Gene expression profiling predicts clinical outcome of prostate cancer Journal Article
| Authors: | Glinsky, G. V.; Glinskii, A. B.; Stephenson, A. J.; Hoffman, R. M.; Gerald, W. L. |
| Article Title: | Gene expression profiling predicts clinical outcome of prostate cancer |
| Abstract: | One of the major problems in management of prostate cancer is the lack of reliable genetic markers predicting the clinical course of the disease. We analyzed expression profiles of 12,625 transcripts in prostate tumors from patients with distinct clinical outcomes after therapy as well as metastatic human prostate cancer xenografts in nude mice. We identified small clusters of genes discriminating recurrent versus nonrecurrent disease with 90% and 75% accuracy in two independent cohorts of patients. We examined one group of samples (21 tumors) to discover the recurrence predictor genes and then validated the predictive power of these genes in a different set (79 tumors). Kaplan-Meier analysis demonstrated that recurrence predictor signatures are highly informative (P < 0.0001) in stratification of patients into subgroups with distinct relapse-free survival alter therapy. A gene expression-based recurrence predictor algorithm was informative in predicting the outcome in patients with early-stage disease, with either high or low preoperative prostate-specific antigen levels and provided additional value to the outcome prediction based on Gleason sum or multiparameter nomogram. Overall, 88% of patients with recurrence of prostate cancer within 1 year alter therapy were correctly classified into the poor-prognosis group. The identified algorithm provides additional predictive value over conventional markers of outcome and appears suitable for stratification of prostate cancer patients at the time of diagnosis into subgroups with distinct survival probability after therapy. |
| Keywords: | cancer survival; controlled study; survival analysis; human cell; major clinical study; disease course; nonhuman; validation process; prostate specific antigen; accuracy; biological markers; mouse; animals; mice; gene expression; gene expression profiling; animal experiment; animal model; cohort analysis; relapse; genetic transcription; algorithms; prostate cancer; prostatic neoplasms; xenograft; algorithm; nucleotide sequence; neoplasm metastasis; reliability; kaplan meier method; genetic marker; disease activity; humans; prognosis; human; male; priority journal; article |
| Journal Title: | Journal of Clinical Investigation |
| Volume: | 113 |
| Issue: | 6 |
| ISSN: | 0021-9738 |
| Publisher: | American Society for Clinical Investigation |
| Date Published: | 2004-03-01 |
| Start Page: | 913 |
| End Page: | 923 |
| Language: | English |
| DOI: | 10.1172/jci200420032 |
| PROVIDER: | scopus |
| PMCID: | PMC362118 |
| PUBMED: | 15067324 |
| DOI/URL: | |
| Notes: | J. Clin. Invest. -- Cited By (since 1996):239 -- Export Date: 16 June 2014 -- CODEN: JCINA -- Molecular Sequence Numbers: GENBANK: AB007945, AB014554, AF001461, D26070, L20861, M92843, S81914, U20979, U90904, V01512, X51345, X58840, Y16521; -- Source: Scopus |
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