Targeting Glioblastoma Stem Cells Through Disruption of the Circadian Clock

Published OnlineFirst August 27, 2019; DOI: 10.1158/2159-8290.CD-19-0215

RESEARCH ARTICLE

Targeting Glioblastoma Stem Cells through Disruption of the Circadian Clock

Zhen Dong1, Guoxin Zhang1, Meng Qu2, Ryan C. Gimple1,3, Qiulian Wu1, Zhixin Qiu1, Briana C. Prager1,3, Xiuxing Wang1, Leo J.Y. Kim1,3, Andrew R. Morton3, Deobrat Dixit1, Wenchao Zhou4, Haidong Huang4, Bin Li5, Zhe Zhu1, Shideng Bao4, Stephen C. Mack6, Lukas Chavez7, Steve A. Kay2, and Jeremy N. Rich1

ABSTRACT 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 immu- noprecipitation 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 effi cacy. Collectively, these fi ndings 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 specifi cally disrupted cancer stem cell growth and self-renewal.

INTRODUCTION informative GSC markers and functional assays, GSCs have been reliably demonstrated in glioblastoma and promote tumor Glioblastoma (World Health Organization grade IV glioma) angiogenesis, brain invasion, and immune evasion (9–11 ). is the most prevalent and malignant primary intrinsic brain Altered circadian regulation in cancer stem cells may tumor (1 ). Standard-of-care treatment includes maximal surgi- contribute to disease progression (12 ). Endogenous circa- cal resection followed by chemoradiation with the oral methyl- dian rhythms are established by two transcription–translation ator temozolomide, then adjuvant temozolomide, which offers negative feedback loops, in which the positive limb is com- only palliation ( 2 ). Although glioblastoma has been extensively posed of the basic helix–loop–helix Per–Arnt–Sim (bHLH-PAS) characterized at the molecular level ( 3 ), translation of this transcriptional factors BMAL1 (also known as ARNTL) and knowledge to clinical practice has been limited. CLOCK, which form heterodimers ( 13 ), with the transcrip- Glioblastomas display remarkable cellular heterogeneity, tional output linked to metabolism, immune regulation, and contributing to high rates of therapeutic resistance and rapid other cellular pathways (14, 15 ). The BMAL1–CLOCK complex recurrence (4, 5). Glioblastomas contain self-renewing tumor- drives the rhythmic expression of the proteins PER1/2/3 and initiating cells, called GSCs ( 6–8 ). Although the precise identity CRY1/2 (the negative limb of the feedback loop), which form of GSCs remains controversial due to a lack of universally a complex to inhibit BMAL1–CLOCK transcriptional activity (16 ). The BMAL1–CLOCK complex also induces REV-ERBα 1 Division of Regenerative Medicine, Department of Medicine, Moores and REV-ERBβ, which directly transcriptionally repress BMAL1 Cancer Center and Sanford Consortium for Regenerative Medicine, Uni- expression, constituting a second feedback loop (17 ). In some versity of California, San Diego, California. 2 Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, cancers and model systems, BMAL1 or CLOCK serve as onco- California. 3Department of Pathology, Case Western Reserve University genes ( 12, 18, 19 ), but in others their targeting is tumor-sup- School of Medicine, Cleveland, Ohio. 4 Department of Cancer Biology, Center pressive ( 20–22 ). Recent systems analysis revealed that alteration for Cancer Stem Cell Research, Lerner Research Institute, Cleveland Clinic, of circadian genes is correlated with patient survival and clinical 5 Cleveland, Ohio. Ludwig Institute for Cancer Research, La Jolla, California. outcomes in several tumor types ( 23 ). Circadian networks in 6 Department of Pediatrics, Baylor College of Medicine, Houston, Texas. 7Department of Medicine, University of California, San Diego, California. glioblastoma may be oncogenic with an association between Note: Supplementary data for this article are available at Cancer Discovery gene variants and tumor incidence, and targeting circadian regu- Online (http://cancerdiscovery.aacrjournals.org/). lators may reduce tumor growth and improve effi cacy of chemo- Z. Dong, G.X. Zhang, and M. Qu share fi rst authorship and contributed therapy ( 24, 25 ). Based on this background, we investigated the equally to this article. integrity of the core circadian circuitry within GSCs. Corresponding Authors: Jeremy N. Rich, University of California, San Diego School of Medicine, La Jolla, CA 92093. Phone: 858-822-2703; E-mail: [email protected]; and Steve A. Kay, Department of Neurology, Keck School RESULTS of Medicine, University of Southern California, Los Angeles, CA 90089. Phone: 213-764-7964; E-mail: [email protected] Genetic Disruption of Core Circadian Genes Cancer Discov 2019;9:1556–73 Inhibits GSC Growth doi: 10.1158/2159-8290.CD-19-0215 To study the circadian rhythm and core circadian genes ©2019 American Association for Cancer Research. in glioblastoma, we monitored circadian clock activity

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RESEARCH ARTICLE Dong et al. utilizing a luciferase reporter driven by the BMAL1 promoter. Targeting Circadian Regulators Induces Cell-Cycle Although MYC has been proposed to disrupt the normal Arrest and Apoptosis in GSCs circadian rhythm (26) and GSCs express high MYC levels To determine the cellular effects of BMAL1 and CLOCK (27), patient-derived GSCs and their differentiated progeny knockdown in GSCs, we analyzed cell-cycle progression and displayed circadian rhythms with similar properties to non- apoptosis upon modulation of BMAL1 and CLOCK. GSCs malignant brain cultures derived from surgical resections transduced with shBMAL1 or shCLOCK displayed reduced from patients with epilepsy (NM), independent of tumor G1 and increased G2–M fractions compared with GSCs trans- genetics (Fig. 1A–D; Supplementary Fig. S1A–S1K). Con- duced with shCONT (Fig. 2A and B). Gene set enrichment sistent with the observed rhythmicity, BMAL1 bound to analysis (GSEA) revealed decreased expression of G2–M and core clock genes, including PER1/2, CRY1/2, and NR1D1/2 M-phase genes with BMAL1 knockdown (Fig. 2C and D). Cell in GSCs, as measured by BMAL1 chromatin immunopre- proliferation rate was substantially reduced in shBMAL1- and cipitation followed by deep sequencing (ChIP-seq; Sup- shCLOCK-transduced GSCs as measured by EdU incorpo- plementary Fig. S1L–S1N). Canonical rhythms observed in ration and Ki-67 staining (Fig. 2E and F; Supplementary normal brain cells and GSCs suggest that cellular transfor- Fig. S3A–S3F). Flow-cytometric measurement of Annexin mation maintains circadian rhythms, despite the activation V and propidium iodide (PI) staining revealed induction of oncogenes. of apoptosis by BMAL1 and CLOCK knockdown relative to To study the functional roles of core circadian genes, shCONT (Fig. 2G; Supplementary Fig. S3G–S3J). Cleaved BMAL1 and CLOCK were targeted by shRNA-mediated caspase-3 was also induced upon targeting BMAL1 or CLOCK knockdown in patient-derived GSCs and NMs using two (Fig. 2H; Supplementary Fig. S3K–S3N), as confirmed by nonoverlapping shRNAs compared with a control non- measurement of cleaved PARP (Supplementary Fig. S3M and targeting shRNA sequence (shCONT). Targeting either S3N). However, Z-VAD-FMK, a pan-caspase inhibitor, did BMAL1 or CLOCK potently impaired proliferation in GSCs not rescue the cellular death induced in GSCs after BMAL1 derived from multiple patients (Fig. 1E–H; Supplementary or CLOCK knockdown, suggesting that multiple mechanisms Fig. S2A–S2F). In contrast, targeting BMAL1 or CLOCK contribute to the loss of GSC viability (Supplementary Fig. minimally reduced cell proliferation in epilepsy-derived S3O and S3P). As Cry knockout improves chemotherapy brain cultures or neural stem cells (NSC; Fig. 1I–L; Supple- efficacy through p73-mediated apoptosis by increasingTP73 mentary Fig. S2G and S2H), with modest antiproliferative expression (29), we examined p73 expression in GSCs after effects in differentiated glioblastoma cells (DGC; Supple- BMAL1 or CLOCK knockdown, but no difference was found mentary Fig. S2I–S2L). Reduced GSC proliferation upon (Supplementary Fig. S3Q and S3R), suggesting alternative BMAL1 or CLOCK knockdown was confirmed by CRISPR/ mechanisms underlie GSC clock dependence. Collectively, Cas9-mediated knockout (Fig. 1M–P). As NPAS2 partially these results indicated that BMAL1 and CLOCK are indispen- compensates for the loss of CLOCK in some tissues (28), sable for proliferation and survival of GSCs. we measured NPAS2 mRNA expression in different cell types; although NSCs and NMs had the lowest and high- est NPAS2 mRNA expression, respectively, GSCs expressed Disruption of Circadian Transcriptional Circuitry moderate NPAS2 mRNA levels (Supplementary Fig. S2M). Impairs GSC Self-Renewal A mild trend toward lower expression of NPAS2 in GSCs To determine whether core circadian genes BMAL1 and was observed compared with that in DGCs (Supplementary CLOCK are important for the maintenance of stemness in Fig. S2N). BMAL1 or CLOCK knockdown in GSCs induced GSCs, self-renewal was measured by limiting dilution sphere minimal changes in NPAS2 expression (Supplementary Fig. formation. Upon downregulation of BMAL1 or CLOCK, both S2O–S2Q). Targeting NPAS2 moderately reduced GSC pro- sphere formation frequency (considered a surrogate of self- liferation compared with CLOCK knockdown (Supplemen- renewal) and sphere size (considered a surrogate of prolife tary Fig. S2R–S2T). These data suggest that NPAS2 may ration) were reduced, revealing impairment of self-renewal function in GSCs, but appears largely distinct from the role (Fig. 2I–L). Disruption of BMAL1 or CLOCK in GSCs of CLOCK. Collectively, our results indicate that core clock decreased the expression of core GSC maintenance transcrip- regulators are required for GSC growth, likely by regulating tion factors, including SOX2, OLIG2, and MYC, as measured novel biological processes rather than cell-specific modula- by RT-PCR and immunoblot (Fig. 2M–P). BMAL1 bound the tion of the core circadian rhythm. promoters of SOX2, OLIG2, and MYC, as measured by ChIP-seq

Figure 1. Genetic disruption of core clock genes suppresses GSC growth despite robust circadian oscillation. A–D, Bioluminescence of BMAL1–Luc in T387 (A) and T3565 (B) GSCs, nonmalignant brain cultures (C), NSC (ENSA; D), synchronized by 100 nmol/L dexamethasone (dex) or 10 μmol/L forskolin. Data are representative of three experiments. E and F, mRNA and protein expression of BMAL1 and CLOCK in T387 (E) and T3565 (F) GSCs transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test. N = 3. G and H, Relative cell numbers of T387 (G) and T3565 (H) GSCs transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test.N = 4. I and J, mRNA and protein expression of BMAL1 and CLOCK in nonmalignant brain cultures (NM 263; I) and NSC (ENSA; J) transduced with shCONT, shBMAL1 or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test.N = 3. K and L, Relative cell numbers of nonmalignant brain cultures (K) and NSCs (L) transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test. N = 4. M–P, Protein expression of BMAL1 or CLOCK and relative cellular numbers in GSCs transduced with Cas9-sgCONT, Cas9-sgBMAL1 (M and N), or Cas9-sgCLOCK (O and P). Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test.N = 3.

