Abstract PO-050: Computational modeling of immunologic response to immune checkpoint inhibitors in COVID-19 patients with and without cancer

Abstract

Abstract Cancer patients have an increased risk of severe COVID-19 infection due to the suppression of the immune system and the development of cytokine release syndrome (CRS) that favor respiratory syndromes and interstitial pneumonia. However, substantial differences exist between patients treated with chemotherapy and patients treated with immune checkpoint inhibitors (ICIs), for which the risk of COVID-19 infection and the immunologic and cytokine profile in case of infection have not yet been well characterized. The administration of ICIs for the treatment of severe COVID-19 infection has been recently suggested. However, no conclusive data have been generated on this matter. To recognize the therapeutic potential of ICIs administration in COVID-19 patients with or without cancer, the Universal Immune System Simulator (UISS) prediction model was used to simulate the immunologic response of COVID-19 patients after ICIs administration. Briefly, UISS represents an appropriate computational modeling infrastructure able to simulate the dynamics of every single entity of the immune system after a stimulus or a therapeutic intervention by using an agent-based methodology. Therefore, the UISS platform, already used for the prediction of the efficacy of specific SARS-CoV-2 candidate vaccines, was here adopted to characterize the immunologic behavior in both COVID-19 and cancer patients and to predict the effects of ICIs in these patients. The computational results allowed us to identify key inflammatory and immune-related factors responsible for severe respiratory syndromes in COVID-19 infected patients with and without cancer. UISS results suggest that the administration of ICIs modulates the immune system and the inflammatory status in both groups of patients with COVID-19 infection, reducing the risk of severe symptoms. Although the results of the present study are still under validation in peripheral blood samples obtained from COVID-19 patients and from cancer patients after two cycles of treatment with ICIs, we can speculate that ICIs may be a good therapeutic approach for the treatment of COVID-19 severe respiratory syndrome even with a concomitant cancer diagnosis. If this is the case, the lower expression levels of inflammatory biomarkers can result in the drop-down of the viral load, assessed by droplet digital PCR in COVID-19 patients. Citation Format: Giulia Russo, Luca Falzone, Bruno Cacopardo, Giuseppe Nunnari, Francesco Torino, Giuseppa Scandurra, Stefania Stefani, Francesco Pappalardo, Massimo Libra. Computational modeling of immunologic response to immune checkpoint inhibitors in COVID-19 patients with and without cancer [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr PO-050.