Computational Pipeline for the PGV-001 Neoantigen Vaccine Trial

Abstract

This paper describes the sequencing protocol and computational pipeline for the PGV-001 personalized vaccine trial. PGV-001 is a therapeutic peptide vaccine targeting neoantigens identified from patient tumor samples. Peptides are selected by a computational pipeline that identifies mutations from tumor/normal exome sequencing and ranks mutant sequences by a combination of predicted Class I MHC affinity and abundance estimated from tumor RNA. The personalized genomic vaccine (PGV) pipeline is modular and consists of independently usable tools and software libraries. We hope that the functionality of these tools may extend beyond the specifics of the PGV-001 trial and enable other research groups in their own neoantigen investigations.

Peptide–TLR-7/8a conjugate vaccines chemically programmed for nanoparticle self-assembly enhance CD8 T-cell immunity to tumor antigens

“…Predicted or measured MHC-I binding affinity is considered an important predictor of immunogenicity 48 and is commonly used in the selection of neoantigens to include in PCVs 6,49,50 .…”

Immunology‐Guided Biomaterial Design for Mucosal Cancer Vaccines

“…The type of antigens investigated, along with any complementary adjuvants or immunotherapy arms, dosing schedules, toxicities, and route of administration may inform the future design of engineered vaccines in order to achieve the desired antitumor response in mucosal tissues. For example, several clinical trials have combined adjuvants with varied TAAs‐derived synthetic peptides, autologous whole tumor cells lysate or personalized genomic vaccines, whereby the resected tumor of each individual is sequenced and synthetic peptides are identified using a computational pipeline . Other trials have examined the therapeutic efficacy of vaccines in combination with immunotherapy, including the programmed death protein 1 (PD‐1) inhibitor nivolumab, programmed death‐ligand 1 (PD‐L1) inhibitor atezolizumab, and utomilumab (a monoclonal antibody against CD137) .…”

“…For example, several clinical trials have combined adjuvants with varied TAAs‐derived synthetic peptides, autologous whole tumor cells lysate or personalized genomic vaccines, whereby the resected tumor of each individual is sequenced and synthetic peptides are identified using a computational pipeline . Other trials have examined the therapeutic efficacy of vaccines in combination with immunotherapy, including the programmed death protein 1 (PD‐1) inhibitor nivolumab, programmed death‐ligand 1 (PD‐L1) inhibitor atezolizumab, and utomilumab (a monoclonal antibody against CD137) . Indeed, identifying combination, synergistic therapies, and exploration of the mucosal route for vaccination may yield further progress.…”

“…[82,83] Other trials have examined the therapeutic efficacy of vaccines in combination with immunotherapy, including the programmed death protein 1 (PD-1) inhibitor nivolumab, programmed deathligand 1 (PD-L1) inhibitor atezolizumab, and utomilumab (a monoclonal antibody against CD137). [83,84] Indeed, identifying combination, synergistic therapies, and exploration of the mucosal route for vaccination may yield further progress.…”

Identification of immunogenic mutant neoantigens in the genome of murine melanoma

“…Основываясь на рекомен дациях, предложенных в работах J.C. Castle, S. Kreiter и соавт. и A. Rubinsteyn, J. Kodysh и соавт., было ре шено использовать длины 25-27 аа [3,12]. Дополни тельно пайплайном производили расчет синтезируемости всех предложенных пептидов по нескольким параметрам и для каждого пептида приводили фи нальный рейтинг, по которому выполняется ранжи рование пептидов.…”