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Targeting the Circadian Clock in Glioblastoma Stem Cells RESEARCH ARTICLE

A BCD

T387 GSC T3565 GSC NM263 ENSA 300 20 40 100

200 10 20 50 100 0 0 0 0 −100 −10 −20 −200 −20 −40 −50 012345 012345 012345 012345 Relative luminescence signal Relative Relative luminescence signal Relative Relative luminescence signal Relative Days after forskolin synchronization luminescence signal Relative Days after dex synchronization Days after dex synchronization Days after dex synchronization E G 40 40 l 1.2 T387 T387 T387

ve *** *** *** *** shCONT shCONT shCONT shBMAL1.1536 30 shBMAL1.1536 30 shCLOCK.1053 shBMAL1.689 shBMAL1.689 shCLOCK.1494 0.6 shCONT 20 20 *** *** e cell number shCLOCK.1053 e cell number

shCLOCK.1494 *** *** 10 10

Relative mRNA le Relative 0 Relativ Relativ BMAL1 CLOCK 0 0 TUBULIN TUBULIN 024 68 0246 8 Days after seeding cells Days after seeding cells F T3565 H l 15 15 1.2 *** *** *** *** T3565 T3565

ve shCONT shBMAL1.1536 shCONT shCONT shBMAL1.689 shBMAL1.1536 shCLOCK.1053 10 shBMAL1.689 10 shCLOCK.1494 0.6 shCONT

shCLOCK.1053 *** *** shCLOCK.1494 e cell number e cell number 5 5 *** ***

Relative mRNA le Relative 0 Relativ BMAL1 CLOCK Relativ TUBULIN TUBULIN 0 0 0246 8 02468 Days after seeding cells Days after seeding cells

I NM263 K 6 NM263 6 NM263 l 1.2 *** *** *** ***

ve shCONT shCONT shCONT shBMAL1.1536 shBMAL1.1536 shCLOCK.1053 shBMAL1.689 4 shBMAL1.689 4 shCLOCK.1494

0.6 shCONT shCLOCK.1053 e cell number shCLOCK.1494 2 e cell number 2 Relative mRNA le Relative Relativ 0 Relativ BMAL1 CLOCK 0 0 TUBULIN TUBULIN 02468 02468 Days after seeding cells Days after seeding cells

J ENSA L ENSA 15 ENSA l 1.2 *** *** *** *** 20

ve shCONT shBMAL1.1536 shCONT shCONT 15 shBMAL1.689 shBMAL1.1536 10 shCLOCK.1053 shBMAL1.689 shCLOCK.1494 0.6 shCONT shCLOCK.1053 10 e cell number shCLOCK.1494 e cell number 5 5 Relative mRNA le Relative

0 Relativ BMAL1 CLOCK Relativ 0 0 TUBULIN TUBULIN 02468 02468 Days after seeding cells Days after seeding cells MN P T387 GSC T3565 GSC O T387 GSC T3565 GSC sgBMAL1 #1 sgCLOCK #1 sgCLOCK #1 sgBMAL1 #1 sgCONT sgCONT sgCONT sgCONT sgCLOCK #2 sgBMAL1 #2 sgBMAL1 #2 sgCLOCK #2 15 15 15 15 sgCONT + −− sgCONT + −− sgCONT + −− sgCONT + − − s s s s sgBMAL1 − #1 #2 sgBMAL1 − #1 #2 sgCLOCK − #1 #2 sgCLOCK − #1 #2 CLOCK CLOCK 10 BMAL1 10 BMAL1 10 10 ACTIN ACTIN ACTIN ACTIN *** *** *** *** e cell number e cell number e cell number 5 5 e cell number 5 5 *** *** *** *** Relativ Relativ Relativ Relativ 0 0 0 0 02468 02468 02468 02468 Days after seeding cells Days after seeding cells Days after seeding cells Days after seeding cells

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RESEARCH ARTICLE Dong et al.

A CD Enrichment plot: G2–M phase Enrichment plot: M phase G1–G0 G1–G0 S S 0.0 0.0 G2–M G2–M T387 GSC T3565 GSC shCONT −0.2 −0.2 shBMAL1.1536 Enrichment score shBMAL1.689 −0.4 Enrichment score −0.4 0204060 80 100 (%) 0204060 80 100 (%) B 2.0 2.0 shCONT 1.0 1.0 shCLOCK.1053 Zero cross at 9,756 Zero cross at 9,756 0.0 0.0 shCLOCK.1494 −1.0 −1.0 (preranked) (preranked) 02040 60 80 100 (%) 020406080100 (%) 05,000 10,000 15,000 05,000 10,000 15,000 Ranked list metric Ranked Rank in ordered dataset list metric Ranked Rank in ordered dataset Enrichment profile Hits Ranking metric scores Enrichment profile Hits Ranking metric scores

E 40 T387 GSC FG100 T387 GSC H T387 GSC * * T387 GSC 80 * * 60 * * * * * ** 60 * * * 40 20 50 *** 40 * * * * *** * * * * *** *** *** *** 20 * * * * 20 ***

0 0 0 0

40 T3565 GSC T3565 GSC 100 T3565 GSC T3565 GSC 80 50

EdU-positive cells (%) EdU-positive ** Ki-67–positive cells (%) Ki-67–positive * * * * * * * * * * 40

Annexin V/PI-positive cells (%) V/PI-positive Annexin ** 60 * * 30 20 50 cells (%) caspase-3–positive Cleaved 40 20 *** *** *** *** *** * * * * *** * * * * 20 * * * * 10 0 0 0 0 shCONT ++− −−− shCONT + − −−+ − shCONT + −−+− − shCONT + − −−+ − shBMAL1 − 1536 689 −− − shBMAL1 −−1536 689 −− shBMAL1 −−1536 689 −− shBMAL1 −−1536 689 −− shCLOCK −−−−1053 1494 shCLOCK − −−− 1053 1494 shCLOCK − −−− 1053 1494 shCLOCK −−−−1053 1494 I T387 GSC J T3565 GSC shCONT 50 shCONT 30 shBMAL1.1536

shBMAL1.1536 1/4.9 1/408.8 − 0.5 − 0.5 1/4.9 1/313.8 40 shBMAL1.689 shBMAL1.689 20 *** *** 30 1/239.5 1/232 *** − 1.5 *** − 1.5 20 10

*** *** tal number of spheres *** ***

tal number of spheres 10 Log fraction nonresponding − 2.5 Log fraction nonresponding − 2.5 To

0 100 200 300 400 500 To 0 100200 300400 500 0 Dose (number of cells) 0 Dose (number of cells) 50 20 10 50 20 10 50 20 10 50 20 10 50 20 10 50 20 10 500 200 100 500 200 100 500 200 100 500 200 100 500 200 100 500 200 100 Cells/well Cells/well

K T387 GSC L T3565 GSC 50 30 shCONT shCONT 1/356.9 40 shCLOCK.1053 1/5.0 1/473.7 shCLOCK.1053 1/5.0 − 0.5 shCLOCK.1494 − 0.5 *** 20 shCLOCK.1494 1/437.6 30 1/301.9 *** *** − 1.5 *** 20 − 1.5 10 *** *** 10 *** *** tal number of spheres tal number of spheres − 2.5 − 2.5 To To Log fraction nonresponding Log fraction nonresponding 0 100 200 300 400 500 0 0100 200300 400 500 0 Dose (number of cells) Dose (number of cells) 50 20 10 50 20 10 50 20 10 50 20 10 50 20 10 50 20 10 500 200 100 500 200 100 500 200 100 500 200 100 500 200 100 500 200 100 Cells/well Cells/well

T387 GSC 1.5 shCONT + − − 80 T387 GSC l 1.5 T387 GSC shCONT + −− l lgG M shBMAL1 − 1536 689 OQve

ve 1053 1494 shCLOCK − BMAL1 60 1.0 * BMAL1 1.0 CLOCK CLOCK * * * * * * * * * * * * * * * * * * * * * * OLIG2 * * * * * OLIG2 40 * * * * * * * * 0.5 * 0.5 * * * * SOX2 * * SOX2 * 20 Relative mRNA le Relative

Relative mRNA le Relative MYC 0 MYC 0 BMAL1 SOX2 OLIG2 MYC CLOCK SOX2 OLIG2 0 TUBULIN MYC TUBULIN T3565 GSC 1.5 T3565 GSC T3565 GSC 200

l 1.5

NPl ve ve BMAL1 lgG CLOCK 150 BMAL1 1.0 OLIG2 1.0 * OLIG2 CLOCK * enrichment at promoter Relative * * * * * * * * * * * SOX2 * * 100 * * * * * * * * SOX2 0.5 * * * 0.5 * * * * * * * * * * MYC * * * * MYC 50 Relative mRNA le Relative Relative mRNA le Relative 0 TUBULIN 0 TUBULIN BMAL1 SOX2 OLIG2 MYC CLOCK SOX2 OLIG2 MYC 0 SOX2 OLIG2 MYC

