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L. Montuenga

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    MS 02 - Are Non-Tissue Biomarkers Ready for the Clinic? (Presentation recordings currently in editing process) (ID 20)

    • Event: WCLC 2015
    • Type: Mini Symposium
    • Track: Screening and Early Detection
    • Presentations: 4
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      MS02.01 - Free Circulating Tumor DNA (ID 1852)

      14:15 - 15:45  |  Author(s): P.C. Mack

      • Abstract

      Abstract not provided

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      MS02.02 - Circulating Tumor Cells (ID 1853)

      14:15 - 15:45  |  Author(s): T. Sundaresan

      • Abstract
      • Slides

      Abstract:
      In EGFR-mutant lung cancer, acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) develops after a median of 9-14 months. The T790M gatekeeper mutation is the most common mechanism of TKI resistance, detected in >50% of tissue biopsies done after the advent of resistance. The recent clinical development of third-generation, irreversible EGFR TKIs that have preliminarily demonstrated durable tumor responses in patients who have developed the EGFR T790M mutation has generated a need for novel methods of T790M detection. Repeating tumor biopsies at the time of acquired resistance to help select second-line therapies is recommended in the NCCN guidelines. However, tissue biopsies do not always supply sufficient material for current sequencing strategies and thus may require multiple invasive procedures for adequate genotyping. Blood-based methods are more readily repeated when necessary and avoid the risks and discomfort of invasive tissue biopsies. As there may be heterogenous mechanisms of acquired resistance, a tissue biopsy of a single site of disease also may not capture the full spectrum of resistance. Blood-based methods theoretically have the potential of more comprehensively illustrating the principal mechanisms of resistance within a patient. Although there are multiple non-invasive sources of tumor-derived genetic material, circulating tumor cells (CTCs) and plasma circulating tumor DNA (ctDNA) are two that have received particular attention for blood-based genotyping. CTCs are cells shed into the bloodstream from primary and metastatic tumors that can be captured through multiple microfluidic platforms. Despite their rarity in the blood there is ongoing development of increasingly sensitive methods of CTC isolation. ctDNA is also shed into the bloodstream from tumor deposits. While more abundant than CTCs, ctDNA analysis is complicated by a high background of plasma DNA shed from normal cells. Techniques for genotyping from these blood-based sources of tumor-derived genetic material have proliferated rapidly, but there have been few studies directly comparing them. In this presentation, I will describe an exploratory study comparing T790M genotyping, using either CTCs or ctDNA versus concurrent tumor biopsies in patients with non-small cell lung cancer progressing on first line EGFR inhibitors.

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      MS02.03 - Blood-Based Proteomics Strategies for the Early Detection of Lung Cancer (ID 1854)

