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Identification of a Novel Mesenchymal Stem Cell-Related Signature for Predicting the Prognosis and Therapeutic Responses of Bladder Cancer

  • 0Institute of Urology, Key Laboratory of Gansu Province for Urological Diseases, Gansu Urological Clinical Center, Lanzhou University Second Hospital, Lanzhou 730030, China.
Stem Cells International +

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December 3, 2024

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December 3, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

This study developed a five-gene prognostic model for bladder cancer (BC) using mesenchymal stem cell (MSC) markers to predict patient outcomes and treatment response. The model identifies high-risk patients who may benefit from specific chemotherapy drugs.

Area Of Science

  • Oncology
  • Cancer Biology
  • Stem Cell Research

Background

  • Mesenchymal stem cells (MSCs) exhibit unique migratory patterns toward tumors, influencing cancer progression, treatment resistance, and immunosuppression.
  • Understanding the role of MSCs in bladder cancer (BC) is crucial for developing effective prognostic and therapeutic strategies.

Purpose Of The Study

  • To formulate a prognostic model based on MSC-associated markers for predicting clinical outcomes in bladder cancer patients.
  • To assess the model's ability to predict responses to chemotherapy and immunotherapy in bladder cancer.

Main Methods

  • Utilized clinical and transcriptome data from TCGA-BLCA and GSE31684 databases.
  • Applied weighted gene coexpression network analysis to identify MSC-correlated genes.
  • Developed a risk signature using univariate and LASSO Cox regression, validated by molecular docking for drug targeting.

Main Results

  • A five-gene prognostic model (ZNF165, MXRA7, CEMIP, ARL4C, CERCAM) was established for MSCs in bladder cancer.
  • High-MSC-risk patients showed unfavorable prognoses, while low-MSC-risk patients responded better to immunotherapy.
  • Specific chemotherapy drug sensitivities varied between high-risk (gemcitabine, vincristine, paclitaxel, gefitinib, sorafenib) and low-risk (cisplatin) groups.

Conclusions

  • The five-gene MSC prognostic model effectively predicts bladder cancer outcomes and treatment response.
  • Identified genes (ZNF165, MXRA7, CEMIP, ARL4C, CERCAM) are potential targets for anti-MSC therapies.
  • This model offers insights for personalized treatment strategies in bladder cancer management.

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