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免疫肽组学分析 HLA-A2 阳性三阴性乳腺癌鉴定潜在免疫治疗靶抗原

Immunopeptidomic Profiling of HLA-A2-Positive Triple Negative Breast Cancer Identifies Potential Immunotherapy Target Antigens.

机构信息

The Jenner Institute, University of Oxford, Oxford, OX3 7FZ, UK.

Target Discovery Institute, Nuffield Department of Medicine, Oxford, OX3 7FZ, UK.

出版信息

Proteomics. 2018 Jun;18(12):e1700465. doi: 10.1002/pmic.201700465.

DOI:10.1002/pmic.201700465
PMID:29786170
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6032843/
Abstract

The recent development in immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cells in the treatment of cancer has not only demonstrated the potency of utilizing T-cell reactivity for cancer therapy, but has also highlighted the need for developing new approaches to discover targets suitable for such novel therapeutics. Here we analyzed the immunopeptidomes of six HLA-A2-positive triple negative breast cancer (TNBC) samples by nano-ultra performance liquid chromatography tandem mass spectrometry (nUPLC-MS ). Immunopeptidomic profiling identified a total of 19 675 peptides from tumor and adjacent normal tissue and 130 of the peptides were found to have higher abundance in tumor than in normal tissues. To determine potential therapeutic target proteins, we calculated the average tumor-associated cohort coverage (aTaCC) that represents the percentage coverage of each protein in this cohort by peptides that had higher tumoral abundance. Cofilin-1 (CFL-1), interleukin-32 (IL-32), proliferating cell nuclear antigen (PCNA), syntenin-1 (SDCBP), and ribophorin-2 (RPN-2) were found to have the highest aTaCC scores. We propose that these antigens could be evaluated further for their potential as targets in breast cancer immunotherapy and the small cohort immunopeptidomics analysis technique could be used in a wide spectrum of target discovery. Data are available via ProteomeXchange with identifier PXD009738.

摘要

最近在癌症治疗中免疫检查点抑制剂和嵌合抗原受体 (CAR) T 细胞的发展不仅展示了利用 T 细胞反应性进行癌症治疗的效力,还强调了需要开发新方法来发现适合这些新型治疗的新靶点。在这里,我们通过纳升超高效液相色谱串联质谱 (nUPLC-MS) 分析了 6 个 HLA-A2 阳性三阴性乳腺癌 (TNBC) 样本的免疫肽组。免疫肽组学分析共从肿瘤和相邻正常组织中鉴定出 19675 种肽,其中 130 种肽在肿瘤组织中的丰度高于正常组织。为了确定潜在的治疗靶标蛋白,我们计算了平均肿瘤相关队列覆盖率 (aTaCC),它代表了每个蛋白在该队列中由肿瘤中丰度较高的肽所代表的百分比覆盖率。丝切蛋白-1 (CFL-1)、白细胞介素-32 (IL-32)、增殖细胞核抗原 (PCNA)、衔接蛋白-1 (SDCBP) 和核糖体蛋白 P2 (RPN-2) 被发现具有最高的 aTaCC 评分。我们提出,这些抗原可以进一步评估其作为乳腺癌免疫治疗靶标的潜力,并且可以在广泛的靶标发现中使用小队列免疫肽组学分析技术。数据可通过 ProteomeXchange 以标识符 PXD009738 获得。

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Cofilin-1 and Other ADF/Cofilin Superfamily Members in Human Malignant Cells.
乳腺癌当前及新的潜在免疫疗法进展:从实验室到临床应用
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Breast cancer immunopeptidomes contain numerous shared tumor antigens.乳腺癌免疫肽组包含许多共同的肿瘤抗原。
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