Rajagopalan Srinivas, Singh Amartya, Khiabanian Hossein
Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, United States.
Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, United States.
Front Genet. 2021 Nov 19;12:758391. doi: 10.3389/fgene.2021.758391. eCollection 2021.
The accurate classification, prognostication, and treatment of gliomas has been hindered by an existing cellular, genomic, and transcriptomic heterogeneity within individual tumors and their microenvironments. Traditional clustering is limited in its ability to distinguish heterogeneity in gliomas because the clusters are required to be exclusive and exhaustive. In contrast, biclustering can identify groups of co-regulated genes with respect to a subset of samples and vice versa. In this study, we analyzed 1,798 normal and tumor brain samples using an unsupervised biclustering approach. We identified co-regulated gene expression profiles that were linked to proximally located brain regions and detected upregulated genes in subsets of gliomas, associated with their histologic grade and clinical outcome. In particular, we present a cilium-associated signature that when upregulated in tumors is predictive of poor survival. We also introduce a risk score based on expression of 12 cilium-associated genes which is reproducibly informative of survival independent of other prognostic biomarkers. These results highlight the role of cilia in development and progression of gliomas and suggest potential therapeutic vulnerabilities for these highly aggressive tumors.
单个肿瘤及其微环境中存在的细胞、基因组和转录组异质性阻碍了胶质瘤的准确分类、预后评估和治疗。传统聚类在区分胶质瘤异质性方面能力有限，因为聚类需要是互斥且详尽无遗的。相比之下，双聚类可以识别相对于样本子集的共调控基因群体，反之亦然。在本研究中，我们使用无监督双聚类方法分析了1798个正常和肿瘤脑样本。我们确定了与近端脑区相关的共调控基因表达谱，并在胶质瘤子集中检测到上调基因，这些基因与其组织学分级和临床结果相关。特别是，我们提出了一种与纤毛相关的特征，当在肿瘤中上调时可预测生存不良。我们还引入了基于12个与纤毛相关基因表达的风险评分，该评分可重复性地提供独立于其他预后生物标志物的生存信息。这些结果突出了纤毛在胶质瘤发生和进展中的作用，并提示了这些高度侵袭性肿瘤潜在的治疗弱点。
