Computational analysis of transcriptomic data to identify PTEN-loss associated alternative splicing (AS) derived neoantigens in cancer datasets

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Neoantigens are a type of tumour specific antigen which can result from aberrations to the DNA or RNA. To date, the most well studied neoantigens have been those arising at the DNA level which predominantly include those arising from genomic variants such as single-nucleotide variants (SNVs) and insertions and deletions (indels) however, exploring other sources of neoantigens for example, from alternative splicing (AS) is important especially in low tumour mutational burden cancers, such as prostate cancer. New non-catalytic functions for PTEN, a tumour suppressor gene, is emerging which include in AS, where PTEN interacting with splicing machinery and the spliceosome has been described. Furthermore, PTEN-loss associated alterations to the immune tumour microenvironment (TME) has been observed. Preliminary findings in our group have found a role for PTEN-loss associated aberrant AS and we hypothesise neoantigens arising from these events could alter tumour cell recognition by immune cells and/or AS-derived proteins from these events could affect immune cell function in the TME. Many machine learning (ML) neoantigen prediction algorithms exist which are trained on data from different stages of the peptide presentation and processing mechanism however, those able to identify AS derived neoantigens are limited. Using a published AS neoantigen prediction algorithm which we updated to predict neoantigens using the latest state-of-the-art ML method, we have extracted putative PTEN-loss associated MHC-I AS-derived neoantigens from DU145 cell-line data that have been depleted of PTEN. Matched mass spectrometry data has been processed to identify translated neoantigens in the samples' own reference proteome. Finally, TCGA prostate cancer data is currently being processed through the same pipelines to identify strong computationally predicted neoantigens in PTEN-loss conditions which will be correlated to the altered immune TME. This research is novel and will elucidate the PTEN-loss associated alterations on the transcriptome and proteome through antigens presented by MHC-I molecules.