Abstract
SIMPLE SUMMARY: Combinations of monoclonal antibodies that activate the immune system have been highly effective for treatment of melanoma that has spread (metastasized). Unfortunately, this type of immunotherapy treatment can trigger serious side effects. Thus, it would be valuable to predict patients who are unlikely to benefit from immunotherapy in advance. We evaluated four cancer-related markers to determine their usefulness. The level of two markers in cancer biopsies, PD-1 ligand (PD-L1) staining and tumor mutation burden (the number of mutations per megabase DNA), seemed to best predict treatment responses. In fact, patients who had low levels of both of these markers universally failed to respond to immunotherapy. Further work will be needed to develop computer tools to utilize these two markers to try to predict the potential usefulness of cancer immunotherapy in metastatic melanoma. BACKGROUND: Combination checkpoint inhibitor therapy with ipilimumab plus nivolumab has significantly improved the treatment of patients with metastatic melanoma. This regimen has induced durable complete remissions and improved survival. However, these benefits are associated with a high risk of immune-related adverse events. We evaluated the usefulness of potential predictive biomarkers to determine which patients were unlikely to benefit from immunotherapy. METHODS: A retrospective chart review was conducted of all metastatic melanoma patients treated by a single oncologist with ipilimumab plus nivolumab for advanced cutaneous or subungual melanoma. Baseline biomarkers including BRAF mutation status, serum lactate dehydrogenase levels, PD-L1 expression, and tumor mutation burden were correlated with progression-free survival (PFS). RESULTS: Treatment outcomes were analyzed in 54 sequential patients. BRAF mutation status did not correlate with PFS. Only rare patients presented with an elevated lactate dehydrogenase (LDH); thus, this marker did not prove informative. There was a correlation of increased tumor mutation burden or PD-L1 expression with treatment response. Expression of either marker appeared to correlate with improved progression-free survival. An exploratory analysis suggested that the combination of low tumor cell PD-L1 expression and a low tumor mutation burden predicted an extremely poor immunotherapy response. CONCLUSIONS: Tumor mutation burden and PD-L1 represent potential predictive biomarkers for response to combination CKI therapy, while LDH and BRAF offer limited predictive value. Further work will be needed to develop a predictive nomogram to better aid in predicting potential immunotherapy benefit.