The T cell receptor β chain repertoire of tumor infiltrating lymphocytes improves neoantigen prediction and prioritization - Pham, Thi Mong Quynh; Nguyen, Thanh Nhan; Tran Nguyen, Bui Que; Diem Tran, Thi Phuong; Diem Pham, Nguyen My; Phuc Nguyen, Hoang Thien; Cuong Ho, Thi Kim; Linh Nguyen, Dinh Viet; Nguyen, Huu Thinh; Tran, Duc Huy; Tran, Thanh Sang; Pham, Truong Vinh Ngoc; et al. (eLife, 2024)
Keywords: Algorithms; Antigen (tumor-associated); Antigens; Antigens, Neoplasm - genetics; Antigens, Neoplasm - immunology; Cancer Biology; Cancer immunotherapy; Colorectal cancer; Colorectal carcinoma; Colorectal Neoplasms - genetics; Colorectal Neoplasms - immunology; CRC; Enzyme-linked immunosorbent assay; Gene expression; Genomics; Humans; Immune system; Immunotherapy; Information processing; Leukocytes; Lymphocytes; Lymphocytes T; Lymphocytes, Tumor-Infiltrating - immunology; Machine Learning; Metastasis; Mutation; neoantigen; Neoantigens; Patients; Peptides; Performance evaluation; Predictions; Receptors, Antigen, T-Cell, alpha-beta - genetics; Receptors, Antigen, T-Cell, alpha-beta - immunology; Receptors, Antigen, T-Cell, alpha-beta - metabolism; T cell receptors; TCR sequencing; TCRseq; Tumor cells; tumor variant calling; Tumor-infiltrating lymphocytes; Tumors; neoantigen; TCRseq; colorectal cancer; TCR sequencing; neoantigen prioritization; CRC; cancer immunotherapy; cancer biology; human; tumor variant calling