Prostate cancer stratification using molecular profiles [CamCap genotype first set]

ABSTRACT: Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behavior, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups wit

ORGANISM(S): Homo sapiens

SUBMITTER: Chandra Chilamakuri 

PROVIDER: E-GEOD-71965 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress