Emerging multifaceted roles of the microbiome in cancer susceptibility
Identifying the factors that contribute to individual susceptibility to cancer is essential for both prevention and treatment. The advancement of biotechnologies, particularly next-generation sequencing, has accelerated the discovery of genetic variants linked to cancer susceptibility. While hundred...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/424435 |
| Acceso en línea: | http://hdl.handle.net/10261/424435 |
| Access Level: | acceso abierto |
| Palabra clave: | Cancer susceptibility Genetic variants Genome-wide association study Missing heritability Microbiome Microbiome-wide association study |
| Sumario: | Identifying the factors that contribute to individual susceptibility to cancer is essential for both prevention and treatment. The advancement of biotechnologies, particularly next-generation sequencing, has accelerated the discovery of genetic variants linked to cancer susceptibility. While hundreds of cancer-susceptibility genes have been identified, they only explain a small fraction of the overall cancer risk, a phenomenon known as "missing heritability". Despite progress, even considering factors such as epistasis, epigenetics, and gene-environment interactions, the missing heritability remains unresolved. Recent research has revealed that an individual's microbiome composition plays a significant role in cancer susceptibility through several mechanisms, such as modulating immune cell activity and influencing the presence or removal of environmental carcinogens. In this review, we examine the multifaceted roles of the microbiome in cancer risk and explore gene-microbiome and environment-microbiome interactions that may contribute to cancer susceptibility. Additionally, we highlight the importance of experimental models, such as collaborative cross mice, and advanced analytical tools, like artificial intelligence, in identifying microbial factors associated with cancer risk. Understanding these microbial determinants can open new avenues for interventions aimed at reducing cancer risk and guide the development of more effective cancer treatments. |
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