| Autor: |
Fang Chen, Shenghui Li, Ruochun Guo, Fanghua Song, Yue Zhang, Xifan Wang, Xiaokui Huo, Qingbo Lv, Hayan Ullah, Guangyang Wang, Yufang Ma, Qiulong Yan, Xiaochi Ma |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Journal of Advanced Research, Vol 49, Iss , Pp 103-114 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2090-1232 |
| DOI: |
10.1016/j.jare.2022.09.012 |
| Popis: |
Introduction: Viruses have been reported as inducers of tumorigenesis. Little studies have explored the impact of the gut virome on the progression of colorectal cancer. However, there is still a problem with the repeatability of viral signatures across multiple cohorts. Objectives: The present study aimed to reveal the repeatable gut vial signatures of colorectal cancer and adenoma patients and decipher the potential of viral markers in disease risk assessment for diagnosis. Methods: 1,282 available fecal metagenomes from 9 published studies for colorectal cancer and adenoma were collected. A gut viral catalog was constructed via a reference-independent approach. Viral signatures were identified by cross-cohort meta-analysis and used to build predictive models based on machine learning algorithms. New fecal samples were collected to validate the generalization of predictive models. Results: The gut viral composition of colorectal cancer patients was drastically altered compared with healthy, as evidenced by changes in some Siphoviridae and Myoviridae viruses and enrichment of Microviridae, whereas the virome variation in adenoma patients was relatively low. Cross-cohort meta-analysis identified 405 differential viruses for colorectal cancer, including several phages of Porphyromonas, Fusobacterium, and Hungatella that were enriched in patients and some control-enriched Ruminococcaceae phages. In 9 discovery cohorts, the optimal risk assessment model obtained an average cross-cohort area under the curve of 0.830 for discriminating colorectal cancer patients from controls. This model also showed consistently high accuracy in 2 independent validation cohorts (optimal area under the curve, 0.906). Gut virome analysis of adenoma patients identified 88 differential viruses and achieved an optimal area under the curve of 0.772 for discriminating patients from controls. Conclusion: Our findings demonstrate the gut virome characteristics in colorectal cancer and adenoma and highlight gut virus-bacterial synergy in the progression of colorectal cancer. The gut viral signatures may be new targets for colorectal cancer treatment. In addition, high repeatability and predictive power of the prediction models suggest the potential of gut viral biomarkers in non-invasive diagnostic tests of colorectal cancer and adenoma. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
