Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA134849 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
2011-11-01 | E-GEOD-28582 | biostudies-arrayexpress
Project description:Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs (provisional dbGaP accession number; phs000299.v2.p1). Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers. Nineteen non-small cell lung cancer cell lines were assayed for genotype, copy number and LOH using Illumina Omni2.5-4 arrays, GenomeStudio V2011.1, and a modified version of the PICNIC (PMID 19837654) algorithm.
2012-09-26 | E-GEOD-40908 | biostudies-arrayexpress
Project description:Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (copy number data)
| PRJNA143019 | ENA
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.
2013-01-10 | E-GEOD-39793 | biostudies-arrayexpress
Project description:Lung cancer, of which more than 80% is non-small cell, is the leading cause of cancer-related death in the United States. Copy number alterations (CNAs) in lung cancer have been shown to be positionally clustered in certain genomic regions. However, it remains unclear whether genes with copy number changes are functionally clustered. Using a dense single nucleotide polymorphism array, we performed genome-wide copy number analyses of a large collection of non-small cell lung tumors (n = 301). We proposed a formal statistical test for CNAs between different groups (e.g., noninvolved lung vs. tumors, early vs. late stage tumors). We also customized the gene set enrichment analysis (GSEA) algorithm to investigate the overrepresentation of genes with CNAs in predefined biological pathways and gene sets (i.e., functional clustering). We found that CNAs events increase substantially from germline, early stage to late stage tumor. In addition to genomic position, CNAs tend to occur away from the gene locations, especially in germline, noninvolved tissue and early stage tumors. Such tendency decreases from germline to early stage and then to late stage tumors, suggesting a relaxation of selection during tumor progression. Furthermore, genes with CNAs in non-small cell lung tumors were enriched in certain gene sets and biological pathways that play crucial roles in oncogenesis and cancer progression, demonstrating the functional aspect of CNAs in the context of biological pathways that were overlooked previously. We conclude that CNAs increase with disease progression and CNAs are both positionally and functionally clustered. The potential functional capabilities acquired via CNAs may be sufficient for normal cells to transform into malignant cells. Copy number analysis was performed on 301 non-small cell lung cancer tumor samples using Affymetrix 250K Nsp GeneChip
2011-12-06 | E-GEOD-34140 | biostudies-arrayexpress
Project description:Copy number analysis of KAT6B gene deletion in small cell lung cancer cell lines
2015-10-07 | GSE62773 | GEO
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.
2021-11-24 | PXD016579 | Pride
Project description:Non-small cell lung cancer (NSCLC) presents a notoriously genomically unstable cancer type, with numerous large scale and focal genomic aberrations resulting in gene copy number variations across the whole genome. The relations of these gene copy number changes to subsequent mRNA levels are only fragmentarily understood. The aim of this study was an integrated analysis of gene copy number changes and corresponding gene expression in a large clinically annotated NSCLC patient cohort. Fresh frozen tumor sample from 190 resected NSCLC patients were subjected to SNP arrays and gene expression array analysis resulting 39788 tested copy number/ RNA expression pairs. Correlation analysis using an externally centered correlation coefficient (ECCC) revealed that gene expression of 19058 genes was significantly influenced by gene copy number changes (FDR < 0.05). However, only 440 probe sets demonstrated high correlations (ECCC > 0.7) that were mostly due to few cases with high gene copy number gains. These gene copy number dependent genes were clustered in only few chromosomal hot spot regions and classical oncogenes (e.g. EGFR, MDM2, KRAS) are overrepresented among these genes. In a meta-analysis, including 1585 NSCLC patients, gene expression levels from 70 of 440 (16%) gene-copy-number-dependent genes were associated with survival. In conclusion, the genome-wide analysis indicates that gene copy number aberrations influence directly gene expression levels in a distinct subset of genes. The concrete illustration of these molecular relations help to interpret the impact of gene copy number changes and may serve as starting points to identify new cancer drivers in NSCLC.
2016-08-31 | GSE76730 | GEO
Project description:DNA copy number profiling of lung adenocarcinomas and patient-matched non-malignant lung
| PRJNA579164 | ENA