a strategy for full interrogation of prognostic gene expression patterns exploring the biology of diffuse large b cell lymphoma审讯的预后基因表达模式的策略探索弥漫性大b细胞淋巴瘤的生物学.pdfVIP

A Strategy for Full Interrogation of Prognostic Gene Expression Patterns: Exploring the Biology of Diffuse Large B Cell Lymphoma 1 2 1 2 Lisa M. Rimsza *, Joseph M. Unger , Margaret E. Tome , Michael L. LeBlanc 1 Department of Pathology, University of Arizona, Tucson, Arizona, United States of America, 2 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America Abstract Background: Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL). Often, data are analyzed with genes classified by whether they fall above or below the median expression level. We sought to determine whether examining multiple cut- points might be a more powerful technique to investigate the association of gene expression with outcome. Methodology/Principal Findings: We explored gene expression profiling data using variable cut-point analysis for 36 genes with reported prognostic value in DLBCL. We plotted two-group survival logrank test statistics against corresponding cut- points of the gene expression levels and smooth estimates of the hazard ratio of death versus gene expression levels. To facilitate comparisons we also standardized the expression of each of the genes by the fraction of patients that would be identified by any cut-point. A multiple comparison adjusted permutation p-value identified 3 different patterns of significance: 1) genes with significant cut-point points below the median, whose loss is associated with poor outcome (e.g. HLA-DR); 2) genes with significant cut-points above the median, whose over-expression is associated with poor outc