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ES11 - Lung Cancer Plasticity and Drug Resistance (ID 14)
- Event: WCLC 2019
- Type: Educational Session
- Track: Biology
- Presentations: 6
- Now Available
ES11.01 - Lung Adenocarcinoma to Squamous Cell Carcinoma Transdifferentiation and Drug Resistance (Now Available) (ID 3211)
15:15 - 16:45 | Presenting Author(s): Hongbin Ji
Lung cancer is notorious for high heterogeneity and strong plasticity, which might contribute to the development of drug resistance. Lineage transition from lung adenocarcinoma (ADC) to squamous cell carcinoma (SCC), as implicated by clinical observation of mixed ADC and SCC pathologies in adenosquamous cell carcinoma (Ad-SCC), reflects strong cancer plasticity and potentially links to drug resistance. Using Genetically Engineered Murine Model (GEMM), we have provided in vivo evidence in supporting the ADC to SCC transdifferentiation (AST): Lkb1-deficient mouse lung ADC transdifferentiates into SCC progressively via pathologically mixed Ad-SCC. Mechanistically, we find that down-regulation of reactive oxygen species (ROS) level through N-acetyl cysteine (NAC) treatment or NRF2 expression inhibits this transition, highlighting the functional importance of ROS in regulating cancer plasticity. Pentose phosphate pathway deregulation and impaired fatty acid oxidation collectively contribute to the redox imbalance and functionally affect the AST process. Importantly, similar tumor and redox heterogeneity are also found in human LKB1-inactivated lung cancer. In preclinical trials toward metabolic stress, Lkb1-inactivated ADC can develop drug resistance through squamous transdifferentiation. Recent observations in clinic further suggest that such pathological transition might be responsible for resistance to tyrosine kinase inhibitor (TKI) therapy and chemotherapy in relapsed EGFR-mutant lung ADC patients. These findings demonstrate that lung cancer plasticity potentially affects therapeutic response and precision medicine through histological transition.
Lung cancers are typically divided into two main histological types: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLC accounts for approximately 85% of all cases and lung adenocarcinoma (LUAD) is the most frequent subtype. Current treatments of LUAD aim to inhibit driver oncogene alterations and have shown unprecedented success. Among the oncogenic alterations in LUAD, EGFR kinase domain mutations are found in ~40-50% of patients in east-Asian countries and 20% of patients in western countries1. EGFR tyrosine kinase inhibitor (TKIs) are highly effective for tumors with EGFR mutations and resistance mechanisms to these compounds have been well documented: the most frequent being the acquisition of a secondary mutation in EGFR (T790M)2, followed by amplification of the hepatocyte growth factor receptor (MET) gene3 and mutations in BRAF and PIK3CA genes4,5. Histological transformation from LUAD to SCLC occurs in up to 15% of cases with acquired resistance to first and second generation EGFR TKIs5. Histological plasticity as a mechanism of resistance is becoming increasingly prominent as other resistant mechanisms can now be successfully targeted: MET-inhibitors are employed for MET-amplified tumours and 3rd generation EGFR TKIs are used to overcome resistance driven by the EGFR T790M muation6. Importantly, the 3rd generation EGFR TKI osimertinib was approved by the FDA in 2018 and thus, cases of treatment-induced SCLC transformation may increase in prominence as other mechanisms are targeted. Currently, conventional platinum doublet chemotherapy is the standard of care for patients with treatment-induced SCLC as well as de novo SCLC. Unfortunately, this treatment often produces an incomplete and non-durable response followed by inevitable relapse within months, leading to poor patient outcomes7. Thus, this mechanism of resistance will represent a major barrier towards the success of 3rd generation TKIs and new strategies to prevent this lineage shift or to treat SCLC transformed tumors are urgently needed.
