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Predicting survival in bladder cancer with a novel apoptotic gene-related prognostic model

  • 0Department of Urology, Jinzhou Medical University, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China.
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November 24, 2024

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November 24, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

This study developed an apoptosis-related gene model (ARGM) to predict bladder cancer prognosis and immunotherapy response. The ARGM demonstrated significant predictive value for overall survival, disease-specific survival, and progression-free survival, offering potential clinical applications.

Area Of Science

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background

  • Apoptosis and its related genes are crucial in bladder cancer development and progression.
  • Existing prognostic models do not incorporate apoptotic genes.

Purpose Of The Study

  • To establish a prognostic model using apoptosis-related genes for bladder cancer.
  • To evaluate the model's predictive capability for patient survival and response to immunotherapy.

Main Methods

  • Utilized The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for mRNA and clinical data.
  • Screened survival-related apoptosis genes using univariate and LASSO Cox regression.
  • Validated the Apoptosis-Related Gene Model (ARGM) using Kaplan-Meier analysis, ROC curves, and qRT-PCR.

Main Results

  • Identified key apoptosis genes (ANXA1, CASP6, CD2, F2, PDGFRB, SATB1, TSPO) forming the ARGM.
  • The ARGM accurately predicted overall survival, disease-specific survival, and progression-free survival in bladder cancer cohorts.
  • The model's score correlated with immune cell infiltration and predicted immunotherapy response, validated by TIDE and Imvigor210 studies.

Conclusions

  • The established ARGM holds significant predictive value for bladder cancer prognosis and immunotherapy.
  • The ARGM can aid in clinical consultation, patient stratification, and treatment selection.
  • Identified immune infiltration and signaling pathway differences between risk groups offer avenues for future research.

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