Abstract B071: Validating sequence similarity-driven neoepitope fitness models via immunogenomics on TCGA and multiregional tumor data

A. Bubie, N. Akers, A. Villanueva, B. Losic
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Abstract

Clonal fitness and survival models for checkpoint blockade response prediction have recently been proposed on the basis of ranking neoepitopes via an interaction between a proxy of T-cell recognition, a nonlinear function of neoepitope sequence similarity to known antigens, and neoantigen relative MHC binding affinity. In this work we examine the SKCM (n = 337) and NSCLC (n = 305) TCGA datasets to explicitly test if sequence similarity to known antigens from the IEDB is associated with tumor infiltrating lymphocyte (TIL) burden in patients, as measured by TCR sequencing and CDR reconstruction in RNA-seq data. We find that there is no statistically significant association between either the inferred clonality or magnitude of TIL response and neoepitope sequence similarity to known antigens. We do, however, find significant, moderate associations of TIL response to neoepitope burden. Further, we examined the LIHC (n = 193) and UCEC (n = 245) TCGA cohorts to explicitly derive tumor and virally derived epitopes (HepB, HPV respectively) and ranked their relative predicted MHC binding affinity profiles. We find a greater MHC binding affinity bias exists towards neoepitopes compared to virally derived peptides in a natural setting where both viral and tumor antigens are simultaneously present. Moreover, we find low and significant associations between TIL burden and overall neoepitope burden, but no association with overall viral epitope or expression burden. Finally, we used multiregionally sampled data (12 patients, 72 regions) from HepB-positive HCC liver cancer patients to confirm preferential MHC binding affinity and TIL response bias towards neoepitopes still holds and is significant. Our results suggest that neoepitopes dominate in their recruitment potential of, and association with, TIL burden compared to viral-cofactors. They also suggest that neoepitope sequence similarity to known antigens does not recapitulate patient TIL burden to first approximation. Citation Format: Adrian Bubie, Nicholas Akers, Augusto Villanueva, Bojan Losic. Validating sequence similarity-driven neoepitope fitness models via immunogenomics on TCGA and multiregional tumor data [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B071.
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B071:基于TCGA和多区域肿瘤数据的免疫基因组学验证序列相似性驱动的新表位适应度模型
最近提出了用于检查点阻断反应预测的克隆适应度和生存模型,该模型基于t细胞识别代理、新表位序列与已知抗原相似性的非线性函数和新抗原相对MHC结合亲和力之间的相互作用对新表位进行排序。在这项工作中,我们检查了SKCM (n = 337)和NSCLC (n = 305)的TCGA数据集,通过TCR测序和RNA-seq数据中的CDR重建,明确测试了与来自IEDB的已知抗原的序列相似性是否与患者的肿瘤浸润性淋巴细胞(TIL)负担相关。我们发现,TIL反应的推断克隆性或大小与新表位序列与已知抗原的相似性之间没有统计学上的显著关联。然而,我们确实发现TIL对新表位负荷的反应有显著的、适度的关联。进一步,我们检查了LIHC (n = 193)和UCEC (n = 245) TCGA队列,明确推导出肿瘤和病毒衍生的表位(分别为HepB和HPV),并对它们的相对预测MHC结合亲和力谱进行了排序。我们发现,在病毒和肿瘤抗原同时存在的自然环境中,与病毒衍生肽相比,MHC结合亲和力偏向于新表位存在更大的差异。此外,我们发现TIL负担与总体新表位负担之间存在低而显著的相关性,但与总体病毒表位或表达负担无关。最后,我们使用来自hepb阳性HCC肝癌患者的多区域采样数据(12例患者,72个区域)来证实MHC的优先结合亲和力和TIL对新表位的反应偏倚仍然存在并且是显著的。我们的研究结果表明,与病毒辅助因子相比,新表位在TIL负荷的招募潜力和关联方面占主导地位。他们还表明,新表位序列与已知抗原的相似性并不能将患者的TIL负担概括为第一近似。引文格式:Adrian Bubie, Nicholas Akers, Augusto Villanueva, Bojan Losic。基于TCGA和多区域肿瘤数据的免疫基因组学验证序列相似性驱动的新表位适应度模型[摘要]。第四届CRI-CIMT-EATI-AACR国际癌症免疫治疗会议:将科学转化为生存;2018年9月30日至10月3日;纽约,纽约。费城(PA): AACR;癌症免疫学杂志,2019;7(2增刊):摘要nr B071。
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