Proteomic determinants of response to checkpoint blockade in malignant pleural mesothelioma

About This Grant

PROJECT SUMMARY / ABSTRACT Malignant pleural mesothelioma (MPM) is a highly aggressive asbestos-related malignancy of the pleura for which effective therapy is highly limited. Recent clinical trials have shown that immune checkpoint inhibition (ICI) result in durable clinical benefit in ~50% of patients with MPM. Reciprocally, only ~50% of patients benefit at all from therapy and objective responses occur in less than 20% of patients. There are currently no reliable biomarkers (including PD-L1 expression) that identify individuals with MPM who are likely to respond to ICI and identification of such a pre-treatment biomarker prior could avoid unnecessary toxicity, triage non-responders to other treatment modalities, and extend long-term survival. We constructed a single cell atlas of immune organization in human MPM using time-of-flight mass cytometry (CyTOF) and identified two dominant cellular networks within its tumor immune microenvironment (TiME) that discriminated response and resistance to ICI. Based on the frequencies of key cell types from these opposing networks, we designed a “real-TiME” score for predicting the likelihood of response to ICI in MPM. To accelerate clinical translation, we developed and validated a bioinformatics platform to abstract this score from clinical tissue sections using imaging mass cytometry (IMC) and show robust prediction of response in a sample cohort of ICI-treated MPM patients. Further, mechanisms of response to ICI in MPM are unknown and their understanding will advance the care of patients with this disease. In some tumor types, neoantigen burden is predictive of response to ICI, however these findings are inconsistent and clinical studies have relied exclusively on in silico prediction methods to derive neoantigen burden. We used mass spectrometry (MS) to quantify the amounts of neoantigens within MPM tumors and our recent studies were the first to evaluate the relationship between the actual presence of tumor neoantigens within tumors and responses to immunotherapy. In Aim 1, we will test our hypothesis that response and resistance to ICI can be predicted by a novel single cell immunoproteomic score that can be translated to clinical tissue sections, using prospectively collected pre-treatment tumors from MPM patients treated with ICI. In Aim 2, we will test our hypothesis that response to ICI is more accurately predicted by neoantigen abundance than computationally- derived estimates of neoantigen burden, and is dependent on concordant expression of neoantigens and the MHC proteins specific for those neoantigens. In Aim 3, we will test our hypothesis that that a balance between the repertoire of HLA-presented peptides of MPM, its immunopeptidome, and its TiME regulate response and resistance to ICI. Our results will define core elements of the immunoproteomic structure of MPM that may improve treatment and potentially redirect efforts in the expanding field of immuno-oncology.