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Adopting a systems approach, we devise a general workflow to define actionable subtypes in human cancers. Applied to small cell lung cancer (SCLC), the workflow identifies four subtypes based on global gene expression patterns and ontologies. Three correspond to known subtypes (SCLC-A, SCLC-N, and SCLC-Y), while the fourth is a previously undescribed ASCL1+ neuroendocrine variant (NEv2, or SCLC-A2). Tumor deconvolution with subtype gene signatures shows that all of the subtypes are detectable in varying proportions in human and mouse tumors. To understand how multiple stable subtypes can arise within a tumor, we infer a network of transcription factors and develop BooleaBayes, a minimally-constrained Boolean rule-fitting approach. In silico perturbations of the network identify master regulators and destabilizers of its attractors. Specific to NEv2, BooleaBayes predicts ELF3 and NR0B1 as master regulators of the subtype, and TCF3 as a master destabilizer. Since the four subtypes exhibit differential drug sensitivity, with NEv2 consistently least sensitive, these findings may lead to actionable therapeutic strategies that consider SCLC intratumoral heterogeneity. Our systems-level approach should generalize to other cancer types.
BACKGROUND - Approximately 10% of patients with SCLC develop a paraneoplastic syndrome (PNS). Neurologic PNS are thought to improve prognosis, which we hypothesized is related to increased tumor-infiltrating lymphocytes and immune recognition.
METHODS - We queried 2,512,042 medical records from a single institution to identify patients who have SCLC with and without PNS and performed manual, retrospective chart review. We then performed multiplexed fluorescence immunohistochemistry and automated quantitative analysis (AQUA Technology) on tumors to assess CD3, CD4, and CD8 T cell infiltrates and programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) interactions. T cell infiltrates and PD-1/PD-L1 interaction scores were compared among patients with neurologic PNS, endocrinologic PNS, and a control group without PNS. Clinical outcomes were analyzed using the Kaplan-Meier method and Cox proportional hazards models.
RESULTS - We evaluated 145 SCLC patients: 55 with PNS (25 neurologic and 30 endocrinologic) and 90 controls. Patients with neurologic PNS experienced improved overall survival compared to patients with endocrinologic PNS and controls (median overall survival of 24 months versus 12 months versus 13 months, respectively). Of the 145 patients, we identified tumor tissue from 34 patients that was adequate for AQUA analysis. Among 37 specimens from these 34 patients, patients with neurologic PNS had increased T cell infiltrates (p = 0.033) and PD-1/PD-L1 interaction (p = 0.014) compared to tumors from patients with endocrinologic PNS or controls.
CONCLUSIONS - Tumor tissue from patients with SCLC with neurologic PNS showed increased tumor-infiltrating lymphocytes and PD-1/PD-L1 interaction consistent with an inflamed tumor microenvironment.
Copyright © 2019 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.
Small cell lung cancer (SCLC) is an exceptionally lethal malignancy for which more effective therapies are urgently needed. Several lines of evidence, from SCLC primary human tumours, patient-derived xenografts, cancer cell lines and genetically engineered mouse models, appear to be converging on a new model of SCLC subtypes defined by differential expression of four key transcription regulators: achaete-scute homologue 1 (ASCL1; also known as ASH1), neurogenic differentiation factor 1 (NeuroD1), yes-associated protein 1 (YAP1) and POU class 2 homeobox 3 (POU2F3). In this Perspectives article, we review and synthesize these recent lines of evidence and propose a working nomenclature for SCLC subtypes defined by relative expression of these four factors. Defining the unique therapeutic vulnerabilities of these subtypes of SCLC should help to focus and accelerate therapeutic research, leading to rationally targeted approaches that may ultimately improve clinical outcomes for patients with this disease.
