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Identification and Validation of Gastric Adenocarcinoma Prognosis Features Based on Neutrophil-Related Genes

  • 0Department of General Surgery, Xiangyang First People's Hospital, Xiangyang First People's Hospital Affiliated to Hubei University of Medicine, Xiangyang City, Hubei Province, China.
Jco Precision Oncology +

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April 28, 2025

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April 28, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

A new prognostic model using seven neutrophil-related genes (NRGs) can predict gastric adenocarcinoma (GA) patient outcomes. This model also helps understand the tumor microenvironment and potential treatment responses.

Area Of Science

  • Oncology
  • Genomics
  • Immunology

Background

  • Gastric adenocarcinoma (GA) poses a significant health challenge, necessitating improved prognostic tools.
  • Understanding the role of neutrophil-related genes (NRGs) in GA's tumor microenvironment (TME) is crucial for developing targeted therapies.

Purpose Of The Study

  • To investigate the prognostic and tumor microenvironment (TME) impact of neutrophil-related genes (NRGs) in gastric adenocarcinoma (GA).
  • To establish a novel prognostic model for GA patients based on NRG expression.
  • To explore differences in TME composition and treatment sensitivity between high-risk and low-risk groups.

Main Methods

  • Utilized The Cancer Genome Atlas (TCGA) database for GA gene expression and clinical data.
  • Developed and validated a prognostic model using seven key NRGs (NHLRC3, PTPRJ, RTEL1, ST6GALNAC2, HRNR, HP, MCEMP1).
  • Assessed TME differences and treatment sensitivities using gene set enrichment analysis and CIBERSORT.

Main Results

  • A validated prognostic model based on seven NRGs was established, proving to be an independent predictor of overall survival in GA.
  • High-risk groups exhibited increased infiltration of macrophages, mast cells, and neutrophils.
  • Low-risk groups demonstrated greater sensitivity to immunotherapy and drugs like axitinib, cisplatin, and ulixertinib.

Conclusions

  • A novel prognostic model for GA was developed using NRG expression levels.
  • The identified NRGs (NHLRC3, PTPRJ, RTEL1, ST6GALNAC2, HRNR, HP, MCEMP1) serve as potential biomarkers for personalized prognosis.
  • This model offers a valuable reference for clinical studies and mechanism research in GA.