Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling by array on 123 paired tumor and non-tumor tissue samples from patients with non-small cell lung carcinoma to gain a systems biology insight into the current clinical classification


ABSTRACT: Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The aim of this study was to gain a systems biology insight into the current clinical classification. Patients and Methods: Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Using integrated systems biology approaches, we sought to find out if combining data types from different levels of biology would improve clinical assessment of NSCLC. Results: At both DNA, RNA and miRNA levels we could identify molecular markers that discriminated significantly between the various clinicopathological entities of NSCLC. Conclusions: We report proofs of distinct molecular profiles that contribute to distinguishing NSCLC tumor subtypes even in small biopsies. The Gene expression experiments have been made in dual color and dye_swap with Agilent human Human Genome Exon 244K arrays (custom design 14891, from commercial 4x44K (design 014850 plus 195000 oligo - 1 per exon- defined with RefSeq hg18 and 1840 probes from viral transcripts). Note date of surgery is the date of the sample was frozen.

ORGANISM(S): Homo sapiens

DISEASE(S): normal

SUBMITTER: Philippe DESSEN 

PROVIDER: E-MTAB-1132 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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<h4>Background</h4>Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC.<h4>Methods</h4>Comparative geno  ...[more]

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