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Targeting the Circadian Clock in Glioblastoma Stem Cells RESEARCH ARTICLE and ChIP-qPCR (Fig. 2Q; Supplementary Fig. S3S–S3U). 3 kb of a TSS that were gained in GSCs revealed an enrich- Thus, the circadian machinery is essential for maintaining ment of pathways regulating circadian clock transcriptional stem-cell transcriptional regulator levels and the subsequent networks, as expected, but also regulation of glucose metab- self-renewal properties of GSCs, likely through transcrip- olism and lipid biosynthesis (Fig. 3E–I; Supplementary tional regulation. Fig. S4G). In differentiated organs, BMAL1 targets across the genome are largely tissue-specific (ref. 31; Supplemen- The GSC Epigenetic Landscape Reprograms tary Fig. S4H). Although many genes bound by BMAL1 in Circadian Regulation murine liver, kidney, or heart overlapped with GSC-specific Circadian gene regulation is mediated through bind- BMAL1 binding sites, the large majority of GSC-specific ing of the BMAL1–CLOCK heterodimeric transcriptional BMAL1 sites were distinct from those seen in normal tissues complex. The selective dependency of GSCs on BMAL1 and (Supplementary Fig. S4I–S4L). These results suggest that CLOCK expression for cell growth and survival relative to their the majority of BMAL1 binding sites gained in GSCs (6,683 normal counterparts suggests that core clock proteins must of 8,508, 78.5%) are distinct from sites in tissues in which regulate gene-expression programs in GSCs distinct from BMAL1 is known to regulate metabolism. Taken together, those in normal stem cells. Therefore, we performed BMAL1 these data suggest that BMAL1 gains unique functions in ChIP-seq in two GSC and two NSC cell lines. Unsupervised GSCs beyond generation of circadian oscillations and that clustering of each BMAL1 ChIP-seq sample by principal this core circadian regulator has been repurposed to regu- component analysis (PCA) revealed that GSCs and NSCs late tumor metabolism in GSCs. showed divergent BMAL1 occupancy across the genome We next aimed to characterize the epigenomic features (Supplementary Fig. S4A). BMAL1 peaks were distributed responsible for the differential binding of BMAL1 between across the genome with enrichment at promoter regions in GSCs and NSCs based on the hypothesis that BMAL1 binds GSCs compared with NSCs, consistent with greater occu- novel binding sites in GSCs due to differential access to pancy of BMAL1 in regions surrounding transcription start chromatin in GSCs and NSCs. Histone H3 lysine 27 acety- sites (TSS) genome-wide (Fig. 3A and B; Supplementary Fig. lation (H3K27ac) ChIP-seq was performed on GSCs and S4B). To understand the functional consequences of differ- NSCs to define active chromatin regions. Overlaying the ential BMAL1 occupancy genome-wide, we defined BMAL1 BMAL1 and H3K27ac ChIP-seq data revealed that BMAL1 peaks with increased occupancy in GSCs and NSCs (Supple- signals strongly correlated with H3K27ac signals (Fig. 3J). mentary Fig. S4C and S4D). Expanded BMAL1 occupancy Almost all GSC-gained BMAL1 peaks (11,338 of 12,386 occurs despite similar BMAL1 or CLOCK expression levels in peaks; 92%) overlapped with H3K27ac peaks, which define GSCs relative to NSCs (Supplementary Fig. S4E and S4F). active promoter/enhancer regions (Fig. 3K). Further, chro- Consistent with previous studies (30), the conserved E-box matin regions with GSC-gained BMAL1 peaks presented motif (CACGTG) was enriched within GSC-gained BMAL1 higher H3K27ac signals in GSCs compared with those in peaks, although additional de novo motifs were revealed by NSCs (Supplementary Fig. S4M). Chromatin regions with motif enrichment analysis (Fig. 3C). Most BMAL1 binding GSC-gained BMAL1 peaks containing E-box motifs exhib- genes in NSCs overlapped with those in GSCs (87%; 7,194 ited higher H3K27ac signals in GSCs compared with NSCs genes out of 8,266 total NSC target genes). In contrast, (Supplementary Fig. S4N). Collectively, these data suggest BMAL1 target genes in GSCs were largely distinct from that the distinct patterns of BMAL1 binding in GSCs and those in NSCs (50%; 8,507 genes out of 16,773 total GSC NSCs may be influenced by differential chromatin activity target genes; Fig. 3D). This suggests that GSCs reprogram surrounding selected E-box motifs in GSCs. This model pre- BMAL1 binding genome-wide, which in turn drives novel dicts stronger overlap between GSC-gained H3K27ac peaks transcriptional function. To gain insight into the unique and BMAL1 binding in GSCs than in NSCs. To test this, biological functions of BMAL1 in GSCs, we applied GSEA we analyzed BMAL1 binding around chromatin regions to identify molecular pathways selectively driven by BMAL1 enriched with GSC-gained H3K27ac peaks and found that occupancy in GSCs. GSEA for BMAL1 binding peaks within BMAL1 signals were much higher at those regions in GSCs

Figure 2. The core clock components BMAL1 and CLOCK are indispensable for GSC proliferation and survival. A and B, Cell-cycle analysis of GSCs following transduction with shCONT, shBMAL1 (A), or shCLOCK (B). N = 3. C and D, GSEA plot of genes in G2–M (C) and M phase (D) during cell cycle after BMAL1 knockdown in GSCs. E, Quantification of EdU incorporation in GSCs transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test.N = 3. F, Quantification of Ki-67–positive cells by immunofluorescence staining in GSCs after transduction with shCONT, shBMAL1, or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test. N = 4. G, Quantification of FITC–Annexin V/PI-positive cells of GSCs transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test. N = 3. H, Quantification of cleaved caspase-3–positive cells by immunofluorescence staining in GSCs after transduction with shCONT, shBMAL1, or shCLOCK. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test. N = 4. I–L, In vitro limiting dilution assays and sphere formation of GSCs transduced with shCONT, shBMAL1 (I and J), or shCLOCK (K and L). The estimated stem-cell frequencies were indicated. Scale bars, 100 μm. Data of sphere numbers, mean ± SD. ***, P < 0.001. Statistical significance of sphere numbers was determined by one-way ANOVA with Tukey multiple comparison test. The χ2 test was used for pair-wise differences in stem population frequency. N = 3. M–P, Transcript and protein levels of GSC regulatory factors (SOX2, OLIG2, and MYC) measured by quantitative PCR and immunoblot in GSCs transduced with shCONT, shBMAL1 (M and N), or shCLOCK (O and P). Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test. N = 3. Q, ChIP-qPCR experiments showing occupancy of BMAL1 at the promoters of SOX2, OLIG2, and MYC. All the results are normalized to IgG control. N = 3.

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RESEARCH ARTICLE Dong et al.

BMAL1 ChIP-seq AB30 Genome background Consensus BMAL1 peaks in GSC Consensus BMAL1 peaks in NSC T387 GSC 8.6% 25 T3565 GSC 1.5% 0.7% 1.1% 0.6% 0.9% 18.2% 1.0% ENSA NSC 0.7% 21.6% 20 0.6%0.4% 1.6% hNP1 NSC 1.4% 29.2% 1.4% 15 1.9% 1.1% Promoter (≤1,000 bp) 5.7% 10 2.1% Promoter (1,000–2,000 bp) 1.0% Promoter (2,000–3,000 bp) 5 1.1% 2.1% 0 0.9% Downstream (≤1,000 bp) 0.8% −3.0 TSS 3.0 kb Downstream (1,000–2,000 bp) T387 GSC T3565 GSC 50.0% Downstream (2,000–3,000 bp) 13.6% 5′UTR 15.5% 41.6% 3′UTR 25.9% Coding exon Intron 32 1.6% Distal intergenic 28 11.2% 34.3%

TSSs 24 20 C GSC-gained BMAL1-ChIP peaks 16 De novo motifs P TF Known motifs P TF D Genes with BMAL1 Genes with BMAL1 ENSA hNP1 12 1e−38 YY2, YY1 1e−27 USF1 peaks in GSC peaks in NSC 8 1e−34 ETV6, ETV4 1e−26 CLOCK 4 0 8,507 7,194 1,072 1e−34 BMAL1, CLOCK 1e−25 CTCF TSSs

T3565 GSC −3.0 TSS 3.0 kb −3.0 TSS 3.0 kb GJ Entrainment of circadian clock 90 70 BMAL1 K E 0.4 50 H3K27ac 4.0 30 Gained BMAL1 peaks 0.2 Lipid biosynthetic process score 10 in GSC

3.5 Enrichment 0 1,048 Glucose metabolic process 3.0 7.5 60 5.0 Increased BMAL1 occupancy in GSCs 11,338 2.5 2.5 Entrainment of circadian clock 0 Zero across at 8,873 40

Ranked list Ranked 2.5 Increased BMAL1 occupancy in NSCs

(FDR corrected q value) −

2 0 2,000 4,000 6,000 8,000 10,000 2.0 metric (preranked) Ranks in ordered dataset 20 2.0 2.2 2.4 Enrichment profile Hit Ranking metric scores BMAL1 ChIP-seq − Log 0 11,326 Normalized gene set enrichment score H Glucose metabolic process 0.4 F Total active enhancer/ 0.2 100 promoters

Lipid metabolism score

Enrichment 0 (H3K27ac peaks) Glucose 50 metabolism

7.5 Increased BMAL1 occupancy in GSCs

5.0 H3K27ac ChIP-seq 0 2.5 Zero across at 8,873 0 EGFR signaling Increased BMAL1 occupancy in NSCs 3.0 StartEnd 3.0 kb Ranked list Ranked −2.5 − and response 0 2,000 4,000 6,000 8,000 10,000

metric (preranked) BMAL1 ChIP H3K27ac ChIP to peptide Ranks in ordered dataset L Enrichment profile HitRanking metric scores T3565 GSC ENSA T3565 GSC ENSA I 100 Lipid biosynthetic process 10 6 60 0.4 Response to 2 20 Circadian rhythm 0.2

oxidative stress chment 24 140

score (ES) 0 En ri

Gained BMAL1 M 7.5 Increased BMAL1 occupancy in GSCs 18 peaks in GSC 1,005 5.0 2.5 Zero across at 8,873 0 Increased BMAL1 occupancy in NSCs 12 70

Ranked list Ranked −2.5 0 2,000 4,000 6,000 8,000 10,000

11,381 metric (preranked) Ranks in ordered dataset Enrichment profile HitRanking metric scores with E-box sites with E-box 6 sites with E-box H3K4me3 peaks 9,547 GSC-gained H3K27ac peaks (active promoters) 0 GSC-gained H3K27ac peaks 0 −3 StartSEndE3 kb −3 tart nd 3 kb −3 StartSEndE3 kb −3 tart nd 3 kb N BMAL1 H3K27ac BMAL1 peaks alone (700) H3K4me3 BMAL1 & H3K27ac peaks (305) 140 O 120 100 BMAL1 & H3K4me3 peaks Neural stem cell 60 (2,940) Core clock genes CLOCK 20 BMAL1 80 −3 Start 3End

Glioma stem cell 140 Glucose metabolism BMAL1 & H3K4me3 & H3K27ac H3K27ac H3K27ac peaks 40 100 genes Lipid synthesis CLOCK (8,441) 60 BMAL1 genes 20 Core clock genes −3 Start End 3 Genomic distance (Kb) −3 StartSEnd 33−3 tart End 3 −3 Start End Genomic distance (Kb)