      14:15 - 15:45  |  Author(s): R. Pio

      • Abstract
      • Slides

      Abstract:
      Blood-based proteomics strategies for the early detection of lung cancer. Since the advent of the new proteomics era, large-scale studies of protein profiling have been exploited to identify the distinctive molecular signatures in a wide array of biological systems spanning areas of basic biological research, various disease states, and biomarker discovery directed toward diagnostic and therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomics approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures specific for invasive lung cancer and preinvasive lesions have begun to emerge. In this presentation, we will provide a critical assessment of the state of recent advances in proteomic approaches to the discovery and validation of blood based biomarker signatures for the early detection of lung cancer. Mass spectrometry and immuno-based detection methods will be reviewed including commercially available blood tests to aid the early detection of lung cancer. Much of this progress was driven by increasing knowledge of tumor-related aberrations that affect nucleic acids at genomic, transcriptional, and posttranscriptional levels. Proteins are the functional end product of genes that ultimately control vital biological processes via their expression level and posttranslational modifications. Moreover, the number of proteins produced by cells far exceeds the number of genes because proteins vary in their stability compared with mRNA and are subjected to many levels of posttranscriptional and posttranslational regulations, such as splicing variants, fusions, and posttranslational modifications. Therefore, to advance our understanding of the biology of lung cancer and to obtain a more integrated view of the disease biology, it is critical to capture the full spectrum of the variations in protein expression patterns, their posttranslational modifications, and their functions in cancer cells. Thus, we hope to take advantage of the molecular complexity of the proteome to improve early detection strategies for lung cancer. Proteomic analysis of blood represents an appealing choice to researchers addressing the discovery of biomarkers because it can be quickly and easily obtained noninvasively in large quantities over time. Several recent studies have investigated the extent to which proteomic technologies can unravel the complexity of the plasma proteome. In this regard, the Human Proteome Organization completed a comprehensive collaborative study to characterize the human serum and plasma proteomes. The rapid proteomic profiling of blood in particular has generated great enthusiasm but has been minimally successful at providing robust signatures to translate to the clinic. The major preanalytical challenges are related to the lack of standardized sample collection and preparation techniques, leading to the introduction of analytical bias and the lack of reproducibility. The extreme complexity of biofluids, such as blood, serum, or plasma, and the low abundance of most of the specific protein markers are among other factors that reduce the sensitivity of detection by proteomic technologies. After the discovery of new biomarkers, the next critical steps are to validate and evaluate their performance in clinically relevant patient populations. Multiple levels of validation have to take place before confirming the clinical utility of the biomarker. This includes confirmation of detected changes in protein level by different techniques and correlation with biological outcomes of lung cancer such as early detection, chemosensitivity, or survival. These phases of clinical validation will evaluate a biomarker's performance in relevant clinical context and how it may affect clinical management of risk or disease. Selected readings: 1. Zeng GQ, Zhang PF, Deng X, Yu FL, Li C, Xu Y, Yi H, Li MY, Hu R, Zuo JH, et al. Identification of candidate biomarkers for early detection of human lung squamous cell cancer by quantitative proteomics. Molecular & cellular proteomics : MCP. 2012;11(6):M111 013946. 2. Massion PP, and Walker RC. Indeterminate pulmonary nodules: risk for having or for developing lung cancer? Cancer Prev Res (Phila). 2014;7(12):1173-8. 3. Hassanein M, Callison JC, Callaway-Lane C, Aldrich MC, Grogan EL, and Massion PP. The state of molecular biomarkers for the early detection of lung cancer. Cancer Prev Res (Phila). 2012;5(8):992-1006. 4. Kikuchi T, Hassanein M, Amann JM, Liu Q, Slebos RJ, Rahman SM, Kaufman JM, Zhang X, Hoeksema MD, Harris BK, et al. In-depth proteomic analysis of nonsmall cell lung cancer to discover molecular targets and candidate biomarkers. Molecular & cellular proteomics : MCP. 2012;11(10):916-32. 5. Skates SJ, Gillette MA, LaBaer J, Carr SA, Anderson L, Liebler DC, Ransohoff D, Rifai N, Kondratovich M, Tezak Z, et al. Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies. Journal of proteome research. 2013;12(12):5383-94. 6. Zhang B, Wang J, Wang X, Zhu J, Liu Q, Shi Z, Chambers MC, Zimmerman LJ, Shaddox KF, Kim S, et al. Proteogenomic characterization of human colon and rectal cancer. Nature. 2014;513(7518):382-7. 7. Neal JW, Gainor JF, and Shaw AT. Developing biomarker-specific end points in lung cancer clinical trials. Nature reviews Clinical oncology. 2015;12(3):135-46.

