Biotechnol. 2023; Online ahead of print . [CrossRef] 37. Lybaert, L.; Lefever, S.; Fant, B.; Smits, E.; De Geest, B.; Breckpot, K.; Dirix, L.; Feldman, S.A.; Van Criekinge, W.; Thielemans, K.; et al. Challenges in Neoantigen-Directed Therapeutics. Cancer Cell 2023 ,41, 15–40. [CrossRef] [PubMed] 38. Xie, N.; Shen, G.; Gao, W.; Huang, Z.; Huang, C.; Fu, L. Neoantigens: Promising Targets for Cancer Therapy. Signal Transduct. Target. Ther. 2023 ,8, 9. [CrossRef] 39. Blass, E.; Ott, P .A. Advances in the Development of Personalized Neoantigen-Based Therapeutic Cancer Vaccines. Nat. Rev. Clin. Oncol. 2021 ,18, 215–229. [CrossRef] 40. Katsikis, P .D.; Ishii, K.J.; Schliehe, C. Challenges in Developing Personalized Neoantigen Cancer Vaccines. Nat. Rev. Immunol. 2024 ,24, 213–227. [CrossRef] 41. Lang, F.; Schrörs, B.; Löwer, M.; Türeci, Ö.; Sahin, U. Identification of Neoantigens for Individualized Therapeutic Cancer Vaccines. Nat. Rev. Drug Discov. 2022 ,21, 261–282. [CrossRef] 42. Bjerregaard, A.-M.; Nielsen, M.; Hadrup, S.R.; Szallasi, Z.; Eklund, A.C. MuPeXI: Prediction of Neo-Epitopes from Tumor Sequencing Data. Cancer Immunol. Immunother. 2017 ,66, 1123–1130. [CrossRef] [PubMed] 43. Zhang, J.; Mardis, E.R.; Maher, C.A. INTEGRATE-Neo: A Pipeline for Personalized Gene Fusion Neoantigen Discovery. Bioinformatics 2017 ,33, 555–557. [CrossRef] [PubMed] 44. Schenck, R.O.; Lakatos, E.; Gatenbee, C.; Graham, T.A.; Anderson, A.R.A. NeoPredPipe: High-Throughput Neoantigen Prediction and Recognition Potential Pipeline. BMC Bioinform. 2019 ,20, 264. [CrossRef] [PubMed] 45. Zhou, C.; Wei, Z.; Zhang, Z.; Zhang, B.; Zhu, C.; Chen, K.; Chuai, G.; Qu, S.; Xie, L.; Gao, Y.; et al. pTuneos: Prioritizing Tumor Neoantigens from next-Generation Sequencing Data. Genome Med. 2019 ,11, 67. [CrossRef] 46. Zhang, Z.; Zhou, C.; Tang, L.; Gong, Y.; Wei, Z.; Zhang, G.; Wang, F.; Liu, Q.; Yu, J. ASNEO: Identification of Personalized Alternative Splicing Based Neoantigens with RNA-Seq. Aging 2020 ,12, 14633–14648. [CrossRef] [PubMed] 47. Fotakis, G.; Rieder, D.; Haider, M.; Trajanoski, Z.; Finotello, F. NeoFuse: Predicting Fusion Neoantigens from RNA Sequencing Data. Bioinformatics 2020 ,36, 2260–2261. [CrossRef] [PubMed] 48. Hundal, J.; Kiwala, S.; McMichael, J.; Miller, C.A.; Xia, H.; Wollam, A.T.; Liu, C.J.; Zhao, S.; Feng, Y.-Y.; Graubert, A.P .; et al. pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens. Cancer Immunol. Res. 2020 ,8, 409–420. [CrossRef] [PubMed] 49. Lu, T.; Wang, S.; Xu, L.; Zhou, Q.; Singla, N.; Gao, J.; Manna, S.; Pop, L.; Xie, Z.; Chen, M.; et al. Tumor Neoantigenicity Assessment with CSiN Score Incorporates Clonality and Immunogenicity to Predict Immunotherapy Outcomes. Sci. Immunol. 2020 ,5, eaaz3199. [CrossRef] 50. Diao, K.; Chen, J.; Wu, T.; Wang, X.; Wang, G.; Sun, X.; Zhao, X.; Wu, C.; Wang, J.; Yao, H.; et al. Seq2Neo: A Comprehensive Pipeline for Cancer Neoantigen Immunogenicity Prediction. Int.