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Targeting the Circadian Clock in Glioblastoma Stem Cells RESEARCH ARTICLE compared with NSCs (Supplementary Fig. S4O). BMAL1 prominently cancer-related metabolic genes, demonstrated binds to multiple gained E-box motifs at the promoter increased BMAL1 and H3K27ac binding in GSCs compared regions of genes in various tissues and cells, so we exam- with NSCs (Supplementary Fig. S5C–S5K). ined BMAL1 binding around chromatin regions contain- Based on the association of BMAL1 with metabolic genes, we ing E-box motifs and enriched with GSC-gained H3K27ac. interrogated BMAL1 and CLOCK regulation of bioenergetics Consistent with the hypothesis, BMAL1 signals are much through glycolysis and the tricarboxylic acid (TCA) cycle in GSCs. higher in GSCs around the chromatin regions having E-box Glycolysis and OXPHOS were monitored using an extracellu- motifs and GSC-gained H3K27ac marks compared with lar flux analyzer (XF) by measuring oxygen consumption rate those in NSCs (Fig. 3L). Combined analysis of H3K4me3 (OCR) and extracellular acidification rate (ECAR) afterBMAL1 ChIP-seq, BMAL1 ChIP-seq, and H3K27ac ChIP-seq data or CLOCK knockdown. OCR was inhibited in two patient- revealed that the majority of gained BMAL1 peaks (11,381 derived GSCs upon knockdown of either BMAL1 or CLOCK (Fig. of 12,386 peaks; 91.9%) in GSCs overlapping with H3K4me3 4A and B). Decreased mitochondrial respiration was reflected in peaks (Fig. 3M). Most of the overlapped peaks (8,441 of reduced basal OCR (Fig. 4C and D), ATP capacity (Fig. 4E and 11,381 peaks; 74.2%) from BMAL1 ChIP-seq and H3K4me3 F), and uncoupled OCR upon targeting BMAL1 or CLOCK (Fig. ChIP-seq overlapped with H3K27ac peaks (Supplementary 4G and H). Further, BMAL1- or CLOCK-deficient GSCs showed Fig. S4P). The strongest BMAL1 signals were found at the significant reduction in ECAR, indicating decreased glycolysis active TSSs marked by H3K4me3 (Fig. 3N). In contrast, few (Supplementary Fig. S6A and S6B). Basal glycolysis after glucose BMAL1 peaks (305 of 12,386 peaks; 2.5%) were found at treatment in BMAL1 or CLOCK shRNA-transduced GSCs was enhancer regions marked by H3K27ac alone (Supplementary similar to that seen in GSCs transduced with shCONT. Target- Fig. S4P). These data indicate preferential binding of BMAL1 ing BMAL1 or CLOCK followed by oligomycin-induced stress at active TSSs in GSCs. glycolysis exhibited greater decrease compared with basal level In summary, BMAL1 occupancy is distinct between GSCs (Supplementary Fig. S6C and S6D). Thus, the circadian regula- and NSCs, with preferential binding defined by the underly- tors BMAL1 and CLOCK promote mitochondrial OXPHOS and ing differences in chromatin activity between GSCs and NSCs. glycolysis in GSCs. Interrogating the differential targets of BMAL1 between GSCs OXPHOS and glycolysis involve many different metabolic and NSCs revealed that BMAL1 may gain novel functions in enzymes. BMAL1 ChIP-seq (Supplementary Fig. S5C-S5K) GSCs to support aberrant tumor metabolism. The greater and ChIP-qPCR (Fig. 4I and J) indicate that BMAL1–CLOCK genome-wide binding of BMAL1 in GSCs than NSCs mirrored heterodimers may directly regulate OXPHOS and glycolysis the greater distribution of active chromatin, as marked by in GSCs by binding to the promoters of glycolysis genes (HK2 H3K27ac, suggesting that differences in downstream BMAL1 and LDHA) and TCA cycle genes (ACO2, IDH3A, SDHA, and transcriptional regulation are derived, at least in part, from CS). This notion is supported by reduced transcription of the greater accessibility of binding sites in GSCs (Fig. 3O). these genes upon BMAL1 or CLOCK knockdown (Fig. 4K; Sup- plementary Fig. S6E–S6H). Metabolites generated by the TCA BMAL1 and CLOCK Maintain Metabolic cycle were measured by mass spectrometry, revealing reduc- Homeostasis in GSCs tion in the levels of succinate, isocitrate, malate, and fumarate Core circadian genes regulate multiple metabolic processes, compared with other metabolites, such as pyruvate, in GSCs including glucose and lipid metabolism, oxidative phosphory following knockdown of BMAL1 or CLOCK (Supplementary lation (OXPHOS), and mitochondrial dynamics (32, 33). Fig. S6I–S6K). Collectively, these results indicate that BMAL1 BMAL1 ChIP-seq showed that GSC-gained BMAL1 occupies and CLOCK control essential metabolic activity, in part, by about half of metabolic genes analyzed (Supplementary Fig. directly regulating the expression of genes important for gly- S5A). Targeting BMAL1 reduced the expression of most selec- colysis and the TCA cycle in GSCs. tively BMAL1-bound metabolic genes in GSCs, as revealed by Mitochondrial fission–fusion dynamics are regulated in RNA-sequencing data (Supplementary Fig. S5B). To better a circadian manner through DRP1 regulation, and target- understand the biological functions of BMAL1 and CLOCK ing BMAL1 induces formation of swollen and dysfunctional in GSCs, we derived gene sets from GSC-gained BMAL1 mitochondria (34, 35). Upon BMAL1 or CLOCK knockdown, binding, revealing enrichment of glucose metabolism (Fig. we detected no obvious differences in protein levels of DRP1 3E–I; Supplementary Fig. S4G). Individual genes, including and PINK1, nor phosphorylated DRP1 in GSCs (data not

Figure 3. BMAL1 exhibits aberrant genome-wide binding patterns in GSCs compared with NSCs. A, Binding profiles and heat maps for BMAL1 ChIP- seq signals in GSCs (T387 and T3565) and NSCs (ENSA and hNP1). ChIP-seq signals are displayed within a region spanning ±3 kb around all canonical TSSs genome-wide. B, Distribution of genomic annotations of BMAL1 peaks in GSCs (middle) and NSCs (right) with background shown on the left. Consensus peaks were derived by selecting all peaks present in both replicates of respective cell types. C, Motif analysis of GSC-gained BMAL1 binding sites as defined in Supplementary Fig. S4C. Bothde novo (left) and known consensus (right) motifs are shown with corresponding enrichment significance values. D, Venn diagram showing the overlap between BMAL1-binding genes in GSCs and NSCs ±3 kb around the TSS. E and F, GSEA (E) and pathway enrichment bubble plots (F) of genes with GSC-gained BMAL1 peaks ±3 kb around the TSS. G–I, GSEA plots of genes involved in circadian rhythm (G), glucose regulation (H), and lipid metabolism (I) with increased BMAL1 binding in GSCs relative to NSCs. J, Heat maps showing the correlation of BMAL1 and H3K27ac ChIP-seq signals in T3565 GSCs. All ChIP-seq signals are displayed from ±3 kb surrounding each annotated BMAL1 peak. K, Venn diagram showing the overlap between gained BMAL1 and H3K27ac peaks in T3565 GSCs. L, Heat maps displaying BMAL1 and H3K27ac ChIP-seq signals across GSC-gained H3K27ac peaks containing an E-box motif. M, Venn diagram showing the overlap between GSC-gained BMAL1 peaks and H3K4me3 peaks in GSCs. N, Heat maps showing correlation of BMAL1, H3K4me3, and H3K27ac ChIP-seq in GSCs. O, Schematic showing differential BMAL1 chromatin binding in NSCs and GSCs.

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A T387 GSC C EG 250 Oligomycin FCCP Rote/antimycin A 150 80 200

* * 200 shCONT * * * * 60 * 150 * shBMAL1.1536 100 * * * * * * * * * * 150 shBMAL1.689 * * * * * * * * * shCLOCK.1053 40 100 * * 100 shCLOCK.1494 50 (pmol/min) 20 50 ATP capacity OCR ATP

OCR (pmol/min) 50 Basal OCR (pmol/min)

0 0 Uncoupled OCR (pmol/min) 0 0 shCONT +−−−− shCONT +−−−− shCONT +−−−− 8244056 72 88 shBMAL1 − 1536 689 −− shBMAL1 − 1536 689 −− shBMAL1 − 1536 689 −− shCLOCK −−− 1053 1494 shCLOCK −−−10531494 shCLOCK −−− 1053 1494 Time (min)

B T3565 GSC D FH 150 150 300 400 Oligomycin FCCP Rote/antimycin A shCONT * * shBMAL1.1536 * * 300 100 * 100 * 200 * * * * shBMAL1.689 * * * * * * * * * * * * * * * * * shCLOCK.1053 * 200 shCLOCK.1494 50 (pmol/min) 50 100

100 capacity OCR ATP Basal OCR (pmol/min) OCR (pmol/min)

0 0 Uncoupled OCR (pmol/min) 0 0 shCONT +−−−− shCONT + −−−− shCONT +−−−− − 1536 689 −− 8244056 72 88 shBMAL1 shBMAL1 − 1536 689 −− shBMAL1 − 1536 689 −− shCLOCK −−− 1053 1494 shCLOCK −−− 1053 1494 shCLOCK −−− 1053 1494 Time (min) l

l 1.5 1.5 LDHA ve

ve shCONT K Glucose HK2 I T387 GSC shBMAL1.1536 100 1.0 1.0 shBMAL1.689 * * * * * 75 BMAL1 * * * * * * * * * * * * HK2 * * * * * shCONT * * * * * * * * 50 CLOCK * * * * * * 0.5 * shCLOCK.1053 0.5 * * * G6P 40 lgG shCLOCK.1494 0 0 mRNA le Relative Relative mRNA le Relative T387 T3565 T387 3565 Lactate Pyruvate l 1.5 LDHA l 1.5 20 ve CS PDC ve ACO2 Acetyl-CoA 1.0 * 1.0 * *

protein at promoter * * * * * * * * * * * * * * * * * * * Relative enrichment of Relative * * * 0 * * * * CS Citrate * * * * * ACO2 * * 0.5 * 0.5 * CS * HK2 1.5 LDHA ACO2 IDH3a SDHA T387 0 Oxaloacetate 0 Negative mRNA le Relative mRNA le Relative T387 T3565 1.0 T387 T3565 l Iso-citrate ve * * * l MDH * * 1.5 IDH3a T3565 GSC 0.5 * * * ve J * * 80 Malate * * IDH3 BMAL1 0.0 1.0 60 1.5 * l FH T3565 * * * CLOCK 1.5 * * * * ve SDHA * * * * 40 * * * * * * * 40 lgG Fumarate 1.0 2-Oxoglutarate 0.5 * * * * *

Relative mRNA le Relative * 1.0 * * * * * * * * * * 0.5 * * * * SDH * * mRNA le Relative 0 * OGDH enrichment of * * * * * T387 T3565 20 0.5 * * * * * * 0.0 BMAL1 CLOCK Succinate Succinyl-CoA 0 Relative mRNA le Relative protein at promoter T387 T3565 SUCLA2

