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Development of a prognostic model for early-stage gastric cancer-related DNA methylation-driven genes and analysis of immune landscape

  • 0The School of Clinical Medical, Fujian Medical University, Fuzhou, Fujian, China.
Frontiers in Molecular Biosciences +

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November 22, 2024

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November 22, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new prognostic model for early-stage gastric cancer uses DNA methylation-driven genes C1orf35 and FAAH to predict patient survival. This model identifies high-risk patients and aids in diagnosis and treatment strategies.

Area Of Science

  • Oncology
  • Genetics
  • Bioinformatics

Background

  • Gastric cancer remains a significant global health challenge, particularly in its early stages.
  • Accurate prognostic models are crucial for effective patient management and treatment stratification.
  • DNA methylation plays a critical role in cancer development and progression.

Purpose Of The Study

  • To develop a prognostic model for early-stage gastric cancer based on DNA methylation-driven genes.
  • To investigate immune cell infiltration and function in relation to different risk levels.
  • To identify potential biomarkers for diagnosis and treatment of early-stage gastric cancer.

Main Methods

  • Analysis of The Cancer Genome Atlas (TCGA) data for stage I/II gastric cancer patients.
  • Identification of differentially expressed genes (DEGs) and DNA methylation-driven genes (DMGs) using limma and MethylMix packages.
  • Application of univariate Cox regression and LASSO analyses to select key prognostic genes.
  • Construction and validation of a risk score prediction model and nomogram.
  • Examination of immune cell infiltration using the CIBERSORT package.

Main Results

  • A four-gene signature (ZC3H12A, GATA3, C1orf35, FAAH) was identified, with C1orf35 and FAAH selected for the final model.
  • The prognostic model demonstrated significant correlation with overall survival (OS) in early-stage gastric cancer patients.
  • Hypomethylation of C1orf35 and FAAH was observed in gastric cancer tissues compared to normal tissues.
  • The model showed predictive accuracy with AUC values of 0.611 (3-year) and 0.564 (5-year).
  • A notable association was found between high-risk scores and resting CD4 memory T cells.

Conclusions

  • Promoter hypomethylation of C1orf35 and FAAH suggests their potential as diagnostic and therapeutic biomarkers.
  • The developed DNA methylation-driven gene model serves as an independent prognostic factor for early-stage gastric cancer.
  • This model can aid in stratifying patients and guiding clinical decision-making for improved outcomes.

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