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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.12209 |
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| _version_ | 1866909319347306496 |
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| author | Shankarnarayanan, Aadhith Gangopadhyay, Dheeman Alzaatreh, Ayman |
| author_facet | Shankarnarayanan, Aadhith Gangopadhyay, Dheeman Alzaatreh, Ayman |
| contents | The global surge in the cases of gastric cancer has prompted an investigation into the potential of gut microbiota as a predictive marker for the disease. The alterations in gut diversity are suspected to be associated with an elevated risk of gastric cancer. This paper delves into finding the correlation between gut microbiota and gastric cancer, focusing on patients who have undergone total and subtotal gastrectomy. Utilizing data mining and statistical learning methods, an analysis was conducted on 16S-RNA sequenced genes obtained from 96 participants with the aim of identifying specific genera of gut microbiota associated with gastric cancer. The study reveals several prominent bacterial genera that could potentially serve as biomarkers assessing the risk of gastric cancer. These findings offer a pathway for early risk assessment and precautionary measures in the diagnosis of gastric cancer. The intricate mechanisms through which these gut microbiotas influence gastric cancer progression warrant further investigation. This research significantly aims to contribute to the growing understanding of the gut-cancer axis and its implications in disease prediction and prevention. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_12209 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multivariate Analysis of Gut Microbiota Composition and Prevalence of Gastric Cancer Shankarnarayanan, Aadhith Gangopadhyay, Dheeman Alzaatreh, Ayman Genomics Artificial Intelligence The global surge in the cases of gastric cancer has prompted an investigation into the potential of gut microbiota as a predictive marker for the disease. The alterations in gut diversity are suspected to be associated with an elevated risk of gastric cancer. This paper delves into finding the correlation between gut microbiota and gastric cancer, focusing on patients who have undergone total and subtotal gastrectomy. Utilizing data mining and statistical learning methods, an analysis was conducted on 16S-RNA sequenced genes obtained from 96 participants with the aim of identifying specific genera of gut microbiota associated with gastric cancer. The study reveals several prominent bacterial genera that could potentially serve as biomarkers assessing the risk of gastric cancer. These findings offer a pathway for early risk assessment and precautionary measures in the diagnosis of gastric cancer. The intricate mechanisms through which these gut microbiotas influence gastric cancer progression warrant further investigation. This research significantly aims to contribute to the growing understanding of the gut-cancer axis and its implications in disease prediction and prevention. |
| title | Multivariate Analysis of Gut Microbiota Composition and Prevalence of Gastric Cancer |
| topic | Genomics Artificial Intelligence |
| url | https://arxiv.org/abs/2409.12209 |