Towards the Prediction of Responses to Cancer Immunotherapy: A Multi-Omics Review.

ABSTRACT: Tumor treatment has undergone revolutionary changes with the development of immunotherapy, especially immune checkpoint inhibitors. Because not all patients respond positively to immune therapeutic agents, and severe immune-related adverse events (irAEs) are frequently observed, the development of the biomarkers evaluating the response of a patient is key for the application of immunotherapy in a wider range. Recently, various multi-omics features measured by high-throughput technologies, such as tumor mutation burden (TMB), gene expression profiles, and DNA methylation profiles, have been proved to be sensitive and accurate predictors of the response to immunotherapy. A large number of predictive models based on these features, utilizing traditional machine learning or deep learning frame

SUBMITTER: Tao W 

PROVIDER: S-EPMC11856636 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature