背景:目前髓母细胞瘤的护理治疗标准是不够的,因为这些标准没有考虑到肿瘤的异质性。较新,更安全,对于标准疗法无法治愈的高危髓母细胞瘤患者,需要采用针对患者的治疗方法.免疫疗法是一种有前途的治疗方式,可能是提高生存率和避免发病率的关键。为了有效的免疫反应,必须靶向适当的肿瘤抗原。虽然先前已经报道了具有亚组特异性遗传替换的髓母细胞瘤患者,这些遗传改变的免疫原性仍然未知。这项研究的目的是确定潜在的肿瘤排斥抗原,以开发针对髓母细胞瘤的抗原定向细胞疗法。
方法:我们开发了癌症免疫基因组学流程,并对髓母细胞瘤亚组特异性转录谱进行了全面分析(n=170,18WNT,46SHH,41组3和65组4患者肿瘤)可通过国际癌症基因组联盟(ICGC)和欧洲基因组-表型档案(EGA)获得。我们在包括新抗原在内的广泛抗原类别中进行了计算机抗原预测,肿瘤相关抗原(TAA),和融合蛋白。此外,我们使用最新的计算反卷积方法评估了肿瘤细胞中的抗原加工和呈递途径以及免疫浸润细胞景观.
结果:发现髓母细胞瘤患者表达多种私有和共有的免疫原性抗原。预测的TAA的比例高于所有分子亚群的新抗原和基因融合,除了声波刺猬(SHH),具有较高的新抗原负担。重要的是,癌症-睾丸抗原,以及以前未被重视的神经发育抗原,发现所有髓母细胞瘤亚组的大多数患者都有表达。尽管免疫寒冷,发现髓母细胞瘤亚组具有不同的免疫细胞基因特征。
结论:使用自定义抗原预测管道,我们确定了潜在的肿瘤排斥抗原,这对于髓母细胞瘤免疫治疗的发展具有重要意义.
BACKGROUND: The current standard of care treatments for medulloblastoma are insufficient as these do not take tumor heterogeneity into account. Newer, safer, patient-specific treatment approaches are required to treat high-risk medulloblastoma patients who are not cured by the standard therapies. Immunotherapy is a promising treatment modality that could be key to improving survival and avoiding morbidity. For an effective immune response, appropriate tumor antigens must be targeted. While medulloblastoma patients with subgroup-specific genetic substitutions have been previously reported, the immunogenicity of these genetic alterations remains unknown. The aim of this study is to identify potential tumor rejection antigens for the development of antigen-directed cellular therapies for medulloblastoma.
METHODS: We developed a cancer immunogenomics pipeline and performed a comprehensive analysis of medulloblastoma subgroup-specific transcription profiles (n = 170, 18 WNT, 46 SHH, 41 Group 3, and 65 Group 4 patient tumors) available through International Cancer Genome Consortium (ICGC) and European Genome-Phenome Archive (EGA). We performed in silico antigen prediction across a broad array of antigen classes including
neoantigens, tumor-associated antigens (TAAs), and fusion proteins. Furthermore, we evaluated the antigen processing and presentation pathway in tumor cells and the immune infiltrating cell landscape using the latest computational deconvolution methods.
RESULTS: Medulloblastoma patients were found to express multiple private and shared immunogenic antigens. The proportion of predicted TAAs was higher than
neoantigens and gene fusions for all molecular subgroups, except for sonic hedgehog (SHH), which had a higher neoantigen burden. Importantly, cancer-testis antigens, as well as previously unappreciated neurodevelopmental antigens, were found to be expressed by most patients across all medulloblastoma subgroups. Despite being immunologically cold, medulloblastoma subgroups were found to have distinct immune cell gene signatures.
CONCLUSIONS: Using a custom antigen prediction pipeline, we identified potential tumor rejection antigens with important implications for the development of immunotherapy for medulloblastoma.