Cross-species genomics matches driver mutations and cell compartments to model ependymoma | |
Article | |
关键词: LIPID-BINDING PROTEIN; NEURAL STEM; RADIAL GLIA; ASSOCIATION; PROGRESSION; EXPRESSION; | |
DOI : 10.1038/nature09173 | |
来源: SCIE |
【 摘 要 】
Understanding the biology that underlies histologically similar but molecularly distinct subgroups of cancer has proven difficult because their defining genetic alterations are often numerous, and the cellular origins of most cancers remain unknown(1-3). We sought to decipher this heterogeneity by integrating matched genetic alterations and candidate cells of origin to generate accurate disease models. First, we identified subgroups of human ependymoma, a form of neural tumour that arises throughout the central nervous system (CNS). Subgroup-specific alterations included amplifications and homozygous deletions of genes not yet implicated in ependymoma. To select cellular compartments most likely to give rise to subgroups of ependymoma, we matched the transcriptomes of human tumours to those of mouse neural stem cells (NSCs), isolated from different regions of the CNS at different developmental stages, with an intact or deleted Ink4a/Arf locus (that encodes Cdkn2a and b). The transcriptome of human supratentorial ependymomas with amplified EPHB2 and deleted INK4A/ARF matched only that of embryonic cerebral Ink4a/Arf(-/-) NSCs. Notably, activation of Ephb2 signalling in these, but not other, NSCs generated the first mouse model of ependymoma, which is highly penetrant and accurately models the histology and transcriptome of one subgroup of human supratentorial tumour. Further, comparative analysis of matched mouse and human tumours revealed selective deregulation in the expression and copy number of genes that control synaptogenesis, pinpointing disruption of this pathway as a critical event in the production of this ependymoma subgroup. Our data demonstrate the power of cross-species genomics to meticulously match subgroup-specific driver mutations with cellular compartments to model and interrogate cancer subgroups.
【 授权许可】
Free