show merged fluorescent images of tdTomato (hTERT), GFP (CDK4 R24C or SV40 LgT), or both tdTomato and GFP (CDK4 R24C +hTERT). Scale bar, 100 µm. 60 Characterization of the transformation state of AEC cell lines Since these AEC cell lines were generated using chemical and genetic modifications, it is possible that the cells had acquired additional changes precluding their use as “normal” cell models. To determine the transformation status of these newly derived cells, I performed proliferation and soft agar assays. As a reference for full cellular transformation, A549 cells were used. A549 cells are a lung adenocarcinoma cell line derived from a patient [Giard et al., 1973]. To assess the rate of proliferation, 1000 cells were plated in a 24-well multiwell plate in quadruplets and counted every day for six days. As shown in Figure 12, AEC-LT cells proliferated faster than AEC-ROCKinh, AEC-hTERT, AEC-CDK4 R24C , or AEC- CDK4 R24C +hTERT cells, comparable to A549 cells. AEC-LT population doubling time (PDT) of 1.1 ± 0.2 days was not statistically significantly different from A549 PDT of 1.3 ± 0.4 days (mean ± stdev, Wilcoxon nonparametric t-test, p-value = 0.504). Population doubling times for the remaining cells were not calculated because exponential growth was not achieved within the assay conditions tested. 61 Figure 12. Proliferation assay on AEC cell lines. One thousand cells were plated per well of a 24-well multiwell plate in quadruplets and counted every day for six days. A549 and AEC-LT cells achieved exponential growth during this time. A549 PDT, 1.3 ± 0.4 days. AEC-LT PDT, 1.1 ± 0.2 days. PDTs were not statistically significantly different between A549 and AEC-LT cells (p=0.504, Wilcoxon nonparametric t-test) Figure 13. Proliferation assay on AEC cell lines at higher initial seeding density. Five thousand cells were plated per well of a 24-well multiwell plate in quadruplets and counted every day for six days. A549 and AEC-LT cells were not assessed under these conditions. AEC-hTERT, and AEC-CDK4 R24C +hTERT cell lines still did not reach exponential growth within the time period of this assay. No PDTs were calculated. AEC-CDK4 R24C cells were not assayed because they were not able to recover from cryopreservation. 62 To determine whether the extended lag phase of the slow-growing cells was due to initial seeding density or truly reflective of the cell’s replicative capacity, I performed the same proliferation assay with a higher initial cell number. Five thousand cells were plated in a 24-well multiwell plate and counted every day for six days, as described above. Under these conditions, AEC-hTERT and AEC-CDK4 R24C +hTERT cells still did not achieve exponential growth, therefore PDTs were not calculated (Figure 13). AEC-ROCKinh cells reached exponential growth within the six-day time frame of the experiment when assayed at very low passage (P4) (PDT 0.8 ± 0.07 days) (Figure 14). However, when assayed at passage 6, after expanding the cells from a 1:3 dilution on a 10 cm dish, exponential growth was not attained (Figure 14). Thus, PDT was not calculated for P6 cells. Table 4 summarizes the PDT data. The drastic difference in cell proliferation kinetics between passages was not readily observed in other AEC cell lines, and may reflect the strong mitogenic effect of ROCK inhibitor on cells in the absence of additional “immortalizing” perturbations [Rizzino, 2010]. AEC-CDK4 R24C cell proliferation was not assessed under these conditions because cells did not revive from stored cryovials, even at low passages. This technical issue is currently being investigated. 63 To determine whether the cells exhibit anchorage-independent growth, a common feature of transformed cells, I performed soft agar assays on all cells. Five thousand cells were suspended in agarose dissolved in growth media containing ROCK inhibitor. Media was changed every other day and colony formation was assessed one month later by crystal violet staining. A549 cells were used as a positive control. No colonies were detected for AEC-ROCKinh, AEC- Figure 14. ROCKinh cells undergo rapid proliferation at very low passages. Similar to Figure 6, five thousand AEC-ROCKinh cells at passage 4 (P4) and 6 (P6) were plated and counted every day for six days. AEC-ROCKinh (P4) cells rapidly reached exponential growth upon one day of culture at higher cell density. By day 2, cells had entered exponential growth with a PDT of 0.8 ± 0.07 days. AEC-ROCKinh (P6) cells, however, did not reach exponential growth during the time frame of this experiment. 64 hTERT, AEC-CDK4 R24C , or AEC-CDK4 R24C +hTERT cells. In contrast, AEC-LT cells consistently generated soft agar colonies comparable to A549 cells (246 ± 55 colonies versus 284 ± 186 colonies; difference not significant by Wilcoxon nonparametric t-test, p-value = 0.781) (Figure 15A, B). Figure 15. Anchorage-independent growth assays. A) Anchorage-independent growth potential is observed only in AEC-LT cells. Whole well images of six-well multiplates. Five thousand cells were plated in soft agar with ROCK inhibitor growth media overlaying the top gel. A549 cells were used as positive control. Colonies were stained with crystal violet and counted after 1 month of growth. Inset images are 2.5X zoomed to show colonies. B) Quantification of total colony growth based on 6 technical replicates, from at least 3 independent experiments. Colony formation was not significantly different between A549 and AEC-LT cells by Wilcoxon nonparametric t-test. Plotted values are centered on mean ± standard deviation. 65 Although the formation of soft agar colonies is typically suggestive of cellular transformation, it is not always indicative of malignancy. BEAS-2B cells, a commonly used normal bronchial epithelial cell line, exhibit anchorage-independent growth in soft agar, but do not form tumors when injected subcutaneously into nude mice [Reddel, 1988]. Subcutaneous injection of AEC- LT cells into nude mice are currently underway at the time of this thesis. Our experimental setup will be as follows: Negative control cells will be AEC-hTERT cells, positive control cells will be A549s, and the test cell line is AEC-LT. One million cells of each cell line will be suspended in Matrigel, then injected into the flanks of nude mice, one cell line per flank. Injection of AEC-LT cells on one flank will be accompanied by injection of either negative or positive control cells on the other flank. Mice will be monitored for at least one month, with tumor size measured every two days. The experiment will be conducted as a single-blind study, where the injector (who will also be the measurer) will not know the identity of the sample. We will use 6 mice per comparison (negative vs AEC-LT; positive vs AEC-LT), 12 mice total. The cell lines that will be used in this study have already been tested for rodent pathogens through the USC Department of Animal Resources and for mycoplasma (see Materials and Methods). Results from this assay will aid in the assessment of the transformed state of these cells in vivo. Preliminary karyotyping by G-banding was performed on AEC cell lines, as well as A549 and BEAS-2B cells. Consistent with reports in the literature, A549 and BEAS-2B cells exhibited abnormal to aneuploid karyotypes. AEC cell lines, including AEC-LT cells, exhibited normal number of chromosomes, suggesting that these cells are genomically stable despite lentiviral transduction and multiple rounds of passaging. 66 Derivation of additional AEC cell lines from two normal lungs Since SV40 LgT transduced cells proliferate well in culture, retain a normal karyotype, and remain contact inhibited similar to primary cells, I generated biological replicates of the AEC-LT cell line from two additional human lung preparations. Table 5 summarizes all de-identified lung donor samples used in this study. Table 6 summarizes the different strategies used in this study to derive proliferating AEC cells, including attempts that failed. The two additional AEC-LT cell lines, termed AEC-ON-LT12E4 and AEC-TN-LT10E1, exhibited epithelial-like morphology and were contact inhibited upon complete confluence (Figure 16). Interestingly, proliferation and soft agar assays of these cells revealed different growth kinetics than the original AEC-LT cell line (hereby termed AEC-FT-LT02A1). Plated at 1000 cells per well, AEC-ON-LT12E4 and AEC-TN-LT10E1 exhibited an extended lag phase similar to AEC-ROCKinh, AEC-CDK4 R24C , and AEC-CDK4 R24C +hTERT cells. Under these conditions, AEC-ON-LT12E4 and AEC-TN- LT10E1 did not reach exponential growth (Figure 17A). However, when plated at a higher density, cells replicated readily, reaching exponential growth four days after plating, with PDTs of 1.1 ± 0.05 days for AEC-ON-LT12E4 and 2.1 ± 0.4 days for AEC-TN-LT10E1 (Figure 17B and Table 7). Under anchorage-independent growth conditions, both AEC-ON-LT12E4 and AEC-TN-LT10E1 cells did not readily form soft agar colonies (2 ± 1 colonies and 3 ± 2 colonies, respectively) unlike AEC-FT-LT02A1 cells (Figure 18A, B), although under 10X bright field magnification, small colonies were visible after 1 month of growth (Figure 18C, D). 