Transcriptional Regulation of the Warburg Effect in Cancer by SIX1

Article

Transcriptional Regulation of the Warburg Effect in Cancer by SIX1 Graphical Abstract

Authors Ling Li, Yingchun Liang, Lei Kang, ..., Shixin Zhao, Xiaojie Xu, Qinong Ye

Correspondence [email protected] (X.X.), [email protected] (Q.Y.)

In Brief Li et al. show that transcription factor SIX1 regulates aerobic glycolysis in cancer by binding promoters and recruiting HBO1 and AIB1 to induce the expression of glycolytic genes. SIX1 is negatively regulated by miR-548a-3p, and modulation of components of this pathway affects tumor metabolism and growth.

Highlights d

SIX1 is a key transcription factor involved in the Warburg effect

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SIX1 potentiates the Warburg effect via HBO1 and AIB1

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SIX1 glycolytic function is directly repressed by microRNA548a-3p

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The miR-548a-3p/Six1 axis regulates the Warburg effect and tumor growth

Li et al., 2018, Cancer Cell 33, 1–18 March 12, 2018 ª 2018 Elsevier Inc. https://doi.org/10.1016/j.ccell.2018.01.010

Data Resources GSE93925

Please cite this article in press as: Li et al., Transcriptional Regulation of the Warburg Effect in Cancer by SIX1, Cancer Cell (2018), https://doi.org/ 10.1016/j.ccell.2018.01.010

Cancer Cell

Article Transcriptional Regulation of the Warburg Effect in Cancer by SIX1 Ling Li,1,11 Yingchun Liang,1,11 Lei Kang,1,2 Yang Liu,1,3 Shan Gao,4 Siyu Chen,1,3 Ying Li,1,5 Wenye You,1,5 Qian Dong,1 Tian Hong,1 Zhifeng Yan,6 Shuai Jin,1,3 Tao Wang,7 Wei Zhao,8 Haixing Mai,9 Jun Huang,9 Xiao Han,1 Quanbo Ji,10 Qi Song,5 Chao Yang,8 Shixin Zhao,1 Xiaojie Xu,1,* and Qinong Ye1,12,* 1Department of Medical Molecular Biology, Beijing Institute of Biotechnology, Collaborative Innovation Center for Cancer Medicine, Beijing 100850, China 2Department of Nuclear Medicine, Peking University First Hospital, Beijing 100034, China 3Department of Thoracic Surgery, PLA General Hospital, Beijing 100853, China 4CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China 5Department of Oncology, PLA General Hospital, Beijing 100853, China 6Department of Gynecology and Obstetrics, PLA General Hospital, Beijing 100853, China 7Department of Oncology, 307 Hospital of People’s Liberation Army, Beijing 100071, China 8Department of Oncology, General Hospital of the PLA Rocket Force, Beijing 100088, China 9Department of Urology, 307 Hospital of People’s Liberation Army, Beijing 100071, China 10Department of Orthopedics, PLA General Hospital, Beijing 100853, China 11These authors contributed equally 12Lead Contact *Correspondence: [email protected] (X.X.), [email protected] (Q.Y.) https://doi.org/10.1016/j.ccell.2018.01.010

SUMMARY

Aerobic glycolysis (the Warburg effect) facilitates tumor growth, and drugs targeting aerobic glycolysis are being developed. However, how the Warburg effect is directly regulated is largely unknown. Here we show that transcription factor SIX1 directly increases the expression of many glycolytic genes, promoting the Warburg effect and tumor growth in vitro and in vivo. SIX1 regulates glycolysis through HBO1 and AIB1 histone acetyltransferases. Cancer-related SIX1 mutation increases its ability to promote aerobic glycolysis and tumor growth. SIX1 glycolytic function is directly repressed by microRNA-548a-3p, which is downregulated, inversely correlates with SIX1, and is a good predictor of prognosis in breast cancer patients. Thus, the microRNA-548a-3p/SIX1 axis strongly links aerobic glycolysis to carcinogenesis and may become a promising cancer therapeutic target.

INTRODUCTION Cancer cells exhibit aberrant metabolism characterized by high glycolysis even in the presence of abundant oxygen. This phenomenon, known as the Warburg effect or aerobic glycolysis, facilitates tumor growth with elevated glucose uptake and lactate production (Koppenol et al., 2011; Liberti and Locasale, 2016). The Warburg effect has now been widely accepted as a

hallmark of cancer, and cancer therapeutic agents targeting the Warburg effect are being developed. More than ten genes encoding glycolytic enzymes are directly responsible for the Warburg effect (Doherty and Cleveland, 2013; Ngo et al., 2015). Transcription factors play a direct role in regulation of the Warburg effect (Yeung et al., 2008). Hypoxia-inducible factor 1a (HIF-1a) is a transcriptional activator that acts as a key regulator of the Warburg effect. HIF-1a increases expression of

