Glioblastoma is a universally lethal cancer driven by glioblastoma stem cells (GSC). Here, we interrogated N6-methyladenosine (m6A) mRNA modifications in GSCs by methyl RNA immunoprecipitation followed by sequencing and transcriptome analysis, finding transcripts marked by m6A often upregulated compared with normal neural stem cells (NSC). Interrogating m6A regulators, GSCs displayed preferential expression, as well as in vitro and in vivo dependency, of the m6A reader YTHDF2, in contrast to NSCs. Although YTHDF2 has been reported to destabilize mRNAs, YTHDF2 stabilized MYC and VEGFA transcripts in GSCs in an m6A-dependent manner. We identified IGFBP3 as a downstream effector of the YTHDF2–MYC axis in GSCs. The IGF1/IGF1R inhibitor linsitinib preferentially targeted YTHDF2-expressing cells, inhibiting GSC viability without affecting NSCs and impairing in vivo glioblastoma growth. Thus, YTHDF2 links RNA epitranscriptomic modifications and GSC growth, laying the foundation for the YTHDF2–MYC–IGFBP3 axis as a specific and novel therapeutic target in glioblastoma.Significance: Epitranscriptomics promotes cellular heterogeneity in cancer. RNA m6A landscapes of cancer and NSCs identified cell type–specific dependencies and therapeutic vulnerabilities. The m6A reader YTHDF2 stabilized MYC mRNA specifically in cancer stem cells. Given the challenge of targeting MYC, YTHDF2 presents a therapeutic target to perturb MYC signaling in glioblastoma.This article is highlighted in the In This Issue feature, p. 211
Glioblastomas are highly lethal cancers, containing self-renewing glioblastoma stem cells (GSC). Here, we show that GSCs, differentiated glioblastoma cells (DGC), and nonmalignant brain cultures all displayed robust circadian rhythms, yet GSCs alone displayed exquisite dependence on core clock transcription factors, BMAL1 and CLOCK, for optimal cell growth. Downregulation of BMAL1 or CLOCK in GSCs induced cell-cycle arrest and apoptosis. Chromatin immunoprecipitation revealed that BMAL1 preferentially bound metabolic genes and was associated with active chromatin regions in GSCs compared with neural stem cells. Targeting BMAL1 or CLOCK attenuated mitochondrial metabolic function and reduced expression of tricarboxylic acid cycle enzymes. Small-molecule agonists of two independent BMAL1–CLOCK negative regulators, the cryptochromes and REV-ERBs, downregulated stem cell factors and reduced GSC growth. Combination of cryptochrome and REV-ERB agonists induced synergistic antitumor efficacy. Collectively, these findings show that GSCs co-opt circadian regulators beyond canonical circadian circuitry to promote stemness maintenance and metabolism, offering novel therapeutic paradigms. Significance: Cancer stem cells are highly malignant tumor-cell populations. We demonstrate that GSCs selectively depend on circadian regulators, with increased binding of the regulators in active chromatin regions promoting tumor metabolism. Supporting clinical relevance, pharmacologic targeting of circadian networks specifically disrupted cancer stem cell growth and self-renewal. This article is highlighted in the In This Issue feature, p. 1469
Brain tumors are dynamic complex ecosystems with multiple cell types. To model the brain tumor microenvironment in a reproducible and scalable system, we developed a rapid three-dimensional (3D) bioprinting method to construct clinically relevant biomimetic tissue models. In recurrent glioblastoma, macrophages/microglia prominently contribute to the tumor mass. To parse the function of macrophages in 3D, we compared the growth of glioblastoma stem cells (GSCs) alone or with astrocytes and neural precursor cells in a hyaluronic acid-rich hydrogel, with or without macrophage. Bioprinted constructs integrating macrophage recapitulate patient-derived transcriptional profiles predictive of patient survival, maintenance of stemness, invasion, and drug resistance. Whole-genome CRISPR screening with bioprinted complex systems identified unique molecular dependencies in GSCs, relative to sphere culture. Multicellular bioprinted models serve as a scalable and physiologic platform to interrogate drug sensitivity, cellular crosstalk, invasion, context-specific functional dependencies, as well as immunologic interactions in a species-matched neural environment.