Somatostatin receptor 2 (SSTR2) is overexpressed in a majority of neuroendocrine neoplasms, including small-cell lung carcinomas (SCLCs). SSTR2 was previously considered an inhibitory receptor on cell growth, but its agonists had poor clinical responses in multiple clinical trials. The role of this receptor as a potential therapeutic target in lung cancer merits further investigation. We evaluated the expression of SSTR2 in a cohort of 96 primary tumors from patients with SCLC and found 48% expressed SSTR2. Correlation analysis in both CCLE and an SCLC RNAseq cohort confirmed high-level expression and identified an association between NEUROD1 and SSTR2. There was a significant association with SSTR2 expression profile and poor clinical outcome. We tested whether SSTR2 expression might contribute to tumor progression through activation of downstream signaling pathways, using in vitro and in vivo systems and downregulated SSTR2 expression in lung cancer cells by shRNA. SSTR2 downregulation led to increased apoptosis and dramatically decreased tumor growth in vitro and in vivo in multiple cell lines with decreased AMPKα phosphorylation and increased oxidative metabolism. These results demonstrate a role for SSTR2 signaling in SCLC and suggest that SSTR2 is a poor prognostic biomarker in SCLC and potential future therapeutic signaling target.
© 2018 UICC.
INTRODUCTION - Patients with SCLC have a poor prognosis and limited treatment options. Because access to longitudinal tumor samples is very limited in patients with this disease, we chose to focus our studies on the characterization of plasma cell-free DNA (cfDNA) for rapid, noninvasive monitoring of disease burden.
METHODS - We developed a liquid biopsy assay that quantifies somatic variants in cfDNA. The assay detects single nucleotide variants, copy number alterations, and insertions or deletions in 14 genes that are frequently mutated in SCLC, including tumor protein p53 gene (TP53), retinoblastoma 1 gene (RB1), BRAF, KIT proto-oncogene receptor tyrosine kinase gene (KIT), notch 1 gene (NOTCH1), notch 2 gene (NOTCH2), notch 3 gene (NOTCH3), notch 4 gene (NOTCH4), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha gene (PIK3CA), phosphatase and tensin homolog gene (PTEN), fibroblast growth factor receptor 1 gene (FGFR1), v-myc avian myelocytomatosis viral oncogene homolog gene (MYC), v-myc avian myelocytomatosis viral oncogene lung carcinoma derived homolog gene (MYCL1), and v-myc avian myelocytomatosis viral oncogene neuroblastoma derived homolog gene (MYCN).
RESULTS - Over the course of 26 months of peripheral blood collection, we examined 140 plasma samples from 27 patients. We detected disease-associated mutations in 85% of patient samples with mutant allele frequencies ranging from 0.1% to 87%. In our cohort, 59% of the patients had extensive-stage disease, and the most common mutations occurred in TP53 (70%) and RB1 (52%). In addition to mutations in TP53 and RB1, we detected alterations in 10 additional genes in our patient population (PTEN, NOTCH1, NOTCH2, NOTCH3, NOTCH4, MYC, MYCL1, PIK3CA, KIT, and BRAF). The observed allele frequencies and copy number alterations tracked closely with treatment responses. Notably, in several cases analysis of cfDNA provided evidence of disease relapse before conventional imaging.
CONCLUSIONS - These results suggest that liquid biopsies are readily applicable in patients with SCLC and can potentially provide improved monitoring of disease burden, depth of response to treatment, and timely warning of disease relapse in patients with this disease.
Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.
Small cell lung cancer (SCLC) is a devastating and aggressive neuroendocrine carcinoma of the lung. It accounts for ~15% of lung cancer mortality and has had no improvement in standard treatment options for nearly 30 years. However, there is now hope for change with new therapies and modalities of therapy. Immunotherapies and checkpoint inhibitors are entering clinical practice, selected targeted therapies show promise, and "smart bomb"-based drug/radioconjugates have led to good response in early clinical trials. Additionally, new research insights into the genetics and tumor heterogeneity of SCLC alongside the availability of new tools such as patient-derived or circulating tumor cell xenografts offer the potential to shine light on this beshadowed cancer.
