ReviewMethods in molecular biology (Clifton, N.J.)2025
Brain Tumor Stem Cells: New Perspectives.
Review in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
3 authors.
Funding
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Abstract
Brain cancer remains to be one of the most formidable challenges in oncology, due to its complexity, heterogeneity, and aggressive nature. Despite advances in treatment, many patients continue to face poor prognoses, underscoring the dire need for ongoing research and innovation to address this clinical enigma. Brain tumor stem cells (BTSCs) have shown to play a significant factor in the transformation and progression of brain tumors. This distinct subpopulation of cancer cells exhibit key characteristics remnant of neural stem cells (NSCs) including self-renewal and asymmetric differentiation. They are also characterized by abhorrent signaling pathways, metabolic processes, and immune surveillance. Current methods utilize fluorescent-activated cell sorting (FAC) methods to isolate and enrich for BTSCs based on cell surface markers. In this chapter, we review the current challenges in BTSC research, highlighting the anomalies of BTSCs and their surrounding niche that lead to therapeutic resistance and relapse. Current and prospective research are explored to address these challenges, including innovative technologies such as single cell RNA sequencing captures genetic and transcriptomic information on the single-cell level. Screening methods utilizing CRISPR technology are discussed to identify targetable vulnerabilities. Finally, with the advent of artificial intelligence (AI), current research utilizing AI and machine learning are explored to introduce novel therapeutic targets and improved diagnostic tools.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.