ABSTRACT: Expression data of different histological subgroups of non-small cell lung cancer in two patient populations with different survival outcomes
Project description: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:We report RNAseq data from two independent mouse syngeneic lung cancer cell lines LLC and UN-SCC679 in an altered DSTYK context Lung cancer remains the leading cause of cancer-related death worldwide. We identify DSTYK, a dual serine/threonine and tyrosine non-receptor protein kinase, as a novel actionable target altered in non-small cell lung cancer (NSCLC). We also show DSTYK´s association with a lower overall survival (OS) and poorer progression-free survival (PFS) in multiple patient cohorts. To ascertain the potential molecular carcinogenesis processes in which DSTYK was involved, we performed an RNAseq analysis of two different lung cancer cell lines with either overexpressed or inhibited DSTYK. Inhibition was achieved through shRNA technology. These cell lines were cultured in RPMI 1640 supplemented with 10% Fetalclone (Thermo Fisher Scientific) and 100 U/mL penicillin-100 µg/mL streptomycin (Thermo Fisher Scientific). All cells were grown in a humidified incubator containing 5% CO2 at 37°C. Cell lines were routinely tested for mycoplasma.
Project description:This SuperSeries is composed of the following subset Series: GSE28571: Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (expression data) GSE28572: Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (copy number data) Refer to individual Series
Project description:Small Cell Lung Cancer (SCLC) tumors are made up of distinct cell subpopulations, including neuroendocrine (NE) and non-NE cells. Proteomic analysis of purified small extracellular vesicles (EV) from these two cell populations were conducted.
Project description:131 patient-derived xenograft models were generated for non-small cell lung carcinoma and were profiled by analysis of gene copy number variation, whole exome sequence, methylome, transcriptome, proteome, and phospho(Tyr)-proteome. Proteome profiling resolved the known major histology subtypes and revealed 3 proteome subtypes (proteotypes) among adenocarcinoma and 2 in squamous cell carcinoma that were associated with distinct protein-phosphotyrosine signatures and patient survival. Proteomes of human tumor were discernible from murine stroma. Stromal proteomes were similar between histological subtypes, but two adenocarcinoma proteotypes had distinct stromal proteomes. Tumor and stromal proteotypes comprise signatures of targetable biological pathways suggesting that patient stratification by proteome profiling may be an actionable approach to precisely diagnose and treat cancer.