Frontiers in Genetics (Jan 2021)

Gene Expression Changes and Associated Pathways Involved in the Progression of Prostate Cancer Advanced Stages

  • Elena A. Pudova,
  • George S. Krasnov,
  • Anastasiya A. Kobelyatskaya,
  • Maria V. Savvateeva,
  • Maria S. Fedorova,
  • Vladislav S. Pavlov,
  • Kirill M. Nyushko,
  • Andrey D. Kaprin,
  • Boris Y. Alekseev,
  • Dmitry Y. Trofimov,
  • Gennady T. Sukhikh,
  • Anastasiya V. Snezhkina,
  • Anna V. Kudryavtseva

DOI
https://doi.org/10.3389/fgene.2020.613162
Journal volume & issue
Vol. 11

Abstract

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Prostate cancer (PC) is one of the most common cancers among men worldwide, and advanced PCs, such as locally advanced PC (LAPC) and castration-resistant PC (CRPC), present the greatest challenges in clinical management. Current indicators have limited capacity to predict the disease course; therefore, better prognostic markers are greatly needed. In this study, we performed a bioinformatic analysis of The Cancer Genome Atlas (TCGA) datasets, including RNA-Seq data from the prostate adenocarcinoma (PRAD; n = 55) and West Coast Dream Team – metastatic CRPC (WCDT-MCRPC; n = 84) projects, to evaluate the transcriptome changes associated with progression-free survival (PFS) for LAPC and CRPC, respectively. We identified the genes whose expression was positively/negatively correlated with PFS. In LAPC, the genes with the most significant negative correlations were ZC2HC1A, SQLE, and KIF11, and the genes with the most significant positive correlations were SOD3, LRRC26, MIR22HG, MEG3, and MIR29B2CHG. In CRPC, the most significant positive correlations were found for BET1, CTAGE5, IFNGR1, and GIMAP6, and the most significant negative correlations were found for CLPB, PRPF19, ZNF610, MPST, and LINC02001. In addition, we performed a gene network interaction analysis using STRINGdb, which revealed a significant relationship between genes predominantly involved in the cell cycle and characterized by upregulated expression in early recurrence. Based on the results, we propose several genes that can be used as potential prognostic markers.

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