Complement-related molecular classification and a gene signature for lung adenocarcinoma

Author:

Zhang Lin,Yang Yannan,Lin Weihao,Shao Fei,Gao Yibo,He Jie

Abstract

Abstract Background Lung adenocarcinoma (LUAD) is a major cause of cancer-related death worldwide, and the roles of complement-related genes in it have not been thoroughly investigated yet. In the study, we aimed to systemically examine the prognostic performance of complement-related genes, classify the patients into two different clusters and stratify the patients into different risk groups using a complement-related gene signature. Methods To achieve this, clustering analyses, Kaplan–Meier survival analyses, immune infiltration analyses were performed. LUAD patients from The Cancer Genome Atlas (TCGA) were classified into two subtypes (C1 and C2). A prognostic signature, consisting of four complement-related genes, was established using TCGA-LUAD cohort and validated in six Gene Expression Omnibus datasets and an independent cohort from our center. Results The prognosis of C2 patients is better than that of C1 patients and the prognosis of low risk patients is significantly better than high risk patients across the public datasets. In our cohort, the OS of patients in low risk group is better than that in high risk group but the difference is not significant. Patients with a lower risk score were characterized by a higher immune score, a higher level of BTLA, higher infiltration levels of T cells, B lineage, myeloid dendritic cells, neutrophils, endothelial cells, and a lower infiltration level of fibroblast. Conclusions In summary, our study has established a new classification method and developed a prognostic signature for LUAD, while future studies are needed for further exploration of the underlying mechanism.

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Oncology,Hematology

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3