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Gene expression of samples derived from normal lung and patients with small cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC)

ABSTRACT: Differences in gene expression profiles regarding the expression of genes encoding for proteins with G protein-coupled receptor (GPCR) activity between SCLC and NSCLC and normal lung samples was successfully examined.

ORGANISM(S): Homo sapiens

PROVIDER: GSE40275 | GEO | 2012/08/25

SECONDARY ACCESSION(S): PRJNA173724

REPOSITORIES: GEO

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Gene expression of samples derived from normal lung and patients with small cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC)

Project description:Differences in gene expression profiles regarding the expression of genes encoding for proteins with G protein-coupled receptor (GPCR) activity between SCLC and NSCLC and normal lung samples was successfully examined. In the present study, 8 SCLC, 16 NSCLC and 14 normal lung RNA samples (human) had been purchased from OriGene Technologies. Gene expression analysis was performed using Affymetrix microarrays (Human Exon 1.0 ST Array).

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Selective Loss of RB in Resistant EGFR Mutant Lung Adenocarcinomas that Transform to SCLC [CGH]

Project description:The study was designed to identify the molecular changes that occur in EGFR mutant NSCLCs that become resistant to TKI by transforming to SCLC. Tyrosine kinase inhibitors (TKIs) are effective treatments for non-small cell lung cancers (NSCLCs) with epidermal growth factor receptor (EGFR) mutations. However, they do not lead to cures, and, on average, relapse occurs after one year of continuous treatment. In a subset of patients, a fundamental histological transformation from NSCLC to small cell lung cancer (SCLC) is observed in the resistant cancers, but the molecular changes associated with this transformation remain unknown. Analysis of a cohort of tumor samples and cell lines derived from resistant EGFR mutant patients with SCLC transformation revealed that RB is lost in 100% of these cases, but rarely in those that remain NSCLC. Global changes in gene expression, including increased neuroendocrine marker expression and absence of EGFR expression, are observed in cancers that transformed to SCLC. Consistent with their genetic and epigenetic similarities to classical SCLC, cell lines derived from resistant EGFR mutant SCLC biopsies are substantially more sensitive to ABT-263 treatment compared to those derived from resistant EGFR mutant NSCLCs. Together, these findings suggest that despite developing initially as EGFR mutant adenocarcinomas, this subset of resistant cancers ultimately take on many of the molecular and phenotypic characteristics of classical SCLC. Overall, we completed array CGH analysis on 4 tumor specimens from EGFR mutant, TKI-resistant patients. Three of these samples had transformed to SCLC and one remained NSCLC.

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Project description:Small cell lungcancer (SCLC) is an aggressive malignancy with dismal clinical outcomes, due inpart to the scarcity of post-relapse tissue samples. To understand more of transcriptional changes associated with treatment resistance, we performed RNAseq analysis of 61 SCLC cell lines.

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The RNAseq of 79 small cell lung cancer (sclc) and 7 normal control

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Project description:Objectives: Small cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based biomarker classifier to assist in SCLC diagnoses. Materials and Methods: We profiled deregulated circulating cell-free miRNA in the plasma of SCLC patients. We tested selected miRs on a training cohort and created a classifier by integrating miRNA expression and patient clinical data. Finally, we applied the classifier on a validation dataset. Results: We determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group. Conclusion: This study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.

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Project description:This study assessed tumor suppressor roles of CREBBP in SCLC and other neuroendocrine tumors. Genetically engineered mouse models were used to determine the tumor suppressor role of Crebbp in SCLC and other neuroendocrine tumors.

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