US 12,462,897 B2
Method and system of targeting epitopes for neoantigen-based immunotherapy
Brandon Malone, Dossenheim (DE); Kousuke Onoue, Kanagawa (JP); and Yoshiko Yoshihara, Kanagawa (JP)
Assigned to NEC CORPORATION, Tokyo (JP)
Appl. No. 17/281,707
Filed by NEC CORPORATION, Tokyo (JP)
PCT Filed Nov. 20, 2019, PCT No. PCT/EP2019/081960
§ 371(c)(1), (2) Date Mar. 31, 2021,
PCT Pub. No. WO2020/104539, PCT Pub. Date May 28, 2020.
Claims priority of provisional application 62/770,220, filed on Nov. 21, 2018.
Prior Publication US 2021/0391031 A1, Dec. 16, 2021
Int. Cl. G16B 20/20 (2019.01); G16B 20/30 (2019.01); G16B 30/10 (2019.01); G16B 40/20 (2019.01)
CPC G16B 20/20 (2019.02) [G16B 20/30 (2019.02); G16B 30/10 (2019.02); G16B 40/20 (2019.02)] 6 Claims
OG exemplary drawing
 
1. A method of ranking candidate epitopes derived from neoantigens as targets for personalized immunotherapy, the method comprising:
extracting experimentally-verified properties of epitopes and domain knowledge about the epitopes;
embedding each of the epitopes in a vector space based on the experimentally-verified properties and the domain knowledge;
collecting candidate epitopes based on patient data of a cancer patient;
calculating a set of scores for each of the candidate epitopes, each score in a respective one of the sets for a respective one of the candidate epitopes representing an independent measure of a likelihood of the respective one of candidate epitopes to elicit an immune response in the cancer patient,
wherein each of the sets of scores includes at least a first score indicating a likelihood of human leukocyte antigen (HLA) binding which is determined using HLA alleles which are specific to the cancer patient, and a second score indicating a T-cell response which is predicted using a T-cell receptor (TCR) repertoire which is identified using healthy ribonucleic acid (RNA) sequence data specific to the cancer patient; combining the scores in each of the sets of scores into a single score for each of the candidate epitopes, the single scores for the candidate epitopes in each case reflecting an overall likelihood of eliciting the immune response in the patient;
ranking the candidate epitopes using the single scores and the embeddings for the immunotherapy, wherein the ranking is performed in an order of largest weighted distances in the vector space, the weighted distances in each case being determined based on Euclidean distances in the vector space multiplied by the single score for each respective one of the candidate epitopes such that one of the candidate epitopes with a largest weighted distance from an origin of the vector space is ranked first followed by one of the candidate epitopes having a largest weighted difference from the top-ranked epitope;
producing a neopeptide, a polynucleotide encoding the neopeptide, a vector containing the polynucleotide encoding the neopeptide, a messenger ribonucleic acid (mRNA) encoding the neopeptide, an antigen-presenting cell presenting a complex of the neopeptide and a human leukocyte antigen (HLA) molecule on the surface, an exosome secreted from the antigen-presenting cell, or a combination thereof,
wherein the neopeptide comprises at least one of the ranked candidate epitopes.