Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation.
Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation.
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DOI：
10.3389/fonc.2022.836821
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发表时间：
2022
影响因子：
4.7
通讯作者：
Hastings KT
中科院分区：
文献类型：
--
作者：
Borden ES;Buetow KH;Wilson MA;Hastings KT
免疫原性新抗原的优先化是通过开发个性化疫苗、过继性T细胞疗法和预测对免疫检查点抑制的应答来增强癌症免疫疗法的关键。新抗原是肿瘤特异性蛋白质，其允许免疫系统识别和破坏肿瘤。癌症免疫疗法，如个性化癌症疫苗，过继性T细胞疗法和免疫检查点抑制，依赖于对患者特异性新抗原谱的理解，以指导个性化治疗策略。预测和优先排序免疫原性新抗原的基因组方法正在迅速扩展，为推进这些工具并增强其临床相关性提供了新的机会。预测新抗原需要获取高质量的样品和测序数据，然后进行变异识别和变异注释。随后，优先考虑这些新抗原中的哪一个可以引发肿瘤特异性免疫应答，需要应用和整合工具来预测新抗原的表达、加工、结合和识别潜力。最后，计算工具的改进与具有经验证的免疫原性新抗原的数据集的可用性保持恒定的张力。这篇综述文章的目的是总结新抗原预测，优先排序和验证的现有知识和局限性，并提出未来的发展方向，以改善个性化癌症治疗。
Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recognize and destroy a tumor. Cancer immunotherapies, such as personalized cancer vaccines, adoptive T cell therapy, and immune checkpoint inhibition, rely on an understanding of the patient-specific neoantigen profile in order to guide personalized therapeutic strategies. Genomic approaches to predicting and prioritizing immunogenic neoantigens are rapidly expanding, raising new opportunities to advance these tools and enhance their clinical relevance. Predicting neoantigens requires acquisition of high-quality samples and sequencing data, followed by variant calling and variant annotation. Subsequently, prioritizing which of these neoantigens may elicit a tumor-specific immune response requires application and integration of tools to predict the expression, processing, binding, and recognition potentials of the neoantigen. Finally, improvement of the computational tools is held in constant tension with the availability of datasets with validated immunogenic neoantigens. The goal of this review article is to summarize the current knowledge and limitations in neoantigen prediction, prioritization, and validation and propose future directions that will improve personalized cancer treatment.
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影响因子：
32.4
作者：
Abelin JG;Keskin DB;Sarkizova S;Hartigan CR;Zhang W;Sidney J;Stevens J;Lane W;Zhang GL;Eisenhaure TM;Clauser KR;Hacohen N;Rooney MS;Carr SA;Wu CJ
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Wu CJ
影响因子：
3
作者：
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Meerzaman D
影响因子：
4.8
作者：
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通讯作者：
Ferrone, Soldano
影响因子：
15.9
作者：
Cohen, Cyrille J.;Gartner, Jared J.;Robbins, Paul F.
通讯作者：
Robbins, Paul F.
影响因子：
4.4
作者：
Bhagwate, Aditya Vijay;Liu, Yuanhang;Wang, Chen
通讯作者：
Wang, Chen