DNA copy number and gene expression profiles of resected non-small cell lung cancer tumors
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE31800 | GEO | 2011/09/12
SECONDARY ACCESSION(S): PRJNA145473
REPOSITORIES: GEO
Similar Datasets
Project description:This SuperSeries is composed of the following subset Series: GSE31798: DNA copy number profiles of NSCLC tumors GSE31799: Gene expression profiles of NSCLC tumors Refer to individual Series
2011-09-11 | E-GEOD-31800 | biostudies-arrayexpress
Project description:Lung cancer is one of the leading causes of cancer mortality worldwide and non-small cell lung cancer (NSCLC) accounts for the most part. NSCLC can be further divided into adenocarcinoma (ACA) and squamous cell carcinoma (SCC). It is of great value to distinguish these two subgroups clinically. In this study, we compared the genome-wide copy number alterations (CNAs) patterns of 208 early stage ACA and 93 early stage SCC tumor samples. As a result, 266 CNA probes stood out for better discrimination of ACA and SCC. It was revealed that the genes corresponding to these 266 probes were enriched in lung cancer related pathways and enriched in the chromosome regions where CNA usually occur in lung cancer. This study sheds lights on the CNA study of NSCLC and provides some insights on the epigenetic of NSCLC.
| S-EPMC3914971 | biostudies-literature
Project description:Integrative analysis of multi-level molecular profiles can distinguish interactions that cannot be revealed based on one kind of data in the analysis of cancer susceptibility and metastasis. DNA copy number variations (CNVs) are common in cancer cells, and their role in cell behaviors and relationship to gene expression (GE) is poorly understood. An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE. This study presents a novel framework to identify important genes and construct potential regulatory networks based on these genes. Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed. Specifically, this approach contains the following steps: (1) select a pool of candidate driver genes, which have significant CNV in lung cancer patient tumors or have a significant association with the clinical outcome at the transcriptional level; (2) rank important driver genes in lung cancer patients with good prognosis and poor prognosis, respectively, and use top-ranked driver genes to construct regulatory networks with the COpy Number and EXpression In Cancer (CONEXIC) method; (3) identify experimentally confirmed molecular interactions in the constructed regulatory networks using Ingenuity Pathway Analysis (IPA); and (4) visualize the refined regulatory networks with the software package Genatomy. The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.
| S-EPMC4218678 | biostudies-literature
Project description:Study aims: to identify critical genes involved in non-small cell lung cancer (NSCLC) pathogenesis that may lead to a more complete understanding of this disease and identify novel molecular targets for use in the development of more effective therapies. Methods: Both transcriptional and genomic profiling were performed on 69 resected NSCLC specimens and results correlated with mutational analyses and clinical data to identify genetic alterations associated with groups of interest. Results: Combined analyses identified specific patterns of genetic alteration associated with adenocarcinoma vs. squamous differentiation; KRAS mutation; TP53 mutation, metastatic potential and disease recurrence and survival. Amplification of 3q was associated with mutations in TP53 in adenocarcinoma. A prognostic signature for disease recurrence, reflecting KRAS pathway activation, was validated in an independent test set. Conclusions: These results may provide the first steps in identifying new predictive biomarkers and targets for novel therapies, thus improving outcomes for patients with this deadly disease. Transcriptional profiling of 82 samples of NSCLC using Peter MacCallum in-house 10,500 element cDNA microarray. RNA from 11 pooled cell lines used as reference for each sample. Replicate of 6 samples included.
| S-ECPF-GEOD-25326 | biostudies-other
Project description:SummarySelecting the optimal cancer cell line for an experiment can be challenging given the diversity of lines available. Here, we present CNpare, which identifies similar cell line models based on genome-wide DNA copy number.AvailabilityCNpare is available as an R package at https://github.com/macintyrelab/CNpare. All analysis performed in the manuscript can be reproduced via the code found at https://github.com/macintyrelab/CNpare_analyses.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9272807 | biostudies-literature
Project description:BACKGROUND: The aim of this study was to identify critical genes involved in non-small cell lung cancer (NSCLC) pathogenesis that may lead to a more complete understanding of this disease and identify novel molecular targets for use in the development of more effective therapies. METHODS: Both transcriptional and genomic profiling were performed on 69 resected NSCLC specimens and results correlated with mutational analyses and clinical data to identify genetic alterations associated with groups of interest. RESULTS: Combined analyses identified specific patterns of genetic alteration associated with adenocarcinoma vs. squamous differentiation; KRAS mutation; TP53 mutation, metastatic potential and disease recurrence and survival. Amplification of 3q was associated with mutations in TP53 in adenocarcinoma. A prognostic signature for disease recurrence, reflecting KRAS pathway activation, was validated in an independent test set. CONCLUSIONS: These results may provide the first steps in identifying new predictive biomarkers and targets for novel therapies, thus improving outcomes for patients with this deadly disease.
