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Integration of single-cell sequencing and bulk transcriptome data develops prognostic markers based on PCLAF+ stem-like tumor cells using artificial neural network in gastric cancer

  • 0Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Heliyon +

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November 11, 2024

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November 11, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Gastric cancer stem cells (GCSCs) identified by PCLAF+ expression correlate with poor prognosis. These stem-like cells and their associated mRNA stemness degree (SD) may predict immunotherapy response in gastric cancer patients.

Area Of Science

  • Oncology
  • Cancer Stem Cell Biology
  • Immunotherapy

Background

  • Gastric cancer stem cells (GCSCs) drive tumorigenesis but their clinical significance is limited by current technologies.
  • Understanding GCSCs is crucial for advancing gastric cancer treatment strategies.
  • This study investigates the clinical value, tumor microenvironment interactions, and molecular mechanisms of GCSCs.

Purpose Of The Study

  • To explore the clinical significance of GCSCs in gastric cancer.
  • To investigate the relationship between GCSCs, the tumor microenvironment, and clinical outcomes.
  • To develop novel prognostic and predictive models for gastric cancer.

Main Methods

  • Single-cell transcriptomic data mining to identify stem-like tumor cells.
  • Integrated analysis of single-cell and bulk transcriptomic data using mRNA stemness degree (SD).
  • Consensus clustering for SD-related molecular classification and artificial neural network-based prognostic model construction.

Main Results

  • A PCLAF+ stem-like tumor cell population was identified in gastric cancer (GC).
  • PCLAF+ stem-like cells and higher SD were associated with poor prognosis and specific clinical features.
  • SD negatively correlated with immune cell abundance, and the prognostic model predicted immunotherapy response.

Conclusions

  • A distinct population of stem-like cells in gastric cancer was identified and their clinical significance elucidated.
  • These findings highlight PCLAF+ stem-like cells as potential immunotherapeutic targets.
  • The developed prognostic model offers insights into patient stratification and treatment response prediction.

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