Small cell lung cancer is initially highly responsive to cisplatin and etoposide but in almost every case becomes rapidly chemoresistant, leading to death within 1 year. We modeled acquired chemoresistance in vivo using a series of patient-derived xenografts to generate paired chemosensitive and chemoresistant cancers. Multiple chemoresistant models demonstrated suppression of SLFN11, a factor implicated in DNA-damage repair deficiency. In vivo silencing of SLFN11 was associated with marked deposition of H3K27me3, a histone modification placed by EZH2, within the gene body of SLFN11, inducing local chromatin condensation and gene silencing. Inclusion of an EZH2 inhibitor with standard cytotoxic therapies prevented emergence of acquired resistance and augmented chemotherapeutic efficacy in both chemosensitive and chemoresistant models of small cell lung cancer.
Copyright © 2017 Elsevier Inc. All rights reserved.
Small cell lung cancer (SCLC) is a devastating disease due to its propensity for early invasion and refractory relapse after initial treatment response. Although these aggressive traits have been associated with phenotypic heterogeneity, our understanding of this association remains incomplete. To fill this knowledge gap, we inferred a set of 33 transcription factors (TF) associated with gene signatures of the known neuroendocrine/epithelial (NE) and non-neuroendocrine/mesenchymal-like (ML) SCLC phenotypes. The topology of this SCLC TF network was derived from prior knowledge and was simulated using Boolean modeling. These simulations predicted that the network settles into attractors, or TF expression patterns, that correlate with NE or ML phenotypes, suggesting that TF network dynamics underlie the emergence of heterogeneous SCLC phenotypes. However, several cell lines and patient tumor specimens failed to correlate with either the NE or ML attractors. By flow cytometry, single cells within these cell lines simultaneously expressed surface markers of both NE and ML differentiation, confirming the existence of a "hybrid" phenotype. Upon exposure to standard-of-care cytotoxic drugs or epigenetic modifiers, NE and ML cell populations converged toward the hybrid state, suggesting possible escape from treatment. Our findings indicate that SCLC phenotypic heterogeneity can be specified dynamically by attractor states of a master regulatory TF network. Thus, SCLC heterogeneity may be best understood as states within an epigenetic landscape. Understanding phenotypic transitions within this landscape may provide insights to clinical applications. .
©2016 American Association for Cancer Research.
INTRODUCTION - The incidence of pulmonary nodules is increasing with the movement toward screening for lung cancer by low-dose computed tomography. Given the large number of benign nodules detected by computed tomography, an adjunctive test capable of distinguishing malignant from benign nodules would benefit practitioners. The ability of the EarlyCDT-Lung blood test (Oncimmune Ltd., Nottingham, United Kingdom) to make this distinction by measuring autoantibodies to seven tumor-associated antigens was evaluated in a prospective registry.
METHODS - Of the members of a cohort of 1987 individuals with Health Insurance Portability and Accountability Act authorization, those with pulmonary nodules detected, imaging, and pathology reports were reviewed. All patients for whom a nodule was identified within 6 months of testing by EarlyCDT-Lung were included. The additivity of the test to nodule size and nodule-based risk models was explored.
RESULTS - A total of 451 patients (32%) had at least one nodule, leading to 296 eligible patients after exclusions, with a lung cancer prevalence of 25%. In 4- to 20-mm nodules, a positive test result represented a greater than twofold increased relative risk for development of lung cancer as compared with a negative test result. Also, when the "both-positive rule" for combining binary tests was used, adding EarlyCDT-Lung to risk models improved diagnostic performance with high specificity (>92%) and positive predictive value (>70%).
CONCLUSIONS - A positive autoantibody test result reflects a significant increased risk for malignancy in lung nodules 4 to 20 mm in largest diameter. These data confirm that EarlyCDT-Lung may add value to the armamentarium of the practitioner in assessing the risk for malignancy in indeterminate pulmonary nodules.
Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.