Jing Jin1, Yuncui Gan1, Huayong Liu2, Zirong Wang2, Jianying Yuan2, Taibing Deng3, Yongzhao Zhou1, Yingying Zhu1, Hui Zhu1, Sai Yang1, Wei Shen4, Dan Xie5, Honglong Wu6, Dan Liu7, Weimin Li8. 1. Department of Respiratory & Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, China. 2. BGI-Guangzhou Medical Laboratory, BGI-Shenzhen, Guangzhou, 510006, China. 3. Department of Respiratory Medicine. West China-Guangan Hospital, Sichuan University, Guangan, 638500, Sichuan Province, China. 4. Hangzhou YITU Healthcare Technology Co, Ltd, Zhejiang, Hangzhou, 310000, China. 5. Center of Precision Medicine, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University and National Collaborative Innovation Center, Chengdu, Sichuan Province, 610041, China. 6. BGI-Guangzhou Medical Laboratory, BGI-Shenzhen, Guangzhou, 510006, China; Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China. Electronic address: wuhonglong@bgi.com. 7. Department of Respiratory & Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, China. Electronic address: liudan_10965@wchscu.cn. 8. Department of Respiratory & Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, China. Electronic address: weimi003@scu.edu.cn.
Abstract
OBJECTIVES: Current evidence suggests that microorganisms are associated with neoplastic diseases; however, the role of the airway microbiome in lung cancer remains unknown. To investigate the taxonomic profiles of the lower respiratory tract (LRT) microbiome in patients with lung cancer. MATERIALS AND METHODS: BALF samples were collected in a discovery set comprising 150 individuals, including 91 patients with lung cancer, 29 patients with nonmalignant pulmonary diseases and 30 healthy subjects, and an independent validation set including 85 participants. The samples were assessed by metagenomics analysis. Random forest regression analysis was performed to select a diagnostic panel. RESULTS: In the discovery set, richness was reduced in lung cancer patients compared with that in healthy subjects, and the microbiome of patients with nonmalignant diseases resembled that of patients with lung cancer. Interestingly, Bradyrhizobium japonicum was only found in patients with lung cancer, whereas Acidovorax was found in patients with cancer and nonmalignant pulmonary diseases. A microbiota-related diagnostic model consisting of age, pack year of smoking and eleven types of bacteria was built, and the area under the curve (AUC) for discriminating the patients with cancer was 0.882 (95%CI: 0.807-0.957) in the training set and 0.796 (95%CI: 0.673-0.920) in the independent validation set. CONCLUSION: Our study demonstrates that the LRT microbiome richness is diminished in lung cancer patients compared with that in healthy subjects and that microbiota-specific biomarkers may be useful for diagnosing patients for whom lung biopsy is not feasible.
OBJECTIVES: Current evidence suggests that microorganisms are associated with neoplastic diseases; however, the role of the airway microbiome in lung cancer remains unknown. To investigate the taxonomic profiles of the lower respiratory tract (LRT) microbiome in patients with lung cancer. MATERIALS AND METHODS: BALF samples were collected in a discovery set comprising 150 individuals, including 91 patients with lung cancer, 29 patients with nonmalignant pulmonary diseases and 30 healthy subjects, and an independent validation set including 85 participants. The samples were assessed by metagenomics analysis. Random forest regression analysis was performed to select a diagnostic panel. RESULTS: In the discovery set, richness was reduced in lung cancerpatients compared with that in healthy subjects, and the microbiome of patients with nonmalignant diseases resembled that of patients with lung cancer. Interestingly, Bradyrhizobium japonicum was only found in patients with lung cancer, whereas Acidovorax was found in patients with cancer and nonmalignant pulmonary diseases. A microbiota-related diagnostic model consisting of age, pack year of smoking and eleven types of bacteria was built, and the area under the curve (AUC) for discriminating the patients with cancer was 0.882 (95%CI: 0.807-0.957) in the training set and 0.796 (95%CI: 0.673-0.920) in the independent validation set. CONCLUSION: Our study demonstrates that the LRT microbiome richness is diminished in lung cancerpatients compared with that in healthy subjects and that microbiota-specific biomarkers may be useful for diagnosing patients for whom lung biopsy is not feasible.
Authors: V G Druzhinin; L V Matskova; P S Demenkov; E D Baranova; V P Volobaev; V I Minina; S V Apalko; M A Churina; S A Romanyuk; S G Shcherbak; V I Ivanov; A V Larionov Journal: Sci Rep Date: 2020-06-15 Impact factor: 4.379