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      MS02.04 - Exhaled Breath (ID 1855)

      14:15 - 15:45  |  Author(s): N. Peled

      • Abstract
      • Slides

      Abstract not provided

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    ORAL 25 - Biology and Other Issues in SCLC (ID 125)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Small Cell Lung Cancer
    • Presentations: 8
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      ORAL25.01 - Screening for Small Cell Lung Cancer: Analysis of the National Lung Cancer Screening Trial Data (ID 2145)

      10:45 - 12:15  |  Author(s): A. Thomas, E. Szabo, P. Pinsky

      • Abstract
      • Slides

      Background:
      Given its widely metastatic nature at the time of diagnosis and the lack of effective therapies, early detection could theoretically have a beneficial impact on small cell lung cancer (SCLC) patient survival. However in the National Lung Screening Trial (NLST), there was no survival advantage for SCLC in the low dose computed tomography (LDCT) arm versus the chest radiography (CXR) arm. We investigated whether LDCT could detect SCLC and whether such screen detection offered a stage and/or survival benefit.

      Methods:
      Subjects randomized to the LDCT arm in NLST received three annual LDCT screens. Incident cancers were tracked with annual surveys and confirmed with medical records, with abstractors coding lung cancer stage and histology. “Best” stage was defined as pathologic stage if available, otherwise clinical stage. Deaths were tracked with the annual surveys and supplemented by the National Death Index. Cancer was denoted as screen-detected if it was diagnosed within one year of a positive screen or if it was diagnosed after a longer period but with no time gap between diagnostic procedures of more than one year. An interval cancer was defined as a cancer diagnosed within one year of a negative screen. Non-screen detected or interval cancers were denoted as non-screened if the subject did not receive any NLST screens or otherwise as post-screening.

      Results:
      26,722 subjects were randomized to the LDCT arm (median follow up 6.5 years; 59% men; median age at enrollment 62). 143 SCLCs were diagnosed [49 (34.2%) screen-detected, 15 (10.5%) interval, 79 (55.2%) non-screened/ post-screening]. The ratio of interval to screen detected cases was significantly higher for SCLC (15/49=0.31) than for NSCLC (29/591=0.05); p < 0.0001. 123 of 143 (86%) SCLCs were detected at late-stages (best stage III/IV); the unfavorable stage-distribution persisted among screen-detected, interval and non-screened/ post-screening cases with only 15 (10.5%) detected in early-stages. Three-year lung cancer-specific survival was 72% for early-stage versus 11% for late-stage disease. There was no significant difference in five-year survival between screen-detected, interval and non-screened/post-screening SCLCs (15.3%, 20.0% and 13.8%, respectively). Unlike NSCLC, even at small nodule sizes the proportion of screen-detected SCLCs that were late stage was very high.

      Conclusion:
      Analysis of SCLC detected in the NLST LDCT arm show that yearly LDCT screens do not detect a significant number of early stage SCLCs. Compared with NSCLC, a higher proportion of SCLCs are interval-detected than screen-detected. Further, there is no stage-shift or survival benefit for screen- detected SCLCs compared with interval or post-screen detected cases. To our knowledge this is the largest analysis to date of SCLC detected in a screening study. Our results indicate that in order for a screening modality to be successful for SCLC, it is necessary (but not sufficient) to be able to detect it earlier than does LDCT.

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      ORAL25.02 - Vasculogenic Mimicry in Small Cell Lung Cancer (ID 2654)

      10:45 - 12:15  |  Author(s): K.L. Simpson, F. Trapani, R.L. Metcalf, R. Polanski, S. Williamson, R.E.B. Seftor, E.A. Seftor, A. Fusi, C.L. Hodgkinson, D. Nonaka, C.J. Morrow, M.J.C. Hendrix, F. Blackhall, C. Dive

      • Abstract
      • Slides

      Background:
      Small cell lung cancer (SCLC) accounts for 15-20% of lung cancer cases worldwide and is characterised by early dissemination. Despite initial responses to chemotherapy, most patients relapse with drug resistant disease and long term survival is rare. Targeting tumour vasculature in SCLC with anti-angiogenic drugs produced disappointing results. However, angiogenesis-independent tumour vascularisation including vasculogenic mimicry (VM), warrant further investigation. VM describes the ability of aggressive tumour cells with ‘stem-like’ plasticity to adopt endothelial characteristics and form fluid conducting channel-like structures independent of host vasculature. We sought to determine the prevalence of VM in SCLC and explore associations of VM with chemotherapy sensitivity and patient outcomes. We investigated the role of a VM-associated protein, VE-Cadherin in vitro and in vivo and in SCLC CTCs. We are testing the hypothesis that VM may contribute to the high prevalence of CTCs in SCLC and components of the VM pathway may be targets for SCLC therapeutics.

