Germline microRNA-based signatures predict toxicity and response to anti-CTLA-4 therapy
Abstract Background Germline microRNA-based variants (mirSNPs) have been shown to be predictive biomarkers of toxicity and tumor response across cancer treatments, including to anti-PD1/PDL1 immune checkpoint therapy. CTLA-4 inhibitors are another immune checkpoint inhibitor with known significant t...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
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| Series: | Journal of Translational Medicine |
| Online Access: | https://doi.org/10.1186/s12967-025-06842-3 |
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| Summary: | Abstract Background Germline microRNA-based variants (mirSNPs) have been shown to be predictive biomarkers of toxicity and tumor response across cancer treatments, including to anti-PD1/PDL1 immune checkpoint therapy. CTLA-4 inhibitors are another immune checkpoint inhibitor with known significant toxicity in the form of immune related adverse events (irAEs). The potential of mirSNPs to predict irAEs and/or response to anti-CTLA-4 therapy alone has not previously been reported and was the purpose of this investigation. Methods We evaluated genetic signatures to predict toxicity and tumor response to anti-CTLA-4 treatment alone in melanoma patients using three separate cohorts. DNA was extracted from blood samples from 77 patients treated with anti-CTLA-4 therapy and analyzed using a custom panel of mirSNPs. We employed a combination of Elastic Net, Random Forest, and Boosted Tree models, incorporating germline mirSNPs, patient demographics, and treatment variables to predict toxicity in the form of irAEs or disease response. Additionally, we conducted a comparative analysis of gene ontology (GO) pathways to discern biological differences influenced by these genetic markers. Results We developed two unique mirSNP signatures predicting toxicity or response to single agent anti-CTLA-4 treatment. These signatures both have excellent predictive accuracy with AUCs of 0.793 for toxicity and of 0.842 for response. The signatures do not overlap, nor is the toxicity signature similar to the toxicity signature for anti-PD1/L1 single agent therapy. Through GO analyses we found that both of these signatures have biological pathways involved in pri-miRNA transcriptional regulation, yet also have unique pathways that differentiate them. Conclusions Our findings continue to support the utility of mirSNPs as predictive biomarkers of immune checkpoint therapy, for both toxicity and response. Further investigation in larger, diverse cohorts as well as to dual checkpoint inhibitor treatment is a planned next step to further their application. |
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| ISSN: | 1479-5876 |