Relati ve 0

CS HK2 LDHA ACO2 IDH3a SDHA 20 Negative N 40 T387 GSC O T3565 GSC shCONT shCONT 30 15 shSDHA.1523 shSDHA.1523 L T387 GSC T3565 GSC shSDHA.619 shSDHA.619 shCONT + −− + −− 20 10 * * * * shSDHA −−1523 619 1523 619 * * * * 10 5 * * SDHA Relative cell number Relative Relative cell number Relative 0 OLIG2 0 2468 024 68 Time (day) Time (day) SOX2

TUBULIN P 1.5

T387 T387DGC M Cleaved 1.0 T3565 caspase-3 T3565DGC 0.5 NM263

Total PARP actional viability Fr

Cleaved PARP 0.0 100 101 102 103 TUBULIN β-Nitropropionic acid (µmol/L)

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Targeting the Circadian Clock in Glioblastoma Stem Cells RESEARCH ARTICLE

shown), suggesting that BMAL1 and CLOCK control OXPHOS sensitivity of GSCs, as measured by EC50 (Fig. 5F and G). independent of mitochondrial dynamics. Consistent with BMAL1 knockdown in GSCs, REV-ERB agonists reduced the expression of genes involved in glycoly- Succinate Dehydrogenase Is Controlled by BMAL1 sis, the TCA cycle, and lipid metabolism (Supplementary Fig. and CLOCK and Essential for GSC Maintenance S7A–S7F), consistent with prior observations (36). To extend the understanding of circadian control of GSC Distinct from REV-ERBs, CRY1 and CRY2, two other metabolism, we interrogated enzymes that have been linked core clock components, function by interacting directly with to tumor growth and were specifically downregulated in BMAL1–CLOCK complexes to repress their activity (16). KL001 GSCs upon targeting BMAL1 or CLOCK. Succinate dehydro- (N-(3-(9H-carbazol-9-yl)-2-hydroxypropyl)-N-(furan-2-ylme- genase (SDHA) is a unique enzyme participating in both the thyl)methanesulfonamide), a carbazole derivative previously TCA cycle and the electron transport chain. We observed discovered in our high-throughput cell-based screens, stabi- consistently decreased SDHA levels after transduction with lizes CRYs by inhibiting FBXL3-mediated ubiquitination and either shBMAL1 or shCLOCK (Supplementary Fig. S6L). degradation of CRY proteins (Fig. 5H; ref. 37). CRYs represent SDHA knockdown reduced the levels of stemness markers attractive targets for agonism/stabilization in several disease SOX2 and OLIG2 (Fig. 4L), induced apoptosis as measured areas such as inflammation, metabolic disease, and cancers (29, by cleavage of caspase-3 and PARP (Fig. 4M), and abolished 38, 39). Here, we found that KL001 treatment led to decreased growth of GSCs (Fig. 4N and O). Pharmacologic inhibition expression of PER1 and PER2 but increased BMAL1 protein of SDHA using ß-nitropropionic acid (NPA) suppressed GSC levels in a concentration-dependent manner in GSCs (Fig. 5I; growth to a greater degree than growth of either DGCs or Supplementary Fig. S7G). KL001 decreased OLIG2 and SOX2 nonmalignant brain cells (Fig. 4P), suggesting that TCA dis- expression in GSCs (Fig. 5J) and inhibited GSC proliferation ruption differentially represses GSC proliferation. more effectively than proliferation of normal brain cells and DGCs (Fig. 5K). CRY1 overexpression decreased MYC levels and Pharmacologic Targeting of Circadian Machinery impaired GSC proliferation (Fig. 5L–N). Thus, pharmacologic in GSCs Specifically Impairs GSC Survival modulation of circadian components may offer a novel strategy BMAL1 and CLOCK are transcription factors, which are for improving glioblastoma treatment. notoriously challenging to target, especially in the brain, where drug delivery is highly restricted. However, the cir- Combinatorial Pharmacologic REV-ERBs and cadian machinery has two independent negative feedback Cryptochrome Agonists Inhibit GSC Growth loops for which pharmacologic agents have been developed Targeting circadian control of GSCs through monotherapies as agonists or stabilizers that would be expected to disrupt with REV-ERB or CRY agonists selectively suppresses GSC the positive circadian activity mediated by BMAL1 and growth. We hypothesized that combinatorial activation of both CLOCK. SR9011 and SR9009 are small-molecule agonists major negative feedback loops of the circadian rhythm could of nuclear receptors REV-ERBα/β, which negatively regulate augment disruption of GSC growth. Indeed, the combination BMAL1 transcription by directly binding to its promoter of REV-ERBs and CRY agonists displayed combinatorial efficacy (Fig. 5A; ref. 36). SR9011 and SR9009 treatment reduced against two patient-derived GSCs (Fig. 6A–D; Supplementary expression of the circadian regulators BMAL1, PER1, and Fig. S8A–S8D). Combinations of SR9011 and KL001 reduced PER2 in a concentration-dependent manner (Fig. 5B and C). cell growth in a concentration-dependent manner to a greater SR9009 and SR9011 treatment attenuated the expression degree than single treatments (Fig. 6E–H). To evaluate the com- of the GSC markers OLIG2 and SOX2, supporting negative bination of SR9011 and KL001 on maintenance of stemness, self- transcriptional regulation of key GSC targets (Fig. 5D and renewal was measured by the limiting dilution assay. Following E). SR9011 and SR9009 also reduced GSC cell proliferation treatment with combined agents, sphere formation frequency to a greater degree than proliferation of DGCs, astrocytes, (Fig. 6I and J) and sphere size (Supplementary Fig. S8E) were and nonmalignant brain cultures, demonstrating greater reduced, revealing greater impairment of self-renewal capacity

Figure 4. Core clock components contribute to oxidative phosphorylation and the TCA cycle in GSCs. A and B, OXPHOS in T387 (A) and T3565 (B) GSCs after transduction with shCONT, shBMAL1, or shCLOCK using a Seahorse Extracellular Flux Analyzer (XF). OCR indicates OXPHOS. Cells were sequentially treated as indicated with oligomycin (2 μmol/L), P-trifluoromethoxy carbonyl cyanide phenylhydrazone (FCCP; 2μ mol/L), antimycin A (1 μmol/L), and rotenone (rote; 1 μmol/L). Vertical line indicates the time points for inhibitor administration. Data, mean ± SEM. N = 3. C and D, Histograms of basal oxidative phosphorylation in T387 (C) and T3565 (D) GSCs transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SEM. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test.N = 3. E and F, ATP capacity of T387 (E) and T3565 (F) GSCs transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SEM. **, P < 0.01; ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test.N = 3. G and H, Levels of uncoupled OXPHOS in T387 (G) and T3565 (H) GSCs transduced with shCONT, shBMAL1, or shCLOCK. Data, mean ± SEM. **, P < 0.01; ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test. N = 3. I and J, ChIP-qPCR experiments showing BMAL1 and CLOCK occupancy at the promoter regions of the indicated genes in T387 (I) and T3565 (J) GSCs. All the results are normalized to IgG control. N = 3. K, Transcript levels of the indicated genes related to glycolysis and the TCA cycle in GSCs upon BMAL1 or CLOCK knockdown. Data, mean ± SD. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test.N = 3. L, Protein levels of critical GSC transcription factors (SOX2 and OLIG2) after targeting SDHA with shRNAs for 48 hours. N = 3. M, Immunoblotting of cleaved caspase-3 and cleaved PARP in GSCs transduced with shCONT or shSDHA. N = 3. N and O, Cell survival analysis of T387 (N) and T3565 (O) GSCs transduced with shCONT or shSDHA. Relative cell survival was measured at indicated day (0, 2, 4, 6, or 8). Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test. N = 3. P, Concentration-response curve of GSCs (T387 GSC and T3565 GSC), DGCs (T387 DGC and T3565 DGC), and nonmalignant brain cultures (NM263) treated with NPA for 3 days. N = 3.

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A B l 1.5 l 1.5

ve T387 GSC ve T3565 GSC Vehicle SR9009 REV-ERBs SR9011 (5 µmol/L)

SR9011 BMAL1 CLOCK 1.0 1.0 SR9011 (10 µmol/L) Activation E-box * * * * SR9011 (20 µmol/L) * * * * * * * * * * * * * * * * BMAL1 0.5 * 0.5 * * * REV-ERBs * * * CLOCK * * * * *

BMAL1 mRNA le Relative 0.0 mRNA le Relative 0.0 BMAL1 PER1 PER2 BMAL1 PER1 PER2

Vehicle C 1.5 T387 GSC DE1.5 Vehicle 1.5 SR9009 (5 µmol/L) T387 GSC T387 GSC Vehicle SR9011 (5 µmol/L) SR9009 (10 µmol/L) SR9009 (5 µmol/L) SR9011 (10 µmol/L) 1.0 SR9009 (20 µmol/L) SR9009 (10 µmol/L) 1.0 SR9011 (20 mol/L) 1.0 * * µ * SR9009 (20 µmol/L) * * * * * l *

* l

* l * * * * * * * * * ve * 0.5 * * ve * * * ve * 0.5 * * 0.5 * * * * * * * 0.0 0.0 0.0 1.5 T3565 GSC 1.5 T3565 GSC 1.5 T3565 GSC

1.0 1.0 1.0 Relative mRNA le Relative Relative mRNA le Relative

* * mRNA le Relative * * * * * * * * * * * * * * * * * * * * * * * * 0.5 * * * 0.5 * * 0.5 * * * * * * * * 0.0 0.0 0.0 BMAL1 PER1 PER2 SOX2 OLIG2 SOX2 OLIG2

FG1.2 EC ( mol/L) 1.5 Cells 50 µ Cells EC50 (µmol/L) T387 GSC 6.41 T387 GSC 8.20 0.8 T3565 GSC 3.93 1.0 T3565 GSC 8.07 T387 DGC 10.08 T387 DGC 13.57 T3565 DGC 10.42 T3565 DGC 19.25 0.4 0.5 NM263 69.97 NM263 20.77 Relative viability Relative NM290 99.04 viability Relative NM290 21.33 0.0 NHA 46.29 0.0 NHA 20.59 10−1 100 101 102 10−1 100 101 102 SR9011 (µmol/L) SR9009 (µmol/L)