67 68 Figure 16. Derivation scheme for two additional AEC-LT cell lines from normal lungs. Previously frozen isolated AECs were initially grown in ROCK inhibitor media, as before, then transduced with lentivirus carrying SV40 LgT. The resultant polyclonal cell lines called AEC-ON-LT12E4 (A) and AEC-TN-LT10E1 (B) maintained an epithelial monolayer in 2D culture and were contact inhibited at full confluence. Scale bar, 100 µm. 69 Figure 17. Proliferation assay on additional AEC cell lines. A) One thousand cells (low density) or five thousand cells (high density) were plated and counted every day for 6 days. Both of the additional cell lines AEC-ON- LT12E4 and AEC-TN-LT10E1 failed to reach exponential growth when plated at low density. B) At high density, AEC-ON-LT12E4 exhibited a population doubling time (PDT) of 1.1 ± 0.05 days. AEC-TN-LT10E1 cells showed a PDT of 2.1 ± 0.4 days. 70 Figure 18. Anchorage-independent growth assays. A) Limited anchorage-independent growth potential was observed for AEC-ON-LT12E4 and AEC-TN-LT10E1 cells. Whole well images of 6-well multiplates. B) Quantification of soft agar colonies after 1 month of growth. C) AEC-ON-LT12E4 and D) AEC-TN-LT10E1 cells formed small colonies in soft agar. 10X magnification images of soft agar wells are included because whole well images of anchorage-independent growth assays did not readily show colony growth for AEC-ON-LT12E4 and AEC-TN-LT10E1 cell lines. Scale bar, 900 µm. 71 AEC cell lines are transcriptomically distinct from primary AECs and LUAD cell lines To compare the transcriptomes of the new AEC cell lines to primary AECs and LUAD cancer cell lines, I performed paired-end RNA-sequencing on my new AEC cell lines. Total RNA was isolated and purified from AEC cell lines at subconfluence to ensure cells were exponentially dividing. Cells between passage 6 and 10 were used. Total RNA from freshly isolated primary alveolar epithelial type 2 cells (AT2s) and AT2 cells transdifferentiated on filters for eight days into alveolar epithelial type 1-like cells (AT1) were isolated and purified previously in the same manner as the AEC cell lines to avoid purification bias (see Materials and Methods). Additional primary lung cell and LUAD cancer cell line RNA-seq data were downloaded from publicly available databases: Encyclopedia of DNA Elements database (ENCODE, www.encodeproject.org) and DataBase of Transcriptional Start Sites from Japan (DBTSS, www.dbtss.hgc.jp) (Table 8). A total of 42 samples were used in this study. I performed exploratory analyses on the sample set to look at salient features in the data. A sample-sample distance matrix plot was generated to look at the relationship between samples based on their overall gene expression (Figure 19). Based on the default Euclidean distance measure, 6 groups stand out comprising the LUAD cancer cell lines, the initial collection of AEC cell lines, the AEC-LT biological replicates, lung fibroblasts, AT1 cells, and AT2 cells. The human fetal lung tissue clustered away from all samples and so will not be considered here. Principal Component Analysis (PCA) (Figure 20) revealed 5 main clusters: primary AECs, LUAD cell lines, the initial collection of AEC cell lines, lung fibroblasts, and the AEC-LT biological replicates. Interestingly, although AEC-ON-LT12E4 and AEC-TN-LT10E1 were generated by transduction of SV40 LgT in a similar fashion to AEC-FT-LT02A1 cells, these two 72 lines clustered separately from the other ROCKinh-derived cells. Thirty-nine percent of the variation in the data divides the sample set between clusters containing cultured cells (LUAD, fibroblasts, AEC cell lines) and uncultured cells (primary AECs and fetal lung tissue), reinforcing the relevance of culture conditions on the identity of human cells. Next, I performed unsupervised hierarchical clustering on the top 500 most variable genes. Initial inspection of the changes in overall gene expression from primary cells to LUAD samples suggests a trend towards loss of lung specificity as cells become cancerous. Some highly expressed genes indicated by the color orange on the heatmap are gradually lost in AEC cell lines, then fully downregulated in LUAD (Figure 21). Because the AEC cell lines clustered more closely to lung fibroblasts than to primary AECs, I determined whether the AEC cell lines expressed lung-related genes more highly compared to lung fibroblasts. I subset the expression data on 75 lung-related genes manually annotated based on articles with RNA-seq data (both bulk and single-cell seq) (Figure 22A) [Treutlein et al., 2014; Xu et al., 2016; Zacharias et al., 2018]. As shown in Figure 22B and C, AEC cell lines expressed these lung-related genes more highly than lung fibroblasts, but much lower than primary AECs, suggesting that the similarity between AEC cell lines and fibroblasts was likely driven by the fibroblasts being the only other sample type that is normal or noncancer but cultured on plastic. 73 74 Figure 19. Sample-sample distance matrix showing 6 salient clusters. A sample-sample distance matrix determines how closely related samples are based on their gene expression profiles. Similarities were measured by Euclidean distances using the DESeq2 R package by Love et al. (2014). The AEC cell lines are distinct from primary AECs (AT2, AT1) and LUAD cancer cell lines. Within the AEC cell lines, the newly derived biological replicates (AEC-ON-LT12E4 and AEC-TN-LT10E1) seem to cluster on their own. LUAD cancer lines AEC cell lines Additional AEC cell lines Fibroblasts AT1 AT2 75 Figure 20. Principal component analysis reveals 5 salient clusters based on analysis of the top 500 most variable genes. Another way to look at sample clustering is by considering the variance in gene expression in the dataset. In this analysis, 5 clusters are revealed: Groups correspond to the primary AECs, the new AEC biological replicates, LUAD cancer cell lines, lung fibroblasts and the original AEC cell line collection, and fetal lung tissue as a sole member in its group. The general clustering trend here is consistent with the Euclidean sample distance matrix in Figure 19. 76 Figure 21. Unsupervised hierarchical clustering of the top 500 most variable genes. Clustering shows large- scale differences between primary AECs, fibroblasts, the AEC cell lines, and LUAD cancer cell lines. F, fetal lung tissue; AT2, primary AEC; AT1, primary AEC; New, AEC-ON-LT12E4 and AEC-TN-LT10E1 lines; Fibro, lung fibroblasts; AEC cell lines, AEC-hTERT, AEC-CDK4 R24C , AEC- CDK4 R24C +hTERT, AEC-FT-LT02A1 lines; LUAD cell lines, lung adenocarcinoma cancer cell lines. LUAD cell lines AEC cell lines Fibro New AT1 AT2 F L 77 Gene_Symbol Cell Type marker Gene_Symbol Cell Type marker SFTPC AT2 SCGB1A1 Clara SFTPA1 AT2 SCGB3A2 Clara SFTPA2 AT2 CHAD Clara SFTPB AT2 UPK3A Clara SFTPD AT2 NUPR1 Clara ABCA3 AT2 CD200 Clara LPCAT1 AT2 KRT15 Clara NKX2-1 AT2 COL23A1 Clara CD36 AT2 CCND2 Clara LAMP3 AT2 NKX2-5 Basal cell EGFL6 AT2 SOX2 Basal cell SLC34A2 AT2 TP63 Basal cell DLK1 AT2 KRT5 Basal cell FABP5 AT2 KRT14 Basal cell SOAT1 AT2 ITGB4 Basal cell SCD AT2 JAG1 Ciliated NAPSA AT2 LYPD2 Ciliated ETV5 AT2 LRRC23 Ciliated PDPN AT1 CCDC39 Ciliated AQP5 AT1 FOXJ1 Ciliated AGER AT1 STK33 Ciliated TSPAN8 AT1 NCS1 Ciliated EMP2 AT1 CCDC113 Ciliated DPYSL2 AT1 CKAP2L Ciliated GPRC5A AT1 EFHC1 Ciliated CAV1 AT1 EFCAB10 Ciliated LMO7 AT1 NEK10 Ciliated AKAP5 AT1 TEKT4 Ciliated CLIC5 AT1 DTL Ciliated CLDN18 AT1 FAM161A Ciliated IGFBP6 AT1 FHAD1 Ciliated TIMP3 AT1 FANK1 Ciliated S100A6 AT1 HS6ST2 Ciliated AHNAK AT1 DNALI1 Ciliated COL4A3 AT1 KNDC1 Ciliated HOPX AT1 LRRIQ1 Ciliated MCM8 Ciliated CCDC40 Ciliated MELK Ciliated A Figure 22. AEC cell lines express lung-related genes more highly than lung fibroblasts, but much lower than primary AECs. (continue on next page) 78 Figure 22. AEC cell lines express lung-related genes more highly than lung fibroblasts, but much lower than primary AECs. A) List of 75 lung-related genes used in the generation of the heatmaps shown in (B) and (C). These genes were chosen based on their specific expression in AT2, AT1, Clara basal, and ciliated cells. B) Heatmap comparing scaled expression levels of RPKMs of AEC cell lines and lung fibroblasts. C) Heatmap comparing AEC cell lines to primary AECs. Pink bar demarcates AEC cell lines, green bar demarcates lung fibroblasts, yellow bar demarcates primary AEC samples. Sample columns were ordered based on unsupervised clustering based on “Ward’s” method. AEC Cell Lines Fibroblasts Primary AECs B AEC cell lines vs Lung Fibroblasts 79 Figure 22. AEC cell lines express lung-related genes more highly than lung fibroblasts, but much lower than primary AECs. A) List of 75 lung-related genes used in the generation of the heatmaps shown in (B) and (C). These genes were chosen based on their specific expression in AT2, AT1, Clara basal, and ciliated cells. B) Heatmap comparing scaled expression levels of RPKMs of AEC cell lines and lung fibroblasts. C) Heatmap comparing AEC cell lines to primary AECs. Pink bar demarcates AEC cell lines, green bar demarcates lung fibroblasts, yellow bar demarcates primary AEC samples. Sample columns were ordered based on unsupervised clustering based on “Ward’s” method. AEC Cell Lines Fibroblasts Primary AECs C AEC cell lines vs Primary AECs 80 AEC-LT cells exhibit expression features of lung progenitor cells ROCK inhibitor is a commonly used small molecule to aid in stem cell survival and proliferation [Claassen et al., 2009; Vernardis et al., 2017]. The addition of ROCK inhibitor, Y27632, and feeder cells has also been shown to enhance culturing of primary epithelial cells from mammary, prostate, and upper airway lung tissues [Liu et al., 2012]. However, in this process of facilitating cell survival, adult cells are reprogrammed to a stem-like state [Suprynowicz et al., 2012]. The RNA-seq data revealed large expression differences between the AEC cell lines and LUAD, lung fibroblasts, and the primary cells in line with the hypothesis that these AEC cell lines grown in ROCK inhibitor media have undergone reprogramming to a stem-like state. To further investigate this hypothesis, I looked at progenitor marker expression in the RNA-seq data. I found that my AEC cell lines expressed both SOX2 and SOX9, known lung progenitor markers, more highly than primary AECs (Figure 23A, B). Examining the expression levels of SOX2 and SOX9 for each AEC cell line, I found that AEC-FT-LT02A1 expressed SOX9 to a lower extent compared to the remaining AEC cell lines (Figure 23C). SOX2 is an important regulator of proximal lung cell fate, committing early lung stem cells to a basal cell fate [Ochieng et al., 2014; Daniely et al., 2004], whereas SOX9 regulates distal lung cell fate, committing early cells to an alveolar epithelial cell lineage [Rockich et al., 2014; Chang et al., 2013]. To corroborate this finding, I performed immunofluorescence staining (IF) on AEC-LT cells to probe for progenitor as well as mature alveolar epithelial cell markers (Figure 24). All three AEC-LT cell lines expressed both SOX2 and SOX9 proteins, in agreement with the RNA- seq data (Figure 24A). 81 Figure 23. Box-and-whiskers plot of RPKM values for SOX2 and SOX9. Raw counts were normalized to get RPKMs. A) and B) Airway epithelial cell RNA-seq data was used as a control for the trend in SOX2 and SOX9 expression in proximal versus distal lung cells. Airway epithelial cells highly express SOX2, a proximal lung marker. AEC cell lines express both SOX2 and SOX9 compared to primary AECs. C) Table of RPKMs for each AEC cell line for SOX2 and SOX9. C 82 Figure 24. Alveolar epithelial cell lines express lung progenitor, and not mature AEC markers. Cells were grown in 2D until confluent, then stained for A) SOX2, a proximal progenitor marker, and SOX9, a distal lung progenitor marker and B) alveolar epithelial cell markers NKX2-1 and pro-SPC, which are AT2 markers in the adult lung, and AQP5 and HOPX, which are AT1 markers. SV40 LgT was stained to confirm that the AEC-LT cell lines still expressed the protein and that the culture was a relatively pure population of transduced cells. ECAD, E-cadherin, an epithelial marker, was stained to show that the AEC-LT cells retained their epithelial cell lineage despite multiple passages. All three AEC-LT lines were positive for SOX2 and SOX9, and negative for mature alveolar epithelial markers, with the exception of AEC-ON-LT12E4 line, which expressed NKX2-1. 