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Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue

BACKGROUND: Lung biopsy tissue samples can be used for infection detection and cancer diagnosis. Metagenomic next-generation sequencing (mNGS) has the potential to further improve diagnosis. METHODS: From July 2018 to May 2020, lung biopsy samples of 133 patients with suspected pulmonary infection o...

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Autores principales: Guo, Yifan, Li, Henan, Chen, Hongbin, Li, Zhenzhong, Ding, Wenchao, Wang, Jun, Yin, Yuyao, Jin, Longyang, Sun, Shijun, Jing, Chendi, Wang, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554462/
https://www.ncbi.nlm.nih.gov/pubmed/34700283
http://dx.doi.org/10.1016/j.ebiom.2021.103639
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author Guo, Yifan
Li, Henan
Chen, Hongbin
Li, Zhenzhong
Ding, Wenchao
Wang, Jun
Yin, Yuyao
Jin, Longyang
Sun, Shijun
Jing, Chendi
Wang, Hui
author_facet Guo, Yifan
Li, Henan
Chen, Hongbin
Li, Zhenzhong
Ding, Wenchao
Wang, Jun
Yin, Yuyao
Jin, Longyang
Sun, Shijun
Jing, Chendi
Wang, Hui
author_sort Guo, Yifan
collection PubMed
description BACKGROUND: Lung biopsy tissue samples can be used for infection detection and cancer diagnosis. Metagenomic next-generation sequencing (mNGS) has the potential to further improve diagnosis. METHODS: From July 2018 to May 2020, lung biopsy samples of 133 patients with suspected pulmonary infection or abnormal imaging findings were collected and subjected to clinical microbiological testing, Illumina and Nanopore sequencing to identify pathogens. The neural networks were pretrained by extracting features of human reads from 2,095 metagenomic next-generation sequencing results, and the human reads of lung biopsy samples were entered into the validated pipeline to predict the risk of cancer. FINDINGS: Based on the pathogen-cancer detection pipeline, the Illumina platform showed 77·6% sensitivity and 97·6% specificity compared to the composite reference standard for infection diagnosis. However, the Nanopore platform showed 34·7% sensitivity and 98·7% specificity. mNGS identified more fungi, which was confirmed by subsequent pathological examination. M. tuberculosis complex was weakly detected. For cancer detection, compared with histology, the Illumina platform showed 83·7% sensitivity and 97·6% specificity, diagnosing an additional 36 cancer patients, of whom half had abnormal imaging findings (pulmonary shadow, space-occupying lesions, or nodules). INTERPRETATION: For the first time, we have established a pipeline to simultaneously detect pathogens and cancer based on Illumina sequencing of lung biopsy tissue. This pipeline efficiently diagnosed cancer in patients with abnormal imaging findings. FUNDING: This work was supported by the National Key Research and Development Program of China and National Natural Science Foundation of China.
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spelling pubmed-85544622021-11-05 Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue Guo, Yifan Li, Henan Chen, Hongbin Li, Zhenzhong Ding, Wenchao Wang, Jun Yin, Yuyao Jin, Longyang Sun, Shijun Jing, Chendi Wang, Hui EBioMedicine Research paper BACKGROUND: Lung biopsy tissue samples can be used for infection detection and cancer diagnosis. Metagenomic next-generation sequencing (mNGS) has the potential to further improve diagnosis. METHODS: From July 2018 to May 2020, lung biopsy samples of 133 patients with suspected pulmonary infection or abnormal imaging findings were collected and subjected to clinical microbiological testing, Illumina and Nanopore sequencing to identify pathogens. The neural networks were pretrained by extracting features of human reads from 2,095 metagenomic next-generation sequencing results, and the human reads of lung biopsy samples were entered into the validated pipeline to predict the risk of cancer. FINDINGS: Based on the pathogen-cancer detection pipeline, the Illumina platform showed 77·6% sensitivity and 97·6% specificity compared to the composite reference standard for infection diagnosis. However, the Nanopore platform showed 34·7% sensitivity and 98·7% specificity. mNGS identified more fungi, which was confirmed by subsequent pathological examination. M. tuberculosis complex was weakly detected. For cancer detection, compared with histology, the Illumina platform showed 83·7% sensitivity and 97·6% specificity, diagnosing an additional 36 cancer patients, of whom half had abnormal imaging findings (pulmonary shadow, space-occupying lesions, or nodules). INTERPRETATION: For the first time, we have established a pipeline to simultaneously detect pathogens and cancer based on Illumina sequencing of lung biopsy tissue. This pipeline efficiently diagnosed cancer in patients with abnormal imaging findings. FUNDING: This work was supported by the National Key Research and Development Program of China and National Natural Science Foundation of China. Elsevier 2021-10-23 /pmc/articles/PMC8554462/ /pubmed/34700283 http://dx.doi.org/10.1016/j.ebiom.2021.103639 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research paper
Guo, Yifan
Li, Henan
Chen, Hongbin
Li, Zhenzhong
Ding, Wenchao
Wang, Jun
Yin, Yuyao
Jin, Longyang
Sun, Shijun
Jing, Chendi
Wang, Hui
Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue
title Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue
title_full Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue
title_fullStr Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue
title_full_unstemmed Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue
title_short Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue
title_sort metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554462/
https://www.ncbi.nlm.nih.gov/pubmed/34700283
http://dx.doi.org/10.1016/j.ebiom.2021.103639
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