Division of Neurosurgery, University of Toronto, Toronto, ON, Canada.
J Neurooncol. 2023 Feb;161(3):491-499. doi: 10.1007/s11060-022-04221-2. Epub 2023 Jan 26.
Vestibular schwannoma (VS) is the most common tumour of the cerebellopontine angle and poses a significant morbidity for patients. While many exhibit benign behaviour, others have a more aggressive nature and pattern of growth. Predicting who will fall into which category consistently remains uncertain. There is a need for a better understanding of the molecular landscape, and important subgroups therein, of this disease.
We select all vestibular schwannomas from our tumour bank with both methylation and RNA profiling available. Unsupervised clustering methods were used to define two distinct molecular subgroups of VS which were explored using computational techniques including bulk deconvolution analysis, gene pathway enrichment analysis, and drug repurposing analysis. Methylation data from two other cohorts were used to validate our findings, given a paucity of external samples with available multi-omic data.
A total of 75 tumours were analyzed. Consensus clustering and similarity network fusion defined two subgroups ("immunogenic" and "proliferative") with significant differences in immune, stroma, and tumour cell abundance (p < 0.05). Gene network analysis and computational drug repurposing found critical differences in targets of immune checkpoint inhibition PD-1 and CTLA-4, the MEK pathway, and the epithelial to mesenchymal transition program, suggesting a need for subgroup-specific targeted treatment/trial design in the future.
We leverage computational tools with multi-omic molecular data to define two robust subgroups of vestibular schwannoma with differences in microenvironment and therapeutic vulnerabilities.
前庭神经鞘瘤（VS）是桥小脑角最常见的肿瘤，会给患者带来很大的发病率。虽然许多肿瘤表现出良性行为，但其他肿瘤则具有更具侵袭性的性质和生长模式。始终如一地预测哪些患者会属于哪种类别仍然不确定。需要更好地了解这种疾病的分子特征及其重要亚组。
我们从肿瘤库中选择了所有具有甲基化和 RNA 谱分析的前庭神经鞘瘤。使用无监督聚类方法定义了 VS 的两个不同的分子亚组，然后使用计算技术（包括批量去卷积分析、基因途径富集分析和药物再利用分析）对其进行了探索。鉴于缺乏具有可用多组学数据的外部样本，使用来自另外两个队列的甲基化数据来验证我们的发现。
共分析了 75 个肿瘤。共识聚类和相似网络融合定义了两个具有显著差异的亚组（“免疫原性”和“增殖性”），在免疫、基质和肿瘤细胞丰度方面存在显著差异（p<0.05）。基因网络分析和计算药物再利用发现免疫检查点抑制剂 PD-1 和 CTLA-4、MEK 途径和上皮间质转化程序的关键靶点存在差异，这表明未来需要针对特定亚组的靶向治疗/试验设计。
我们利用具有多组学分子数据的计算工具来定义具有不同微环境和治疗脆弱性的前庭神经鞘瘤两个稳健的亚组。
