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Germline microRNA-based signatures predict toxicity and response to anti-CTLA-4 therapy
Joanne B Weidhaas1, Kristen M McGreevy2, Nicholas Marco2,3
1UCLA David Geffen School of Medicine, Los Angeles, CA, USA. JWeidhaas@mednet.ucla.edu.
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.
Insights
Germline microRNA variants (mirSNPs) can predict toxicity and response to CTLA-4 inhibitors in melanoma. These genetic signatures offer valuable biomarkers for personalized immune checkpoint therapy.
Area of Science:
- Oncology
- Immunotherapy
- Genetics
Background:
- Germline microRNA variants (mirSNPs) are known biomarkers for anti-PD1/PDL1 therapy response and toxicity.
- CTLA-4 inhibitors cause significant immune-related adverse events (irAEs), but predictive biomarkers are needed.
- The predictive potential of mirSNPs for anti-CTLA-4 therapy has not been previously investigated.
Purpose of the Study:
- To investigate the utility of mirSNPs in predicting irAEs and/or response to anti-CTLA-4 therapy alone.
- To identify genetic signatures for toxicity and tumor response in melanoma patients treated with anti-CTLA-4 inhibitors.
Main Methods:
- Evaluated genetic signatures in three melanoma patient cohorts (n=77) treated with anti-CTLA-4 therapy.
- Utilized DNA from blood samples analyzed with a custom mirSNP panel.
- Employed machine learning models (Elastic Net, Random Forest, Boosted Tree) with mirSNPs, demographics, and treatment variables.
- Conducted gene ontology (GO) pathway analysis to understand biological underpinnings.
Main Results:
- Developed two distinct mirSNP signatures with high predictive accuracy for toxicity (AUC=0.793) and response (AUC=0.842).
- Signatures were unique and did not overlap with each other or with previously reported anti-PD1/L1 toxicity signatures.
- GO analysis revealed shared pathways in pri-miRNA transcriptional regulation and unique differentiating pathways for each signature.
Conclusions:
- Germline mirSNPs are valuable predictive biomarkers for both toxicity and response in immune checkpoint therapy.
- Findings support the utility of mirSNPs for predicting outcomes in anti-CTLA-4 therapy.
- Future research will focus on larger cohorts and dual checkpoint inhibitor treatments.
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