Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

CaArray_beer-00153: Gene-expression profiles predict survival of patients with lung adenocarcinoma

ABSTRACT: Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy. beer-00153 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Disease States: lung cancer, normal

ORGANISM(S): Homo sapiens

SUBMITTER: Mervi Heiskanen

PROVIDER: E-GEOD-68571 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Gene-expression profiles predict survival of patients with lung adenocarcinoma.

Beer David G DG Kardia Sharon L R SL Huang Chiang-Ching CC Giordano Thomas J TJ Levin Albert M AM Misek David E DE Lin Lin L Chen Guoan G Gharib Tarek G TG Thomas Dafydd G DG Lizyness Michelle L ML Kuick Rork R Hayasaka Satoru S Taylor Jeremy M G JM Iannettoni Mark D MD Orringer Mark B MB Hanash Samir S

Nature medicine 20020715 8

Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 g ...[more]

PMID: 12118244

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Project description:A key step in bringing gene expression data into clinical practice is the conduct of large studies to confirm preliminary models. The performance of such confirmatory studies and the transition to clinical practice requires that microarray data from different laboratories are comparable and reproducible. We designed a study to assess the comparability of data from four laboratories that will conduct a larger microarray profiling confirmation project in lung adenocarcinomas. To test the feasibility of combining data across laboratories, frozen tumor tissues, cell line pellets, and purified RNA samples were analyzed at each of the four laboratories. Samples of each type and several subsamples from each tumor and each cell line were blinded before being distributed. The laboratories followed a common protocol for all steps of tissue processing, RNA extraction, and microarray analysis using Affymetrix Human Genome U133A arrays. High within-laboratory and between-laboratory correlations were observed on the purified RNA samples, the cell lines, and the frozen tumor tissues. Intraclass correlation within laboratories was only slightly stronger than between laboratories, and the intraclass correlation tended to be weakest for genes expressed at low levels and showing small variation. Finally, hierarchical cluster analysis revealed that the repeated samples clustered together regardless of the laboratory in which the experiments were done. The findings indicate that under properly controlled conditions it is feasible to perform complete tumor microarray analysis, from tissue processing to hybridization and scanning, at multiple independent laboratories for a single study. dobbi-00100 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133A Organism: Homo sapiens (ncbitax) Tissue Sites: Kidney, Lung, Stomach, Uterus, Liver, Lymphoid tissue, Ovary, Skin, Adrenal Gland, Lymph_Node Material Types: cell, nuclear_RNA, synthetic_RNA, organism_part, total_RNA Disease States: Recurrent Renal Cell Carcinoma, Squamous Cell Carcinoma,Conventional_Clear_Cell_Renal_Cell_Carcinoma,Gastrointestinal_Stromal_Tumor, Lung_Adenocarcinoma, Leiomyoma, Non neoplastic liver with cirrosis, Stomach Adenocarcinoma, Large Cell Lymphoma, Ovarian Adenocarcinoma, Melanoma, Malignant G1 Stromal Tumor, Adrenal Cortical Adenoma, Metastatic Renal Cell Carcinoma, Malignant Melanoma

Dataset Information

CaArray_beer-00153: Gene-expression profiles predict survival of patients with lung adenocarcinoma

Publications

Gene-expression profiles predict survival of patients with lung adenocarcinoma.

Similar Datasets

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