      Methods:
      VM was evaluated using CD31/periodic acid-Schiff (PAS) staining in a tissue micro-array (TMA) from 41 limited stage SCLC chemo-naive patients and in tumours from 11 Circulating Tumour Cell (CTC) Derived Explant (CDX) models (Hodgkinson et al Nature Medicine, 2014). The relative abundance of VM channels (CD31-ve/PAS+ve) compared to host derived blood vessels (CD31+ve/PAS+ve), (VM/total vessels) in the TMA was compared to patient overall survival (OS). VM was evaluated in vitro by network formation in Matrigel (Hendrix et al., PNAS 2001) in a panel of SCLC cells lines and in H446 cells where VE-Cadherin was knocked down with shRNA. H446 cells +/- VE-Cadherin were grown in vivo as xenografts and evaluated for VM. ISET filtered, DAPI stained CTCs were immune-stained for CD45, cytokeratin and VE-cadherin and a VM score was generated.

      Results:
      In the TMA, a VM/Total Vessels score >10% was a poor prognostic factor for OS by univariate (p=0.011) and multivariate (p=0.014) analyses. VM was present in all CDX models provide surrogate tissues in which to study VM. Of 12 SCLC cell lines studied, H446 showed significant VE-Cadherin expression and formed networks in Matrigel; VE-Cadherin shRNA abrogated this network formation. Similarly, a pilot in vivo study demonstrated that there were fewer VM vessels when VE-Cadherin was reduced. In CTC samples 37/38 chemonaive SCLC patients contained a sub-population of VE-Cadherin expressing CTCs where the VM score ranged from 0 – 100% (median 11%, mean 21%).

      Conclusion:
      We present the first evidence of VM in SCLC which correlates with poor OS consistent with findings in other cancer types. VE-Cadherin is required in SCLC for VM network formation in vitro and preliminary data indicate that VE-Cadherin influences VM in vivo. Furthermore, VE-Cadherin and pan-cytokeratin co-expression was found in SCLC CTC sub-populations. We are investigating the role of VE-Cadherin in VM in SCLC and are exploring the hypotheses that VE-cadherin and VM may play a role in drug delivery and/or sensitivity and may represent an aggressive, ‘stem-like’ population that may contribute to dissemination and relapse in this highly aggressive disease.

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      ORAL25.03 - Establishment of Lung Cancer Xenograft Models Derived from Bronchoscopy Biopsy and Investigating Mechanism of Refractory Small Cell Lung Cancer (ID 3097)

      10:45 - 12:15  |  Author(s): J. Wang, S. Fu, J. Zhao, T. An, H. Bai, J. Duan, Z. Wang

      • Abstract
      • Presentation

      Background:
      There were mainly two kinds of lung cancer xenograft models, xenograft models derived from stable cell lines and patient derived xenograft (PDX) models which adopted tissues resected by surgeries. However, these animal models may not reflect biological and genetic characteristics of advanced lung cancer, especially small cell lung cancer (SCLC). We utilized bronchoscopy-guided biopsy tumor tissues of advanced lung cancer to establish xenograft models and analyzed fidelity of histopathology, genetic profile and chemotherapeutic efficacy with their parental tumors. At last the molecular mechanism of drug resistance in refractory SCLC was studied.