83 AEC-LT cells were also positive for SV40 LgT and E-cadherin (ECAD), an epithelial cell-cell junction protein, indicating that cells maintained expression of SV40 LgT, while retaining their epithelial cell phenotype despite numerous passages. AEC-LT cell lines were negative for mature AT1 markers AQP5 and HOPX, and AT2 markers pro-SPC and NKX2-1, except for AEC-ON-LT12E4 which highly expressed NKX2-1 (or thyroid transcription factor-1, TTF1) (Figure 24B). NKX2-1 is a central transcriptional regulator of lung endoderm specification as well as of lung cell differentiation [Herriges and Morrisey, 2014; Minoo, 2000]. Notably, although NKX2-1 regulates expression of the AT2 marker surfactant protein C (SFTPC), I did not detect expression of SFTPC in AEC-ON-LT12E4 by IF staining. AEC-LT cells retain the ability to form lung spheroids in three-dimensional co-culture Purified alveolar epithelial cells from mice have been shown to form lung organoids when cultured with stromal cells and suspended in Matrigel [Barkauskas et al., 2013; Jain et al., 2014; Zacharias et al., 2018]. This three-dimensional culture system has also been used to assess differentiation capabilities of iPSC-derived alveolar epithelial cells [Jacob et al., 2017] To determine whether AEC-LT cells possess the ability to form three-dimensional (3D) structures, I cultured exponentially-growing AEC-FT-LT02A1, AEC-ON-LT12E4, and AEC-TN-LT10E1 cells in this co-culture system, adapting conditions based on previously reported findings [Barkauskas et al., 2013; Zhou et al., 2018; Zacharias et al., 2018]. For my 3D co-culture experiments, I used the neonatal mouse fibroblast cell line (MLg) purchased from ATCC as supportive cells. Figure 25A illustrates the general setup of the 3D co-culture system. 84 Since the literature reported varying numbers of fibroblasts used in this co-culture system, I tested different ratios of MLgs to epithelial cells to determine which condition facilitated sphere growth. The growth media I used contained 10% filtered fetal bovine serum (FBS), insulin- transferrin-selenium solution, and 10 µM TGFβ inhibitor, SB-431542, as was reported by Zhou et al. (2018). In duplicate, I plated 5000 AEC-FT-LT02A1 cells mixed with either 5,000, 10,000, 25,000, or 50,000 MLgs in 50% growth factor-reduced Matrigel. Cells were grown for about 1.5 months, with media changes every two days. Figure 26 shows bright field images of the Transwell inserts at 4X magnification using a standard light microscope. More spheres seemed to form with 25,000 and 50,000 MLgs, therefore all my 3D culture experiments used 50,000 fibroblasts. These results suggest that sphere formation is affected by the number of fibroblasts in co-culture. I also observed that sphere formation was dependent on the confluency of MLgs Figure 25. General set up of 3D co-culture system. A) Five thousand epithelial cells were mixed with 50,000 mouse neonatal fibroblasts (MLgs) in 50% growth factor-reduced Matrigel and cultured in media containing TGFβ inhibitor, SB431542. After at least 1 month, noticeable spheres appeared. Depending on the AEC cell line, at least 2 months is required to observe an appreciable number and size of spheres. B) Confluency of MLgs prior to 3D set up is crucial for efficient sphere formation. Left panel shows MLgs at ~50% confluence, which best supports sphere growth. Right panel shows MLgs that are too confluent. 85 prior to 3D culture setup. More spheres formed when MLgs were maintained in culture at a maximum of 50% confluency (Figure 25B) prior to use as supportive cells. This difference may be due to the confluence-dependent differentiation status of fibroblasts, which affects their response to paracrine signaling [Kimani et al., 2009]. Figure 27 shows spheres arise from a single-cell suspension of SV40 LgT+ epithelial cells. In the absence of MLgs, no spheres form. Figure 26. Optimization of the number of MLg fibroblasts in 3D co-culture with AEC-LT epithelial cells. Five thousand AEC-LT epithelial cells were mixed with increasing numbers of MLgs and suspended in 50% growth factor-reduced Matrigel. Cultures were grown for 2 months before visualizing under a light microscope at 4X magnification. Red arrows point to spheres. 86 Using 5000 epithelial cells and 50000 fibroblasts, I next performed a time-course experiment on all three AEC-LT cell lines. As shown in Figure 28, the rate of sphere formation was noticeably slower for AEC-FT-LT02A1 than for either AEC-TN-LT10E1 or AEC-ON-LT12E4 cells. AEC- FT-LT02A1 cells required at least 5 weeks to form detectable spheres at 2.5X magnification on a stereomicroscope, compared to 3 weeks for AEC-TN-LT10E1, and as early as 1 week for AEC- ON-LT12E4 cells. Although sphere formation efficiency was somewhat variable with epithelial Figure 27. Spheres arise from a single-cell suspension. A) Fluorescent images of 3D culture one day following set up. Cells are in a single-cell suspension and AEC-LT cells are GFP+ due to transduction with the SV40 LgT transgene containing IRES sequence driving GFP expression. After about 2 months of culture, spheres comprised of GFP+ AEC-LT cells formed, exhibiting varying shapes and sizes. B) Spheres do not form in the absence of supporting MLgs. Scale bar, 100 µm. 87 cell passage number, differences in sphere formation persisted between AEC-FT-LT02A1 and both AEC-TN-LT10E1 and AEC-ON-LT12E4, even when comparing cultures of early passage cells. Figure 28. Time course of 3D culture growth for all three AEC-LT cell lines. A) AEC-FT-LT02A1 cells form spheres at the slowest rate, requiring at least one month for spheres to be easily visible under light microscopy. In this panel imaging was not started until 5 weeks (wks) into 3D culture since no spheres were readily observed before then. B) AEC-ON-LT12E4 cells form spheres in the shortest amount of time compared to the other AEC-LT lines. Nascent spheres are noticeable as early as 1 wk post 3D culture set up. Several large spheres are seen at 2 wks. C) AEC-TN-LT10E1 cells form visible spheres by 3 wks, however at 4 wks the spheres are much more prominent in the dish. AEC-TN-LT10E1 cells did not form more spheres than AEC-FT-LT02A1 cells despite its faster growth rate. Scale bar, 1000 µm. 88 To quantitatively characterize sphere growth of the AEC-LT lines, I calculated sphere formation efficiency and sphere size after two months of culture. Spheres greater than 20 µm diameter were considered for these measurements. Table 9 summarizes the results. Sphere formation efficiency is defined by the total number of spheres divided by the initial cell seed number (5,000 epithelial cells). Sphere formation efficiency for AEC-FT-LT02A1 was 0.35 ± 0.1%, for AEC-ON- LT12E4, 1.2 ± 0.5%, and for AEC-TN-LT10E1 cells, 0.2 ± 0.08% (Figure 29). AEC-ON- LT12E4 sphere formation efficiency is within the range reported for human primary distal cells (approximately 2% [Zacharias et al., 2018]). Sphere size (diameter) was measured as the largest distance between two points on the sphere membrane. The range of sphere sizes for AEC-FT- LT02A1 was 25 – 445 µm (mean 82 µm; median 64 µm), for AEC-ON-LT12E4, 24 – 661 µm (mean 144 µm; median 108 µm), and for AEC-TN-LT10E1 cells 25 – 427 µm (mean 63 µm; median 44 µm) (Figure 29 and Table 9). 89 Figure 29. Sphere size and formation efficiencies for each AEC-LT cell line after two months in culture. Sphere sizes were determined by the longest distance between two points on a sphere. Spheres of with diameters greater than 20 µm were considered for both sphere size and efficiency calculations. Percent sphere efficiency was determined by the total number of spheres divided by the initial seed number (5000 cells) multiplied by 100. n=12 inserts counted for each cell line. 90 Sphere shapes were variable across cultures for each AEC-LT line, however general growth patterns were observed. AEC-FT-LT02A1 cells formed spheres of predominantly round morphology with a single lumen. Occasionally, across different cultures, spheres containing multiple lumens were observed (Figure 30A). AEC-TN-LT10E1 cells also formed rounded, single lumen spheres more commonly than multi-lumen spheres. However, the multi-lumen spheres tended to appear more complex in structure (Figure 30C). In contrast to AEC-FT- LT02A1- and AEC-TN-LT10E1-derived spheres, AEC-ON-LT12E4 spheres were more heterogeneous in morphology. A remarkable population of spheres were large and floret-like, some generally retaining a spheroid shape, others exhibiting a lobulated structure (Figure 30B). These intricate structures also displayed complex lumens. 91 AEC-LT spheroids robustly express alveolar epithelial markers AEC-LT cells grown in 3D culture exhibit morphological features reminiscent of primary mouse and human AT2 cells grown under similar conditions. To determine whether this morphological behavior was accompanied by changes in lung-specific marker expression, I isolated the spheres to perform IF staining on sections. Spheres from AEC-FT-LT02A1, AEC-ON-LT12E4, and AEC-TN-LT10E1 cells were harvested after at least one month of growth, or until spheres were clearly visible under a light microscope at 4X magnification. For AEC-FT-LT02A1 cells, spheres were not harvested for sectioning until after two months of 3D growth. AEC-ON- LT12E4 and AEC-TN-LT10E1 cells were harvested after approximately one month of growth. Consistent with variations in sphere size and shape within a given well for a given AEC-LT cell line, sphere sections revealed a mix of lumen structures. Figure 31 shows composite images of several sphere sections stained with DAPI for each AEC-LT cell line. These composite images are meant to show the diversity in lumen structure for the different cells. These figure panels do not reflect the density of spheres in a given culture section. As was deduced from looking at the Figure 30. Phase contrast images of AEC-LT 3D spheres showing diversity in sphere shape. A) AEC-FT-LT02A1 spheres B) AEC-ON-LT12E4 spheres C) AEC-TN-LT10E1 spheres. AEC-FT-LT02A1 and AEC-TN-LT10E1 cells infrequently form spheres that are as large or intricate as AEC-ON-LT12E4 spheres. However, some AEC-FT- LT02A1 spheres do exhibit multiple lumens despite a spherical morphology. AEC-TN-LT10E1 cells rarely form spheres with “folds” but seem to have the potential to do so. AEC-ON-LT12E4 generally form larger spheres with more irregular surfaces. Large spheres then to have “floret” or lobulated morphologies. Scale bar, 170 µm. 92 morphology of spheres by brightfield microscopy, AEC-FT-LT02A1 spheres seemed to form spheres with more hollowed lumens. Some spheres had multiple lumens, but the basic morphology of AEC-FT-LT02A1 spheres was still spherical (Figure 31A). AEC-TN-LT10E1 spheres were generally smaller-sized and therefore had small lumens. However, I did observe spheres with multiple lumens despite an overall spherical structure (Figure 31C). AEC-ON- LT12E4 spheres exhibited complex, multi-lumen structures reminiscent of a transverse section through alveolar sacs (Figure 31B). 