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  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Comprehensive Analysis And Prognostic Assessment Of Senescence-associated Genes In Bladder Cancer.
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  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Comprehensive Analysis And Prognostic Assessment Of Senescence-associated Genes In Bladder Cancer.

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Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer.

Ruilin Yang1,2, Jieling He3, Wenfeng Luo4

  • 1Jinan University, 601 Huangpu Avenue West, Tianhe District, Guangzhou, 511400, China.

Discover Oncology
|April 26, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study identifies ten key senescence-related genes to predict bladder cancer patient survival. These findings offer a new approach for clinical oversight and treatment strategies in bladder cancer.

Keywords:
Bladder cancerImmunotherapyPrognosisSenescence-associated genes

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Area of Science:

  • Oncology
  • Genetics
  • Bioinformatics

Background:

  • Bladder cancer (BLCA) has high prevalence and mortality.
  • Senescence-related genes are implicated in tumor development, but their prognostic value in BLCA is underexplored.

Purpose of the Study:

  • To investigate the prognostic significance of senescence-related genes in bladder cancer.
  • To develop a predictive model for bladder cancer patient survival based on senescence gene signatures.

Main Methods:

  • Utilized TCGA and GEO datasets for BLCA transcriptome analysis.
  • Employed differential gene expression, NMF, and Cox regression for gene identification.
  • Developed and validated nomograms for survival prediction and assessed immune response and drug sensitivity.
Transcriptomic analysis

Main Results:

  • Identified two distinct clusters based on senescence-related gene expression in BLCA.
  • A panel of ten key senescence-related genes was established for risk stratification.
  • Validated nomograms accurately predicted patient survival; low-risk patients showed higher sensitivity to specific chemotherapeutic agents.

Conclusions:

  • Senescence-related gene signatures hold promise for improving bladder cancer patient risk assessment.
  • This approach can enhance clinical management and guide personalized treatment strategies for bladder cancer.