Background, rationale: Adenocarcinoma of the esophagus or esophagus/gastric junction (EAC) is an aggressive disease with median overall survival of less than a year. EAC patients undergo neoadjuvant chemo/chemoradiotherapy (NAC/R) followed by surgery, but only 20-30% of them respond. However, a fraction of patients failing NAC/R respond to adjuvant immunotherapy by immune checkpoint blockade with anti-PD-1 mAb, suggesting the ability of EAC to generate tumor antigens stimulating autologous T cell responses.
Hypothesis: We posit that adjuvant immunotherapy response of EAC patients can be further improved by enhancing anti-tumor T cell responses by approaches, entailing vaccination with tumor-specific antigens and/or adoptive transfer of ex vivo expanded tumor-specific T cells.
Aims: Our main objective is to provide proof of concept for the feasibility of integrating bioinformatics, biotechnology, artificial intelligence and immunology to T-Plex-Capture, an innovative multiplex platform enabling the identification of HLA-I-presented neoantigens for cancer vaccines, and the isolation of respective autologous CD8+ T cells and T cell receptors (TCRs) for adoptive cell therapy.
Methods: WES and RNA-seq data from EAC samples of patients not responding to NAC/R will be utilized to in silico predict HLA-I presented mutated or frameshift tumor peptides by advanced artificial intelligence platforms. Predicted epitopes will be incorporated into recombinant HLA-I proteins and coated onto color-coded T-Plex-Capture magnetic beads, which will be applied to isolate autologous tumor-specific CD8+ T cells, followed by single-cell TCR sequencing and functional validation of cloned TCRs.
Expected results and potential impact: With this innovative strategy, we intend to accelerate the presently cumbersome workflow of identification of tumor neoantigens and of specific T cells/TCRs, for their clinical application to improve the response of EAC patients to adjuvant immunotherapy.