Abstract

Abstract Skin toxicity after anti-PD1 treatment in melanoma patients is the most common type of immune related adverse effect (irAE) and has been associated with improved overall response rate and survival. Nonetheless, not many mechanistic biomarkers have been identified so far, that could be associated with low-grade skin toxicity and good response rates. In this study we have addressed this question by analyzing tumor tissue samples from late-stage melanoma patients with first-line anti-PD1 treatment. Samples obtained prior to treatment were submitted for an unbiased deep proteomic analysis using mass spectrometry (LC-MS) and a targeted transcriptomic analysis. Using the unbiased analysis as a discovery platform we were able to define a potential biomarker panel associated not only with improved response but also low-grade skin toxicity. Unbiased quantification of proteins in tumor tissues was done using data-independent acquisition (DIA) LC-MS technology. Proteins from tissue samples were denatured, digested, and analyzed on a mass spectrometer. A deep spectral library was generated, and proteins were quantified using Spectronaut software (Biognosys). In addition, from the same tumor tissue RNA was extracted and subjected to transcriptomic analysis with NanoString nCounter using the PanCancer IO 360 panel. Subsequent data analysis was done using a sPLS-DA using combined factor of skin toxicity and response. Unbiased analysis of 22 baseline tumor tissue samples from late-stage melanoma patients treated in first line with anti-PD1 resulted in identification and quantification of more than 8000 proteins. Progression free survival analysis showed difference between patients with reported low-grade skin toxicity against all others. Therefore, for sPLS-DA both factors, presence/absence of skin toxicity and response status, were used (non-responders with low-grade skin toxicity were not present in this cohort). Complete separation of subjects was achieved with a panel of 21 proteins. This panel was used for hierarchical clustering and was able to fully restore all three groups of patients. Among all proteins identified in the proteomic panel, melanoma-associated antigen C1 (MAGEC1) has been also assessed in the targeted transcriptomic analysis and represents strikingly similar results. MAGEC1 is also found as a strong predictor in the Human Protein Atlas project. Interestingly, MAGE protein family are tumor-specific antigens that can be recognized by autologous cytolytic T lymphocytes and could serve as a novel ICI target or predictive biomarker. In this study we confirm prior observations of a survival benefit related to irAEs after treatment with PD-1 blockade in late-stage melanoma patients. We also demonstrate the power of deep proteomic profiling and transcriptomic analysis in molecular biomarker selection associated to response and irAEs which further benefit patient survival. Citation Format: Jakob Vowinckel, Domenico Mallardo, Kamil Sklodowski, Martin Soste, Mariaelena Capone, Gabriele Madonna, Vito Vanella, Sarah Warren, Kristina Beeler, Paolo A. Ascierto. Response and skin toxicity related protein signature in late stage melanoma patients after anti-PD-1 treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1623.

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