Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis
ABSTRACT 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 liter...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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American Society for Microbiology
2023-10-01
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| Series: | mSystems |
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| Online Access: | https://journals.asm.org/doi/10.1128/msystems.00747-23 |
| _version_ | 1797617684522729472 |
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| author | Jijun Chen Siru Nie Xunan Qiu Shuwen Zheng Chuxuan Ni Yuan Yuan Yuehua Gong |
| author_facet | Jijun Chen Siru Nie Xunan Qiu Shuwen Zheng Chuxuan Ni Yuan Yuan Yuehua Gong |
| author_sort | Jijun Chen |
| collection | DOAJ |
| description | ABSTRACT 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. |
| first_indexed | 2024-03-11T07:59:18Z |
| format | Article |
| id | doaj.art-f64f468d384b4c0e90c182a54373ded2 |
| institution | Directory Open Access Journal |
| issn | 2379-5077 |
| language | English |
| last_indexed | 2024-03-11T07:59:18Z |
| publishDate | 2023-10-01 |
| publisher | American Society for Microbiology |
| record_format | Article |
| series | mSystems |
| spelling | doaj.art-f64f468d384b4c0e90c182a54373ded22023-11-17T03:22:37ZengAmerican Society for MicrobiologymSystems2379-50772023-10-018510.1128/msystems.00747-23Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysisJijun Chen0Siru Nie1Xunan Qiu2Shuwen Zheng3Chuxuan Ni4Yuan Yuan5Yuehua Gong6Tumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University , Shenyang, Liaoning, ChinaTumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University , Shenyang, Liaoning, ChinaTumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University , Shenyang, Liaoning, ChinaTumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University , Shenyang, Liaoning, ChinaTumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University , Shenyang, Liaoning, ChinaTumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University , Shenyang, Liaoning, ChinaTumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Hospital of China Medical University , Shenyang, Liaoning, ChinaABSTRACT 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.https://journals.asm.org/doi/10.1128/msystems.00747-2316S rRNAdiagnostic biomarkergastric cancermeta-analysis |
| spellingShingle | Jijun Chen Siru Nie Xunan Qiu Shuwen Zheng Chuxuan Ni Yuan Yuan Yuehua Gong Leveraging existing 16S rRNA microbial data to identify diagnostic biomarker in Chinese patients with gastric cancer: a systematic meta-analysis mSystems 16S rRNA diagnostic biomarker gastric cancer 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 | 16S rRNA diagnostic biomarker gastric cancer meta-analysis |
| url | https://journals.asm.org/doi/10.1128/msystems.00747-23 |
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