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Updated: May 9, 2025

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Identification and Validation of Gastric Adenocarcinoma Prognosis Features Based on Neutrophil-Related Genes
Xiaole Han1, Qiuling Tang2, Chaojie Cheng2
1Department of General Surgery, Xiangyang First People's Hospital, Xiangyang First People's Hospital Affiliated to Hubei University of Medicine, Xiangyang City, Hubei Province, China.
Purpose:
The aim of this study was to investigate the effect of neutrophil-related genes (NRGs) on prognosis and tumor microenvironment (TME) of patients with gastric adenocarcinoma (GA), to provide a new reference for prognosis evaluation and related mechanism research of GA.
Methods:
The gene expression data and clinical information of patients with GA were collected from The Cancer Genome Atlas database. NRG data are from the literature. Differential NRGs were obtained by difference analysis and regression analysis for the construction of the prognostic model, which was validated using the GSE84426 data set. The independent prognostic effect of risk score was analyzed by constructing a nomogram. The single-sample gene set enrichment analysis and CIBERSORT methods were used to evaluate differences in TME between a high-risk group (HRG) and a low-risk group (LRG) and to evaluate the differences in response to immunotherapy and sensitivity to different drugs in high and low risk score groups.
Results:
We established a prognostic model on the basis of seven NRGs (NHLRC3, PTPRJ, RTEL1, ST6GALNAC2, HRNR, HP, and MCEMP1) and validated its predictive value. Multivariable Cox regression analysis further demonstrated that the model remained an independent prognostic factor for overall survival, and a nomogram was constructed for clinical practice. Differential analysis of immune cell infiltration levels showed that macrophages, mast cells, and neutrophils were highly infiltrated in HRG compared with LRG. Compared with HRG, LRG was more sensitive to immunotherapy and more sensitive to candidates such as axitinib, cisplatin, and ulixertinib.
Conclusion:
In summary, on the basis of expression levels of NRGs, a new prognostic model was established. NHLRC3, PTPRJ, RTEL1, ST6GALNAC2, HRNR, HP, and MCEMP1 were valid candidate biomarkers that may help personalize prognostic predictions and serve as references for clinical studies.

