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ORIGINAL RESEARCH article

Front. Cell. Infect. Microbiol.
Sec. Clinical Microbiology
Volume 14 - 2024 | doi: 10.3389/fcimb.2024.1518199
This article is part of the Research Topic Application and Reliability Assessment of Next Generation Sequencing (NGS) and targeted NGS (tNGS) in the Diagnosis of Infectious Diseases-Volume III View all 36 articles

Metagenomic next-generation sequencing for lung cancer low respiratory tract infections diagnosis and characterizing microbiome features

Provisionally accepted
Qiong Zhou Qiong Zhou *Yao Liu Yao Liu Han bo Yang Han bo Yang Qi Qi Qi Qi Jie shi Liu Jie shi Liu Heng yi Du Heng yi Du Lin lin Ye Lin lin Ye
  • Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

The final, formatted version of the article will be published soon.

    The capability of mNGS in diagnosing suspected LRTIs and characterizing the respiratory microbiome in lung cancer patients requires further evaluation.Methods: This study evaluated mNGS diagnostic performance and utilized background microbial sequences to characterize LRT microbiome in these patients. GSVA was used to analyze the potential functions of identified genera.Results: Bacteria were the most common pathogens (n=74) in LRTIs of lung cancer patients, and polymicrobial infections predominated compared to monomicrobial infections (p<0.001). In diagnosing LRTIs in lung cancer patients, the pathogen detection rate of mNGS (83.3%, 70/84) was significantly higher than that of sputum culture (34.5%, 29/84) (p<0.001). This result was consistent with that of non-lung cancer patients (p<0.001). Furthermore, in the specific detection of bacteria (95.7% vs. 22.6%) and fungi (96.0% vs. 22.2%), the detection rate of mNGS was also significantly higher than that of CMTs mainly based on culture (p<0.001, p<0.001). However, in the detection of CMV/EBV viruses, there was no significant difference between the detection rate of mNGS and that of viral DNA quantification (p = 1.000 and 0.152). mNGS analysis revealed Prevotella, Streptococcus, Veillonella, Rothia, and Capnocytophaga as the most prevalent genera in the LRT of lung 4 cancer patients. GSVA revealed significant correlations between these genera and tumor metabolic pathways as well as various signaling pathways including PI3K, Hippo, and p53. Conclusion: mNGS showed a higher pathogen detection rate than culture-based CMTs in lung cancer patients with LRTIs, and also characterizing LRT microbiome composition and revealing potential microbial functions linked to lung carcinogenesis.

    Keywords: Metagenomic next-generation sequencing (mNGS), lung cancer, Lower respiratory tract infections (LRTIs), microbiome, Gene Set Variation Analysis (GSVA)

    Received: 28 Oct 2024; Accepted: 31 Dec 2024.

    Copyright: © 2024 Zhou, Liu, Yang, Qi, Liu, Du and Ye. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Qiong Zhou, Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.