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Human Pluripotent Stem Cell-Derived Tumor Model Uncovers the Embryonic Stem Cell Signature as a Key Driver in Atypical Teratoid/Rhabdoid Tumor.

Cell reports | 2019

Atypical teratoid/rhabdoid tumor (AT/RT), which harbors SMARCB1 mutation and exhibits a characteristic histology of rhabdoid cells, has a poor prognosis because of the lack of effective treatments. Here, we establish human SMARCB1-deficient pluripotent stem cells (hPSCs). SMARCB1-deficient hPSC-derived neural progenitor-like cells (NPLCs) efficiently give rise to brain tumors when transplanted into the mouse brain. Notably, activation of an embryonic stem cell (ESC)-like signature confers a rhabdoid histology in SMARCB1-deficient NPLC-derived tumors and causes a poor prognosis. Consistently, we find the activation of the ESC-like gene expression signature and an ESC-like DNA methylation landscape in clinical specimens of AT/RT. Finally, we identify candidate genes that maintain the activation of the ESC-like signature and the growth of AT/RT cells. Collectively, SMARCB1-deficient hPSCs offer the human models for AT/RT, which uncover the role of the activated ESC-like signature in the poor prognosis and unique histology of AT/RT.

Pubmed ID: 30840885 RIS Download

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ATCC (tool)

RRID:SCR_001672

Global nonprofit biological resource center (BRC) and research organization that provides biological products, technical services and educational programs to private industry, government and academic organizations. Its mission is to acquire, authenticate, preserve, develop and distribute biological materials, information, technology, intellectual property and standards for the advancement and application of scientific knowledge. The primary purpose of ATCC is to use its resources and experience as a BRC to become the world leader in standard biological reference materials management, intellectual property resource management and translational research as applied to biomaterial development, standardization and certification. ATCC characterizes cell lines, bacteria, viruses, fungi and protozoa, as well as develops and evaluates assays and techniques for validating research resources and preserving and distributing biological materials to the public and private sector research communities.

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RRID:SCR_001881

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RRID:SCR_002798

Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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RRID:SCR_005780

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