文献类型：期刊文献

英文题名：An Immunity-Associated lncRNA Signature for Predicting Prognosis in Gastric Adenocarcinoma

作者：Zhao, Xiaowen[1,2];Wu, Pingfan[1,2];Liu, Dongling[1,3];Li, Changtian[1];Xue, Ling[1];Liu, Zhe[1];Zhu, Meng[1];Yang, Jie[1];Chen, Ziyi[1,2];Li, Yaling[1,3];She, Yali[1,3]

第一作者：Zhao, Xiaowen

通信作者：Li, YL[1];She, YL[1];Li, YL[2];She, YL[2]

机构：[1]Gansu Univ Chinese Med, Sch Basic Med, Dept Pathol, Lanzhou, Gansu, Peoples R China;[2]940th Hosp Joint Logist Support Force Chinese Peop, Lab Preclin Med, Key Lab Stem Cells & Gene Drug Gansu Prov, Lanzhou, Gansu, Peoples R China;[3]Gansu Univ Chinese Med, Prov Level Key Lab Mol Med Major Dis & Study Preve, Lanzhou, Gansu, Peoples R China

第一机构：甘肃中医药大学

通信机构：[1]corresponding author), Gansu Univ Chinese Med, Sch Basic Med, Dept Pathol, Lanzhou, Gansu, Peoples R China;[2]corresponding author), Gansu Univ Chinese Med, Prov Level Key Lab Mol Med Major Dis & Study Preve, Lanzhou, Gansu, Peoples R China.|[10735]甘肃中医药大学;

年份：2022

卷号：2022

外文期刊名：JOURNAL OF HEALTHCARE ENGINEERING

收录：;EI(收录号：20222012124092);Scopus(收录号：2-s2.0-85129454184);WOS:【SCI-EXPANDED(收录号:WOS:000795104700002)】；

基金：The authors acknowledged the grants from the National Natural Science Foundation of China (grant no. 81560667), the Colleges and Universities Innovation Ability Improvement Project of Gansu Province, China (grant nos. 2019A074 and 2021B-166), the Foundation of Key Laboratory of Dunhuang Medicine and Transformation Constructed by Chinese Ministry of Education and Gansu Province (grant no. DHYX20-07), and Science and Technology Planning Project of Chengguan District, Lanzhou City, Gansu Province, China (grant no. 2021-2-11).The authors are grateful for the data provided by TCGA.

语种：英文

外文关键词：Cytology - Diagnosis - Drug therapy - Forecasting - Genes - Regression analysis - Risk assessment

摘要：Background. Gastric adenocarcinoma (GAD) is one of the most common tumors in the world and the prognosis is still very poor. Objective. We sought to identify reliable prognostic biomarkers for the progression of GAD and the sensitivity to drug therapy. Method. The RNA sequencing data of GAD was downloaded from the Cancer Genome Atlas (TCGA) database and used for analysis. Differentially expressed, immune-related lncRNA (DEIRlncRNA) was characterized by differential analysis and correlation analysis. Univariate Cox regression analysis was used to identify DEIRlncRNA associated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis allowed us to determine a signature composed of eight IRlncRNAs. Based on this signature, we further performed gene set enrichment analysis (GSEA) and somatic mutation analysis to evaluate the ability of this signature to predict prognosis. Results. In total, 72 immune-related lncRNAs (DEIRlncRNAs) with prognostic value were identified. These lncRNAs were used to construct a model containing eight immune-related lncRNAs (8-IRlncRNAs). Based on this risk model, we divided GAD patients into high-risk and low-risk groups. The analysis showed that the prognosis of the two groups was different and that the high-risk group had worse overall survival (OS). Immune cell infiltration analysis showed that the proportion of memory B cells increased in the high-risk group while the proportion of macrophages M1, T cells, CD4 memory-activated cells, and T cell follicular helpers decreased. GSEA results showed that 8-IRlncRNA was significantly enriched in tumorigenesis pathways such as myc. The results of somatic mutation analysis showed that the CDH1 gene was significantly mutated in the high-risk group. Conclusion. A prognostic signature of 8-IRlncRNAs in GAD was established and this signature was able to predict the prognosis of GAD patients.