Figure 5. Targeting BMAL1 with small molecules provides a therapeutic strategy for glioma. A, Schematic of negative feedback loop driven by REV- ERBs and BMAL1–CLOCK. The small molecules SR9011 and SR9009 repress BMAL1 expression by activating REV-ERBs. B and C, Transcript levels of core clock genes measured by quantitative RT-PCR in two GSCs treated with different concentrations of SR9011 (B) or SR9009 (C) for 3 days. Data, mean ± SD. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test. N = 3. D and E, Transcript level of GSC markers in two GSCs incubated with different concentrations of SR9011 (D) or SR9009 (E) for 3 days in vitro. N = 3. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test. N = 3. F and G, Con- centration–response curves and EC50 of various cell types treated with SR9011 (F) or SR9009 (G; x axis, log scale). T387 and T3565 are GSCs, T387 DGC and T3565 DGC are DGCs, NM263 and NM290 are nonmalignant brain cultures, NHA is astrocyte. N = 3. Data, mean ± SD. (continued on following page) than either single agent alone. Combined treatment also Genetic and Small-Molecule Targeting of Core reduced the expression of core clock genes and the metabolic Clock Components in GSCs Inhibits Tumor Growth genes, indicating on-target affects (Fig. 6K). Cleaved caspase-3 staining in GSCs following combined drug treatment showed To address whether disruption of core circadian genes a marked induction of apoptosis compared with either single influences in vivo brain tumor growth, we implanted GSCs agent (Fig. 6L and M; Supplementary Fig. S8F). Combined drug transduced with either shCONT or shRNAs targeting BMAL1 treatment also augmented disruption of cell-cycle progression, or CLOCK into the frontal lobes of immunocompromised as assessed by EdU incorporation assay and Ki-67 staining (Fig. mice. The life span of tumor-bearing mice nearly doubled 6N and O; Supplementary Fig. S8G–S8H). Enhanced apop- upon BMAL1 or CLOCK knockdown relative to controls tosis in GSCs after combined drug treatment was confirmed (Fig. 7A and B). Tumor-bearing brains harvested 20 days after by increased cleaved PARP (Fig. 6P). GSCs display potent cell GSC transplantation revealed no visible or very small tumors migration, so we performed wound-healing assays, revealing in mice bearing GSCs transduced with either shBMAL1 or that wound closure was delayed following treatment with two shCLOCK, whereas tumors reaching our endpoint criteria agonists (Fig. 6Q and R), suggesting that the combination of were present in mice bearing GSCs transduced with shCONT SR9011 and KL001 impaired cell migration ability in GSCs. (Fig. 7C–F). To validate these loss-of-function studies, we Collectively, these results demonstrate proof of concept for performed reciprocal gain-of-function experiments, revealing combinatorial targeting of both negative circadian feedback that GSCs with BMAL1 overexpression proliferated more loops in the disruption of GSC proliferation and survival. rapidly than GSCs expressing EGFP (Supplementary Fig. S8I

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Targeting the Circadian Clock in Glioblastoma Stem Cells RESEARCH ARTICLE

KL001 l Stabilization l H I 1.5 1.5 Vehicle ve

ve T387 GSC T3565 GSC CRY KL001 (10 µmol/L) KL001 (20 µmol/L) PER 1.0 1.0 Dimerization * * * * * * * * PER 0.5 * 0.5 CRY PERs * * BMAL1 CLOCK * * * CRYs * * * E-box * Relative mRNA le Relative Relative mRNA le Relative 0.0 0.0 BMAL1 PER1 PER2 BMAL1 PER1 PER2

J K 1.5 Cells EC50 (µmol/L) l l 1.5 1.5 T387 GSC T3565 GSC Vehicle T387 GSC 21.22 ve ve KL001 (10 µmol/L) 1.0 T3565 GSC 19.76 1.0 KL001 (20 µmol/L) 1.0 * T387 DGC 51.19 * * * T3565 DGC 46.49 * * * * * 0.5 NM263 42.38 0.5 * 0.5

Relative viability Relative NM290 44.75

Relative mRNA le Relative NHA 44.91 Relative mRNA le Relative 0.0 0.0 0.0 SOX2 OLIG2 SOX2 OLIG2 10−1 100 101 102 KL001 (µmol/L)

LMT387 GSC N T3565 GSC T387 GSC T3565 GSC 40 40 GFP +− +− GFP GFP CRY1 −+ −+ 30 CRY1 30 CRY1

CRY1 20 * 20 * * * 10 10 MYC Relative cell numbers Relative Relative cell numbers Relative 0 0 ACTIN 0246 0246 Days after seeding cells Days after seeding cells

Figure 5. (Continued) H, Schematic of CRY feedback loop. The small-molecule modulator KL001 inhibits BMAL1 activity via stabilizing CRY1. I and J, Transcript expression of core clock genes (I) and GSC markers (J) measured by quantitative RT-PCR following treatment of GSCs with different concentrations of KL001 for 3 days. Data, mean ± SD. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison test. N = 3. K, Concentration–response curves and EC50 of GSCs (T387 and T3565), DGCs (T387DGC and T3565DGC), nonmalignant brain cultures (NM263 and NM290), and astrocytes (NHA) treated with different concentrations of KL001 (x axis, log scale) for 3 days. N = 3. L, Immunoblot of CRY1 and MYC in GSCs overexpressing CRY1. Data are representative results from three independent experiments. M and N, Relative cell numbers of GSCs overexpressing CRY1 or GFP. Data, mean ± SD. ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison test. N = 3. and S8J). Mice bearing GSCs overexpressing BMAL1 survived the frontal lobes of mice, and treatment was initiated once for shorter periods than mice bearing GSCs transduced with measurable tumors were evident. SHP656 was well toler- EGFP (Supplementary Fig. S8K and S8L). Taken together, ated, with no evidence of weight loss or changes in mouse these results demonstrate that BMAL1 and CLOCK contrib- behavior (Supplementary Fig. S8M and S8N). SHP656 treat- ute significantly toin vivo tumor growth of GSCs. ment prolonged the survival of mice bearing two different Although REV-ERB agonists have been previously tested in patient-derived GSCs compared with nontreatment (Fig. 7H glioblastoma preclinical studies using mouse cells (25), CRY and I). Thus, targeting the circadian rhythm of GSCs via CRY- agonists offer a novel therapeutic route. In vivo tool molecules stabilizing compounds to inhibit tumor growth in vivo is a derived from KL001 have been developed and shown to be viable treatment paradigm to pursue. efficacious in preclinical models of diabetes (40). We tested To determine the potential clinical utility of targeting one of the most promising proof-of-concept tool molecules, the circadian rhythm machinery, we interrogated BMAL1 SHP656, to characterize the potential utility of CRY stabiliz- expression in The Cancer Genome Atlas (TCGA), revealing ers for glioblastoma therapy. Treating patient-derived GSCs, that BMAL1 mRNA levels were elevated in glioblastomas rela- DGCs, or NM epilepsy-derived neural cells with different tive to lower grades of glioma and other glioma histologies concentrations of the compound showed that SHP656 selec- (Fig. 7J and K). High BMAL1 expression was associated with poor tively reduced the cell number of GSCs without obvious prognosis across tumor grades and within glioblastoma suppression of DGCs or NMs at the same concentrations (Fig. 7L and M), whereas higher levels of mRNAs encoding (2–30 μmol/L; Fig. 7G). To determine potential in vivo effi- the circadian clock repressors CRY2, REV-ERBα, PER2, and PER3 cacy, we implanted GSCs bearing a luciferase reporter into were associated with improved survival in patients with glioma

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T387 GSC T387 GSC AC T387 GSC T387 GSC −0 −20 −10 0102030 −20 −15 −10 −5 0510 15 20 E G

60 60 30 20 Vehicle Vehicle 20 15 KL001 (10 µmol/L) KL001 (15 mol/L) 10 µ 10 5 40 SR9011 (5 µmol/L) 40 SR9011 (7.5 µmol/L) * 0 0 Combined *** Combined −10 −5 −10 *** 20 score Synergy − 15 *** Synergy score Synergy − 20 20 −30 −20 100 SR9011 ( 50 *** 50 25 25 SR9009 (µmol/L)

100 12.5 cell number Relative 12.5 50 50 0 cell number Relative 0 µmol/L) 25 6.25 25 6.25 12.5 3.1 12.5 3.1 6.25 6.25 0246 0246 3.1 1.6 3.1 1.6 0 0 0 Days after treatment Days after treatment KL001 (µmol/L) 0 KL001 (µmol/L) B T3565 GSC D T3565 GSC F T3565 GSC H T3565 GSC −30 −20 −10 0102030 −20 −15 −10 −5 0510 15 20 40 45 Vehicle Vehicle 30 20 30 KL001 (10 µmol/L) KL001 (15 µmol/L) 20 15 SR9011 (5 mol/L) * 30 SR9011 (7.5 µmol/L) 10 10 µ * 5 Combined 0 20 Combined 0 *** −10 −5 *** 15 −20 −10 ***

Synergy score Synergy 10 Synergy score Synergy −30 −15 50 −20 *** SR9011 25( 50 Relative cell number Relative SR900925 (µmol/L) 0 cell number Relative 0 12.5 100 12.5 0246 0246 µmol/L)6.25 50 6.25 50 25 25 3.1 12.5 3.1 12.5 6.25 Days after treatment Days after treatment 6.25 1.6 3.1 0 0 1.6 KL001 (µmol/L) 0 0 KL001 (µmol/L)

I Vehicle SR9011 (10 µmol/L) J K 30 Vehicle 1.2 T387 GSC Vehicle KL001 (20 µmol/L) T387 GSC Combined * * KL001 (20 µmol/L) * * * KL001 (20 µmol/L) SR9011 (10 µmol/L) * SR9011 (10 µmol/L) 20 Combined * Combined − 0.5 * *** 0.6 * * *** * * * * * *** l * * * * * * *** *** *** * * * * * * *

10 ve * − 1.5 * * * * * * * *

− 2.5 0 40 1.2 T3565 GSC T3565 GSC 30 * * * − 0.5 * * * *** * * * Relative mRNA le Relative * *** tal number of spheres/well * 0.6 * * * * * Log fraction nonresponding *** 20 * * To ** * * * − 1.5 *** *** *** ** * * * * * ** * 10 * * * * − 2.5 050 100 150 200 0 0.0 PER1 PER2 LDHA ACO2 OGDH

Dose (number of cells) 50 25 50 25 50 25 50 25 200 100 200 100 200 100 200 100 Cells/well

LMT387 GSC T3565 GSC N T387 GSC O T3565 GSC 50 *** 40 100 100 Vehicle * KL001 (20 mol/L) *** µ 80 80 SR9011 (10 mol/L) 40 30 µ ** Combined 60 60 30 ** cells (%) cells (%) ** cells (%) cells (%) 20 *** 20 ** * 40 40 10 ***

positi ve 10 positi ve 20 20 Cleaved caspase-3 Cleaved Cleaved caspase-3 Cleaved

0 0 EdU positi ve 0 EdU positi ve 0

P Q T3565 GSC R T387 GSC Vehicle KL001 (20 µmol/L) SR9011 (10 µmol/L) Combined T3565 GSC SR9011 (µmol/L) −−10 10 1.2 KL001 (µmol/L) − − 2020 0 hr Cleaved PARP * * 0.6 * * ACTIN *

24 hr wound area after T3565 GSC 0 alization to day SR9011 (µmol/L)1−− 010 0.0 KL001 (µmol/L) − − 2020 no rm 012 Relati ve Cleaved Days after treatment 48 hr PARP Vehicle SR9011 (10 µmol/L) KL001 (20 µmol/L) ACTIN Combined

