Research on stem cells has developed as one of the most promising areas of neurobiology. In the beginning of the 1990s, neurogenesis in the adult brain was indisputably accepted, eliciting great research efforts. Neural stem cells in the adult mammalian brain are located in the 'neurogenic' areas of the subventricular and subgranular zones. Nevertheless, many reports indicate that they subsist in other regions of the adult brain. Adult neural stem cells have arisen considerable interest as these studies can be useful to develop new methods to replace damaged neurons and treat severe neurological diseases such as neurodegeneration, stroke or spinal cord lesions. In particular, a promising field is aimed at stimulating or trigger a self-repair system in the diseased brain driven by its own stem cell population. Here, we will revise the latest findings on the characterization of active and quiescent adult neural stem cells in the main regions of neurogenesis and the factors necessary to maintain their active and resting states, stimulate migration and homing in diseased areas, hoping to outline the emerging knowledge for the promotion of regeneration in the brain based on endogenous stem cells.

Glioblastoma is the most common and aggressive brain tumor, with a subpopulation of stem-like cells thought to mediate its recurring behavior and therapeutic resistance. The epithelial-mesenchymal transition (EMT) inducing factor Zeb1 was linked to tumor initiation, invasion, and resistance to therapy in glioblastoma, but how Zeb1 functions at molecular level and what genes it regulates remain poorly understood. Contrary to the common view that EMT factors act as transcriptional repressors, here we show that genome-wide binding of Zeb1 associates with both activation and repression of gene expression in glioblastoma stem-like cells. Transcriptional repression requires direct DNA binding of Zeb1, while indirect recruitment to regulatory regions by the Wnt pathway effector Lef1 results in gene activation, independently of Wnt signaling. Amongst glioblastoma genes activated by Zeb1 are predicted mediators of tumor cell migration and invasion, including the guanine nucleotide exchange factor Prex1, whose elevated expression is predictive of shorter glioblastoma patient survival. Prex1 promotes invasiveness of glioblastoma cells highlighting the importance of Zeb1/Lef1 gene regulatory mechanisms in gliomagenesis.

Glioblastoma is the most common and deadly malignant brain cancer. We now demonstrate that loss of function of the endosomal GTPase Rab35 in human brain tumor initiating cells (BTICs) increases glioblastoma growth and decreases animal survival following BTIC implantation in mouse brains. Mechanistically, we identify that the GTPase Arf5 interacts with the guanine nucleotide exchange factor (GEF) for Rab35, DENND1/connecdenn, and allosterically enhances its GEF activity toward Rab35. Knockdown of either Rab35 or Arf5 increases cell migration, invasiveness, and self-renewal in culture and enhances the growth and invasiveness of BTIC-initiated brain tumors in mice. RNAseq of the tumors reveals up-regulation of the tumor-promoting transcription factor SPOCD1, and disruption of the Arf5/Rab35 axis in glioblastoma cells leads to strong activation of the epidermal growth factor receptor, with resulting enhancement of SPOCD1 levels. These discoveries reveal an unexpected cascade between an Arf and a Rab and indicate a role for the cascade, and thus endosomal trafficking, in brain tumors.

With the recent surge of single cell RNA sequencing datasets (scRNAseq) the extent of cellular heterogeneity has become apparent, yet it remains poorly characterized on a protein level in brain tissue and induced pluripotent stem cell (iPSC) derived brain models. With this in mind, we developed a high-throughput, standardized approach for the reproducible characterization of cell types in complex neuronal tissues. We designed a flow cytometry (FC) antibody panel coupled with a computational pipeline to quantify cellular subtypes in human iPSC derived midbrain organoids. Our pipeline, termed CelltypeR, contains scripts to transform and align multiple datasets, optimize unsupervised clustering, annotate cell types, quantify cell types, and compare cells across conditions. We identified the expected brain cell types, then sorted neurons, astrocytes, and radial glia, confirming these cell types with scRNAseq. We present an adaptable analysis framework providing a generalizable method to reproducibly identify cell types across FC datasets.

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