4.6 Article

Alterations of the Human Lung and Gut Microbiomes in Non-Small Cell Lung Carcinomas and Distant Metastasis

期刊

MICROBIOLOGY SPECTRUM
卷 9, 期 3, 页码 -

出版社

AMER SOC MICROBIOLOGY
DOI: 10.1128/Spectrum.00802-21

关键词

gut microbiota; lung microbiota; machine learning; patient stratification; NSCLC; distant metastasis; brain metastasis

资金

  1. National Key R&D Program of China [2019YFC1316205, 2018YFC0910500]
  2. National Natural Science Foundation of China [81773233, 61932008, 61772368, 61572363]
  3. Natural Science Foundation of Shanghai [17ZR1445600]
  4. Shanghai Municipal Science and TechnologyMajor Project [2018SHZDZX01]
  5. ZJLab

向作者/读者索取更多资源

The study revealed significant disturbances in both gut and sputum microbiota in non-small cell lung cancer (NSCLC) patients, with the sputum microbiota being associated with distant metastasis (DM). Mathematical models utilizing both microbiotas showed better performance in patient stratification, while sputum models performed similarly to combined models, suggesting a potential noninvasive diagnostic method for NSCLC. Shared microbial biomarkers across different disease stages indicate the underlying progression of the disease, with signals for distant metastasis potentially detectable at early stages.
Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Although dysbiosis of the lung and gut microbiota have been associated with NSCLC, their relative contributions are unclear; in addition, their roles in distant metastasis (DM) are still illusive. We recruited in total 121 participants, including 87 newly diagnosed treatment-naive NSCLC patients of various stages and 34 healthy volunteers, and surveyed their fecal and sputum microbiota. We compared the microbial profiles between groups, identified microbial biomarkers, and generated machine learning models for distinguishing healthy individuals from patients with NSCLC and patients of various stages. We found significant perturbations of gut and sputum microbiota in patients with NSCLC and DM. A machine learning model combining both microbiota (combined model) performed better than an individual data set in patient stratification, with the highest area under the curve (AUC) value of 0.896. Sputum and gut microbiota both contributed to the combined model; in most cases, sputum-only models performed similar to the combined models. Several microbial biomarkers were shared by both microbiotas, indicating their similar roles at distinct body sites. Microbial biomarkers of distinct disease stages were mostly shared, suggesting biomarkers for DM could be acquired early. Furthermore, Pseudomonas aeruginosa, a species previously associated with wound infections, was significantly more abundant in brain metastasis, indicating that distinct types of DMs could have different microbes. Our results indicate that alterations of the sputum microbiota have stronger relationships with NSCLC and DM than the gut and strongly support the feasibility of metagenome-based noninvasive disease diagnosis and risk evaluation. (This study has been registered at ClinicalTrials.gov under registration no. NCT03454685). IMPORTANCE Our survey on gut and sputum microbiota revealed that both were significantly disturbed in non-small cell lung cancer (NSCLC) and associated with distant metastasis (DM) while only the sputum microbiota was associated with non-DM NSCLC. The lung microbiota could therefore have a stronger association with (and thus may contribute more to) disease development than the gut microbiota. Mathematic models using both microbiotas performed better in patient stratification than using individual microbiota. Sputum models, however, performed similar to the combined models, suggesting a convenient, noninvasive diagnostic for NSCLC. Microbial biomarkers of distinct disease stages were mostly shared, suggesting that the same set of microbes were underlying disease progression, and the signals for distant metastasis could be acquired at early stages of the disease. Our results strongly support the feasibility of noninvasive diagnosis of NSCLC, including distant metastasis, are of clinical importance, and should warrant further research on the underlying molecular mechanisms.

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