93 Figure 31. Composite image of several DAPI nuclear stainings of AEC-LT sphere sections showing diversity in lumen structure These panels do not reflect sphere density. A) AEC-FT-LT02A1 spheres B) AEC-ON-LT12E4 spheres C) AEC-TN-LT10E1 spheres. For each cell line, sphere images were taken from one glass slide containing 4 serial sections each 5 µm thick. If a particular sphere sample was present in multiple sections, only one of the images would be included in the composite panel. This is to avoid giving reader the false impression of more spheres than in actuality. Scale bar, 100 µm. 94 Spheres were composed of AEC-LT epithelial cells by SV40 LgT positivity and maintained their epithelial phenotype by ECAD (Figure 32). Ki67 was also used to detect proliferative cells within spheres, since I previously observed that spheres grew larger with longer culture times. All spheres contained Ki67+ cells distributed throughout. Probing for mature AT2 (NKX2-1; surfactant protein C, SFTPC) and AT1 (aquaporin 5, AQP5; HOP homeobox protein, HOPX) cell markers, I found that all spheres robustly expressed AQP5 and NKX2-1, whereas HOPX expression was variable, and SFTPC was tentatively negative due to issues with the human- Figure 31. Composite image of several DAPI nuclear stainings of AEC-LT sphere sections showing diversity in lumen structure These panels do not reflect sphere density. A) AEC-FT-LT02A1 spheres B) AEC-ON-LT12E4 spheres C) AEC-TN-LT10E1 spheres. For each cell line, sphere images were taken from one glass slide containing 4 serial sections each 5 µm thick. If a particular sphere sample was present in multiple sections, only one of the images would be included in the composite panel. This is to avoid giving reader the false impression of more spheres than in actuality. Scale bar, 100 µm. 95 specific antibody (data not shown). In AEC-FT-LT02A1 (Figure 32A) and AEC-TN-LT10E1 cells (Figure 32C), AQP5 and NKX2-1 expression seemed to have been reactivated under 3D co-culture conditions, since in 2D no cells were positive for these genes. In contrast, AEC-ON- LT12E4 cells maintained NKX2-1 expression in both 2D and 3D cultures, and re-expressed AQP5 only in 3D culture (Figure 32B). Additional images showing AQP5 membrane expression is shown in Figure 33. Figure 32. Immunofluorescent staining on AEC-LT sphere sections for alveolar epithelial markers. A) AEC-FT- LT02A1 spheres B) AEC-ON-LT12E4 spheres C) AEC-TN-LT10E1 spheres. Ki67, proliferation marker; ECAD, epithelial marker; AQP5, aquaporin 5, and HOPX, are AT1 markers; NKX2-1, is an AT2 marker in the adult lung. Unlike in 2D, cells robustly express AT1 markers AQP5 and to a lesser extent HOPX, as well as the AT2 marker NKX2-1. Cells were also proliferative by Ki67 positivity. Scale bar, 50 µm. 96 Figure 32. Immunofluorescent staining on AEC-LT sphere sections for alveolar epithelial markers. A) AEC-FT- LT02A1 spheres B) AEC-ON-LT12E4 spheres C) AEC-TN-LT10E1 spheres. Ki67, proliferation marker; ECAD, epithelial marker; AQP5, aquaporin 5, and HOPX, are AT1 markers; NKX2-1, is an AT2 marker in the adult lung. Unlike in 2D, cells robustly express AT1 markers AQP5 and to a lesser extent HOPX, as well as the AT2 marker NKX2-1. Cells were also proliferative by Ki67 positivity. Scale bar, 50 µm. 97 AQP5 DAPI AQP5 DAPI AQP5 AQP5 Figure 33. Additional immunofluorescence staining images to show membrane expression of AQP5. AEC-LT-derived spheres were sectioned and stained for AEC mature type 1 marker, aquaporin-5, AQP5. AQP5 is a water channel protein that is localized to the apical membrane of AT1 cells in the lung, facilitating water transport in response to osmotic gradients [Verkman, 2007]. In AEC-LT spheres, AQP5 is localized to the cell membrane, however, this expression pattern seems to be more general than specified by the orientation of cells within the sphere. Scale bar, 50 µm. AEC-FT-LT02A1 AEC-ON-LT12E4 98 Activation of WNT or FGF signaling has cell line-specific effects on sphere growth WNT and FGF signaling pathways are important for patterning and growth of the developing lung bud. Wnt signaling is crucial for alveologenesis and maturation through regulation of AT2 self-renewal [Nabhan et al., 2018; Frank et al., 2016]. FGF7 (also known as keratinocyte growth factor, KGF) and FGF10 are two key activators of early lung morphogenesis. Fgf7 also regulates lung branching and alveolar formation by promoting alveolar epithelial cell proliferation [Cardoso et al., 1997; Padela et al., 2008]. FGF10 regulates branching chemotactically, maintaining SOX9-expressing epithelial cells of the growing distal tip in an undifferentiated, progenitor-like state [Park et al., 1998; Yuan et al., 2018]. Addition of Wnt agonists to lung organoid cultures increases the percentage of AT2 cells within spheres. Treatment with FGFs increases colony formation efficiency, as well as colony size [Zacharias et al., 2018]. AQP5 DAPI AQP5 AEC-TN-LT10E1 Figure 33. Additional immunofluorescence staining images to show membrane expression of AQP5. AEC-LT-derived spheres were sectioned and stained for AEC mature type 1 marker, aquaporin-5, AQP5. AQP5 is a water channel protein that is localized to the apical membrane of AT1 cells in the lung, facilitating water transport in response to osmotic gradients [Verkman, 2007]. In AEC-LT spheres, AQP5 is localized to the cell membrane, however, this expression pattern seems to be more general than specified by the orientation of cells within the sphere. Scale bar, 50 µm. 99 To determine whether activation of WNT or FGF signaling can modulate AEC-LT sphere growth characteristics, I established 3D cultures for AEC-FT-LT02A1, AEC-TN-LT10E1, and AEC-ON-LT12E4. Two days following culture setup, media was replaced with that containing either the GSK3 inhibitor, CHIR99021 (CHIR), or a mix of FGF7 and FGF10 (FGF7+10) protein ligands. GSK3 kinase is a negative regulator of the Wnt/β-catenin pathway by indirectly maintaining the phosphorylation state of β-catenin such that it is marked for degradation Inhibiting GSK3 results in stabilization of β-catenin and transcriptional activation of target genes [Wu et al., 2010]. Figure 34 shows brightfield images of representative wells for vehicle (DMSO), CHIR-, and FGF7+10-treated AEC-FT-LT02A1, AEC-TN-LT10E1, and AEC-ON- LT12E4 cells after 2 months of culture. The median sphere sizes for vehicle-treated AEC-LT cells were consistent with median sphere sizes reported under basal conditions (no additives) (Table 10). When treated with CHIR, no difference in sphere size was detected for either AEC- FT-LT02A1 (p-value = 0.83) or AEC-TN-LT10E1 (p-value =0.34) cultures compared to vehicle. In addition, treatment with FGF7+10 did not yield a statistically significant difference in sphere sizes for AEC-FT-LT02A1 (p-value = 0.12) or AEC-TN-LT10E1 cultures (p-value =0.051) (Figure 34D, F). However, it is interesting to note the presence of larger “outlier” spheres (data points lying outside of the upper whisker in Figure 34D, F boxplots) under FGF7+10 treatment in both AEC-FT-LT02A1 and AEC-TN-LT10E1 cultures compared to either vehicle or CHIR conditions. Treatment of AEC-ON-LT12E4 cultures with either CHIR or FGF7+10 yielded a statistically significant difference in sphere size. Under CHIR, median sphere size increased from 83 µm to 155 µm (mean, 126 µm to 207 µm; p-value < 2.2 X 10 -16 ). Under FGF7+10, median sphere size increased from 83 µm to 174 µm (mean, 126 µm to 202 µm; p-value < 2.2 X 10 -16 ) (Figure 34E). Sphere formation efficiencies for AEC-LT cultures were generally unchanged 100 upon CHIR or FGF7+10 treatment (Figure 34H, I), except for AEC-FT-LT02A1, in which treatment with FGF7+10 resulted in increased mean percentage sphere efficiency from 0.3 ± 0.1% to 0.6 ± 0.2% (p-value = 0.03) (Figure 34G). Taken together, treatment with either CHIR or FGF7+10 did not affect the three AEC-LT cell lines equally, and changes in sphere size did not correlated with changes in sphere formation efficiency. 101 Figure 34. Treatment of 3D cultures results in larger sized spheres from AEC-ON-LT12E4 cells. Three- dimensional co-cultures of AEC-FT-LT02A1, AEC-ON-LT12E4, and AEC-TN-LT10E1 cells with MLgs were treated with either vehicle (DMSO), 1 µM CHIR99021, or a mix of 50 ng/mL FGF7 and 50 ng/mL FGF10 for 2 months (A- C). Whole-well, 4X magnification, and 10X magnification images of a representative well are shown for each cell line, for each treatment condition. Each panel under a treatment condition is a different magnification. Sphere sizes (D-F) and percent sphere formation efficiencies (G-I) were measured for spheres of diameter > 20 µm after 2 months. Plotted values are centered on mean ± standard deviation; n = 4, * p < 0.05, ** p < 0.005 by nonparametric Wilcoxon t-test. Scale bars for A-C: top, 1000 µm; middle, 900 µm; bottom, 100 µm 102 CONCLUSIONS In this study, I established a reproducible approach to derive alveolar epithelial cell lines from human adult lungs. These cells can be maintained under standard 2D culture conditions in the presence of the small molecule ROCK inhibitor, Y27632, and retain the morphological ability to form organoids in 3D co-culture, reactivating expression of alveolar epithelial cell-specific markers AQP5 and NKX2-1, suggesting an intermediate, AT1-like phenotype. To my knowledge, this is the first report of such a proliferative phenotype for AT1 cells. These alveolar epithelial cell lines offer a promising new model system in which to study peripheral lung diseases, such as lung adenocarcinoma. 