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Targeting the Circadian Clock in Glioblastoma Stem Cells RESEARCH ARTICLE

(Fig. 7N-Q). These data support targeting the BMAL1–CLOCK connecting circadian regulators to cancer biology, including axis as a promising strategy for glioblastoma therapy in humans. tumor metabolism, metastasis, and immune dysregulation (14, 21, 41). The observation that specifically targeting circadian regulators diminishes viability of GSC populations DISCUSSION opens the possibility that modulating circadian machin- Disruption of circadian function in oncogenic processes has ery could offer novel treatment paradigms, e.g., combina- been largely considered at the systems level. Analysis of TCGA tions with traditional cytotoxic therapies, antiangiogenics, or data identified correlations between tumor types and tumor emerging immuno-oncology approaches. We recently identi- stage–specific alteration of cyclic clock genes with patient fied GO289, a highly potent and specific inhibitor of casein survival across 32 cancer types (23). Despite these insights into kinase 2 that regulates PER phosphorylation and circadian a role of circadian dysregulation in cancer, few novel mecha- gene expression (42), which suppressed BMAL1 transcrip- nisms of action to guide new cancer therapies have emerged. tion and reduced viability in renal cell carcinoma and acute Here, we report that cancer stem cells derived from patients myeloid leukemia cells versus nonmalignant cell lines. Math- afflicted with glioblastomas recruit core components of the ematical modeling of radiation administration has indicated circadian molecular machinery to regulate noncanonical target that timing of radiation treatment for glioblastoma may also genes distinct from those in the corresponding normal cells. improve tumor control (43). Circadian timing of treatment GSCs exhibit unique chromatin landscapes that reprogram affected the sensitivity of glioblastoma cells to temozolomide the output of BMAL1–CLOCK-dependent transcriptional in vitro, with maximal chemotherapy-induced DNA damage regimes. Circadian rhythmicity was preserved in multiple responses, activation of apoptosis, and growth inhibition patient-derived GSCs with different genetic backgrounds. occurring near the daily peak of BMAL1 expression (24). In Although MYC antagonizes circadian rhythms in cancer cells contrast to the traditional focus on chronotherapy being on (26), GSCs with MYC amplification or high expression demon- optimal timing of treatments, we propose that the identifi- strated robust cyclic activity of luminescence. Growth of nor- cation of the ectopic rewiring of BMAL1–CLOCK in GSCs mal brain cells and differentiated tumor cells was resistant to provides the rationale to develop glioblastoma therapies with genetic or pharmacologic disruption of circadian circuitry. In novel mechanisms of action. contrast, GSCs display high sensitivity to circadian targeting, The observations that GSCs express and depend on core with associated loss of viability and diminished self-renewal. circadian regulators could have several explanations, all of Furthermore, gain-of-function studies in GSCs revealed that which can contribute to the development of experimental BMAL1 expression accelerates tumor growth, providing further therapeutics. BMAL1 binding to cell type–specific promoters support for an oncogenic role for BMAL1–CLOCK activity in is mediated by tissue-specifically distributed histone modifi- the cancer stem cell compartment. Our findings in fully trans- cations controlling transcription factor accessibilities at the formed cancer cells stand in contrast to previous reports that TSSs of target genes that regulate the output profile (44). a circadian rhythm and core clock genes function as tumor Our analysis of BMAL1 and H3K27ac ChIP-seq in GSCs suppressors during initial tumorigenesis (20, 21), suggesting and NSCs revealed a strong correlation between BMAL1 that the role of core clock function in tumor progression may peaks, H3K27ac peaks, and H3K4me3 peaks. Genome-wide differ based on tumor development stage, cell type, and species BMAL1 occupancy in GSCs was more extensive and showed differences. Consistent with our observations presented here, higher peak intensity at active chromatin regions, as indi- BMAL1 and CLOCK are oncogenic in myeloid leukemia stem cated by H3K27ac modification, compared with occupancy in cells (12). These findings point to a global reprogramming of NSCs. BMAL1 displayed higher enrichment at E-box motifs circadian gene regulation, rather than the presence or absence with higher H3K27ac occupancy in GSCs, as compared with of overt rhythms in cancer cells, as being critical for under- NSCs. Thus, differential BMAL1 binding between GSCs and standing how the clock can be targeted for novel therapies. NSCs is most likely driven by the different epigenetic states Widespread transcriptional regulation by circadian net- and subsequently different chromatin accessibility at target works is reflected in the breadth of reported phenotypes sites including stemness genes. Based on our analysis of the

Figure 6. Synergism of REV-ERB and CRY agonists in vitro. A–D, Synergy indices of SR9011 and KL001 (A and B), SR9009 and KL001 (C and D) analyzed by R package “synergyfinder.”E and F, Relative cell survival of T387 (E) and T3565 (F) GSCs following treatment with indicated concentration of KL001 (10 μmol/L), SR9011 (5 μmol/L), or a combination. Data, mean ± SD. *, P < 0.05; ***, P < 0.001. Statistical significance was determined by two- way ANOVA with Tukey multiple comparison. N = 3. G and H, Relative cell viability of T387 (G) and T3565 (H) GSCs following treatment with indicated concentration of KL001 (15 μmol/L), SR9011 (7.5 μmol/L), or a combination. Data, mean ± SD. *, P < 0.05; ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison. N = 3. I and J, In vitro limiting dilution assays (I) and sphere numbers of GSCs (J) following treatment with KL001 and SR9011 at indicated concentrations for 8 days. Data of sphere numbers, mean ± SD. ***, P < 0.001. Statistical significance of sphere numbers was determined by one-way ANOVA with Tukey multiple comparison. The χ2 test was used for pair-wise differences in stem population frequency. N = 3. K, Relative mRNA level of circadian and metabolic genes after treatment with KL001 (20 μmol/L), SR9011 (10 μmol/L), or a combination. Data, mean ± SD. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison. N = 3. L and M, Quantification of cleaved caspase-3–positive cells by immunofluorescent staining in T387L ( ) and T3565 (M) GSCs after treatment with indicated agonists. Data, mean ± SD. *, P < 0.05; **, P < 0.01; ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison. N = 3. N and O, Quantification of EdU-positive cells by immunofluorescent staining in T387N ( ) and T3565 (O) GSCs after treatment with indicated agonists for 48 hours. Data, mean ± SD. **, P < 0.01; ***, P < 0.001. Statistical significance was determined by one-way ANOVA with Tukey multiple comparison. N = 3. P, Immunoblot of cleaved PARP in GSCs after treatment with indicated agonists for 48 hours. Data are representative results of three independent experiments. Q and R, In vitro wound-healing assay (Q) and calculated relative wound area (R) of T3565 GSC treatment with indicated agonists. Scale bar, 0.4 mm. N = 6. Data, mean ± SD. **, P < 0.01; ***, P < 0.001. Statistical significance was determined by two-way ANOVA with Tukey multiple comparison.

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A shCONT shBMAL1.1536 shBMAL1.689 B shCONT shCLOCK.1053 shCLOCK.1494 T387 GSC T3565 GSC T387 GSC T3565 GSC 100 100 100 100

**P < 0.01 **P < 0.01 **P < 0.01 **P < 0.01 **P < 0.01 50 **P < 0.01 50 50 50 **P < 0.01 **P < 0.01

Percent survival Percent 0 survival Percent 0 survival Percent 0 survival Percent 0 0102030 40 50 0102030 40 50 0102030 40 50 0102030 40 50 Time (days) Time (days) Time (days) Time (days)

C T387 GSC E T387 GSC shCONT shBMAL1.1536 shBMAL1.689 shCONT shCLOCK.1053 shCLOCK.1494

T3565 GSC F D T3565 GSC shCONT shBMAL1.1536 shBMAL1.689 shCONT shCLOCK.1053 shCLOCK.1494

G HIT387 GSC T3565 GSC 100 100 1.5 Cells EC50 (µmol/L) T387 GSC 15.03 1.0 T3565 GSC 8.50 *P = 0.047 T387 DGC 94.61 50 *P = 0.0103 50 0.5 T3565 DGC 68.42 Vehicle (n = 15) Vehicle (n = 10) SHP656 (n = 15) SHP656 (n = 10)

actional viability NM263 55.15 Percent survival Percent Percent survival Percent

Fr NM290 47.84 0.0 0 0 −1 0 12 010 20 30 010 20 30 SHP656 concentration (Log, µmol/L) Days after treatment Days after treatment

***P = 5.6e−31 ***P = 1.2e−39 J KL***P = 1.7e−24 100% M 100% −29 *** Log-rank P = 0 ** Log-rank P = 0.0042 12 ***P = 9.1e 12 −29 ***P = 2.2e *** Wilcoxon P = 0 * Wilcoxon P = 0.0185 75% 75% ) ) 2 10 2 10 50% 50% 8 Surviving 8 Surviving level (log level level (log level 25% 25% BMAL1 mRNA BMAL1 mRNA 6 6 0% 0% II III IV 050 100 150 200 050 100 Grade GBM TCGA-LGG GBM survival time (months) TCGA-GBM survival time (months) Astrocytoma BMAL1 high (n = 165, events = 116, media = 15.8) BMAL1 high (n = 125, events = 105, media = 14) BMAL1 low (n = 163, events = 24, media = 114.1) BMAL1 low (n = 120, events = 98, media = 16.5) OligoAstrocytoma Oligodendroglioma Histology

NOP Q 100% *** Log-rank P value = 0 100% *** Log-rank P value = 0 100% *** Log-rank P value = 0 100% *** Log-rank P value = 0 *** Wilcoxon P value = 0 *** Wilcoxon P value = 0 *** Wilcoxon P value = 0 *** Wilcoxon P value = 0 HR = 13.28 (7.8−22.58) HR = 2.44 (1.72−3.46) HR = 3.72 (2.51−5.52) HR = 7.36 (4.75−11.41) 75% 75% 75% 75%

50% 50% 50% 50% Surviving Surviving Surviving Surviving 25% 25% 25% 25%

0% 0% 0% 0% 050 100 150 200 050 100 150 200 050 100 150 200 050 100 150 200 TCGA-LGG GBM survival time (months) TCGA-LGG GBM survival time (months) TCGA-LGG GBM survival time (months) TCGA-LGG GBM survival time (months) CRY2 high (n = 167, events = 19, median = 134.3) NR1D1 high (n = 166, events = 47, median = 75) PER2 high (n = 167, events = 34, median = 98.2) PER3 high (n = 167, events = 27, median = 94.5) CRY2 low (n = 168, events = 114, median = 16.2) NR1D1 low (n = 168, events = 95, median = 22.2) PER2 low (n = 167, events = 94, median = 22.2) PER3 low (n = 166, events = 112, median = 16.8)

