CapHLA: a comprehensive tool to predict peptide presentation and binding to HLA class I and class II.

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Briefings in bioinformatics Pub Date : 2024-11-22 DOI:10.1093/bib/bbae595
Yunjian Chang, Ligang Wu
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Abstract

Human leukocyte antigen class I (HLA-I) and class II (HLA-II) proteins play an essential role in epitope binding and presentation to initiate an immune response. Accurate prediction of peptide-HLA (pHLA) binding and presentation is critical for developing effective immunotherapies. However, current tools can predict antigens exclusively for pHLA-I or pHLA-II, but not both; have constraints on peptide length; and commonly show unsatisfactory predictive accuracy. Here, we developed a convolution and attention-based model, CapHLA, trained with eluted ligand and binding affinity mass spectrometry data, to predict peptide presentation probability (PB) and binding affinities (BA) for HLA-I and HLA-II. In comparison with 11 other methods, CapHLA consistently showed improved performance in predicting pHLA BA and PB, particularly in HLA-II and non-classical peptide length datasets. Using CapHLA PB and BA predictions in combination with antigen expression level (EP) from transcriptomic data, we developed a neoantigen quality model for predicting immunotherapy response. In analyses of clinical response among 276 cancer patients given immunotherapy and overall survival in 7228 cancer patients, our neoantigen quality model outperformed other genetics-based models in predicting response to checkpoint inhibitors and patient prognosis. This study provides a versatile neoantigen screening tool, illustrating the prognostic value of neoantigen quality.

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CapHLA:预测肽呈现和结合HLA I类和HLA II类的综合工具。
人类白细胞抗原I类(HLA-I)和II类(HLA-II)蛋白在表位结合和呈递中发挥重要作用,从而启动免疫应答。准确预测肽- hla (pHLA)结合和呈递对于开发有效的免疫疗法至关重要。然而,目前的工具只能预测phla - 1或pHLA-II的抗原,但不能同时预测两者;对肽长度有限制;并且通常表现出令人不满意的预测准确性。在这里,我们开发了一个基于卷积和注意力的模型CapHLA,使用洗脱配体和结合亲和质谱数据进行训练,以预测HLA-I和HLA-II的肽呈现概率(PB)和结合亲和度(BA)。与其他11种方法相比,CapHLA在预测pHLA BA和PB方面始终表现出更好的性能,特别是在HLA-II和非经典肽长度数据集中。利用CapHLA PB和BA预测结合转录组学数据的抗原表达水平(EP),我们建立了一个预测免疫治疗反应的新抗原质量模型。在对276名接受免疫治疗的癌症患者的临床反应和7228名癌症患者的总生存期的分析中,我们的新抗原质量模型在预测对检查点抑制剂的反应和患者预后方面优于其他基于遗传学的模型。这项研究提供了一种多功能的新抗原筛选工具,说明了新抗原质量的预后价值。
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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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