103 Chapter 4 DISCUSSION 104 In this study, I reported on an efficient method for long-term expansion of primary human alveolar epithelial cells (AECs) in vitro in the absence of a feeder layer. I discussed the different chemical and lentiviral strategies I used to maintain the cells in a proliferative state. I found that the addition of ROCK inhibitor, Y27632, into growth media promoted cell survival of previously cryopreserved human AECs. The pro-survival and mitogenic effect of Y27632 allowed the cells to recover, attach, and proliferate on plastic tissue culture dishes. I was then able to lentivirally transduce these cells with ‘immortalizing’ genes CDK4 R24C , hTERT, and SV40 LgT in different combinations. Clustering analyses of RNA-se data from AEC cell lines, primary AEC, lung fibroblasts, and LUAD cancer cell lines revealed widespread transcriptional changes. Characterization of the cells’ growth kinetics and ability to form colonies in soft agar revealed differences among the transduced cell lines. Cells expressing SV40 LgT were significantly more proliferative than those expressing CDK4 R24C singly, hTERT singly or CDK4 R24C +hTERT in combination. Based on these results, I established two additional SV40 LgT cell lines from two different normal lungs as biological replicates. Despite being transformed by the LgT viral oncogene, AEC-LT cell lines exhibited an epithelial morphology, were contact-inhibited, and retained the ability to organize into AT1-like spheroids in 3D culture with fibroblasts. The original aim of this study was to develop a faithful cell model system of the adult distal lung. Since LUAD arises from the alveoli and typically presents in older individuals (median age of 70 years [Makrantonakis 2004; ACS 2019]), cells from adult lung would provide the most suitable model. Moreover, a faithful model system would be derived from the correct cell-of-origin. LUAD and LUSQ are distinct subtypes of lung cancer arising from AECs and HBECs, respectively. AECs and HBECs have vastly different physiological functions dictated by their 105 positions along the vertical axis of the lung [Rackley and Stripp, 2012]. AT2 and AT1 cells of the alveoli are arranged in a one-cell thick epithelium, optimized to facilitate gas diffusion between the outside environment and the adjoining capillary network [Viccaro and Brody, 1981]. AECs are bathed in an aqueous layer comprised of surfactant proteins and oxygen [Fronius et al., 2012], are adapted to the dynamic stretch forces induced by breathing [Sanchez-Esteban et al 1985; Cavanaugh et al., 2006], and are generally quiescent [Blenkinsopp, 1967; Hogan et al., 2014; Peng et al., 2015]. The bronchial epithelium is much more diverse in its cellular composition, with basal cells, ciliated cells, goblet cells, serous cells, and Clara cells distributed at varying densities along the airways. [Rackley and Stripp, 2012]. The main function of the airways is to act as a conduit for air and to provide a first-line defense against harmful airborne pathogens and particles. Unlike AECs, bronchial cells are adapted to an air-liquid environment. Airway cells must trap foreign particles, move particles out, and be poised to activate antiviral and antibacterial responses [Kai’i and Bajaj., 2019]. Consequently, these cells are subjected to continuous cycles of injury and progenitor-activated regeneration and repair [Puchelle et al., 2006]. Due to their unique microenvironments, AECs and HBECs have different susceptibilities to environmental and genetic insults. The general intractability of culturing human AECs has been well-documented in the literature [Isakson et al., 2002; Mao et al., 2015]. Optimization of in vitro culturing methods for AT2 cells has been the focus in the field, generally, because AT2 cells are stem cells of the distal lung [Barkauskas et al., 2013] and AT2 isolation protocols have been extensively reported [Dobbs and Gonzalez, 2013; Dobbs, 2002]. Efficient isolation of AT1 cells, especially from human lung tissue, is still under active investigation [Sunohara et al., 2016]. Another challenge encountered 106 when culturing AT2 cells is the propensity for the cells to spontaneously transdifferentiate into AT1-like cells [Demaio et al., 2009]. Although the AT2-AT1 phenotype has been shown to be reversible in rat cells, this has not been extensively studied in human cells [Danto et al., 1995; Wang et al., 2007]. Loss of an AT2 phenotype and acquisition of a terminally differentiated AT1-like phenotype may be the reason for the inability of AECs to proliferate in culture. This growth arrest posed a challenge to my AEC immortalization strategy. I found that direct transduction of ‘immortalizing’ genes either induced apoptosis or epithelial-to-mesenchymal transition. Successful long-term expansion of AECs occurred only when cells were first stimulated to proliferate in media containing ROCK inhibitor, Y27632, then lentivirally transduced with SV40 LgT. The small molecule Y27632 inhibits ROCK1 and ROCK2 Rho- kinase proteins by competitively binding to their ATP binding pocket, preventing relief of kinase domain auto-inhibition [Ishizaki et al 2000]. Inhibition of these Rho kinases prevents formation of stress fibers and cell contraction, thereby promoting cell survival [Amano et al 2010; Liao et al 2007]. Indeed, my derived AEC-LT cell lines were proliferative in culture, even in the absence of feeder cells or matrix-coated plates. ROCK inhibitor has been found to reprogram epithelial cells from different tissues to a stem-like state [Suprynowicz et al., 2012], which may be the reason for its success in maintaining human primary epithelial cells in vitro. This reprogrammed state was recently found to be reversible even in cells derived from diseased tissue. Martinovich et al. (2017) cultured lung airway epithelial cells from control, asthmatic, and cystic fibrosis (CF) patients in ROCK inhibitor media with irradiated mouse feeder cells. As was well-documented in other tissues, the airway cells were proliferative and maintained their epithelial morphology. Remarkably, removal of 107 ROCK inhibitor media and feeder cells allowed airway cells to fully differentiate into a stratified layer of ciliated and mucus-producing cells when cultured at air-liquid interface (ALI). Differences in differentiation capabilities were then revealed between control and diseased individuals. A striking point in this study is that asthma is generally an environmentally-induced disease [Holgate et al., 2007], so the reprogramming effect of ROCK inhibitor media and feeder cells would likely confound the asthma patient samples’ disease phenotype. The fact that the authors were able to detect differences between both asthma and CF patient samples compared to controls supports the effectiveness of this approach in culturing otherwise intractable human epithelial cells. Using the same conditional reprogramming conditions afforded by ROCK inhibitor and feeder cells, Bove et al. (2014) attempted to extend the proliferative potential of human AT2 cells in vitro. Purified AT2 cells proliferated in culture and were passaged up to two times. As observed under standard culturing conditions, these AT2 cells lost their AT2 phenotype after the first passage. AT2 markers HTII-280, SFTPC, and SFTPA were downregulated and AT1 markers PDPN and AQP5 were upregulated. Although the authors used purified alveolar epithelial cells, they detected high levels of markers associated with basal cells (KRT5, ΔNp63α). They did not report expression of distal lung stem cell markers. In contrast to the findings by Bove et al. (2014), immunofluorescent staining of my three AEC-LT cell lines revealed dual expression of SOX2 and SOX9, suggesting that my derived AEC-LT cells were reprogrammed to a lung progenitor-like state after expansion in ROCK inhibitor media [Danopoulos et al., 2017]. In line with this observation, AEC-LT cells were negative for mature AT1 and AT2 markers. Interestingly, I observed variability in NKX2-1 positivity among the AEC-LT cell lines. Only 108 AEC-ON-LT12E4 cells robustly expressed this lung-specific transcription factor. Although expression of NKX2-1 is a potent lung-lineage regulator, especially during development, its expression in cells under different culture conditions can vary [Nikolic et al., 2017]. This variation may be due to epigenetic regulation of NKX2-1 expression directly [Kondo et al., 2009] or of an upstream factor that regulates NKX2-1. Organotypic culture systems have emerged as a tool to investigate epithelial self-renewal and differentiation properties morphologically ex vivo. In one of the earliest organotypic studies, isolated fetal rat lung cells cultured on a gelatin matrix formed alveolar-like spheres containing cells with microvilli and lamellar bodies [Douglas and Teel, 1976]. Since then, 3D culture conditions have been refined for different species and different lung cell types [Barkauskas et al. 2017; Nadkarni et al, 2015; Choi et al, 2016]. Purified mouse Sftpc+ AT2 cells form ‘alveolospheres’ when cultured with either Pdgfrα+ mouse stromal cells or unsorted mouse fibroblasts. Over a course of 14 to 21 days in culture, colony forming efficiency (CFE) was reported between ~2 – 11% by different investigators [Barkauskas et al 2013; Jain et al 2015; Zacharias et al 2018]. The wide range of CFE was possibly due to different growth media conditions: Barkauskas et al. and Jain et al. used MTEC Plus media, whereas Zacharias et al. used SAGM media from Lonza. Reported sizes of mouse AT2 colonies can be as small as 25 µm [Zacharias et al 2018] to between 100 – 200 µm [Barkauskas et al 2013; Jain et al 2015]. Despite variabilities in CFE and sphere size, mouse AT2-derived organoids are consistently positive for Sftpc (AT2 marker) and AT1 markers, Aqp5, Pdpn (T1α), or Hopx [Barkauskas et al 2013; Jain et al 2015; Zacharias et al 2018]. In a study by Lee et al (2014), mouse AT2 cells co-cultured with primary mouse lung endothelial cells (LuMECs) formed alveolar spheroids that were much 109 larger than previously observed when grown with fibroblasts. Sphere sizes ranged between 200 – 500 µm. CFE was ~ 5% and these spheres stained positive for Sftpc; no AT1 markers were assessed. It should be noted that AT2 cells were isolated by fluorescence-assisted cell sorting (FACS) based on Cd31 neg Cd45 neg Epcam pos Sca1 neg gating. This AT2 population may be distinct from the commonly isolated Sftpc+ AT2 cells and may, therefore, have vastly different morphological properties in organotypic culture. In addition to AT2 cells, rare murine bronchioalveolar stem cells, or BASCs, have been found to possess multipotent capabilities in vivo [Kim et al., 2005]. In 3D co-culture with mouse LuMECs, BASCs form three different types of structures: alveolar, bronchiolar, and bronchioalveolar. CFE was ~ 9% after 14 days in culture, and sphere sizes ranged between 250 – 350 µm, but were observed to be as large as 500 µm. Alveolar spheres were Sftpc+, bronchiolar spheres were CC10+ (Clara cell marker), and bronchioalveolar spheres were both Sftpc+/CC10+ [Lee et al., 2014]. Interestingly, these BASC- derived spheres exhibited complex morphologies, unlike previous reports of AT2-derived organoids. Since mouse and human physiologies differ, human lung cell organotypic cultures have been established. Co-culture of adult human AT2 cells positive for the AT2 human marker, HTII-280, [Gonzalez et al., 2010] with human fetal lung fibroblasts (MRC5) resulted in spheroid formation between 14 – 21 days, with CFE between 2 – 4%, depending on media conditions [Barkauskas et al., 2013; Zacharias et al., 2018]. In the study by Barkauskas et al. (2013), spheroids were ~ 100 – 200 µm in diameter and were comprised of AT2 cells only (HTII-280+/SFTPC+). In contrast, Zacharias et al. (2018) reported sphere sizes of 25 µm and the presence of both AT2 (SFTPC+) and AT1 (AQP5+) cells, although the paper only included one image of their organoid staining. 