Significance The Warburg effect (aerobic glycolysis) is a hallmark of cancer, and cancer therapeutic agents targeting the Warburg effect are being developed. HIF-1a and c-Myc transcription factors are well-known key regulators of the Warburg effect. Our study identifies SIX1 as a major transcription factor playing a causal role in glycolysis regulation and represents an advance in the field of transcriptional regulation of glucose metabolism. SIX1 promotes aerobic glycolysis through HBO1 and AIB1 histone acetyltransferases and is directly repressed by microRNA-548a-3p. Since SIX1 is overexpressed and microRNA-548a-3p is downregulated in cancer patients, and both of them predict cancer patient survival, targeting the microRNA-548a-3p/SIX1 axis may open an avenue for cancer therapy. Cancer Cell 33, 1–18, March 12, 2018 ª 2018 Elsevier Inc. 1

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the majority of glycolytic genes by binding hypoxia-responsive elements of glycolytic gene promoters. The c-Myc oncogenic transcription factor also directly transactivates glycolytic genes and stimulates aerobic glycolysis. In contrast, the tumor-suppressive transcription factor p53 directly represses glycolytic gene transcription, causing a decrease in aerobic glycolysis. Although a few transcription factors have been shown to control the Warburg effect, transcriptional regulation of this effect remains largely unknown. Transcription factor sine oculis homeobox 1 (SIX1) is a key regulator of organogenesis (Kumar, 2009; Wu et al., 2015). Six1 knockout (KO) mouse embryos have defects in several organs and are relatively smaller in size than wild-type (WT) littermates (El-Hashash et al., 2011; Laclef et al., 2003). Six1 KO mice die shortly after birth. SIX1 is overexpressed in many cancers, such as breast cancer, liver cancer, and colorectal cancer (Coletta et al., 2008; Ng et al., 2006; Wu et al., 2015). Increased SIX1 expression predicts poor clinical outcomes. SIX1 can promote tumor growth and metastasis. However, whether SIX1 regulates cancer metabolism is unclear. RESULTS Identification of SIX1 as a Key Regulator of Glycolytic Gene Expression To identify SIX1 downstream effectors, we performed RNA sequencing (RNA-seq) using SIX1 stable knockdown (KD) ZR75-1 breast cancer cell line or control cell line. Consistent with previous reports (Coletta et al., 2008; Liu et al., 2014), SIX1 had two major bands in immunoblots (Figure 1A). SIX1 regulated the expression of over 1,900 genes, including previously reported SIX1-regulated genes (accession number GEO: GSE93925) (Figure 1A and Table S1). KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis showed that the top 20 enriched pathways included the glycolysis pathway (Figure 1B). Real-time RT-PCR confirmed the altered expression of known SIX1 target genes and 11 glycolysis-related genes (GLUT1/4 [glucose transporter 1/4 or SLC2A1/4], HK2 [hexokinase 2], PFKL [6-phosphofructokinase, liver type], ALDOA [aldolase A], GAPDH [glyceraldehyde 3-phosphate dehydrogenase], PGK1 [phosphoglycerate kinase 1], ENO1 [enolase 1], ENO2, PKM2 [pyruvate kinase M2], and LDHA [lactate dehydrogenase A]) (Figure S1A). Some known SIX1 target genes and glycolysis-related genes were further validated using previously reported microarray data from MCF7 breast cancer cells overexpressing SIX1 (Micalizzi et al., 2009) (Table S2). The effect of SIX1 KD on glyco-

lytic gene transcription could be rescued by SIX1 re-expression in SIX1 KD ZR75-1 breast cancer cells and HepG2 hepatoma cells (Figure S1B). Breast cancer and hepatoma cells were chosen for glycolysis experiments since previous research has shown that these cells exhibit the Warburg effect (Dome´nech et al., 2015; Finley et al., 2011). SIX1 KD also decreased the expression of GLUT1, HK2, PFKL, ALDOA, GAPDH, PGK1, ENO1, PKM2, and LDHA proteins, but not GPI (glucose-6phosphate isomerase) and PGAM1 (phosphoglycerate mutase) proteins (Figure S1C). Again, this effect could be rescued by SIX1 re-expression. In contrast, SIX1 overexpression increased the expression of these glycolytic genes except GPI and PGAM1 (Figure S1D). Overexpression of HIF-1a, a well-known master regulator of glycolysis, enhanced the expression of these glycolytic genes except PGAM1. However, SIX1 promotion of glycolytic gene expression was not dependent on HIF-1a, because HIF-1a KD had no effect on enhancement of glycolytic gene expression by SIX1 overexpression (Figure S1E). Moreover, compared with SIX1 WT ZR75-1 cells, SIX1 KO cells generated by CRISPR/Cas9 showed markedly reduced GLUT1, HK2, PFKL, ALDOA, GAPDH, PGK1, ENO1, PKM2, and LDHA, but not GPI and PGAM1, at the mRNA and protein levels (Figures 1C, 1D, and S1F). SIX1 re-expression in the SIX1 KO cells rescued these effects. Similar results were observed in Six1 KO mouse embryonic fibroblasts (MEFs), Six1 KO embryos, and liver, intestine, and lung tissues from Six1 KO embryos (Figures 1E–1H and S1G). These data indicate that SIX1 is a key regulator of glycolytic gene expression. SIX1 Binds SIX1-Responsive Elements to Promote Glycolytic Gene Promoter Activity Genome-wide analysis of SIX1 binding sites using chromatin immunoprecipitation sequencing (ChIP-seq) and ChIP-on-chip revealed that the SIX1 DNA binding motif contains TCAG/TG (Wegert et al., 2015; Liu et al., 2010, 2012a). In addition, these datasets showed that SIX1 binds six glycolytic genes (PFKL, ALDOA, PGK1, ENO1, PKM2, and LDHA). To test whether SIX1 transcriptionally regulates glycolytic gene expression, we searched up to approximately 3 kb of promoter regions of these genes for putative SIX1 binding sites and constructed promoter reporters containing the putative binding sites (Figures 2A and S2A). SIX1 overexpression increased the reporter activity of GLUT1, HK2, PFKL, ALDOA, GAPDH, PGK1, ENO1, PKM2, and LDHA promoters. GLUT1, ALDOA, and PGK1 contained one putative SIX1 binding site, and mutation of these binding sites each abrogated SIX1-mediated potentiation of promoter