Despite the increasing clinical importance of LUAD to SCLC transformation, the biological pathways regulating this process are poorly understood. Since the first description in 20068, numerous studies have aimed to characterize the molecular changes that drive transformation in the context of drug resistance. Assessment of clinical samples has revealed that EGFR-mutant tumors universally lose EGFR protein expression upon SCLC transformation, despite still harboring EGFR mutations that confirms their clonal origin9. Furthermore, the mutation spectrum of these transformed cases often resemble de novo SCLC, containing inactivation of the tumor suppressors RB and p53 in nearly all cases9. This mirrors neuroendocrine transformation that occurs in prostate adenocarcinoma, where loss of RB/p53 are known to upregulate the reprogramming transcription factor SOX2, driving lineage plasticity and resistance upon anti-androgen therapy10. Furthermore, loss of RB and inactivation of p53 are required to reprogram a normal cell of epithelial lineage to a neuroendocrine lineage, and when combined with expression of myristoylated AKT1 and overexpression of MYC and BCL2, leads to the development of lethal SCLC in vivo11. Inactivation of p53 and RB also leads to the development of SCLC in transgenic mouse models, even when targeted in specifically to type-II airway epithelial cells, the putative cell of origin for EGFR-mutant LUAD12. Together, these studies highlight the essential role for these tumor suppressor genes in reprograming transcriptional profiles and chromatin accessibility in facilitating neuroendocrine lineage transformation.
However, accumulating experimental evidence has demonstrated that while necessary, dual inactivation of RB and p53 is not sufficient to cause SCLC lineage transformation in EGFR-mutated LUAD, suggesting that additional factors are required9. MYC amplification and PIK3CA mutation have been proposed to potentially cooperate with RB/p53 loss to facilitate transformation13, and specific epigenetic regulators may also provide the appropriate context for lineage reprograming to occur. Despite this, no in vitro or in vivo models of SCLC transformation in EGFR TKI resistance have been developed, making it difficult to comprehensively explore the molecular events driving this lineage shift. Interestingly, there are clear differences between LUAD and SCLC regarding EGFR expression and gene alterations in MAPK pathway including EGFR/KRAS mutations: EGFR is usually not expressed14 and EGFR/KRAS mutations are extremely rare in SCLC15; in contrast, EGFR/KRAS play crucial roles in LUAD biology, including regulating differentiation in addition to prolferation16. To date, however, no clear explanation has been given for these differences. We have recently shown that activation of MAPK signaling in SCLC leads to suppression of the neuroendocrine phenotype - including downregulation of the transcription factors NEUROD1, INSM1, BRN2 and ASCL1 - and transformation to a NSCLC-like state17. Using this model system, we have begun to elucidate the key transcription factors and epigenetic changes that drive SCLC to NSCLC transformation in the hope that the same processes will also be involved in the clinically relevant scenario: SCLC transformation from EGFR mutant LUAD during TKI resistance. We suggest that only EGFR-mutant LUADs that do not reactivate MAPK signaling through secondary EGFR mutations or alterations in parallel kinase pathways (ie. MET) during development of TKI resistance will be able to undergo SCLC lineage transformation, and that RB/p53 loss and epigenetic plasticity provide the permissive context for which this transformation can occur. Greater understanding of lineage transformation in LUAD will provide important insights in terms of managing outcomes of patients undergoing targeted therapy and offer new avenues towards treatment of TKI resistant tumors.
