김성민 (지니너스)

한빛사논문

조회111

김성민Sung-Min Kim

지니너스

Exp. Mol. Med., Jun 12 2024, | https://doi.org/10.1038/s12276-024-01259-2 The identification of effective tumor-suppressing neoantigens using a tumor-reactive TIL TCR-pMHC ternary complex

Sang Hoon Kim^1,10, Bo Ryeong Lee^1,10, Sung-Min Kim^1,10, Sungsik Kim¹, Min-seok Kim¹, Jaehyun Kim², Inkyu Lee^2,3, Hee-Soo Kim¹, Gi-Hoon Nam^2,4, In-San Kim^3,5, Kyuyoung Song¹, Yoonjoo Choi⁶, Dong-Sup Lee⁷ and Woong-Yang Park^1,8,9

¹Geninus Inc., Seoul 05836, Korea.

²Department of Research and Development, SHIFTBIO Inc., Seoul 02751, Korea.

³KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Korea.

⁴Department of Biochemistry and Molecular Biology, Korea University College of Medicine, Seoul 02841, Korea.

⁵Chemical & Biological Integrative Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea.

⁶Combinatorial Tumor Immunotherapy MRC, Chonnam National University Medical School, Hwasun-gun, Jeollanam-do 58128, Korea.

⁷Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea.

⁸Department of Health Science and Technology, Samsung Advanced Institute of Health Science and Technology, Sungkyunkwan University, Seoul, Korea.

⁹Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.

¹⁰These authors contributed equally: Sang Hoon Kim, Bo Ryeong Lee, Sung-Min Kim.

Corresponding authors

Correspondence to Yoonjoo Choi, Dong-Sup Lee or Woong-Yang Park.

Abstract

Neoantigens are ideal targets for cancer immunotherapy because they are expressed de novo in tumor tissue but not in healthy tissue and are therefore recognized as foreign by the immune system. Advances in next-generation sequencing and bioinformatics technologies have enabled the quick identification and prediction of tumor-specific neoantigens; however, only a small fraction of predicted neoantigens are immunogenic. To improve the predictability of immunogenic neoantigens, we developed the in silico neoantigen prediction workflows VACINUS _pMHC and VACINUS _TCR: VACINUS _pMHC incorporates physical binding between peptides and MHCs (pMHCs), and VACINUS _TCR integrates T cell reactivity to the pMHC complex through deep learning-based pairing with T cell receptors (TCRs) of putative tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs). We then validated our neoantigen prediction workflows both in vitro and in vivo in patients with hepatocellular carcinoma (HCC) and in a B16F10 mouse melanoma model. The predictive abilities of VACINUS _pMHC and VACINUS _TCR were confirmed in a validation cohort of 8 patients with HCC. Of a total of 118 neoantigen candidates predicted by VACINUS _pMHC, 48 peptides were ultimately selected using VACINUS _TCR. In vitro validation revealed that among the 48 predicted neoantigen candidates, 13 peptides were immunogenic. Assessment of the antitumor efficacy of the candidate neoepitopes using a VACINUS _TCR in vivo mouse model suggested that vaccination with the predicted neoepitopes induced neoantigen-specific T cell responses and enabled the trafficking of neoantigen-specific CD8 + T cell clones into the tumor tissue, leading to tumor suppression. This study showed that the prediction of immunogenic neoantigens can be improved by integrating a tumor-reactive TIL TCR-pMHC ternary complex.

논문정보

형식Research article
게재일2024년 06월 (BRIC 등록일 2024-07-04)
연구진국내 연구진
분야 의약학 > 면역의학

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