Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Molecular Classification and Prediction of Survival in Non-Small-Cell Lung Cancer

ABSTRACT: BACKGROUND: Global gene expression analysis provides a comprehensive molecular characterization of non-small cell lung cancer. The aim of this study was to evaluate the feasibility of integrating expression profiling into routine clinical work-up by including minute bronchoscopic biopsies and develop a robust prognostic gene expression signature METHODS: Tissue samples from a series of 41 chemotherapy-naïve non-small cell lung cancer patients and 15 control patients with inflammatory lung diseases were obtained during routine clinical work-up and gene expression profiles were gained using a highly sensitive oligonucleotide array platform (Novachip ; 34'207 transcripts). Gene expression signatures were analyzed by correlation with histological and clinical parameters and validated on independent published datasets and immunohistochemistry. RESULTS: Tumor tissue classification based on the gene expression results was strongly dependent on the proportion of tumor cells present in the biopsies and showed an overall sensitivity of 80% and specificity of 89%. For prognostication we developed a metagene consisting of 13 genes, which was validated on 4 independent published datasets. The robustness of this metagene has been demonstrated by a virtual independence from tumor cells present in the biopsies. Furthermore, vascular endothelial growth factor-beta, one of the key prognostic genes was validated by immunohistochemistry on 508 independent tumor samples. CONCLUSIONS: The proposed strategy of integrating functional genomics into routine clinical work-up allows molecular tumor classification and prediction of survival in patients with non-small cell lung cancer of all stages and is suitable for an integration in the daily clinical practice. Keywords: Gene expression profiling for disease state analysis in lung cancer patients 56 lung biopsies, 4 different Phenotypes: NSCLC-squa., NSCLC-NOS, NSCLC-Adeno, Ctr.-Infl.

ORGANISM(S): Homo sapiens

SUBMITTER: Wolfgang Budach

PROVIDER: E-GEOD-11117 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Gene profiling of clinical routine biopsies and prediction of survival in non-small cell lung cancer.

Baty Florent F Facompré Michaël M Kaiser Sergio S Schumacher Martin M Pless Miklos M Bubendorf Lukas L Savic Spasenija S Marrer Estelle E Budach Wolfgang W Buess Martin M Kehren Jeanne J Tamm Michael M Brutsche Martin H MH

American journal of respiratory and critical care medicine 20091015 2

<h4>Rationale</h4>Global gene expression analysis provides a comprehensive molecular characterization of non-small cell lung cancer (NSCLC).<h4>Objectives</h4>To evaluate the feasibility of integrating expression profiling into routine clinical work-up by including both surgical and minute bronchoscopic biopsies and to develop a robust prognostic gene expression signature.<h4>Methods</h4>Tissue samples from 41 chemotherapy-naive patients with NSCLC and 15 control patients with inflammatory lung ...[more]

PMID: 19833826

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Project description:The tumor microenvironment strongly influences cancer development, progression and metastasis. The role of carcinoma-associated fibroblasts (CAFs) in these processes and their clinical impact has not been studied systematically in non-small cell lung carcinoma (NSCLC). We established primary cultures of CAFs and matched normal fibroblasts (NFs) from 15 resected NSCLC. We demonstrate that CAFs have greater ability than NFs to enhance the tumorigenicity of lung cancer cell lines. Microarray gene expression analysis of the 15 matched CAF and NF cell lines identified 46 differentially expressed genes, encoding for proteins that are significantly enriched for extracellular proteins regulated by the TGF-beta signaling pathway. We have identified a subset of 11 genes that formed a prognostic gene expression signature, which was validated in multiple independent NSCLC microarray datasets. Functional annotation using protein-protein interaction analyses of these and published cancer stroma-associated gene expression changes revealed prominent involvement of the focal adhesion and MAPK signalling pathways. Fourteen (30%) of the 46 genes also were differentially expressed in laser-capture micro-dissected corresponding primary tumor stroma compared to the matched normal lung. Six of these 14 genes could be induced by TGF-beta1 in NF. The results establish the prognostic impact of CAF-associated gene expression changes in NSCLC patients. This SuperSeries is composed of the following subset Series: GSE22862: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [expression profiling_CAFs] GSE22863: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [expression profiling_NSCLC stroma] GSE27284: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [methylation profiling] GSE27289: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [genome variation profiling]

Dataset Information

Molecular Classification and Prediction of Survival in Non-Small-Cell Lung Cancer

Publications

Gene profiling of clinical routine biopsies and prediction of survival in non-small cell lung cancer.

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