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Identification of hub genes in bladder cancer based on weighted gene co-expression network analysis from TCGA database

  • Lei Wang* (Co-first Author)
  • , Xudong Liu (Co-first Author)
  • , Miao Yue (Co-first Author)
  • , Zhe Liu
  • , Yu Zhang
  • , Ying Ma
  • , Jia Luo
  • , Wuling Li
  • , Jiangshan Bai
  • , Hongmei Yao
  • , Yuxuan Chen
  • , Xiaofeng Li
  • , Dayun Feng*
  • , Xinqiang Song*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

64 Downloads (CityUHK Scholars)

Abstract

Background: Muscular invasive bladder cancer (MIBC) is a common malignant tumor in the world. Because of their heterogeneity in prognosis and response to treatment, biomarkers that can predict survival or help make treatment decisions in patients with MIBC are essential for individualized treatment. 
Aim: We aimed to integrate bioinformatics research methods to identify a set of effective biomarkers capable of predicting, diagnosing, and treating MIBC. To provide a new theoretical basis for the diagnosis and treatment of bladder cancer. 
Methods and results: Gene expression profiles and clinical data of MIBC were obtained by downloading from the Cancer Genome Atlas database. A dataset of 129 MIBC cases and controls was included. 2084 up-regulated genes and 2961 down-regulated genes were identified by differentially expressed gene (DEG) analysis. Then, gene ontology analysis was performed to explore the biological functions of DEGs, respectively. The up-regulated DEGs are mainly enriched in epidermal cell differentiation, mitotic nuclear division, and so forth. They are also involved in the cell cycle, p53 signaling pathway, PPAR signaling pathway, and so forth. The weighted gene co-expression network analysis yielded five modules related to pathological stages and grading, of which blue and turquoise were the most relevant modules for MIBC. Next, Using Kaplan–Meier survival analysis to identify further hub genes, the screening criteria at p ≤.05, we found CNKSR1, HIP1R, CFL2, TPM1, CSRP1, SYNM, POPDC2, PJA2, and RBBP8NL genes associated with the progression and prognosis of MIBC patients. Finally, immunohistochemistry experiments further confirmed that CNKSR1 plays a vital role in the tumorigenic context of MIBC. 
Conclusion: The research suggests that CNKSR1, POPDC2, and PJA2 may be novel biomarkers as therapeutic targets for MIBC, especially we used immunohistochemical further to validate CNKSR1 as a therapeutic target for MIBC which may help to improve the prognosis for MIBC.
Original languageEnglish
Article numbere1557
Number of pages12
JournalCancer Reports
Volume5
Issue number9
Online published20 Sept 2021
DOIs
Publication statusPublished - Sept 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • biomarker
  • MIBC
  • mutation
  • TCGA database
  • WGCNA

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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