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Targeting the Circadian Clock in Glioblastoma Stem Cells RESEARCH ARTICLE genome-wide binding of BMAL1 and the differential chro- are bHLH-PAS transcription factors, which are commonly matin landscape of GSCs compared with NSCs, we propose considered undruggable, but pharmacologic modulation that BMAL1 (and CLOCK) drives ectopic transcriptional of the core circadian feedback loop has been undertaken programs via novel target binding sites, including canoni- through two distinct feedback mechanisms, both of which we cal binding sites (CLOCK and BMAL1), but also conserved have investigated. Here, SR9011 and SR9009 displayed high binding sites associated with ETS family members (ETV4 efficacy against GSCs ∼( 2-fold more responsive than DGCs and ETV6) as well as key regulators of chromatin tertiary and up to ∼25-fold more responsive than nonmalignant cells), structure (YY1, YY2, and CTCF; Fig. 3C). The broad net effect which is consistent with previous reports in mouse cell lines on transcriptional programs promotes key tumor metabolic (25), although SR9009 also has REV-ERB–independent effects effects on glucose and lipid metabolism, as well as EGFR (51). We extend the therapeutic hypothesis by demonstrating signaling (Fig. 3F), which itself has been linked to lipid reduced stemness upon treatment, supporting the potential metabolism (45). Consistent with the idea that BMAL1 and benefit of targeting core clock genes for cancer therapy. CLOCK drive networks that promote oncogenesis, we see spe- Suppressing BMAL1–CLOCK activity by modulating CRYs cific molecular targets that are regulated byBMAL1 in GSCs presents an entirely novel approach for glioblastoma treat- (e.g., hexokinase 2 and SDHA) that have been independently ment, and offers the possibility of combinatorial therapy with linked to tumor maintenance (46, 47). The collective emer- emerging as well as established agents. KL001 is a carbazole gent properties of this previously unidentified reprogram- derivative identified in a phenotypic cell-based screen (37). ming in GSCs strongly support the maintenance of tumor KL001 treatment results in the stabilization of CRY1 and CRY2 growth selectively in the stem-like tumor cells. proteins by binding the FAD pocket, subsequently reducing The disordered mitochondrial OXPHOS observed in our binding to the FBXL3 ubiquitin ligase and proteolysis (52). study, which is consistent with previous studies in other Here, we found that KL001 and its derivative, SHP656, are models (32), reinforced the critical roles of core clock genes highly potent in killing GSCs compared with other cell types. in maintaining metabolic states that support tumor growth. Parallel to this high specificity, SHP656 has shown minor tox- We and others have found that glucose metabolism is critical icity when administered to mouse (Supplementary Fig. S8M to maintenance of GSCs, which selectively take up glucose and S8N). Consistent with the known mode of action of CRY through a high-affinity uptake mechanism (48).BMAL1 or proteins (12), KL001 treatment suppressed E-box–dependent CLOCK maintained GSCs by promoting glycolysis and TCA expression of core clock genes such as PER1 and PER2. In addi- cycle activity, supported by the reduced glycolysis and TCA tion to its canonical effects, KL001 potently reduces the expres- cycle activity accompanied by decreased levels of TCA metab- sion of several genes required to maintain stemness. Although olites in GSCs upon BMAL1 or CLOCK knockdown (Fig. preclinical derivates of KL001 and SHP656 have been devel- 4A–H; Supplementary Fig. S6A–S6F, S6I, and S6J). Main- oped and applied to treatment for metabolic diseases (37, 40), tenance of pyruvate levels in GSCs after BMAL1 or CLOCK this is their first known application in oncology. knockdown may be attributed to reduced consumption of The link between the circadian clock and aging (53) sug- pyruvate due to reduced TCA cycling (Supplementary Fig. gests that circadian control may be differentially regulated S6K). Tumor metabolism generates oncometabolites that in pediatric brain tumors. Recent studies have demonstrated can serve as functional modulators or cofactors of chromatin that pediatric brain tumors are molecularly distinct from regulators (49, 50). GSC circadian rhythms may have a feed- adult brain tumors, with frequent mutations in core histone forward effect, whereby co-option of BMAL1–CLOCK activ- proteins (54), which induce epigenetic reprogramming, pos- ity, aligned with the relatively open chromatin of GSCs, may sibly altering available binding sites for BMAL1. Future stud- promote oncogenic effects that ultimately feed back to main- ies will define circadian regulation of pediatric brain tumors tain the open chromatin state. Thus, the targeting of core and the potential utility of targeting the circadian clock in circadian clock machinery in GSCs may represent a topologic these cancers. vulnerability that results in disruption of this feed-forward GSC resistance to current therapies represents a significant mechanism and collapse of cell state, which does not occur unmet medical need for patients with glioblastoma. Target- in NSCs or DGCs. Therapies that directly modulate circadian ing of one or more components of the circadian machinery regulators may augment the efficacy of pharmacologic agents offers a compelling new path for the development of novel that target tumor metabolism (e.g., DCA) or chromatin states therapies in combination with conventional therapies, radia- (e.g., EZH2, BMI1, or KDM inhibitors). BMAL1 and CLOCK tion and chemotherapy.

Figure 7. Targeting core clock components suppresses in vivo tumor growth. A and B, Kaplan–Meier survival curves of immunocompromised mice bearing GSCs transduced with shCONT (N = 5), shBMAL1 (N = 4; A), or shCLOCK (N = 4; B). Statistical significance was determined by Mantel–Cox log-rank test.C–F, Hematoxylin and eosin staining of tumor-bearing brains following implantation of GSCs transduced with either shCONT, shBMAL1 (C and D), or shCLOCK (E and F). Scale bars, 2 mm. G, Concentration–response curves and EC50 of GSCs (T387 and T3565), DGCs (T387DGC and T3565DGC), nonmalignant brain cultures (NM263 and NM290), and astrocytes (NHA) treated with different concentrations of SHP656 (x axis, log scale) for 3 days. N = 3. H and I, Kaplan–Meier survival curves of mice bearing T387 GSC (H) or T3565 GSC (I) treated with SHP656. Fifteen mice were used per arm for T387 GSC, and mice were treated twice a day at 10 mg/kg. Ten mice were used per arm for T3565 GSC and mice were treated once a day at 10 mg/kg. Statistical significance was determined by Mantel–Cox log-rank test.J and K, BMAL1 mRNA level in different grades (J) or histologies (K) of patients with glioma from TCGA data set. Data, mean ± SD. Statistical significance of sphere numbers was determined by one-way ANOVA with Tukey multiple comparison test. L and M, Kaplan–Meier survival curves of patients with higher or lower BMAL1 expression in low grades of glioma and glioblastoma (L) or glioblastoma alone (N). Statistical significance was determined by Mantel–Cox log-rank test.N–Q , Kaplan–Meier survival curves of patients with higher or lower CRY2 (N), NR1D1 (O), PER2 (P), or PER3 (Q) expression in low grades of glioma and glioblastoma. Statistical significance was determined by Mantel–Cox log-rank test. GBM, glioblastoma; LGG, low grades of glioma.

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METHODS Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Z. Dong, G. Zhang, M. Qu, Derivation of Glioblastoma Stem Cells R.C. Gimple, Z. Qiu, B.C. Prager, L.J.Y. Kim, A.R. Morton, D. Dixit, Patients undergoing surgical resection for glioblastomas at Duke B. Li, Z. Zhu, L. Chavez, S.A. Kay University or University Hospitals–Case Medical Center provided Writing, review, and/or revision of the manuscript: Z. Dong, written informed consent in accordance with a protocol (090401) G. Zhang, M. Qu, R.C. Gimple, S. Bao, J.N. Rich approved by Institutional Review Board. All patient-related studies Administrative, technical, or material support (i.e., reporting were conducted in accordance with the Declaration of Helsinki. After or organizing data, constructing databases): Z. Dong, X. Wang, review by neuropathology, excess glioblastoma surgical specimens H. Huang, L. Chavez, J.N. Rich were obtained. Validated brain tumor–initiating cells were isolated Study supervision: L. Chavez, J.N. Rich from glioma specimens and xenografts through prospective sorting and functionally characterized, as previously described (55). Short Acknowledgments tandem repeat analyses were performed yearly to authenticate the We appreciate the UCSD Histology Core for their work on histo- identity of GSCs used in this article. Mycoplasma testing was per- logic experiments and analysis. We thank Kunliang Guan, Bing Ren, formed by PCR using cellular supernatants. To decrease the incidence Mark Perelis, and Rich lab members for their help. We thank Synchro- of artifacts caused by in vitro culture, patient-derived xenografts were nicity Pharma for providing the CRY stabilizer, SHP656. Figure 3O propagated as a renewable source of tumor cells. Cells were grown was prepared in part using images from Servier Medical Art by Ser- in vitro fewer than 10 passages for in vitro and in vivo experiments. vier (https://smart.servier.com/). This work was supported by NIH grants (CA197718, CA154130, CA169117, CA171652, NS087913, and Intracranial Tumor Formation In Vivo NS089272 to J.N. Rich; DK108087 to S.A. Kay; CA184090, NS091080, All mouse procedures were performed under an animal protocol and NS099175 to S. Bao; CA217066 to B.C. Prager; CA217065 to R.C. approved by the University of California, San Diego, Institutional Gimple; CA203101 to L.J.Y. Kim; and CA236313 to A.R. Morton). Animal Care and Use Committee. Intracranial transplantation of GSCs was performed as previously described (55). Fifty thousand The costs of publication of this article were defrayed in part by viable cells transduced with shRNA for 48 hours were injected intrac- the payment of page charges. This article must therefore be hereby ranially into the right cerebral cortex of NSG (NOD.Cg-Prkdcscid marked advertisement in accordance with 18 U.S.C. Section 1734 ll2rgtm1Wjl/SzJ; The Jackson Laboratory) immunocompromised mice. solely to indicate this fact. To compare the tumor growth, brains were isolated from mice implanted with GSCs on the same day when there was development Received February 16, 2019; revised May 29, 2019; accepted August of neurologic signs after implantation. For the survival experiment, 1, 2019; published first August 27, 2019. mice were maintained until manifestation of neurologic signs. For in vivo therapy, NSG mice were implanted intracranially with 20,000 cells. After 7 days, mice were divided into a vehicle control (1% REFERENCES carboxymethyl cellulose) group and an SHP656 group. The reagents 1 Ostrom QT, Gittleman H, Liao P, Vecchione-Koval T, Wolinsky Y, were administered by oral gavage (10 mg/kg twice a day for T387, Kruchko C, et al. 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NOVEMBER 2019 CANCER DISCOVERY | 1573

Targeting Glioblastoma Stem Cells through Disruption of the Circadian Clock

Zhen Dong, Guoxin Zhang, Meng Qu, et al.

Cancer Discov 2019;9:1556-1573. Published OnlineFirst August 27, 2019.

Updated version Access the most recent version of this article at: doi:10.1158/2159-8290.CD-19-0215

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