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DNA damage response-related immune activation signature predicts the response to immune checkpoint inhibitors: from gastrointestinal cancer analysis to pan-cancer validation. | LitMetric

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Article Abstract

Objective: DNA damage response (DDR) deficiency has emerged as a prominent determinant of tumor immunogenicity. This study aimed to construct a DDR-related immune activation (DRIA) signature and evaluate the predictive accuracy of the DRIA signature for response to immune checkpoint inhibitor (ICI) therapy in gastrointestinal (GI) cancer.

Methods: A DRIA signature was established based on two previously reported DNA damage immune response assays. Clinical and gene expression data from two published GI cancer cohorts were used to assess and validate the association between the DRIA score and response to ICI therapy. The predictive accuracy of the DRIA score was validated based on one ICI-treated melanoma and three pan-cancer published cohorts.

Results: The DRIA signature includes three genes (, , and ). In the discovery cancer cohort, DRIA-high patients with gastric cancer achieved a higher response rate to ICI therapy than DRIA-low patients (81.8% 8.8%; < 0.001), and the predictive accuracy of the DRIA score [area under the receiver operating characteristic curve (AUC) = 0.845] was superior to the predictive accuracy of PD-L1 expression, tumor mutational burden, microsatellite instability, and Epstein-Barr virus status. The validation cohort demonstrated that the DRIA score identified responders with microsatellite-stable colorectal and pancreatic adenocarcinoma who received dual PD-1 and CTLA-4 blockade with radiation therapy. Furthermore, the predictive performance of the DRIA score was shown to be robust through an extended validation in melanoma, urothelial cancer, and pan-cancer.

Conclusions: The DRIA signature has superior and robust predictive accuracy for the efficacy of ICI therapy in GI cancer and pan-cancer, indicating that the DRIA signature may serve as a powerful biomarker for guiding ICI therapy decisions.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10976329PMC
http://dx.doi.org/10.20892/j.issn.2095-3941.2023.0303DOI Listing

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