| S-EPMC3058106 | biostudies-literature
Project description:ObjectiveWe aimed to assess MET intratumoral heterogeneity and its potential impact on biomarker-based patient selection as well as potential surrogate biomarkers of MET activation.MethodsOur study included 120 patients with non-squamous Non-small-cell Lung Cancer (nsNSCLC), of which 47 were incorporated in tissue microarrays (TMA). Four morphologically distinct tumor areas were selected to assess MET heterogeneity. MET positivity by immunohistochemistry (IHC) was defined as an above-median H-score and by +2/+3 staining intensity in >50% of tumor cells (Metmab criteria). MET FISH positivity was defined by MET/CEP7 ratio ≥ 2.0 and/or MET ≥ 5.0. MET staining pattern (cytoplasmic vs. membranous) and mesenchymal markers were investigated as surrogates of MET activation.ResultsMedian MET H-score was 140 (range 0-400) and 47.8% of patients were MET positive by Metmab criteria. Eight cases (6.8%) were MET FISH positive and showed higher H-scores (p = 0.021). MET positivity by IHC changed in up to 40% of cases among different tumor areas, and MET amplification in 25-50%. Cytoplasmic MET staining and positivity for vimentin predicted poor survival (p = 0.042 and 0.047, respectively).ConclusionsMET status is highly heterogeneous among different nsNSCLC tumor areas, hindering adequate patient selection for MET-targeted therapies. MET cytoplasmic staining and vimentin might represent surrogate markers for MET activation.
| S-EPMC4599265 | biostudies-literature
Project description:Background: Lung cancer has the highest mortality rate of all the cancers in the world and asbestos-related lung cancer is one of the leading occupational cancers. The identification of the asbestos-related molecular changes has been a topic of major research interest over the years. The aim of the current study was to identify novel asbestos-related molecular correlates by integrating miRNA expression profiling with previously obtained microarray data (aCGH and mRNA expression) from the same patient material. Results: Twelve novel asbestos-related miRNAs (over-expressed: miR-148b, miR-374a, miR-24-1*, Let-7d, Let-7e, miR-199b-5p, miR-331-3p and under-expressed: miR-939, miR-671-5p, miR-605, miR-1224-5p, miR-202) which inversely correlated with target genes (e.g. GADD45A, LTBP1, FOSB, NCALD, CACNA2D2, MTSS1, EPB41L3) were identified. In addition, several known and new lung cancer-associated miRNAs were identified. DNA copy number alterations were also correlated with the deregulation of four miRNAs in lung cancer. The importance of integrated analysis was highlighted by the interesting finding of linking of the over-expression of well known squamous cell carcinoma-associated miR-205 with the down-regulation of the gene DOK4. Conclusions: Novel deregulated miRNAs and inversely correlating expression of target genes associated with lung cancer etiology and histology were identified. In addition, DNA copy number alterations correlated with the deregulation of some of the miRNAs. The results of the current study could have potential diagnostic implications, but require further investigation. Methods: The patient material used in the study consisted of 26 tumour and normal lung tissue from highly asbestos-exposed (13 samples) and non-exposed (13 samples) patients. Control lung tissue samples were obtained from 7 patients without cancer as well as from a commercial lung tissue RNA. Data analysis on miRNA expression and integration of miRNA and mRNA data were performed using Chipster (http://chipster.csc.fi/). In addition, miRNA and aCGH data were integrated in a separate analysis. *** This submission represents the microRNA component of the study
| S-ECPF-GEOD-25508 | biostudies-other
Project description:BackgroundThe prognostic value of the copy number (GCN) and protein expression of the mesenchymal-epithelial transition (MET) gene for survival of patients with non-small cell lung cancer (NSCLC) remains controversial. This study aims to comprehensively and quantitatively asses the suitability of MET GCN and protein expression to predict patients' survival.MethodsPubMed, Embase, Web of Science and Google Scholar were searched for articles comparing overall survival in patients with high MET GCN or protein expression with those with low level. Pooled hazard ratio (HR) and 95% confidence intervals (CIs) were calculated using the random and the fixed-effects models. Subgroup and sensitivity analyses were also performed.ResultsEighteen eligible studies enrolling 5,516 patients were identified. Pooled analyses revealed that high MET GCN or protein expression was associated with poor overall survival (OS) (GCN: HR = 1.90, 95% CI 1.35-2.68, p<0.001; protein expression: HR = 1.52, 95% CI 1.08-2.15, p = 0.017). In Asian populations (GCN: HR = 2.22, 95% CI 1.46-3.38, p<0.001; protein expression: HR = 1.89, 95% CI 1.34-2.68, p<0.001), but not in the non-Asian subset. For adenocarcinoma, high MET GCN or protein expression indicated decreased OS (GCN: HR = 1.49, 95% CI 1.05-2.10, p = 0.025; protein expression: HR = 1.69, 95% CI 1.31-2.19, p<0.001). Results were similar for multivariate analysis (GCN: HR = 1.61, 95% CI 1.15-2.25, p = 0.005; protein expression: HR = 2.18, 95% CI 1.60-2.97, p<0.001). The results of the sensitivity analysis were not materially altered and did not draw different conclusions.ConclusionsIncreased MET GCN or protein expression was significantly associated with poorer survival in patients with surgically resected NSCLC; this information could potentially further stratify patients in clinical treatment.
| S-EPMC4055667 | biostudies-literature
Project description:Whole genome tiling path array CGH was used to measure the copy number profiles of 271 NSCLC tumors
2011-09-12 | GSE31798 | GEO