Single cell RNA sequencing analysis of freshly resected non-small cell lung carcinoma (NSCLC) tissues
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ABSTRACT: Lung cancer is the leading cause of cancer-related deaths world-wide. ~85% of lung carcinomas are non–small cell lung carcinoma (NSCLC). Tumor cell heterogeneity is very poorly defined. However, it is known to be important for tumor response to cancer therapy and cancer agressivenes. We subjected three NSCLC tumors resected from different patients to Drop-seq in order to 1) elucidate the capability of scRNA-seq analysis in identifying different tumor cell populations; and 2) ascertain the clinical value of the genes which distinguish cancer cells from other cells in the tissue. As anticipated, the tissue composition of independently collected samples varied. Despite deficient populations in some samples, both donor and patient samples contributed to the majority of cell populations. However, cancer cells were all patient-specific. These findings emphasize the utility of single cell gene expression data in identification of tumor cell populations. The collected data might be further used for predicting of drugs specific to the biology of activated pathways and patient outcome.
Project description:The non-small cell lung carcinoma (NSCLC) PC9 cell line is an established preclinical model for tyrosine kinase inhibitors. Using PC9 cells, we generated EGFR-mutant lung cancer xenografts to study the differences in response between individual cells and cell populations. We performed treatment of PC9 xenograft tumors with the combination of osimertinib and crizotinib as well as single drugs, followed by Drop-seq. The addition of crizotinib was guided by our previous data in PC9 grown in cell culture that identified an erlotinib-resistant drug population sensitive to crizotinib. The results of the xenograft study show that combination treatment targets specific osimertinib-tolerant cell populations but leaves a subset of the population that is tolerant to the combo. Each cell subpopulation is characterized by specific molecular signatures. The results of our study help to address emerging drug resistance that limits clinical usefulness of targeted strategies, particularly in NSCLC.
Project description:Copy number profiling of 92 human lung tumors on Affymetrix 100K SNP arrays was conducted in order to assess the interaction of common genomic alterations with response to targeted anti-cancer therapeutics. Class 1 phosphatidylinositol 3' kinase (PI3K) plays a major role in cell proliferation and survival in a wide variety of human cancers. Here we investigate biomarker strategies for PI3K pathway inhibitors in non-small-cell lung cancer (NSCLC). Molecular profiling of NSCLC tumor samples showed that copy number gains in PIK3CA and total loss of PTEN protein were common in squamous cell carcinoma samples, whereas LKB1 loss and mutations in KRAS and EGFR were common in adenocarcinomas. A panel of NSCLC cell lines characterized for alterations in the PI3K pathway was screened with PI3K and dual PI3K/mTOR inhibitors to assess the preclinical predictive value of candidate biomarkers. Cell lines harboring pathway alterations (RTK activation, PI3K mutation or amplification, PTEN loss) were exquisitely sensitive to the PI3K inhibitor GDC-0941. A dual PI3K/mTOR inhibitor had broader activity across the cell line panel and in tumor xenografts. The combination of GDC-0941 with paclitaxel, erlotinib, or a MEK inhibitor had greater effects on cell viability than PI3K inhibition alone. CONCLUSIONS: Candidate biomarkers for PI3K inhibitors have predictive value in preclinical models and show histology-specific alterations in primary tumors, suggesting that distinct biomarker strategies may be required in squamous compared with non-squamous NSCLC patient populations. Lung tumors were profiled on Affymetrix GeneChip Mapping 100K Set Arrays Tumor samples were profiled for copy number without any treatment of the tumor.
Project description:RNA from patient samples was isolated to examine the TGFb pathway expression between matching pairs of tumor-free lung and NSCLC specimen RNA from patient samples was isolated to examine the TGFb pathway expression between matching pairs of tumor-free lung and NSCLC specimen
Project description:To identify genes encoding cell surface proteins that are preferentially expressed in NSCLC cells, CD45-CD31-EpCAM+ cells were purified by FACS from either tumor regions or unaffected regions in resected lung tissues from patients with NSCLC, then subjected to RNA sequencing analysis.
Project description:To identify genes encoding cell surface proteins that are preferentially expressed in NSCLC cells, CD45-CD31-EpCAM+ cells were purified by FACS from either tumor regions or unaffected regions in resected lung tissues from patients with NSCLC, then subjected to RNA sequencing analysis.
Project description:Lung cancer is the leading cause of cancer-related death worldwide, and non-small cell lung cancer (NSCLC) accounts for approximately 85% of lung cancers. Lymphatic metastasis serves as a predominant NSCLC metastatic route and an essential predictor of patient prognosis. Recently, circular RNA (circRNA) has emerged as critical mediator in various tumor initiation and progression. To identify essential circRNA that involves in the lymphatic metastasis of NSCLC, Next generation sequencing (NSG) was performed in 6 paired NSCLC tissues and normal adjacent tissues (NAT).
Project description:ost characterized tumor antigens are ‘genomic’, i.e. encoded by canonical, non-canonical or somatically mutated genomic sequences. We investigate here the presentation and immunogenicity of tumor antigens derived from non-canonical mRNA splicing events between coding exons and transposable elements (TEs). Comparing non-small cell lung cancer (NSCLC), an immunogenic tumor type, and diverse non-tumor tissues, we identify several thousand splicing junctions between exons and diverse TE classes. A subset of these junctions is both tumor-specific and shared across patients. HLA-I peptidomic identifies peptides encoded by tumor-specific junctions in primary NSCLC samples and lung tumor cell lines. Recurrent junction-encoded peptides are immunogenic in vitro and CD8+ T cells specific for junction-encoded epitopes are present in tumors and tumor-draining lymph nodes from NSCLC patients. We conclude that non-canonical splicing junctions between exons and TEs represent a source of recurrent, immunogenic tumor-specific antigens in NSCLC cancer patients.
Project description:Introduction: Macrophage phenotype in the tumor microenvironment correlates with prognosis in non-small cell lung cancer (NSCLC). Immunosuppressive macrophages promote tumor progression, while pro-inflammatory macrophages may drive an anti-tumor immune response. How individual NSCLCs impact macrophage phenotype is a major knowledge gap. Methods: To systematically study the impact of lung cancer cells on macrophage phenotypes, we developed an in vitro co-culture model comprised of molecularly and clinically-annotated patient-derived NSCLC lines, human cancer-associated fibroblasts, and murine macrophages. Induced macrophage phenotype was studied through qRT-PCR and validated in vivo using NSCLC xenografts through quantitative immunohistochemistry and clinically with TCGA “matched” patient tumors. Results: 72 NSCLC cell lines were studied. The most frequent highly induced macrophage-related gene was Arginase-1, reflecting an immunosuppressive M2-like phenotype. This was independent of multiple clinicopathologic factors, which also did not impact M2:M1 ratios in matched TCGA samples. In vivo, tumors established from high Arginase-1-inducing lines (Arghi) had a significantly elevated density of Arg1+ macrophages. Matched TCGA clinical samples to Arghi NSCLC lines had a significantly higher ratio of M2:M1 macrophages. Conclusions: In our preclinical model, a large panel of patient-derived NSCLC lines most frequently induced high expression Arginase-1 in co-cultured mouse macrophages, independent of major clinicopathologic and oncogenotype-related factors. Arghi cluster-matched TCGA tumors contained a higher ratio of M2:M1 macrophages. Thus, this preclinical model reproducibly characterizes how individual NSCLCs modulate macrophage phenotype, correlates with macrophage polarization in clinical samples, and can serve as an accessible platform for further investigation of macrophage-specific therapeutic strategies.