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Methods: We apply an unsupervised model called Latent Process Decomposition (LPD), which can handle heterogeneity within cancer samples, to genome-wide expression data from eight prostate cancer clinical series including 1,785 malignant samples with the clinical endpoints of PSA failure and metastasis.
Results: We show that PSA failure is correlated with the level of an expression signature called DESNT (HR = 1.52, 95% CI = [1.36, 1.7], P = 9.0x10-14, Cox model) and that patients with a majority DESNT signature have an increased metastasic risk (X2-test, P = 0.0017, and P = 0.0019). Additionally, we develop a stratification framework that incorporates DESNT and identifies three novel molecular subtypes of prostate cancer.
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- 1 Finished
1/06/15 → 31/05/18