Germline biomarkers predict adverse events from PD-1/PD-L1 checkpoint inhibitors
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Germline microRNA-based biomarkers accurately predicted grade 2 or higher immune-related adverse events associated with anti-PD-1/PD-L1 therapy among patients with various cancer types, according to study results.
Researchers described the findings, published in Journal for Immunotherapy of Cancer, as a key step toward personalizing checkpoint inhibitor therapy among patients with cancer.
Rationale
“This project came out of a collaborative discussion between Antoni Ribas, MD, PhD, FAACR, and I when I first came to UCLA — I was recruited to apply our microRNA genetics to explain patient side effects from radiation therapy,” Joanne B. Weidhaas, MD, PhD, MS, professor and vice chair of the division of molecular and cellular oncology at UCLA Health, told Healio. “It is known that even when patients are treated the same way, some are at risk for toxicity because of their baseline genetics. This is something that we know preexists the treatment but that we had not been able to previously identify. In our discussion, we realized it made a lot of sense to see if the same baseline genetics would explain immune side effects from checkpoint inhibitor therapy.”
Methodology
Weidhaas and colleagues used four classifiers to evaluate microRNA pathway variants for associations with grade 2 or higher adverse events among 62 patients with melanoma. They then validated the performance of the panel among 99 patients with various other cancer types and evaluated the predicted probability of toxicity for its association with response categories to anti-PD-1/PD-L1 therapy in the melanoma cohort.
Key findings
Results showed a biomarker panel predicted toxicity with 80% accuracy (area under the curve [AUC] = 0.82) among individuals in the melanoma cohort and with 77.6% accuracy (AUC = 0.77) among those with other cancer types.
Researchers found no association of the predictive probability of toxicity among patients in the melanoma cohort with response categories to anti-PD-1/PD-L1 therapy. They also found a significant biomarker of toxicity in RAC1 that predicted a more than ninefold increased risk for toxicity (P < .001) had no association with anti-PD-1/PD-L1 therapy treatment response.
“We identified a signature that predicts a very high risk for developing toxicity when given checkpoint inhibitor therapy, an almost 10-fold risk,” Weidhaas said. “Because we measure baseline genetics, this signature can be checked before someone starts treatment.”
Implications
It is critical that physicians and patients know the pros and cons of a treatment to make the best choice of therapy, Weidhaas said.
“Toxicity is a clear con, and in some cases, knowing that someone is at significant risk for toxicity might lead to a different delivery of the treatment or an alternative treatment choice altogether,” she added.
For more information:
Joanne B. Weidhaas, MD, PhD, MS, can be reached at UCLA Health, Westwood Radiation Oncology, 200 Medical Plaza, Suite B265, Los Angeles, CA 90095; email: jweidhaas@mednet.ucla.edu.
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