The presence of exhausted T cells in tumors is associated with response to PD-1 and CTLA4 checkpoint blockade. However, we do not understand on a mechanistic level how this operates. There are currently two models of T cell-mediated cell killing: the first model is of short-lived activation of exhausted cells followed by clonal replacement and the second model is one of generation of longer-lived clonal cells from exhausted T cells. I discuss these models and the implications arising from these and consider the possibilities for drug development.

Despite partial success of tumor mutational burden and PD-1 expression as predictors of responsiveness to immune checkpoint inhibitors (ICI), precise prediction of patient responsiveness to ICIs is still an open problem. We present an approach wherein putative predictors, in this case CT imaging radiomic features, are tested as covariates in a dynamic model of tumor size changes. We believe this approach can become a platform for testing ICI predictive markers.

Among immunotherapies, checkpoint inhibitors targeting CTLA-4 and PD-1/L1 have had the greatest and most widespread impact on patient outcomes to date. However, identification of the biomarkers and mechanisms associated with benefit – and rare immune-related adverse effects (irAEs) – have not yet been effectively established. We will discuss translational efforts to identify patients who benefit most from PD-1-targeted immunotherapy as well as early efforts to understand the mechanisms of irAEs in order to identify and minimize risk to patients.

Autoantibodies, also referred to as tumour-associated antibodies, are being increasingly recognised and a biomarker class for the prediction of response and immune-related adverse events (irAEs) for immuno-oncology treatments. This presentation will cover Oncimmune's ImmunoINSIGHTS profiling activities with examples in CPI therapies, oncolytic viruses and vaccines.

The CITN coordinates multi-center immunotherapy trials paired closely with cross-platform correlative biomarker studies shared across trials, including multiparametric cytometry performed in real time on longitudinal samples (for pharmacodynamics) matched with subsequent multiplex analyses of the TME. Re-analyses of cytometry PD data using a unique, unbiased computational approach has uncovered unexpected minor cell subtypes in peripheral blood associated with clinical outcomes. Corresponding TME analyses support these results, suggesting their relevance as predictive biomarkers.

In cancer, small (30-150 nm) extracellular vesicles (sEVs) also referred to as “exosomes” emerge as potential biomarkers of disease progression and response to therapy. Specifically, tumor-derived exosomes (TEX), which mimic tumor cells in molecular content, serve as non-invasive tumor biopsy surrogates. TEX can be isolated by immunocapture from patients’ plasma, and their molecular cargo as well as functions determined, allowing for correlations of the TEX molecular profiles with each patient’s clinicopathologic endpoints. Exosome-based monitoring of cancer progression is a potentially transformative approach to precision oncology.

We will review the role of the cancer genome on tumor immunity. We will focus on new development of utilizing tumor mutation burden in clinical practice, the role of HLA diversity, and how a variety of oncogenic mutations and tumor suppressors affect cancer immunity. We will briefly review latest findings from scRNA-seq data on microenvironmental influences on tumor immunity.

We demonstrate that a replication stress response (RSR) defect gene expression signature accurately predicts immune checkpoint blockade (ICB) response in 10 independent non-hypermutated patient cohorts from 5 tumor lineages for which other biomarkers failed. Our preclinical studies indicate that aberrant origin firing in RSR deficient tumor cells causes exhaustion of replication protein A, resulting in accumulation of immunostimulatory cytosolic DNA. Pharmacological RSR defect induction further enhances the responses of cancers to ICB.

Malignant mesothelioma is a fatal asbestos-associated malignancy arising in the mesothelial layer of lung, heart and most of the organs in the abdomen. The response to checkpoint inhibition therapy in mesothelioma patients has been neither uniform nor predictable. To address this, we explored both innate and adaptive immune signatures among mesothelioma patients and found distinct signatures associated with specific clinical features. Immune profiling of the mesothelioma tumor microenvironment may provide a deeper understanding of immune responses to this tumor and potentially guide therapeutic strategies of individual mesothelioma patients.