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MicroRNA-regulated transcriptome analysis identifies four major subtypes with prognostic and therapeutic implications in prostate cancer.

Authors :
Lin BB
Lei HQ
Xiong HY
Fu X
Shi F
Yang XW
Yang YF
Liao GL
Feng YP
Jiang DG
Pang J
Source :
Computational and structural biotechnology journal [Comput Struct Biotechnol J] 2021 Aug 31; Vol. 19, pp. 4941-4953. Date of Electronic Publication: 2021 Aug 31 (Print Publication: 2021).
Publication Year :
2021

Abstract

MicroRNA (miRNA) deregulation plays a critical role in the heterogeneous development of prostate cancer (PCa) by tuning mRNA levels. Herein, we aimed to characterize the molecular features of PCa by clustering the miRNA-regulated transcriptome with non-negative matrix factorization. Using 478 PCa samples from The Cancer Genome Atlas, four molecular subtypes (S-I, S-II, S-III, and S-IV) were identified and validated in two merged microarray and RNAseq datasets with 656 and 252 samples, respectively. Interestingly, the four subtypes showed distinct clinical and biological features after comprehensive analyses of clinical features, multiomic profiles, immune infiltration, and drug sensitivity. S-I is basal/stem/mesenchymal-like and immune-excluded with marked transforming growth factor β , epithelial-mesenchymal transition and hypoxia signals, increased sensitivity to olaparib, and intermediate prognosis. S-II is luminal/metabolism-active and responsive to androgen deprivation therapy with frequent TMPRSS2-ERG fusion and a good prognosis. S-III is characterized by moderate proliferative and metabolic activity, sensitivity to taxane-based chemotherapy, and intermediate prognosis. S-IV is highly proliferative with moderate EMT and stemness, frequent deletions of TP53 , PTEN and RB , and the poorest prognosis; it is also immune-inflamed and sensitive to anti-PD-L1 therapy. Overall, based on miRNA-regulated gene profiles, this study identified four distinct PCa subtypes that could improve risk stratification at diagnosis and provide therapeutic guidance.<br /> (© 2021 The Author(s).)

Details

Language :
English
ISSN :
2001-0370
Volume :
19
Database :
MEDLINE
Journal :
Computational and structural biotechnology journal
Publication Type :
Academic Journal
Accession number :
34527198
Full Text :
https://doi.org/10.1016/j.csbj.2021.08.046