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ORIGINAL RESEARCH article

Front. Mol. Biosci.
Sec. Molecular Diagnostics and Therapeutics
Volume 11 - 2024 | doi: 10.3389/fmolb.2024.1455890
This article is part of the Research Topic Methods of Tumor Diagnosis and Pivotal Gene Regulatory Mechanisms in Tumorigenesis and Development View all 4 articles

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

Provisionally accepted
  • Xiamen University, Xiamen, China

The final, formatted version of the article will be published soon.

    We analyzed data from stage I/II gastric cancer patients in The Cancer Genome Atlas (TCGA), which included clinical details, mRNA expression profiles, and Level 3 DNA methylation array data. Using the empirical Bayes method of the limma package, we identified differentially expressed genes (DEGs), and the MethylMix package facilitated the identification of DNA methylation-driven genes (DMGs). Univariate Cox regression and LASSO analyses were utilized to pinpoint critical genes. A risk score prediction model was formulated using two genes that demonstrated the most significant hazard ratios (HR). Model performance was evaluated within the initial cohort and verified in the GSE84437 cohort; a nomogram was also constructed based on these genes. We further examined 50 methylation sites associated with three CpG islands in C1orf35 and 14 methylation sites linked to one CpG island in FAAH. The CIBERSORT package was employed to identify immune cell clusters in the prediction model. Results A total of 176 DNA methylation-driven genes were refined down to a 4-gene signature (ZC3H12A was hypermethylated; GATA3, C1orf35, and FAAH were hypomethylated), which exhibited a significant correlation with overall survival (OS) as evidenced by p-values below 0.05 following univariate Cox regression and LASSO analysis. Specifically, for the risk score prediction model, C1orf35, which had the highest hazard ratio (HR = 2.035, P = 0.028), and FAAH, with the lowest hazard ratio (HR = 0.656, P = 0.012), were selected. Kaplan-Meier analysis demonstrated distinct survival outcomes between the high-risk and low-risk score groups. The model's predictive accuracy was confirmed with an area under the curve (AUC) of 0.611 for 3-year survival and 0.564 for 5-year survival. Notably, the hypomethylation of the three CpG islands in C1orf35 and the single CpG island in FAAH was significantly different in stage I/II gastric cancer patients compared to normal tissues. Additionally, the high-risk score group showed a notable association with resting CD4 memory T cells.Promoter hypomethylation of C1orf35 and FAAH in early-stage gastric cancer underscores their potential as biomarkers for accurate diagnosis and treatment. The developed predictive model employing genes affected by DNA methylation serves as a crucial independent prognostic factor in early-stage gastric cancer.

    Keywords: gastric cancer, FAAH, C1orf35, DNA methylation-driven gene, prognosis

    Received: 27 Jun 2024; Accepted: 13 Sep 2024.

    Copyright: © 2024 Su, Ye, Yu, Lin, Wan and Hou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jingjing Hou, Xiamen University, Xiamen, China

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