Coelho Ana Carolina M F, Fonseca André L, Martins Danilo L, Lins Paulo B R, da Cunha Lucas M, de Souza Sandro J
Bioinformatics Multidisciplinary Enviroment (BioME), Institute Metropolis Digital, Federal University of Rio Grande do Norte, UFRN, Natal, Brazil.
PhD Program in Bioinformatics, UFRN, Natal, Brazil.
BMC Med Genomics. 2020 Feb 22;13(1):30. doi: 10.1186/s12920-020-0694-1.
Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives.
We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity.
neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available through github at https://github.com/neoanthill/neoANT-HILL.
癌症新抗原因其引发抗肿瘤反应的能力而在免疫治疗中引起了极大关注。这些分子源于癌细胞中的体细胞突变，导致原始蛋白质发生改变。新抗原的鉴定仍然是一项具有挑战性的任务，主要原因是假阳性率很高。
我们开发了一种高效且自动化的流程来鉴定潜在的新抗原。neoANT-HILL整合了多种免疫基因组分析，以改进从下一代测序（NGS）数据中检测新抗原的方法。该流程已编译到一个预构建的Docker镜像中，下载和设置所需的计算背景最少。neoANT-HILL应用于癌症基因组图谱（TCGA）黑色素瘤数据集，发现了几个推定的新抗原，包括源自复发性RAC1:P29S和SERPINB3:E250K突变的新抗原。neoANT-HILL还用于以高灵敏度和特异性鉴定RNA测序数据中的潜在新抗原。
neoANT-HILL是一个用户友好的工具，具有图形界面，能够高效地进行新抗原预测。neoANT-HILL能够处理多个样本，提供多种结合预测器，能够对肿瘤浸润免疫细胞进行定量，并考虑RNA测序数据以鉴定潜在的新抗原。该软件可通过github获取，网址为https://github.com/neoanthill/neoANT-HILL。
