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Comprehensive molecular characterization of high-stemness gastric cancer cells using single-cell transcriptomics,

Ziyi Wang1,2,3, Xuehao Li3, Jin Wang4

  • 1Department of Surgical Oncology and General Surgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.

NPJ Precision Oncology
|December 17, 2025
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Summary

This study identifies key genes in high-stemness gastric cancer (GC) cells, revealing their role in tumor aggressiveness and chemoresistance. These findings offer potential biomarkers for personalized GC treatment strategies.

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Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Gastric cancer (GC) presents significant clinical challenges due to late diagnosis, heterogeneity, and poor prognosis.
  • Tumor stemness is a critical driver of GC aggressiveness and therapeutic resistance.
  • Systematic characterization of high-stemness GC cells and their molecular features is limited.

Purpose of the Study:

  • To identify and characterize high-stemness GC cells using integrated multi-omics data.
  • To explore genomic instability, genetic susceptibility, and microenvironmental interactions in high-stemness GC cells.
  • To develop a predictive model for high-stemness GC cells and validate potential therapeutic targets.

Main Methods:

  • Integrated analysis of single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and bulk RNA-seq data.
  • Calculation of stemness scores using CytoTRACE and classification of cell subpopulations.
  • Genomic and cell-cell communication profiling, WGCNA, machine learning for feature screening, and SHAP analysis for model interpretation.
  • Experimental validation via gene knockdown and assessment of pathway activity and chemosensitivity.

Main Results:

  • High-stemness GC cells exhibit enhanced intercellular signaling, metabolic reprogramming, and stemness pathway activity.
  • Five robust HighStem features identified: APMAP, MAPRE1, GLB1, TSPAN6, and CDKN2A.
  • A Support Vector Machine (SVM) model using these genes achieved high accuracy (AUC=0.973) in distinguishing HighStem cells.
  • Gene knockdown reduced JAK1-STAT3 pathway activity and increased GC cell sensitivity to chemotherapy (5-FU, cisplatin).

Conclusions:

  • This study provides a comprehensive molecular and functional characterization of high-stemness GC cells.
  • Identified signature genes and predictive models offer insights into GC stemness biology and personalized therapeutic strategies.
  • The core genes may serve as potential biomarkers for predicting treatment outcomes and monitoring therapeutic resistance in GC.