Validating novel AI-predicted targets for alternative cancer immunotherapy

Anti-cancer Immunotherapy (IT) has a huge potential but faces challenges of insufficient efficacy and resistance, in part due to the immunosuppressive (ImmuSup) nature of the endothelial cells (ECs) lining the tumor vasculature. I aim to tune these ECs from ImmuSup to immunostimulatory as an alternative IT (alterIT). I fully realize that (too) many basic research results run ashore in the proverbial ‘Valley of Death’ and fail to translate into drugs/clinical treatments due to selectivity and toxicity issues following suboptimal initial target selection and validation. Therefore, I will 1) use the in-house developed artificial intelligence (AI)-based scMysterYdentifier tool to identify truly novel ImmuSup genes in the ‘mystery genome’ (1/3 of the genome that lacks functional annotation), a true goldmine for innovative target discovery; 2) directly validate in vivo the predicted ImmuSup mystery genes by generating EC-selective knockout mice rapidly (days)/inexpensively using a new in-house developed transgenic REVOLT technology; 3) perform initial selectivity/toxicity assessment by elaborate (in silico) target expression analyses. All approaches are operational. Perspectives: thoroughly in vivo validated innovative and selective EC ImmuSup mystery targets for alterIT with enhanced potential to ‘bridge the Valley of Death’.