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Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis
Gastric cancer is the second most prevalent and deadly cancer in China. Microbiota play an important role in gastric tumorigenesis. However, the available microbial marker studies for gastric cancer do not have consistent results. We searched PubMed for 16S rRNA sequencing in relevant literature on...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10654077/ https://www.ncbi.nlm.nih.gov/pubmed/37787561 http://dx.doi.org/10.1128/msystems.00747-23 |
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author | Chen, Jijun Nie, Siru Qiu, Xunan Zheng, Shuwen Ni, Chuxuan Yuan, Yuan Gong, Yuehua |
author_facet | Chen, Jijun Nie, Siru Qiu, Xunan Zheng, Shuwen Ni, Chuxuan Yuan, Yuan Gong, Yuehua |
author_sort | Chen, Jijun |
collection | PubMed |
description | Gastric cancer is the second most prevalent and deadly cancer in China. Microbiota play an important role in gastric tumorigenesis. However, the available microbial marker studies for gastric cancer do not have consistent results. We searched PubMed for 16S rRNA sequencing in relevant literature on Chinese patients from 1 January 2005 to 18 July 2022, and 16 original articles were finally obtained. Alpha diversity, beta diversity, and bacterial taxa were used to explore the differences in gastric microbiota. Linear discriminant analysis of effect size and a random forest model were used to find the combination of genera with the best diagnostic efficacy. Streptococcus, Pseudomonas, Fusobacterium, Selenomonas, Peptostreptococcus, and Prevotella showed significant differences between gastric cancer and non-gastric cancer, but a single genus performed poorly in identifying patients with gastric cancer. However, a combination of genera Streptococcus, Peptostreptococcus, Selenomonas, Pseudomonas, and Prevotella had excellent performance in screening gastric cancer with the median area under the curve values of 0.7525 (range: 0.5859–0.9350), 0.8818 (range: 0.7397–0.9533), and 0.7435 (range: 0.7131–0.8483) in the Matched, Unmatched, and Other groups, respectively. Therefore, the results indicated that this combination of genera has good diagnostic efficacy and wide applicability for patients with gastric cancer, which may provide new clues for the non-invasive diagnosis of gastric cancer. IMPORTANCE: Gastric cancer is a significant and growing health problem in China. Studies have revealed significant differences in gastric microbiota between patients with gastric cancer and non-cancerous patients, suggesting that microbiota may play a role in tumorigenesis. In this meta-analysis, existing 16S rRNA microbial data were analyzed to find combinations consisting of five genera, which had good efficacy in distinguishing gastric cancer from non-cancerous patients in multiple types of samples. These results lend support to the use of microbial markers in detecting gastric cancer. Moreover, these biomarkers are plausible candidates for further mechanistic research into the role of the microbiota in tumorigenesis. |
format | Online Article Text |
id | pubmed-10654077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-106540772023-10-03 Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis Chen, Jijun Nie, Siru Qiu, Xunan Zheng, Shuwen Ni, Chuxuan Yuan, Yuan Gong, Yuehua mSystems Research Article Gastric cancer is the second most prevalent and deadly cancer in China. Microbiota play an important role in gastric tumorigenesis. However, the available microbial marker studies for gastric cancer do not have consistent results. We searched PubMed for 16S rRNA sequencing in relevant literature on Chinese patients from 1 January 2005 to 18 July 2022, and 16 original articles were finally obtained. Alpha diversity, beta diversity, and bacterial taxa were used to explore the differences in gastric microbiota. Linear discriminant analysis of effect size and a random forest model were used to find the combination of genera with the best diagnostic efficacy. Streptococcus, Pseudomonas, Fusobacterium, Selenomonas, Peptostreptococcus, and Prevotella showed significant differences between gastric cancer and non-gastric cancer, but a single genus performed poorly in identifying patients with gastric cancer. However, a combination of genera Streptococcus, Peptostreptococcus, Selenomonas, Pseudomonas, and Prevotella had excellent performance in screening gastric cancer with the median area under the curve values of 0.7525 (range: 0.5859–0.9350), 0.8818 (range: 0.7397–0.9533), and 0.7435 (range: 0.7131–0.8483) in the Matched, Unmatched, and Other groups, respectively. Therefore, the results indicated that this combination of genera has good diagnostic efficacy and wide applicability for patients with gastric cancer, which may provide new clues for the non-invasive diagnosis of gastric cancer. IMPORTANCE: Gastric cancer is a significant and growing health problem in China. Studies have revealed significant differences in gastric microbiota between patients with gastric cancer and non-cancerous patients, suggesting that microbiota may play a role in tumorigenesis. In this meta-analysis, existing 16S rRNA microbial data were analyzed to find combinations consisting of five genera, which had good efficacy in distinguishing gastric cancer from non-cancerous patients in multiple types of samples. These results lend support to the use of microbial markers in detecting gastric cancer. Moreover, these biomarkers are plausible candidates for further mechanistic research into the role of the microbiota in tumorigenesis. American Society for Microbiology 2023-10-03 /pmc/articles/PMC10654077/ /pubmed/37787561 http://dx.doi.org/10.1128/msystems.00747-23 Text en Copyright © 2023 Chen et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Chen, Jijun Nie, Siru Qiu, Xunan Zheng, Shuwen Ni, Chuxuan Yuan, Yuan Gong, Yuehua Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis |
title | Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis |
title_full | Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis |
title_fullStr | Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis |
title_full_unstemmed | Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis |
title_short | Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis |
title_sort | leveraging existing 16s rrna microbial data to identify diagnostic biomarker in chinese patients with gastric cancer: a systematic meta-analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10654077/ https://www.ncbi.nlm.nih.gov/pubmed/37787561 http://dx.doi.org/10.1128/msystems.00747-23 |
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