Transcription profiling of human stage IB lung adenocarcinomas and large cell carcinomas to predict outcomes (Merlion lung cancer study)
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Philippe Broët
PROVIDER: E-GEOD-10445 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Series of stage IB lung adenocarcinomas and large cell carcinomas. The aim of the study was to predict outcome using a Copy Number Driven Gene Expression signature. Keywords: disease state analysis, stage I lung cancer
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Project description:Lung cancer is still the leading cause of cancer-related deaths in the US and worldwide. Understanding the global molecular profiles or transcriptome of lung cancers would strengthen our understanding of the biology of this malignancy. We performed gene expression profiling using the Human Gene 1.0 ST platform of 80 lung adenocarcinomas and 30 normal lung tissues to better understand the biology of this significant fraction of non-small cell lung carcinomas (NSCLCs) Lung adenocarcinomas were comrpised of never-smoker (n=40) and smoker (n=40) adenocarcinomas. Normal lung tissue (n=30) were paired to 30 of the never-smoker cases. Gene expression profiling was performed on the samples to identify differentially expressed profiles between lung adenocarcinomas and normal lung tissues.
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Project description:Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, however, not all lung cancers can be attributable to smoking. The genetic aberrations that differ between smokers' and never-smokers’ lung carcinomas remain to a large extent unclear. We analyzed 72 early-stage primary lung carcinomas including small cell lung cancers LCNEC, adenocarcinomas and squamous cell carcinomas by Illumina HT12 gene expression microarrays.
2012-05-17 | GSE29016 | GEO
Project description:Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, however, not all lung cancers can be attributable to smoking. The genetic aberrations that differ between smokers' and never-smokersM-bM-^@M-^Y lung carcinomas remain to a large extent unclear. We analyzed 72 early-stage primary lung carcinomas including small cell lung cancers, adenocarcinomas and squamous cell carcinomas by Illumina HT12 gene expression microarrays. Gene expression profiling of 72 lung carcinomas using Illumina HT-12 V3.0 microarrays.
2012-05-16 | E-GEOD-29016 | biostudies-arrayexpress
Project description:Lung cancer is still the leading cause of cancer-related deaths in the US and worldwide. Understanding the global molecular profiles or transcriptome of lung cancers would strengthen our understanding of the biology of this malignancy. We performed gene expression profiling using the Human Gene 1.0 ST platform of 80 lung adenocarcinomas and 30 normal lung tissues to better understand the biology of this significant fraction of non-small cell lung carcinomas (NSCLCs)
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Project description:Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. Experimental Design Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 12 normal lung tissues and 124 tumors including 83 adenocarcinomas, 23 squamous cell carcinomas (SqCC), one adenosquamous cancer, five large cell carcinomas, nine large cell neuroendocrine carcinomas (LCNEC), and three small cell carcinomas (SCLC). Complimentary gene expression analyses was performed on 117 of the 124 tumors using Illumina HT12 V4 arrays (reported here). Gene expression profiling of 117 lung carcinomas using Illumina HT-12 V4 microarrays.
2014-10-05 | E-GEOD-60644 | biostudies-arrayexpress
Project description:Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. Experimental Design Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 12 normal lung tissues and 124 tumors including 83 adenocarcinomas, 23 squamous cell carcinomas (SqCC), one adenosquamous cancer, five large cell carcinomas, nine large cell neuroendocrine carcinomas (LCNEC), and three small cell carcinomas (SCLC). Complimentary gene expression analyses was performed on 117 of the 124 tumors using Illumina HT12 V4 arrays (reported here).
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Project description:Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. So far, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer which account for 20% and 80% of lung carcinomas, respectively. While SCLCs express properties of neuroendocrine cells, NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. A contamination of the tumor sample with normal epithelia, blood vessels, stromal cells, leucocytes and tumor necrosis may confound the true expression profile of the tumor. The use of laser capture microdissection (LCM) greatly improves the sample preparation for microarray expression analysis. Consequently, we used advanced technology including LCM and microarray analysis. In detail, we examined gene expression profiles of tumor cells from 29 previously untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), 9 small cell lung cancer (SCLC)) in comparison to normal lung tissue (LT) of 5 control patients without tumor. Bronchoscopical biopsies from the primary lung tumor were taken before treatment. Biopsies were cut into 8µm sections and from each section cancer cells were isolated using laser capture microdissection in order to obtain pure samples of tumor cells. Total RNA was extracted, reversely transcribed, in-vitro transcribed, labelled and hybridized to the array. For expression analysis, microarrays covering 8793 defined genes (Human HG Focus Array, Affymetrix) were used. Following quality control, array data were normalized and analysed for significant differences using variance stabilizing transformation (VSN) and significance analysis of microarrays (SAM), respectively. Based on differentially expressed genes cancer samples could be clearly separated from non cancer samples using hierarchical clustering. Comparing AC, SCC and SCLC with normal lung tissue, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed with an estimated false discovery rate < 2.6%. Each histological subtype showed a distinct expression profile. Further, using a genetic programming approach we constructed a classificator to discriminate AC, SCC, NT and SCLC. To this end, the 50 genes with the greatest signal-to-noise ratio were selected to train the classificator. By leave-one-out cross validation all 34 samples were correctly classified in this training set. In order to validate the 50-gene-classificator on a test set, further 13 microdissected lung cancer samples were used and correctly classified in concordance to pathologic finding. In conclusion, the different lung cancer subtypes have distinct molecular phenotypes which reflect biological characteristics of the tumor cells and which might be the basis for development of targeted therapy. Moreover, gene expression profiling and genetic programming is a suitable tool for classification and discrimination of different histological subtypes in lung cancer in comparison to normal lung tissue. Experiment Overall Design: Comparison of gene expression profiles of normal lung tissues, adenocarcinomas, squamous cell carcinomas and small cell lung cancers.
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