Novel multi-disciplinary strategy to identify and target unconventional (neo)epitopes suitable for immunotherapy against colorectal cancer.

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Identification of neoepitopes in cancer patient allows for the development of immunotherapies aimed at targeting them. Currently, there is a lack of known targetable epitope identified in colorectal cancer (CRC). Prediction algorithms have been developed that aim to predict the repertoire of antigens that will be presented at the cell surface. This includes prediction of peptide products generated following proteasomal cleavage, the binding affinity of those products to antigen-presenting MHC-I molecules, as well as predictors of MHC-bound peptide binding to T-cell receptors (TCR). These predictors currently suffer from lack of accuracy, due to insufficient amount of high-quality datasets for training. The highly specific interaction between HLA-I molecules and antigens dictated by stringent motif requirements restricts binding of many antigenic sequences. Recently the potential of proteasome-generated spliced epitopes in immunotherapies have garnered attention, as the theoretical combination of sequences that can be generated from this opens up an untapped pool of potential targets. However, the frequency of spliced peptide presentation remains a controversy, with estimates ranging from 1-34%. Nonetheless, previous works, including some in the Mishto lab (1), have demonstrated that proteasome-generated spliced epitopes could be targets for immunotherapies. Other noncanonical sources of epitopes such as non-coding regions of the genome have recently been investigated and proposed as immunotherapy targets. Response to therapy with immune checkpoint inhibitors (ICI) has been associated with activation and expansion of antigen-specific T-cells. Relatedly, the neoantigen burden has been found to correlate with response to ICI, however on its own is not sufficient as a predictor. Indeed, research conducted by the Ciccarelli lab investigating data obtained from a cohort of 29 CRC patients recently demonstrated the predictive power of mutational clonality in determining response to ICI (2). From this cohort, TCRsequences have been obtained, which indicated the presence of expanded clones. Hence investigating their cognate antigens, in relation to clonality and response to ICI therapy may aid in identifying optimal targets for combination therapy (adoptive T-cell therapy + ICI). Additionally, targeting of antigens that are shared or that derive from driver mutations present an attractive therapeutic option, given that it would enable the development of a broad-spectrum therapy, or would target a protein that drives cancer-cell survival, respectively.