Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk
The gut microbiota significantly impacts human health, influencing metabolism, immunological responses, and disease prevention. Dysbiosis, or microbial imbalance, is linked to various diseases, including cancer. It is crucial to preserve a healthy microbiome since pathogenic bacteria, such as <i&...
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2024-12-01
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| author | Mohammad Amin Hemmati Marzieh Monemi Shima Asli Sina Mohammadi Behina Foroozanmehr Dariush Haghmorad Valentyn Oksenych Majid Eslami |
| author_facet | Mohammad Amin Hemmati Marzieh Monemi Shima Asli Sina Mohammadi Behina Foroozanmehr Dariush Haghmorad Valentyn Oksenych Majid Eslami |
| author_sort | Mohammad Amin Hemmati |
| collection | DOAJ |
| description | The gut microbiota significantly impacts human health, influencing metabolism, immunological responses, and disease prevention. Dysbiosis, or microbial imbalance, is linked to various diseases, including cancer. It is crucial to preserve a healthy microbiome since pathogenic bacteria, such as <i>Escherichia coli</i> and <i>Fusobacterium nucleatum</i>, can cause inflammation and cancer. These pathways can lead to the formation of tumors. Recent advancements in high-throughput sequencing, metagenomics, and machine learning have revolutionized our understanding of the role of gut microbiota in cancer risk prediction. Early detection is made easier by machine learning algorithms that improve the categorization of cancer kinds based on microbiological data. Additionally, the investigation of the microbiome has been transformed by next-generation sequencing (NGS), which has made it possible to fully profile both cultivable and non-cultivable bacteria and to understand their roles in connection with cancer. Among the uses of NGS are the detection of microbial fingerprints connected to treatment results and the investigation of metabolic pathways implicated in the development of cancer. The combination of NGS with machine learning opens up new possibilities for creating customized medicine by enabling the development of diagnostic tools and treatments that are specific to each patient’s microbiome profile, even in the face of obstacles like data complexity. Multi-omics studies reveal microbial interactions, biomarkers for cancer detection, and gut microbiota’s impact on cancer progression, underscoring the need for further research on microbiome-based cancer prevention and therapy. |
| format | Article |
| id | doaj-art-5bf05e924a4e4ebbb47953be7367c701 |
| institution | OA Journals |
| issn | 2073-4409 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Cells |
| spelling | doaj-art-5bf05e924a4e4ebbb47953be7367c7012025-08-20T02:38:47ZengMDPI AGCells2073-44092024-12-011323198710.3390/cells13231987Using New Technologies to Analyze Gut Microbiota and Predict Cancer RiskMohammad Amin Hemmati0Marzieh Monemi1Shima Asli2Sina Mohammadi3Behina Foroozanmehr4Dariush Haghmorad5Valentyn Oksenych6Majid Eslami7Student Research Committee, Semnan University of Medical Sciences, Semnan 35147-99442, IranDepartment of Basic Science, Faculty of Pharmacy and Pharmaceutical Science, Tehran Medical Science, Islamic Azad University, Tehran 19395-1495, IranFaculty of Medicine, Semnan University of Medical Sciences, Semnan 35147-99442, IranFaculty of Medicine, Semnan University of Medical Sciences, Semnan 35147-99442, IranStudent Research Committee, Semnan University of Medical Sciences, Semnan 35147-99442, IranDepartment of Immunology, Semnan University of Medical Sciences, Semnan 35147-99442, IranDepartment of Clinical Science, University of Bergen, 5020 Bergen, NorwayCancer Research Center, Faculty of Medicine, Semnan University of Medical Sciences, Semnan 35147-99442, IranThe gut microbiota significantly impacts human health, influencing metabolism, immunological responses, and disease prevention. Dysbiosis, or microbial imbalance, is linked to various diseases, including cancer. It is crucial to preserve a healthy microbiome since pathogenic bacteria, such as <i>Escherichia coli</i> and <i>Fusobacterium nucleatum</i>, can cause inflammation and cancer. These pathways can lead to the formation of tumors. Recent advancements in high-throughput sequencing, metagenomics, and machine learning have revolutionized our understanding of the role of gut microbiota in cancer risk prediction. Early detection is made easier by machine learning algorithms that improve the categorization of cancer kinds based on microbiological data. Additionally, the investigation of the microbiome has been transformed by next-generation sequencing (NGS), which has made it possible to fully profile both cultivable and non-cultivable bacteria and to understand their roles in connection with cancer. Among the uses of NGS are the detection of microbial fingerprints connected to treatment results and the investigation of metabolic pathways implicated in the development of cancer. The combination of NGS with machine learning opens up new possibilities for creating customized medicine by enabling the development of diagnostic tools and treatments that are specific to each patient’s microbiome profile, even in the face of obstacles like data complexity. Multi-omics studies reveal microbial interactions, biomarkers for cancer detection, and gut microbiota’s impact on cancer progression, underscoring the need for further research on microbiome-based cancer prevention and therapy.https://www.mdpi.com/2073-4409/13/23/1987microbiomedysbiosisnext-generation sequencingmetagenomicsmetabolomics |
| spellingShingle | Mohammad Amin Hemmati Marzieh Monemi Shima Asli Sina Mohammadi Behina Foroozanmehr Dariush Haghmorad Valentyn Oksenych Majid Eslami Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk Cells microbiome dysbiosis next-generation sequencing metagenomics metabolomics |
| title | Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk |
| title_full | Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk |
| title_fullStr | Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk |
| title_full_unstemmed | Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk |
| title_short | Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk |
| title_sort | using new technologies to analyze gut microbiota and predict cancer risk |
| topic | microbiome dysbiosis next-generation sequencing metagenomics metabolomics |
| url | https://www.mdpi.com/2073-4409/13/23/1987 |
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