110 This stark difference in spheroid cell composition may suggest an intrinsic sensitivity of human AT2 cells to suboptimal media conditions, or different methods of isolating AT2 cells. Barkauskas et al. used FACS sorting while Zacharias et al. used MACS bead purification. Human embryonic lung ‘tip’ progenitor cells are found at the distal tips of growing lung buds [Danopoulos et al 2017; Nikolic et al. 2017]. Three-dimensional culturing of these tip cells in defined media and in the absence of stromal cells resulted in robust formation of self-renewing organoids composed of SOX2+, SOX9+, and NKX2-1+ cells. Spheres were observed within 12 hours and continued growing spherically for a week before branching. These spheres had a reported CFE of 100%. In representative images, these tip organoids grew to about 1 mm in diameter by 2 weeks in culture. When co-cultured with human fetal lung mesenchyme, under media conditions promoting alveolar differentiation, these tip organoids were able to differentiate into AT2 and AT1 expressing cells, losing SOX2 and SOX9 expression while maintaining NXK2-1 expression [Nikolic et al., 2017]. In my study, all three SV40 LgT-transduced cell lines were able to form spheroids in 3D culture only in the presence of fibroblasts. Two AEC-LT lines (AEC-FT-LT02A1 and AEC-TN- LT10E1) were NKX2-1 negative, while one AEC-LT line (AEC-ON-LT12E4) was positive for NKX2-1 prior to growth in 3D culture. Surprisingly, AEC-ON-LT12E4 cells formed spheres relatively quickly and with complex morphologies. These cells formed a subset of large “floret” spheres after at least 1 month of culture. The morphologies of these florets were reminiscent of bronchiolar BASC spheres and human embryonic tip organoids (Figure 35). 111 However, unlike the BASCs and tip organoids, these AEC-ON-LT12E4 spheres were negative for CC10 and SFTPC and exhibited low CFE (1%, vs 2% for human AT2s and 5% for mouse AT2s). Perhaps my culture conditions lacked essential growth factors to support efficient sphere formation. It would be interesting to culture the AEC-ON-LT12E4 cells under tip organoid self- renewal conditions to see whether AEC-ON-LT12E4 cells form spheres that maintain SOX2, SOX9, and NKX2-1 expression, as was observed in 2D. This would suggest that AEC-ON- LT12E4 cells have potential self-renewal properties. It would also be interesting to see what sort of structures the AEC-ON-LT12E4 cells can form under the alveolar differentiation media conditions published by Nikolic et al. Treatment of my AEC-LT-derived spheres with either WNT agonist, CHIR99021, or a mix of FGF7 and FGF10 yielded variable results. Only AEC-ON-LT12E4 cultures treated with CHIR or FGF7 and FGF10 showed a significant increase in sphere size, consistent with what has been reported for HTII-280+ AT2 cells [Zacharias et al., 2018]. Interestingly, the large spheres observed in FGF7+FGF10-treated wells appeared to be more lobulated in structure, compared to Figure 35. Left panel is a snapshot taken from Nikolic et al. paper (2017) on human embryonic tip progenitors that form self-renewing organoids that are SOX2+ and SOX9+. The authors’ reported 12-day old organoid looks similar to my spheroid from AEC-ON-LT12E4 cells after 2 months of culture. 112 spheres of similar sizes in CHIR-treated wells. This is consistent with my RNA-seq data showing high expression of FGFR2 in AEC-ON-LT12E4 cells compared to AEC-FT-LT02A1 cells. AEC-TN-LT10E1 also expressed high levels of FGFR, but did not form as many intricately structured spheroids as AEC-ON-LT12E4 cells. This may be attributed to technical issues with culture setup rather than to the biology of the cell line. I have observed quite a bit of variability in sphere number and size in my cultures. Since sphere formation is dependent on paracrine signaling from the surrounding fibroblasts, I believe this discrepancy can be address by increasing sample size and using only low passage MLgs. Moreover, we can test sphere formation in the presence of freshly isolated mesenchyme. AT2 cells have long been considered to be the only alveolar epithelial cell type to possess proliferative and progenitor qualities [Ward and Nicholas, 1984; Beers et al., 2017]. However, increasing reports suggest that AT1 cells are not merely terminally differentiated cells. Jain et al. (2015) showed that Hopx+ AT1 mouse cells can give rise to both AT1 and AT2 cells in organoid co-culture. Liebler et al. (2016) identified an intermediate AEC differentiation state marked by co-expression of AT1 and AT2 markers Hopx, Pdpn, and Nkx2-1 in transdifferentiating rat AT2 cells. Wang et al. (2018) identified a subpopulation of Hopx+ AT1 cells in mice expressing Igfbp2 that cannot give rise to Prospc+ AT2 cells in organoid culture and do not proliferate. These three findings reveal a subset of AT1 cells possessing intrinsic cellular plasticity. Corroborating these rodent data, my spheroid results show that human AT1-like cells exhibit stem cell-like properties in 3D co-culture, forming complex structures that are NKX2-1+, AQP5+, and, in a subset of spheres, HOPX+. The observed increase in AEC-LT-derived sphere 113 sizes in response to WNT and FGF signaling activation further reinforces the plastic nature of these cultured AT1-like cells. To my knowledge, this study is the first to report on an AT1-like spheroid derived from adult human alveolar epithelial cells. I found that these spheres were consistently positive for the mature AT1 marker, AQP5 and AT2 marker, NKX2-1. Additional stainings for AT1 markers PDPN and AGER are currently underway at the time of this thesis. Although AQP5 is expressed in some airway cells, it is an accepted AT1 marker when comparing cells in the alveolar region [Flodby et al., 2017]. Results from my study show that AEC-LT cell lines are a promising new cellular tool to investigate distal lung disease as well as alveolar cell biology. 114 Chapter 5 FUTURE DIRECTIONS 115 In this thesis, I have reported on a novel cellular system derived from long-term expansion of normal human alveolar epithelial cells. I have shown that these cells are capable of long-term growth on plastic tissue culture dishes, allowing them to be molecularly manipulated for different experimental purposes. Based on their growth kinetics, these cells are as tractable as common lung cancer cells lines, but are contact inhibited and, preliminarily, display a near- normal ploidy similar to normal human cells. Although these cells have been generated by transduction of SV40 LgT antigen, I have found that they retain the ability to form lung spheroids in 3D culture, similar to what has been reported in the literature for primary, uncultured alveolar epithelial cells. This new system now opens a number of opportunities. Because the cells were derived from adult alveolar epithelial cells, it allows us to investigate human alveolar epithelial cell biology. In addition, it provides us with a simple and rapid approach to generate many more normal cell lines in the future. Such cell lines would be a valuable resource for the greater research community. In this section, I discuss further investigations and applications of this cell model system, some of which are actively underway in the laboratory at the time of this thesis. Transcriptomically profile AEC-LT-derived spheres at the single cell level In my 3D co-culture experiments, I found that AEC-ON-LT12E4 cells form intricately structured spheroids, unlike any published organoid derived from human adult alveolar epithelial cells. To understand the cellular dynamics underlying formation of these spheres, I harvested, pooled and isolated cells from 3D culture wells containing these spheroids. We compiled three samples to process, two of which are shown in Figure 36. Single-cell suspensions were FACS sorted to 116 enrich for GFP+ cells, corresponding to AEC-LT epithelial cells (MLg fibroblast support cells are not fluorescent). Following the 10X Genomics manual (v3), I successfully generated gel-beads for two of the three samples: the 2D-cultured cells and the pooled spheroids. Unfortunately, the step in which single cells were mixed with gel-beads failed in the attempt to obtain single cell sequencing from a single spheroid. The likely reason it failed is the limited number of cells in a single sphere (estimated by be approximately 5,000, conservatively). It may be possible to optimize the approach to allow single spheroids to be profiled, which would avoid possible confounding effects due to inter-spheroid variability. I proceeded with processing the two samples for which the gel-bead generation was successful, carrying out cDNA synthesis, amplification, fragmentation, barcoding, and library-generation. The libraries are currently awaiting sequencing. Preliminary data on pooled spheres will help us devise and prioritize follow-up experiments. The single cell data would help us address whether there are rare subpopulations of stem/progenitor cells in our culture. The AEC-LT cells were derived from a polyclonal Figure 36. (Left) Representative image of 3D culture well used in pooling of spheres for single-cell sequencing. (Right) Single sphere that was collected for single-cell sequencing, but which failed in the gel-bead preparation step. 117 population of proliferating cells. Because the formation of spheres is very slow, we may be enriching for different subsets of cells during the process. If we can identify pathways that are enriched in each subcluster of cells comprising the spheres, we can find ways to optimize our culture conditions, or manipulate it to understand the biology of our new AEC cell lines Investigate AT1 plasticity Until this study, there were no reports on generation of a human AT1-like organoid. AT1 cells are generally thought to be terminally differentiated, unable to proliferate, and incapable of self- renewal. Recent studies in mice suggest the existence of a subpopulation of AT1 cells that are more dynamic than previously reported. Here, we have a human AT1-like system with which to further investigate alveolar cell plasticity. My data shows that AEC-LT-derived spheroids are positive for mature AT1 marker AQP5 and the adult AT2 marker NKX2-1. Since I was not able to detect pro-SPC expression, NKX2-1 expression in this