1. Dearden S et al. Ann Oncol 2013;24:2371-6.
2. Kobayashi S et al. NEJM 2005;352:786-92.
3. Bean J et al. PNAS 2007;104:20932-7.
4. Ohashi K et al. PNAS 2012;109:E2127-33.
5. Sequist LV et al. Sci Transl Med 2011;3:75ra26.
6. Mok TS et al. NEJM 2017;376:629-40.
7. Roca E et al. Cancer Treat Rev 2017;59:117-22.
8. Zakowski MF et al. NEJM 2006;355:213-5.
9. Niederst MJ et al. Nat Commun 2015;6:6377.
10. Mu P et al. Science 2017;355: 84-8.
11. Park et al. Science. 2018;362:91-95.
12. Sutherland KD et al. Cancer Cell 2011;19:754-64
13. Lee JK et al. J Clin Oncol. 2017;35:3065-3074.
14. Gamou S et al. Cancer Res 1987;47:2668-73.
15. Cristea S et al. J Thorac Oncol 2016;11:1233-41.
16. Byers LA et al. Cancer Discov 2012;2:798-811.
17. Y. Inoue and W. Lockwood. J Thorac Oncol 2018;13:S433–S434.
ES11.03 - Immunotherapy and Endogenous Retroviruses in Small-Cell Lung Cancer (Now Available) (ID 3213)
15:15 - 16:45 | Presenting Author(s): Israel Canadas
Introduction: Tumor cell heterogeneity is a key determinant of cancer progression and drug resistance, which is often mediated by
mesenchymal cell subpopulations. While these subclones can secrete growth factors, chemokines and cytokines, the immune signaling
networks that fuel this pro-tumorigenic state remain incompletely defined. Elucidating what underlies this state would provide insights into
tumor biology and inform clinical strategies to improve anti-cancer therapies.
Methods: Because of their well-defined nature, we used the phenotypically distinct H69M and H69AR Small Cell Lung Cancer (SCLC)
mesenchymal subclones to uncover a novel mechanism of dysregulated innate immune signaling as compared with parental neuroendocrine
H69 cells. Analysis of gene signatures across TCGA and CCLE databases, functional studies in additional cell lines, and ex vivo testing of
patient-derived organotypic tumor spheroids (PDOTS) were conducted to determine the broader relevance across human cancers.
Results: We discovered a novel epigenetically regulated subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in
mesenchymal cancer subpopulations. Stimulated 3 Prime Antisense Retroviral Coding Sequences (SPARCS) are oriented inversely in 3’UTRs of
certain interferon-inducible genes and silenced by EZH2. De-repression of these loci resulted in dsRNA generation following IFNγ exposure
due to bi-directional transcription from the STAT1-activated gene promoter and the 5’ LTR of the antisense ERV. We found that dsRNA sensing
preferentially by MAVS fuels activation of TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction across
specific human tumors and cell lines is tightly associated with downregulation of chromatin modifying enzymes, including EZH2, a
mesenchymal AXL positive cell state, and B2M and MHC class 1 antigen expression. SPARCS high tumors were marked by immune infiltration,
but also exhibited multiple features of tumor
immune suppression. IFNγ treatment of PDOTS with de-repressed SPARCS markedly enhanced CXCL10 production and sensitized them to
Conclusions: Together, these data unveil a novel subclass of ERVs whose de-repression triggers pathologic innate immune signaling in cancer,
with potentially important implications for cancer immunotherapy.
ES11.04 - Mechanisms for Resistance to TKI and ICI (Now Available) (ID 3214)
15:15 - 16:45 | Presenting Author(s): Katerina Politi
Targeted therapies and immunotherapies have transformed the treatment landscape for lung cancer over the past 15 years. These therapies are effective in subsets of patients, however, acquired resistance is an impediment to cures. In the case of targeted therapies, acquired resistance occurs in all cases although new generations of targeted therapies delay inevitable relapse. Upon treatment with immune checkpoint inhibitors, data suggest that acquired resistance occurs in ~50% of cases following an initial response to the therapies. However, studies of acquired resistance to these immunotherapies are limited and the exact frequency remains to be determined. Therefore understanding the mechanisms of acquired resistance to targeted therapies and immunotherapies is of critical importance to developing new therapeutic strategies to overcome and prevent the emergence of drug resistance.
EGFR mutant lung cancer is a paradigm for the use of targeted therapies in this disease. Tyrosine kinase inhibitors (TKIs) are the first line of treatment for EGFR mutant lung cancer and are effective in 70-80% of cases. Acquired resistance to first and second generation inhibitors, like erlotinib, gefitinib and afatinib, most frequently is the result of a secondary mutation in EGFR, EGFR T790M. Third generation TKIs that can inhibit the activity of EGFR T790M-containing mutants were recently developed and one of these, osimertinib, is now approved for the first- and second-line treatment of EGFR mutant lung cancer and is increasingly used in the clinic. Even with osimertinib, acquired resistance occurs and there is a need to understand the mechanisms of resistance to this TKI. We will review current knowledge of acquired resistance to osimertinib and discuss new findings from studies in genetically engineered mouse models, patient-derived xenografts, patient specimens and cell line models.
