Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome.

IF 11.1 Q1 CELL BIOLOGY
Cell genomics Pub Date : 2024-06-12 Epub Date: 2024-05-23 DOI:10.1016/j.xgen.2024.100566
H Nayanga Thirimanne, Damian Almiron-Bonnin, Nicholas Nuechterlein, Sonali Arora, Matt Jensen, Carolina A Parada, Chengxiang Qiu, Frank Szulzewsky, Collin W English, William C Chen, Philipp Sievers, Farshad Nassiri, Justin Z Wang, Tiemo J Klisch, Kenneth D Aldape, Akash J Patel, Patrick J Cimino, Gelareh Zadeh, Felix Sahm, David R Raleigh, Jay Shendure, Manuel Ferreira, Eric C Holland
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引用次数: 0

Abstract

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

脑膜瘤转录组图谱显示了与区域生物学和患者预后相关的新型亚型。
脑膜瘤虽然多为良性,但也可能复发和致命。世界卫生组织(WHO)对肿瘤的分级并不总能识别高危脑膜瘤,因此需要更好地描述其侵袭性生物学特征。为了解决这个问题,我们结合了 13 个大容量 RNA 测序(RNA-seq)数据集,创建了一个包含 1298 个脑膜瘤的降维参考图谱。临床和基因组元数据与图谱区域有效相关,从而确定了具有特定生物学特征的脑膜瘤亚型。复发时间也与地图位置相关。此外,我们还开发了一种算法,可将新患者映射到该图谱上,其中的近邻可预测预后。这项研究强调了结合大容量转录组数据集来直观显示肿瘤群体复杂性的实用性。此外,我们还提供了一种互动工具,用于了解疾病和预测患者预后。这一资源可通过在线工具 Oncoscape 访问,科学界可在该工具中探索脑膜瘤景观。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
7.10
自引率
0.00%
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