      Methods:
      Primary pulmonary tumor tissues taken from bronchoscopy were implanted to NOD-SCID (nonobese diabetic-severe combined immunodeficiency disease) mice subcutaneously for model establishment and consecutive passage. The histopathology and genetic profile in samples of bronchoscopy-guided biopsy tumor tissues-derived xenograft (BDX) models and their parental tumors were detected. Parental fidelity of BDXs’ chemotherapeutic response was detected by chemosensitivity in vivo. Next generation sequencing (NGS) of target gene was taken in SCLC BDXs to analyze high-fidelity with their parental samples. Based on bioinformatic analysis, molecular mechanism of sensitive and refractory SCLC was discussed.

      Results:
      66 BDXs from 188 patients (35%) were successfully established. Successful rate of BDXs in SCLC was significantly higher than that in squamous cell cancer (SCC) (50.72% vs. 32.00%, p=0.005) and in adenocarcinoma (ADC) (50.72% vs. 16.22%, p=0.025). The growth rate of passage 1 BDXs in SCLC was slower than it in SCC or ADC (P<0.0001). Almost all BDXs kept similar histology, pathological marker and driver-gene mutations with their corresponding patients’ tissues. The gene mutations of which frequency was more than 10% in patient’s SCLC were kept consistent in BDXs with same genotype and frequency. Gene mutations which regulated mitogen activated protein kinase (MAPK) pathway as KRAS, KIT, MET were only detected in refractory SCLC and corresponding BDXs rather than sensitive disease. In further functional verification, the percentage of positive pERK was 100% (5/5) in refractory BDXs, but 20% (1/5) in sensitive BDXs (p=0.0476).

      Conclusion:
      BDXs which were successfully established with high-fidelity of histopathology, genetic profile and chemotherapeutic response could be utilized as animal models in research of unresectable lung cancer. MAPK pathway related gene mutations found in both BDXs and primary tumor tissues may be associated with resistance in refractory SCLC. PERK was promising to be used as molecular markers in genotype and prediction of chemotherapy-resistance for SCLC.

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      ORAL25.04 - Discussant for ORAL25.01, ORAL25.02, ORAL25.03 (ID 3360)

      10:45 - 12:15  |  Author(s): C.M. Rudin

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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      ORAL25.05 - Predictive and Prognostic Significance of Myeloid-Derived Suppressor Cells in Patients with Small-Cell Lung Cancer (ID 571)

      10:45 - 12:15  |  Author(s): Y. Cheng, H. Li, Y. Liu, X. Liu, L. Ma, J. Zhu, Y. Wang, Y. Liu, J. Liu, S. Zhang

      • Abstract
      • Presentation
      • Slides

      Background:
      Myeloid-derived suppressor cells (MDSCs) play a key role in microenvironment for tumor progression and have been emerged as a promising target in immunotherapy for tumor. We reported the existence and characteristics of monocytoid MDSCs in peripheral blood of patients with small-cell lung cancer (SCLC). In this study, we further identify the predictive and prognostic of MDSCs in a larger cohort of SCLC patients.

      Methods:
      60 healthy and 228 chemotherapy-naïve patients with SCLC participated. Peripheral venous blood samples prior to chemotherapy (baseline) and after the second cycle of chemotherapy (2[nd] cycle) were collected and detected for MDSCs (CD11b[+]HLA-DR[-]CD33[+]) by flow cytometry.

      Results:
      Median age of the patients was 58 years (range 18-79). MDSCs in limited-stage (n=147) and extensive-stage patients (n=81) were (16.41±8.54)% and (17.20±10.43)% respectively, higher than those in healthy control (11.04±3.76)%, P<0.001。The level of MDSCs were lower after 2[nd] cycle than those pre-treatment, (8.47±5.51)% versus (17.61±6.69)%, P<0.001. Patients with response to chemotherapy (CR+PR+SD) showed lower MDSCs level than those with progression disease at both time points, (15.85±9.07)% versus (18.42±8.89)%, P=0.026 at baseline and (8.20±5.31)% vs (10.65±6.73)%, P=0.045 after 2[nd] cycle. Patients with MDSCs level ≥22% (2 fold of healthy control) showed favorable overall survival than those with MDSCs level <22% (13.9 months versus 7.9 months respectively, log rank P=0.003). No difference regarding to median progression–free survival was observed between the two groups.