In contrast to the extensive knowledge of the mechanisms of acquired resistance to TKIs, very little is known about acquired resistance to immune checkpoint inhibitors. In melanoma, lung cancer and colon cancer, defects in antigen processing and presentation have emerged as a mechanism of acquired resistance to these agents. Defects in this pathway can occur in different ways including loss of specific neoantigens and genetic loss or downregulation of essential components of the pathway like b2-microglobulin. In the presentation, we will discuss known mechanisms of acquired resistance to immune checkpoint inhibitors and new approaches and models that we and others are developing to study this problem.
ES11.05 - MSK-IMPACT, a Hospital Based Genetic Screening Using FDA-Approved NGS System (Now Available) (ID 3215)
15:15 - 16:45 | Presenting Author(s): Alexander Drilon
A variety of actionable genomic signatures are found across different cancer types. These signatures have been associated with clinical benefit from a variety of therapeutics, including targeted therapy and immunotherapy. MSK-IMPACT is a broad, hybrid capture-based next-genereation sequencing platform that is capable of detecting sequence mutations, small insertions and deletions, copy number alterations, and select structural rearrangements. The assay has been validated and approved for clinical use by the New York State Department of Health Clinical Laboratory Evaluation Program. Furthermore, the assay has received authorization by the United States Food and Drug Authority. Comprehensive profiling of various cancers with assays such as MSK-IMPACT has advanced genomic medicine by increasing the identification of patients for whom matched therapies may be appropriate, elucidating putative resistance mechanisms, and identifying novel, potentiallly actionable signatures.
ES11.06 - Toxicology of Tobacco and Metabolites, and Impact on Cancer (Now Available) (ID 3216)
15:15 - 16:45 | Presenting Author(s): Maciej L. Goniewicz
Tobacco smoke is a significant source of exposure to toxic compounds among active smokers and those exposed to secondhand smoke (SHS). Over 7000 chemicals have been identified in tobacco smoke, including 69 known carcinogens. Characterizing human exposure to tobacco smoke constituents is important for public health efforts aimed at reducing exposure to these chemicals. Tobacco smoke exposure can be assessed through biomonitoring, i.e., by measuring the concentration of a toxicant or its metabolites in human physiological fluids. Biomarkers, ideally unique to a toxic mixture such as tobacco smoke, are useful for exposure assessment and for source apportionment. Nicotine, its metabolites, and the tobacco-specific nitrosamine (TSNA) metabolite 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) are the most specific of the commonly used biomarkers for tobacco smoke exposure. Carbon monoxide, metabolites of volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs) metabolites, are also useful biomarkers, but they have sources other than tobacco smoke. Levels of these biomarkers are generally elevated in smokers as compared to nonsmokers, but specificity may be inadequate to measure SHS exposure. In general, biomarker studies can demonstrate internal exposure to toxic constituents due to tobacco product use and can be used to assess relative harm of modified-risk tobacco products. Epidemiologic studies directly support a link between exposure to tobacco-specific toxicants and subsequent risk for cancer in smokers of conventional cigarettes as well as lifelong never-smokers.
Nicotine metabolites and total nicotine equivalents (sum of nicotine, cotinine, 3ʹ-hydroxycotinine, and their glucuronides), which can be measured in urine, blood or saliva, represent approximately 73%–96% of the nicotine dose and provide a superb indicator of nicotine uptake. Although nicotine was one of the first biomarkers to be used for assessing exposure to cigarette smoke, its short half-life (t1/2=~2 h) and variable rate of metabolism led to the use of cotinine and other nicotine metabolites as biomarkers of nicotine exposure. Cotinine is the major metabolite of nicotine, and its longer elimination half-time (t1/2=16–18 h) makes it a good biomarker for nicotine uptake in various biological fluids and tissues. The nicotine metabolite ratio (ratio of 3ʹ-hydroxycotinine to cotinine) in plasma is an excellent phenotypic indicator of hepatic CYP2A6 activity in smokers and can be used as a measure of individual risk for addiction.
