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  1. Home
  3. Comprehensive Landscape Of M6a Regulator-related Gene Patterns And Tumor Microenvironment Infiltration Characterization In Gastric Cancer.
  1. Home
  3. Comprehensive Landscape Of M6a Regulator-related Gene Patterns And Tumor Microenvironment Infiltration Characterization In Gastric Cancer.

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Comprehensive landscape of m6A regulator-related gene patterns and tumor microenvironment infiltration

Bin Peng1, Yinglin Lin1, Gao Yi1

  • 1Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, State Key Laboratory of Respiratory Disease, The Fifth Affiliated Hospital, Guangzhou Medical University, The Fifth Clinical College of Guangzhou Medical University, Guangzhou, China.

Scientific Reports
|July 16, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study reveals how N6-methyladenosine (m6A) regulators impact gastric cancer and its tumor microenvironment (TME). A new scoring system predicts prognosis and immunotherapy response, aiding personalized treatment strategies.

Keywords:
Gastric cancerImmunotherapyN6-methyladenosine (m6a) modificationTumor microenvironmentm6A regulator-related patternm6A-related score

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Area of Science:

  • Oncology
  • Epigenetics
  • Computational Biology

Background:

  • N6-methyladenosine (m6A) epigenetic regulation is crucial in cancer research.
  • The role of m6A regulators in gastric cancer (GC) and its tumor microenvironment (TME) is not fully understood.

Purpose of the Study:

  • To identify m6A regulator-related genes and patterns in GC.
  • To elucidate their mechanisms and impact on TME.
  • To develop a scoring system for prognosis and immunotherapy response prediction.

Main Methods:

  • Utilized data mining and computational biology on multiple datasets.
  • Analyzed 28 m6A regulators and identified 56 m6A regulator-related genes.
  • Performed unsupervised clustering and TME characterization.
  • Developed and validated an m6A-related scoring system.

    • Main Results:

    • Identified three distinct m6A regulator-related patterns correlating with immune-inflamed, excluded, and desert TME phenotypes.
    • Developed an m6A score predicting survival, immune activation, stromal activation, and tumor malignancy.
    • The score showed predictive value across digestive system and all tumor types.
    • Low scores correlated with better responses to anti-PD-1/L1 and anti-CTLA4 immunotherapy.

    Conclusions:

    • m6A regulator-related genes significantly influence TME diversity and GC traits.
    • The developed scoring system aids in predicting prognosis and guiding immunotherapy strategies for GC.
    • This research offers potential for personalized treatment approaches in gastric cancer.