      Conclusion:
      MDSCs level at both baseline and after the second cycle of chemotherapy was associated with response of SCLC patients to chemotherapy and overall survival, implying it is likely a new predictive and prognostic biomarker for SCLC patients.

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      ORAL25.06 - Association of Expression of PD-L1 with the Tumor Immune Microenvironment in Small Cell Lung Cancer (ID 859)

      10:45 - 12:15  |  Author(s): H. Yu, A. Badzio, T.A. Boyle, D. Chan, C.J. Rivard, X. Lu, A.A. Kowalewski, K. Ellison, F.R. Hirsch

      • Abstract
      • Presentation
      • Slides

      Background:
      Small cell lung cancer (SCLC) accounts for 15% of all lung cancers and has been under-studied relative to novel therapies. Therapeutic antibodies to immune checkpoints are showing promising clinical results. Programmed death-ligand 1 (PD-L1), which can be expressed on many cancer and immune cells, plays an important role in blocking the cancer immunity cycle by binding programmed death-ligand 1 receptor (PD-1), which is a negative regulator of T-lymphocyte activation. Since knowledge about PD-L1 expression in SCLC is limited, we aimed to characterize PD-L1 expression in a cohort of 98 SCLC patients.

      Methods:
      PD-L1 protein expression and mRNA levels were determined by immunohistochemistry (IHC, SP142, Spring Bioscience) and mRNA in situ hybridization (ISH) in primary tumor tissue microarrays obtained from 98 SCLC patients. Membranous staining of PD-L1 protein and mRNA expression on tumor cells and protein expression on tumor-infiltrating immune cells (TIICs) were scored separately using semi-quantitative scores (H-score 0-300 and RNA score 0-4). An H-score ≥ 5 and an RNA score > 2 were defined as the cutoffs for PD-L1 protein and RNA expression positivity. The degree of TIICs was semi-quantitatively scored on hematoxylin and eosin-stained TMA slides as having “0” (no), “1” (mild), “2” (moderate), or “3” (marked) infiltration. The data was analyzed using the Fisher’s exact test, Spearman correlation, two-sample t-test, log-rank test and Kaplan- Meier survival analysis with significance level assumed to be 0.05.

      Results:
      3.16% of cases (3/95) were positive for PD-L1 protein expression in tumor cells, and 30.21% were positive for PD-L1 in TIICs (29/96, p<0.0001). PD-L1 mRNA expression was positive in 15.46% of the tumor cells (15/97). PD-L1 protein and mRNA expression on tumor cells demonstrated a positive correlation (p<0.0001, r=0.431). PD-L1 mRNA expression on tumor cells positively correlated with PD-L1 protein expression on TIICs (p<0.0001, r=0.354). The degree of TIICs positively correlated with both PD-L1 protein expression in tumor cells (p=0.011, r=0.264) and PD-L1 mRNA expression in tumor cells (p<0.0001, r=0.405). The degree of TIICs positively correlated with PD-L1 protein expression in TIICs (p<0.0001, r=0.625). The only significant association observed between PD-L1 expression with clinical characteristics or prognosis of the 78 SCLC patients with clinical data, was between age of patients and PD-L1 protein (p<0.0001) and mRNA expression (p=0.0006) on tumor cells.

      Conclusion:
      A subset of SCLCs is characterized by positive PD-L1 protein and/or mRNA expression in tumor cells and TIICs. PD-L1 mRNA expression was more frequently positive than PD-L1 protein expression in the tumor cells. PD-L1 protein expression was expressed more in TIICs than tumor cells. Higher PD-L1 protein and mRNA expression correlated with more infiltration of TIICs. PD-L1 expression represents the immune response in SCLC. The microenvironment may play a major role on the PD-1/PD-L1 pathway of SCLC. SCLC Patients with PD-L1 expression may respond to anti-PD-L1 treatment.