state may function more as a lineage marker than an AT2 differentiation marker. Additional studies on NKX2-1’s function in this intermediary state are necessary to understand the biology of these new cell lines. To determine the effect of media conditions on the differentiation status of these spheres, a small-scale media screen of published growth conditions for human lung organoids could be performed. In addition, it would be interesting to test different configurations of organotypic culture to see the effect on sphere growth and patterning. Sucre et al. (2018) cultured human fetal AT2 cells on top of a mixture of fibroblasts and Matrigel overlaid with media containing dexamethasone, 8- bromo-cAMP, and IBMX, previously found to maintain AT2 phenotype after isolation from tissue [Gonzales et al., 2002; Ballard et al., 2010]. In iPSC-derived distal lung organoid cultures, cells are grown in a ‘Matrigel droplet’ overlaid with induction media [Miller et al., 2018; 118 McCauley et al., 2017; Hawkins et al., 2018]. Changes in AEC-LT sphere growth could give us insight into signaling pathways regulating this process. We could then compare this to what has been reported in the literature for purified alveolar epithelial cells. Investigate epithelial-mesenchymal interactions During lung development, the surrounding mesenchyme plays a critical role in providing paracrine signals to direct the proper morphogenesis of the nascent lung. Mesenchymal cells also aid in cellular differentiation along the proximal to distal axis by secretion of growth factors and signaling molecules [Shannon et al., 2004; Arias, 2001; Chao et al., 2015]. We can test the effect of different types of mesenchymal cells on AEC-LT gene expression in 2D as well as in 3D cultures. I have found that MLg mouse fibroblasts and MRC5 human fetal lung fibroblasts similarly support sphere growth. Preventing these cells from growing too confluently prior to use in experiments is the most crucial point. Additional support cells to test are primary lung endothelial cells, crude primary fetal lung fibroblasts, sorted Pdgfrα+ mouse stromal cells, and the combination of endothelial cells with fibroblasts. We can also test whether physical contact with these different supportive cells is necessary for mesenchyme-mediated sphere growth and morphogenesis, or whether conditioned medium might suffice. These observations will then influence how spheres are cultured in the future. Track stepwise molecular alterations during lung carcinogenesis As mentioned in the Introduction, in order to understand the progressive changes involved in lung adenocarcinoma, we need to begin with a cell line that is as close as possible to a normal human primary cell. Currently available lung cell models are either tumor-derived or, if normal, 119 bronchial epithelial cell-derived, neither of which are suitable for understanding lung adenocarcinoma. Using our new AEC-LT cell model, we can introduce driver mutations and ascertain the resulting transformative effect by soft agar assays, migration and invasion assays, and subcutaneous injection of cells into nude mice. We can also molecularly profile the cells by RNA-seq, ChIP-seq, ATAC-seq, and Whole-Genome Bisulfite sequencing. Patients with lung cancer driven by gene fusions currently have limited therapeutic options. Unlike patients with EGFR or KRAS mutations, lung cancer patients with gene fusions are typically younger than the average cancer patient female, and nonsmokers. The patient frequency for these gene fusions is very low (3 – 5% for EML4-ALK, 0.5 - 2 % for ROS1 fusions) [Soda et al., 2007; Marchetti, et al., 2017]. Thus, there are few opportunities to study primary tumor samples to understand the underlying etiology of this molecular subtype. To circumvent this, with our new approach to generating cell lines from normal alveolar epithelial cells, we can potentially study EML4-ALK and ROS fusions in a cell model derived from young females. We can also mimic smoking-caused alterations, such as KRAS mutation, which is found in 30% of LUAD cases, predominantly in those of smokers. To date, KRAS has been studied in HBEC cells, which are a poor model since KRAS mutations are very infrequent in squamous cell lung cancer [TCGA 2012]. As a pilot experiment to introduce diver mutations into the AEC cell lines, we are currently working on introducing mutant EGFR to determine its transformative effect. Previous studies using LUAD cell lines showed that ectopic expression of mutant EGFR is sufficient to activate downstream ERK signaling and enhance cell invasion properties [Tsai et al., 2015]. We are currently optimizing transfection and serial transduction methods. 120 Investigate differences in intrinsic cell susceptibility to genetic alterations As mentioned above, driver genes seen in LUAD have been introduced into immortalized bronchial cells. While the experiment was not in line with what is generally observed in patients, the cells were responsive to the genetic alterations [Vaughan et al., 2006; Sato et al., 2006; Sato et al., 2013]. This suggests that it would be interesting to compare driver gene effects in cell lines derived using comparable methods from both the airways and the alveoli. Thus, one could compare bronchial cells (ie basal cells of the small airways) grown in ROCK inhibitor media and transduced with SV40 LgT to my AEC-LT cell lines both in 2D and 3D cultures. One could then introduce the same genetic hits to both types of cells to assess effects on the transcriptome and on the hallmarks of transformation. Given that the two different cell types have distinct characteristics, their responses to driver genes may differ. I would be of great interest to introduce the resultant oncogenic cells into nude mice to determine what histological type of tumors are formed. I hypothesize that LUAD-associated EGFR mutations in alveolar epithelial cells would give rise to LUAD histological tumors, while the same mutations in basal cells might give rise to other histological subtypes of lung cancer, and LUAD at a lower frequency. In contrast, introduction of LUSQ PIK3CA mutations into alveolar epithelial cells might yield mixed histologies in tumors from nude mice, while these mutations in basal cells might give rise to more frequent LUSQ tumors. These studies might shed light on how different histological subtypes of lung cancer develop. If we see robust differences in histologies of the tumors developing in the mice, we can perform RNA-seq on the malignant cells to see what pathways are activated or suppressed and compare this to lung cancer data from human tumors, such as that from TCGA. 121 Screen novel chemotherapeutic drugs If driver genes can be used to transform the AEC-LT cells, these cells would be a very useful model to study the development of resistance to targeted therapies, since large numbers of cells can be grown and treated to select resistant clones. Currently, resistance is studied using tumors from patients and mouse models, neither of which are high throughput. In vitro-derived resistant clones can be exome sequenced to more efficiently identify secondary mutations. It is also interesting to consider doing these experiments with the cells in 2D or 3D cultures. Chemotherapy drug screens using of cancer cell lines plated on plastic tissue culture dishes lack a three-dimensional microenvironment, and may exhibit incomplete sensitivities or resistance to drugs. Using cells grown in 3D as a screen would aid in our understanding of drug response and resistance. [Hagemann et al., 2017]. Thus, we can re-purpose our 3D co-culture system to grow genetically-defined ‘pseudotumors’ within spheroids. We can then treat the system with candidate drugs and monitor the effect on each cell component of the system. Simultaneously, within the same microenvironment, we can potentially determine whether a drug is selective against abnormal cells as they grow in proximity to normal cells. Resistant clones obtained in vitro can be used in screening for follow up therapeutics, for example using the USC small molecule facility. Currently, PDX models, in which tumors are transplanted into immunocompromised mice, are used for this purpose, but these experiments are very expensive. 122 Investigate the effects of environmental exposures Recent work in our lab showed that exposure to cigarette smoke concentrate (CSC) led to epigenetic alterations in lung adenocarcinoma cell line A549. These changes happened quickly, within 48 hours [Stueve et al., 2017]. In recent experiments using HBEC cells, long term treatment with cigarette smoke concentrate potentiated the cells for transformation by oncogenic driver genes, to which they were not initially susceptible [Vaz et al., 2017]. It would be of interest to treat the AEC-LT in 2D and as spheroids with CSC and monitor the short and long term changes, both molecularly and morphologically. Investigate the effect of ethnic/racial diversity in lung cancer Epidemiological studies have shown there is a remarkable variation in incidence of lung cancer among different ethnic and racial groups in the US [Haiman et al., 2006]. This difference is governed mainly by differences in smoking habits across ethnic groups. However, there are significant differences in the prevalence of frequently mutated genes in lung cancer among different populations of people. For example, in Western populations EGFR mutations are at ~10% frequency, whereas among Asian populations, the mutational frequency is ~35%. For STK11/LKB1 mutations, among Western populations the frequency is ~ 9 - 17%, whereas in Asian populations the frequency is ~3 - 7% [Schabath et al., 2016]. Since we now have an efficient method of long-term expansion of human alveolar epithelial cells, we are in an advantageous position to establish a collection of alveolar epithelial cell lines from an ethnically and racially diverse group of individuals in order to determine underlying effects of ethnicity/race on a given lung cancer mutation. 123 The above examples illustrate that the work described in this thesis opens up many exciting avenues of investigation. Immortalized alveolar epithelial cells are a long awaited addition to the tool kit of the lung adenocarcinoma investigator. I look forward with excitement to see what can be accomplished with these cells. 124 REFERENCES 125 CHAPTER 1: INTRODUCTION REFERENCES Alder JK, Barkauskas CE, Limjunyawong N, Stanley SE, Kembou F, Tuder RM, Hogan BL, Mitzner W, Armanios M. (2015). Telomere dysfunction causes alveolar stem cell failure. Proc Natl Acad Sci U S A. 112(16):5099-104. American Cancer Society: Cancer Facts and Figures 2019. 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Abstract (if available)

