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The characterization of lung microbiome in lung cancer patients with different clinicopathology.

ABSTRACT: There were few knowledge concerned correlation between lung microbiome and different clinicopathology of lung cancer. Bronchial washing fluid (BWF) and sputum are commonly used sample types but there was no study comparing difference of microbiome between these two in lung cancer. In this study, we aimed to compare difference of microbiome between these two sample types and characterize lung microbiome in squamous cell lung carcinoma with (SCC_M1) or without distant metastasis (SCC_M0) and lung adenocarcinoma with (AD_M1) or without distant metastasis (AD_M0). We collected 40 BWF samples and 52 sputum samples from newly diagnosed lung cancer patients. Bacterial species were sequenced via 16S rRNA sequencing. Phylum Proteobacteria in BWF samples were significantly higher than sputum samples (Wilcoxon test, P = 0.003). At phylum level, microbiome of BWF samples was more similar to that of lung cancer tissues reported in the previous literature. LEFse analysis showed that in BWF group, genera Veillonell, Megasphaera, Actinomyces and Arthrobacter in AD_M0 were significantly higher than those in SCC_M0, and genera Capnocytophaga and Rothia in AD_M1 were significantly lower than that in SCC_M1. Compared with AD_M0, genus Streptococcus of AD_M1 was significantly lower, and genera Veillonella and Rothia in SCC_M1 were significantly higher than that in SCC_M1. Our study suggested that BWF samples might better reflect the microbiome of lung cancer tissues. In different metastatic states of lung cancer, differential genera between squamous cell carcinoma and adenocarcinoma were different. And in different histologic types of lung cancer, distant metastasis-related genera were not the same.

SUBMITTER: Huang D

PROVIDER: S-EPMC6780665 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Clinical manifestations of pancreatic cancer often do not occur until the cancer has undergone metastasis, resulting in a very low survival rate. In this study, we investigated whether salivary bacterial profiles might provide useful biomarkers for early detection of pancreatic cancer. Using high-throughput sequencing of bacterial small subunit ribosomal RNA (16S rRNA) gene, we characterized the salivary microbiota of patients with pancreatic cancer and compared them to healthy patients and patients with other diseases, including pancreatic disease, non-pancreatic digestive disease/cancer and non-digestive disease/cancer. A total of 146 patients were enrolled at the UCSD Moores Cancer Center where saliva and demographic data were collected from each patient. Of these, we analyzed the salivary microbiome of 108 patients: 8 had been diagnosed with pancreatic cancer, 78 with other diseases and 22 were classified as non-diseased (healthy) controls. Bacterial 16S rRNA sequences were amplified directly from salivary DNA extractions and subjected to high-throughput sequencing (HTS). Several bacterial genera differed in abundance in patients with pancreatic cancer. We found a significantly higher ratio of Leptotrichia to Porphyromonas in the saliva of patients with pancreatic cancer than in the saliva of healthy patients or those with other disease (Kruskal-Wallis Test; P < 0.001). Leptotrichia abundances were confirmed using real-time qPCR with Leptotrichia specific primers. Similar to previous studies, we found lower relative abundances of Neisseria and Aggregatibacter in the saliva of pancreatic cancer patients, though these results were not significant at the P < 0.05 level (K-W Test; P = 0.07 and P = 0.09 respectively). However, the relative abundances of other previously identified bacterial biomarkers, e.g., Streptococcus mitis and Granulicatella adiacens, were not significantly different in the saliva of pancreatic cancer patients. Overall, this study supports the hypothesis that bacteria abundance profiles in saliva are useful biomarkers for pancreatic cancer though much larger patient studies are needed to verify their predictive utility.

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The characterization of lung microbiome in lung cancer patients with different clinicopathology.

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