Gene Signatures Predict Outcome in Prostate Cancer

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Gene Signatures Predict Outcome in Prostate Cancer
Gene Signatures Predict Outcome in Prostate Cancer

(HealthDay News) -- Gene expression signatures can identify men with low- or high-risk advanced prostate cancer, according to two studies published online Oct. 9 in The Lancet Oncology.

Robert W. Ross, M.D., from Harvard Medical School in Boston, and colleagues analyzed RNA transcripts in 62 men with castration-resistant prostate cancer to assess the effectiveness of a whole-blood RNA transcript-based model as a prognostic biomarker. The researchers identified a six-gene signature identifying a low-risk group with a median survival of more than 34.9 months and a high-risk group with a median survival of 7.8 months, which was confirmed in an independent set of 140 patients.

David Olmos, M.D., from the Royal Marsden National Health Service Foundation Trust in Sutton, U.K., and colleagues analyzed blood mRNA expression arrays to identify the prognostic outcome for patients with metastatic castration-resistant prostate cancer. Based on latent process decomposition (LPD) analyses of mRNA expression data, the researchers divided the evaluable patients into four groups. The LPD1 subgroup correlated with the worse prognosis and poorer overall survival compared with other LPD subgroups (10.7 versus 25.6 months). A nine-gene signature classified patients into this subgroup with a low percentage of misclassification. The prognostic utility of this signature was confirmed in a validation cohort and LPD1 remained an independent prognostic factor correlating with worse overall survival.

"[These results] suggest that transcript levels of a few selected genes in blood samples from patients with castration-resistant prostate cancer can improve outcome prediction significantly," writes the author of an accompanying editorial.

Several authors from the Ross study disclosed financial ties to Source MDx, which funded the study. The Olmos study was partially funded by AstraZeneca.

Abstract - Ross

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Abstract - Olmos

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