Abstract The focus of this thesis study was to develop an alveolar epithelial cell system that can be used to recapitulate lung adenocarcinoma-specific cancer events. The study builds upon published culture conditions found to promote proliferation of primary human cells and Weinberg's two-hit model of cell immortalization to generate a collection of novel cell lines derived from adult human alveolar epithelial cells. My results address these key challenges: 1) alveolar epithelial cell growth arrest upon isolation from human lung tissue 2) optimal immortalization conditions have not been reported for adult alveolar epithelial cells and 3) primary epithelial cells tend to lose their cell-type specific characteristics after long-term expansion in culture.

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Asset Metadata

Creator Tran, Evelyn (author)

Core Title Long-term expansion of human alveolar epithelial cells as a novel model system to study lung disease progression in vitro

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Genetic, Molecular and Cellular Biology

Publication Date 07/30/2021

Defense Date 06/20/2019

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag alveolar epithelial cells,cell immortalization,distal lung,Lung,lung cancer,lung cell lines,lung organoids,lung progenitor,lung spheres,lung stem cells,normal lung cells,OAI-PMH Harvest,ROCK inhibitor,SB-431542,three-dimensional culture,Y-27632

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Zhou, Beiyun (committee chair), Offringa, Ite (committee member), Subramanyan, Ram (committee member)

Creator Email evelyntr@usc.edu,evelyntran27@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-206032

Unique identifier UC11663263

Identifier etd-TranEvelyn-7710.pdf (filename),usctheses-c89-206032 (legacy record id)

Legacy Identifier etd-TranEvelyn-7710.pdf

Dmrecord 206032

Document Type Dissertation

Format application/pdf (imt)

Rights Tran, Evelyn

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA