Predictive biomarkers of ipilimumab toxicity in metastatic melanoma.

Abstract

9559 Background: There are no predictive biomarkers of ipilimumab (IPI) toxicity. Of metastatic melanoma (MM) patients (pts) receiving IPI (3mg/kg), 35% require systemic therapies to treat immune-related adverse events (irAEs) and 20% must terminate treatment (Horvat et al., JCO 2015). Here we tested the hypothesis that a pre-existing autoantibody (autoAb) profile is predictive of IPI irAEs. Methods: We measured autoAb levels in pre- and post-treatment sera from mm pts who received IPI (3mg/kg) monotherapy on a proteome microarray containing ~20,000 unique full-length human proteins (HuProt array, CDI Laboratories). Clinical data were prospectively collected with protocol-driven follow-up. IrAEs were categorized by CTCAE guidelines as none (grade 0), mild (grade 1-2), or severe (grade 3-4). AutoAb levels were standardized using median quantile normalization and considered positive hits if > 2-SD above the peak array signal and differed by ≥2 fold with p < 0.05 between toxicity groups (Non-parametric Analysis/Wilcox test). Results: Seventy-eight sera from 37 mm pts were analyzed. Antibodies against CTLA-4 were significantly elevated post IPI treatment (p < 0.0001), validating the assay. The pre-treatment levels of 190 IgG autoAbs were significantly different in pts who experienced irAEs (n = 28) compared to those with no irAEs (n = 9). Comparison of severe irAE (n = 9) and no irAE (n = 9) groups revealed 129 IgG autoAbs that significantly differed in pre-treatment sera. Localization and pathway analysis (UniProt, KEGG, Reactome) showed 81/190 (43%) of the autoAbs targeted nuclear and mitochondrial antigens and were enriched in metabolic pathways (p = 0.015). AutoAbs associated with irAEs did not correlate with treatment response. Conclusions: AutoAbs to antigens enriched in metabolic pathways prior to treatment may predict IPI-induced toxicity in MM. The subcellular localization of targeted antigens could explain the autoimmune toxicities associated with IPI. Studies in larger cohorts and in pts receiving other checkpoint inhibitors and/or combination therapies are essential to determine the validity of the data. If validated, our results would support the discovery of the first toxicity predictor in cancer immunotherapy.