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      ORAL25.07 - DNA Methylation in Small Cell Lung Cancer Defines Distinct Disease Subtypes and Correlates with High Expression of EZH2 (ID 3031)

      10:45 - 12:15  |  Author(s): J. Poirier, E. Gardner, N. Connis, A. Moreira, E. De Stanchina, C. Hann, C.M. Rudin

      • Abstract
      • Presentation
      • Slides

      Background:
      Small cell lung cancer (SCLC) is an aggressive neuroendocrine lung tumor characterized by extreme plasticity, high metastatic potential, and capacity for acquired resistance to chemotherapy. Despite significant advances in our understanding of SCLC genetics and etiology, the epigenetics of this deadly disease remain under studied. This study profiles DNA methylation in primary SCLC, patient-derived xenografts (PDX) and cell lines at single-nucleotide resolution.

      Methods:
      This study profiled DNA methylation at single-nucleotide resolution in 47 extensively characterized SCLC samples, including 34 fresh frozen primary SCLC tumors as well as 6 distinct primary patient-derived xenografts and 7 cell lines using the Illumina Human Methylation 450k Bead Chip array. Importantly, 24 primary SCLC in this study have previously been analyzed by whole exome sequencing and RNAseq, allowing integrated analysis of these data types with measurements of DNA methylation. We applied unsupervised clustering, discrete and locally clustered differential methylation analysis, correlation with gene expression, spacial correlation with genomic features, and interrogated the role of the EZH2 methyltransferase in SCLC using bioinformatic and pharmacologic approaches.

      Results:
      Unsupervised clustering of all samples revealed that PDX clustered with primary SCLC, while cell lines were easily discriminated. We explored this phenomenon further and found that while the top differentially methylated CpGs in both PDX and cell lines were >80% concordant with primary SCLC, only PDX maintained high concordance across larger probe lists. Unsupervised clustering of primary SCLC revealed three distinct subgroups at both the DNA methylation and gene expression levels that correlated with expression of the neurogenic transcription factors ASCL1 and NEUROD1. The chromatin modifier EZH2 was expressed >12-fold higher in SCLC than in normal lung. In addition to the high expression observed in SCLC compared to normal lung, we observed a significant correlation between median EZH2 gene expression and promoter methylation using data from The Cancer Genome Atlas (TCGA). Overall, EZH2 expression in SCLC is greater than or comparable to that of any other tumor type represented in TCGA. EZH2 protein expression was detected by Western blot in 15/17 SCLC PDXs (88%). We assessed the efficacy of the potent EZH2 inhibitor EPZ-5687 in the LX92 SCLC PDX in vivo. EPZ-5687 was well-tolerated and demonstrated remarkable efficacy at 100 mg/kg either QD or BID.

      Conclusion:
      DNA methylation patterns in primary SCLC are more closely mirrored by those found in PDX, compared to cell lines, including PDX lines of very high passage. Distinct epigenetic subtypes could be observed in SCLC, even among histologically indistinguishable samples with similar mutation profiles. SCLC is notable for consistent high level DNA methylation clustered in promoters containing CpG islands. Promoter methylation in SCLC is distinct from other lung cancers and correlates strongly with high-level expression of the histone methyltransferase gene EZH2. Pharmacologic inhibition of EZH2 in a SCLC PDX markedly inhibited tumor growth. These findings point to a critical role of EZH2 in SCLC tumor biology and support further preclinical efficacy studies in models of SCLC.

