Designing a risk prognosis model based on natural killer cell-linked genes to accurately evaluate the prognosis of gastric cancer
作者机构：Department of GastroenterologyZibo Central HospitalZibo255036China
出 版 物：《BIOCELL》 (生物细胞（英文）)
年 卷 期：2023年第47卷第9期
页 面：2081-2099页
核心收录：
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Natural killer cells Gastric cancer Risk model Molecular typing
摘 要：Background:This study was aimed at identifying natural killer(NK)cell-related genes to design a risk prognosis model for the accurate evaluation of gastric cancer(GC)***:We obtained NK cell-related genes from various databases,followed by Cox regression analysis and molecular typing to identify prognostic *** immune algorithms and enrichment analyses were used to investigate the mutations,immune status,and pathway variations among different *** key prognostic genes were assessed using the least absolute shrinkage and selection operator(Lasso)regression analysis and univariate Cox regression ***,the risk score(RS)prognosis model was constructed based on the selected important prognostic genes.A Receiver Operating Characteristics(ROC)curve was plotted for analyzing the robustness of the ***,the decision and calibration curves were used for assessing the reliability and prediction accuracy of the proposed ***‘pRRophetic’R software package was utilized for predicting the half-maximal inhibitory concentration(IC50)of immunotherapy and chemotherapy ***:We screened 21 prognostic genes and three molecular subtypes and found that the C1 subtype had the worst ***,the pathways promoting tumor proliferation,such as epithelial-mesenchymal transition were significantly *** results also showed that the macrophages in the M2 stage were significantly infiltrated in the C1 subtype,and there was significant overexpression in the C1 subtype,accompanied by a severe inflammatory *** C1 was highly sensitive to drugs like 5-fluorouracil and *** ROC,calibration curve,and decision curve showed that the risk model was robust and strongly ***:Overall,our proposed NK cell-related RS model can be used as a more accurate prediction index for GC patients,providing a valuable contribution to personalized medicine.
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