Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, 1011 Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University Hospital of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
Agora Cancer Research Centre, 1011 Lausanne, Switzerland; Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University Hospital of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
CD8 +
识别病原体或癌症特异性表位
T 细胞对于感染的清除和对癌症免疫疗法的反应至关重要。此过程需要表位呈现在 I 类人类白细胞抗原 (HLA-I) 分子上并被 T 细胞受体 (TCR) 识别。捕捉免疫识别的这两个方面的机器学习模型是改进表位预测的关键。在这里,我们组装了一个高质量的自然呈现的 HLA-I 配体和实验验证的新表位数据集。然后,我们将这些数据整合到一个改进的计算框架中,以预测抗原呈递 (MixMHCpred2.2) 和 TCR 识别 (PRIME2.0)。我们训练数据的深度和算法的发展改进了对 HLA-I 配体和新表位的预测。前瞻性地将我们的工具应用于 SARS-CoV-2 蛋白揭示了几个表位。
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T 细胞针对这些表位之一,并与其他冠状病毒的同源肽发生交叉反应。
The recognition of pathogen or cancer-specific epitopes by CD8
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T cells is crucial for the clearance of infections and the response to cancer immunotherapy. This process requires epitopes to be presented on class I human leukocyte antigen (HLA-I) molecules and recognized by the T-cell receptor (TCR). Machine learning models capturing these two aspects of immune recognition are key to improve epitope predictions. Here, we assembled a high-quality dataset of naturally presented HLA-I ligands and experimentally verified neo-epitopes. We then integrated these data in a refined computational framework to predict antigen presentation (MixMHCpred2.2) and TCR recognition (PRIME2.0). The depth of our training data and the algorithmic developments resulted in improved predictions of HLA-I ligands and neo-epitopes. Prospectively applying our tools to SARS-CoV-2 proteins revealed several epitopes. TCR sequencing identified a monoclonal response in effector/memory CD8
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T cells against one of these epitopes and cross-reactivity with the homologous peptides from other coronaviruses.