Genome Engineering Evolves Brain Tumor Modeling.

Abstract

Genome engineering using programmable nucleases such as transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeat-associated protein nine facilitated the introduction of genetic alterations at specific genomic sites in various cell types. These tools have been applied to cancer modeling to understand the pathogenic effects of the growing catalog of mutations found in human cancers. Pertaining to brain tumors, neural progenitor cells derived from human induced pluripotent stem cells (iPSCs) engineered with different combinations of genetic driver mutations observed in distinct molecular subtypes of glioblastomas, the most common form of primary brain cancer in adults, give rise to brain tumors when engrafted orthotopically in mice. These glioblastoma models recapitulate the transcriptomic signature of each molecular subtype and authentically resemble pathobiology of glioblastoma, including inter- and intra-tumor heterogeneity, chromosomal aberrations, and extrachromosomal DNA amplifications. Similar engineering with genetic mutations found in medulloblastoma and atypical teratoid rhabdoid tumors in iPSCs have led to genetically trackable models that bear clinical relevance to these pediatric brain tumors. These models have contributed to improved comprehension of the genetic causation of tumorigenesis and offered a novel platform for therapeutic discovery. Studied in the context of three-dimensional cerebral organoids, these models have aided in the study of tumor invasion as well as therapeutic responses. In summary, modeling brain tumors through genome engineering enables not only the establishment of authentic tumor avatars driven by bona fide genetic mutations observed in patient samples but also facilitates functional investigations of particular genetic alterations in an otherwise isogenic background.