Bioinformatics Analysis Reveals Prognostic Significance of the Macrophage Marker Gene Signature in Gastric Adenocarcinoma

签名(拓扑) 胃腺癌 基因签名 基因 腺癌 癌症 生物 医学 内科学 基因表达 遗传学 数学 几何学
作者
Zhipeng Li,Hui Chen,Zhongqing Chen,Lihe Xie,Dun Pan
出处
期刊:Frontiers in bioscience [Bioscience Research Institute Pte. Ltd.]
卷期号:29 (5)
标识
DOI:10.31083/j.fbl2905172
摘要

Background: Gastric adenocarcinoma (GAC) is a malignant tumor with the highest incidence in the digestive system. Macrophages have been proven to play important roles in tumor microenvironment. Methods: Herein, single-cell RNA sequencing (scRNA-seq) profiles from the Gene Expression Omnibus (GEO) and bulk RNA-seq data from the Cancer Genome Atlas (TCGA) database were utilized to construct a macrophage marker gene signature (MMGS) to predict the prognosis of GAC patients. Subsequently, a risk score model based on the MMGS was built to predict the prognosis of GAC patients; further, this was validated in the GEO cohort. The risk score categorized patients into the high- and low-risk groups. A nomogram model based on the risk score and clinic-pathological characteristics was developed. Results: Seven genes, ABCA1, CTHRC1, GADD45B, NPC2, PLTP, PRSS23, and RNASE1, were included in the risk score model. Patients with a low-risk score showed a better prognosis. The MMGS had good sensitivity and specificity for predicting the prognosis inGAC patients. The risk score was an independent prognostic factor. The constructed nomogram exhibited favorable predictability and reliability for predicting GAC prognosis. Conclusion: In conclusion, the risk score model based on the seven MMGSs performed well in the predicting prognosis of GAC patients. Our study may provide new insights into clinical decision-making for the personalized treatment of patients with gastric cancer (GC).
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