Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 12, 2025AgingOpen Access

Identification of key genes with differential correlations in prostate cancer

View Full Paper
Ask AI
Bookmark
Share

Authors

ZCZepai ChiYZYuanfeng ZhangXHXuwei Hong

Discussion

Loading...

Member takes

Overview

Observational analysis reveals 21 biomarkers for prostate cancer, suggesting novel insights into tumorigenesis.

Key Points

  • Twenty-one genes were identified as potential biomarkers for prostate cancer after analyzing gene co-expression networks.
  • The analysis utilized differential correlation metrics via Fisher's z-test to assess gene representation in tumor versus normal tissues.
  • Weighted gene co-expression network analysis (WGCNA) was used to construct gene interaction networks with high precision.
  • Findings support the need for deeper exploration of genetic mechanisms behind prostate cancer progression.

Cite This Study

Chi et al. (2025) studied this question.

synapsesocial.com/papers/68ebe3d6becc64ad52fdae04https://doi.org/10.18632/aging.206323
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Identification of Signaling Pathways and Prognostic Biomarkers in Prostate Cancer using Bioinformatics Approaches2024
  2. 2Identification and verification of exosome-related gene signature to predict the cancer status and prognosis of prostate cancer2025 · 3 citations
  3. 3Transformative insights from transcriptome analysis of colorectal cancer patient tissues: identification of four key prognostic genes2025
  4. 4Integrative bioinformatics and drug repurposing for metastatic prostate cancer: identifying novel therapeutic targets by transcriptional profiling and molecular Modeling2025
  5. 5Identification of progression markers for prostate cancer.2025