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Predictable regulation of survival by intratumoral microbe-immune crosstalk in patients with lung adenocarcinoma

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机构: [1]The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi, China. [2]Geneis Beijing Co., Ltd., Beijing 100102, China. [3]Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao 266000, Shandong, China. [4]College of Information Engineering, Changsha Medical University, Changsha 410219, Hunan, China. [5]Academician Workstation, Changsha Medical University, Changsha 410219, Hunan, China. [6]Clinical Medical Research Center, Inner Mongolian People’s Hospital, No. 20, Zhaowuda Road, Hohhot, Inner Mongolia, China. [7]Inner Mongolia Key Laboratory of Gene Regulation of The Metabolic Disease, Inner Mongolian People’s Hospital, No. 20, Zhaowuda Road, Hohhot, Inner Mongolia, China. [8]Inner Mongolia Academy of Medical Sciences, Inner Mongolian People’s Hospital, No. 20, Zhaowuda Road, Hohhot, Inner Mongolia, China. [9]Pulmonary and Critical Care Medicine, Inner Mongolian People’s Hospital, No. 20, Zhaowuda Road, Saihan District, Hohhot, Inner Mongolia, China. [10]Hospital of Chengdu University of Traditional Chinese Medicine/No. 39, 12th Bridge Road, Jinniu District, Chengdu City, Sichuan Province, 610072, China. [11]Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research.
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关键词: lung adenocarcinoma intratumoral microbiota tumor microenvironment immune cell prognosis

摘要:
Intratumoral microbiota can regulate the tumor immune microenvironment (TIME) and mediate tumor prognosis by promoting inflammatory response or inhibiting anti-tumor effects. Recent studies have elucidated the potential role of local tumor microbiota in the development and progression of lung adenocarcinoma (LUAD). However, whether intratumoral microbes are involved in the TIME that mediates the prognosis of LUAD remains unknown. Here, we obtained the matched tumor microbiome and host transcriptome and survival data of 478 patients with LUAD in The Cancer Genome Atlas (TCGA). Machine learning models based on immune cell marker genes can predict 1- to 5-year survival with relative accuracy. Patients were stratified into high- and low-survival-risk groups based on immune cell marker genes, with significant differences in intratumoral microbial communities. Specifically, patients in the high-risk group had significantly higher alpha diversity (p < 0.05) and were characterized by an enrichment of lung cancer-related genera such as Streptococcus. However, network analysis highlighted a more active pattern of dominant bacteria and immune cell crosstalk in TIME in the low-risk group compared to the high-risk group. Our study demonstrated that intratumoral microbiota-immune crosstalk was strongly associated with prognosis in LUAD patients, which would provide new targets for the development of precise therapeutic strategies.Copyright: © 2024 Shi et al.

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出版当年[2023]版:
大类 | 3 区 生物学
小类 | 4 区 细胞生物学 4 区 微生物学
最新[2023]版:
大类 | 3 区 生物学
小类 | 4 区 细胞生物学 4 区 微生物学
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第一作者机构: [1]The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi, China.
通讯作者:
通讯机构: [10]Hospital of Chengdu University of Traditional Chinese Medicine/No. 39, 12th Bridge Road, Jinniu District, Chengdu City, Sichuan Province, 610072, China. [11]Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research. [*1]Hospital of Chengdu University of Traditional Chinese Medicine/No. 39, 12th Bridge Road, Jinniu District, Chengdu City,Sichuan Province, 610072, China [*2]Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research
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