Tobacco-specific nitrosamines (TSNAs) include the potent lung carcinogen NNK and the oral cavity and esophageal carcinogen N′-nitrosonornicotine (NNN) and are—as indicated by their common name—regarded as completely specific to tobacco. Consequently, these compounds and their metabolites are among the most important biomarkers for monitoring tobacco exposure and evaluating cancer risk in tobacco users. NNAL is a metabolite of NNK and itself is a carcinogen. A key benefit of NNAL assays is the compound’s elimination half-time ( t1/2 of 10–18 days), which is longer than other tobacco biomarkers. The main disadvantage is that the urinary concentration of NNAL is many times lower than that of cotinine, so the assay is more technically challenging and expensive to perform. Measurements of NNAL typically require extensive sample preparation and fewer laboratories can reliably measure NNAL than cotinine or nicotine.
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants formed from incomplete combustion of organic matter and use of combustible tobacco products results in substantial exposure to those chemicals. Over 500 PAHs and their alkyl derivatives have been identified in tobacco smoke. Some PAHs induce tumors in animals and are carcinogenic to humans. For example, benzo[a]pyrene induces malignant lesions in animal studies. Urinary concentrations of PAH metabolites, specifically monohydroxylated PAHs, have been used as biomarkers of human exposure to PAHs including naphthalene, fluorene, phenanthrene and pyrene. The PAH exposure profiles for tobacco smoke may differ from other sources, and it may be possible to identify PAH biomarkers that are more selective for tobacco smoke than others.
Volatile organic compounds (VOCs) are a diverse group of chemicals that are abundant in tobacco product emissions and in the polluted atmosphere. Many VOCs are formed by incomplete combustion of organic materials, and tobacco is not the only source of exposure. Although VOCs are also present in foods and beverages, the levels of many VOCs and VOC metabolites are elevated in smokers’ urine compared with nonsmokers. Several VOCs in tobacco smoke, including acrolein, benzene, and 1,3-butadiene, can cause cardiovascular and lung damage. 1,3-butadiene is also a human carcinogen and benzene is a human carcinogen known to cause leukemia. A number of harmful VOCs and their metabolites can be measured in human blood, urine, and breath and those biomarkers serve as a surrogate measure for tobacco smoke exposure.
While tobacco-specific biomarkers are useful for interim assessments of exposure, there are several sources of variation to consider when interpreting such data. These include frequency and intensity of tobacco use product type, inter- and intra-individual variability, biomarker/chemical half-life, and variability in lab methods. Differences in carcinogen exposure from different cigarette products could contribute to differences in smoking-associated cancer incidence. Due to the introduction of new tobacco-derived products and the development of novel ways to modify and use conventional tobacco products, biomarker studies can be used to assess relative harm of modified-risk tobacco products. For example, short-term observational studies have shown reduction in biomarker levels for VOCs, TSNAs, and PAHs in cigarette smokers who switched to e-cigarettes, smokeless or heated tobacco products. This suite of biomarkers has the potential to provide objective data on levels of nicotine as well as selected important carcinogens and toxicants that may be associated with use of novel tobacco products.
Selected Biomarkers of Exposure to Tobacco Products Toxicant Group Tobacco Constituents Biomarkers Clinical Relevance Nicotine Metabolites Nicotine Cotinine Addictive chemical Tobacco Specific Nitrosamines (TSNAs) 4-methylnitrosamino)-4-(3-pyridyl)-1-butanon (NNK) 4-methylnitrosaminol)-4-(3-pyridyl)-1-butanol (NNAL) Carcinogen Polycyclic Aromatic Hydrocarbons (PAHs) Naphthalene and Pyrene 2-Napthol and 1-Hydroxypyrene Possible human carcinogens Volatile Organic Compounds (VOCs) Acrylonitrile, acrolein, acrylamide CYMA, CEMA, AAMA Probable human carcinogens