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      ORAL25.08 - Discussant for ORAL25.05, ORAL25.06, ORAL25.07 (ID 3361)

      10:45 - 12:15  |  Author(s): C. Dive

      • Abstract
      • Slides

      Abstract not provided

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Author of

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    MINI 12 - Biomarkers and Lung Nodule Management (ID 109)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Screening and Early Detection
    • Presentations: 1
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      MINI12.05 - Discussant for MINI12.01, MINI12.02, MINI12.03, MINI12.04 (ID 3418)

      16:45 - 18:15  |  Author(s): L. Montuenga

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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    MINI 34 - RNA and miRNA (ID 162)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 1
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      MINI34.11 - Identification and Functional Characterization of Non-Small Cell Lung Cancer-Associated Splice Variants and Splicing Factors (ID 2101)

      18:30 - 20:00  |  Author(s): L. Montuenga

      • Abstract
      • Presentation
      • Slides

      Background:
      Deregulation of alternative splicing has become a hallmark of cancer. In non-small cell lung cancer (NSCLC), the biological importance of splicing is evidenced by the identification of aberrant RNA transcripts associated with somatic mutations in genes encoding splicing factors. We have previously developed ExonPointer, an algorithm optimized to detect differential splicing cassette events from data obtained in microarrays containing probes in exons and junctions. Our present objective was to apply this technology for the identification and characterization of cancer-associated splice variants and splicing factors in NSCLC.

      Methods:
      We applied ExonPointer for the identification of differential splice forms in lung cancer tissues (8 adenocarcinomas, 13 squamous cell carcinomas and 1 large cell carcinoma) and matched normal lung. We validated the events by RT-PCR and used bioinformatics tools, such as DAVID and Ingenuity Pathway Analysis, for cluster enrichment analyses. siRNA knockdown of specific splice isoforms was used for functional analyses. Prognostic studies were performed by immunohistochemistry in 127 primary tissues from patients with NSCLC.

      Results:
      The validation rate for the top 20 differentially expressed splice events identified by ExonPointer was 70%. Gene cluster analyses using the first 250 events showed a significant enrichment of cancer-related clusters such as Cellular Growth and Proliferation, or Cell Death and Survival. Among the validated genes, we identified Extended synaptotagmin-2 (ESYT2). ESYT2 is a membrane protein that mediates fibroblast growth factor receptor-1 (FGFR1) endocytosis and actin dynamics. A significantly different pattern of ESYT2 alternative splicing was found in primary lung tumors as compared to normal lung tissue (p<0.001). In particular, an isoform containing an extra exon was overexpressed in cancer tissues, while the expression of the canonical isoform was decreased. We found a significant correlation between the splicing pattern of ESYT2 and the expression of FGFR1 in a panel of 43 lung cancer cell lines (r=-0.724, p<0.001). Using siRNA downregulation, we analyzed the implication of the ESYT2 isoforms in tumor biology and demonstrated a distinct role of the splice isoforms in actin and tubulin cytoskeleton organization. We also searched for splicing factors responsible for the splicing of ESYT2. We found that the ratio of ESYT2 isoforms correlated with the expression of the splicing factor QKI in lung cancer cell lines (r=-0.793, p<0.001). Moreover, in vitro downregulation of QKI markedly affected ESYT2 splicing. Interestingly, we found a significant enrichment of QKI targets in the list of differentially spliced genes identified by ExonPointer (p<0.001), suggesting that this factor is a critical regulator of splicing in lung cancer. Finally, we observed a significant downregulation of QKI expression in primary NSCLC compared to adjacent normal lung cancer cells (p<0.001), and an association between the nuclear expression of this factor and disease-free survival (HR=0.61; 95%CI=0.35-1.05) or overall survival (HR=0.44; 95%CI=0.21-0.94).

      Conclusion:
      Using a novel analytical tool we have identified new splicing variants with functional relevance in lung cancer. Moreover, changes in splicing events in lung primary tumors were found to be largely regulated by the splicing factor QKI, a potential tumor suppressor gene downregulated in NSCLC and associated with the prognosis of the disease.

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