Figure 1. SIX1 Regulates Glycolytic Gene Expression (A) Heatmap of known SIX1 target genes and glycolytic genes identified by RNA-seq using ZR75-1 cells stably infected with lentivirus carrying SIX1 short hairpin RNA (shRNA) or control shRNA. Typical immunoblot shows the knockdown of SIX1 expression. (B) KEGG pathway analysis of genes differentially expressed between ZR75-1 cells stably infected as in (A). (C and D) Analysis of glycolytic gene expression in SIX1 wild-type (WT) or knockout (KO) ZR75-1 cells or SIX1 KO ZR75-1 cells transiently transfected with SIX1. qRT-PCR (C) and immunoblot (D). Schematic diagram of aerobic glycolysis pathway is shown on the left (C). (E and F) Glycolytic gene expression in Six1 WT or KO MEFs isolated from corresponding mouse. qRT-PCR (E) and immunoblot (F). The WT mice were littermates of the KO mice (n = 5). (G) Representative whole-mount IHC analysis of GAPDH and LDHA for Six1 WT and KO mouse embryos at day 15.5 of gestation. The anatomy image is shown. Scale bar, 1 mm. (H) Representative immunoblot analysis of glycolytic gene expression in livers, intestines, or lungs from Six1 WT and KO mouse embryos at day 15.5 of gestation. Data shown are mean ± SD of triplicate measurements that have been repeated 3 times with similar results. Data were analyzed using two-tailed Student’s t test. *p < 0.05, **p < 0.01 versus corresponding WT cells. See also Figure S1; Tables S1 and S2.

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reporter activity. For genes with multiple putative binding sites, mutation of one or of multiple sites was needed to abrogate activity, depending on the promoter. Mutation of binding site 1, but not other site(s), abolished SIX1-mediated induction of PKM2 and HK2 promoter reporter activity. For GAPDH and LDHA promoter reporters, mutation of binding site 1 or 2 attenuated activity mediated by SIX1, and mutation of both binding sites completely abolished the activity. Finally, mutation of binding site 1, 2, or 3 attenuated SIX1-mediated enhancement of ENO1 and PFKL promoter reporter activity, and the mutation of the three sites completely abolished the activity. ChIP assay indicated that endogenous SIX1 was recruited to the regions containing the binding sites whose mutation reduced or abolished SIX1-mediated enhancement of the promoter reporter activity, but not the binding sites whose mutation did not alter that of the promoter reporter activity or the regions upstream of the promoters (Figures 2B and S2B). These data suggest that SIX1 promotes glycolytic gene transcription by binding to glycolytic gene promoters. SIX1 Promotes Glycolytic Gene Expression Largely through Interaction with Histone Acetyltransferases HBO1 and AIB1 Interaction of transcription factors with histone-modifying enzymes is required to regulate gene transcription, and histone acetylation regulated by histone acetyltransferases is often associated with active transcription (Thorne et al., 2009). To investigate how SIX1 stimulates glycolytic gene transcription, we used co-immunoprecipitation (CoIP) combined with mass spectrometry to identify its interaction partners (Figure 3A and Table S3). Besides the previously reported SIX1-interacting proteins eyes absent (EYA) family members, we identified only two histone acetyltransferases, HBO1 (Myst2/Kat7) and AIB1 (ACTR/NCOA-3/SRC-3/RAC3/TRAM-1) (Duong et al., 2013; Zhao et al., 2014), as potential SIX1 interaction partners (Figures 3A and S3A). CoIP of endogenous proteins confirmed the SIX1-HBO1/AIB1 interaction (Figures 3B, S3B, and S3C). DNase I treatment did not alter the SIX1-HBO1/AIB1 interaction, indicating that the interaction is not mediated by DNA (Figure 3C). The interaction is direct because glutathione S-transferase (GST) or histidine (His) pull-down experiments showed that purified His-tagged HBO1/AIB1 protein interacted with purified GST-SIX1, but not GST alone (Figures S3D–S3F). HBO1 (1–330) containing the serine-rich domain, but not HBO1 (331–611) containing the MYST domain, and AIB1 (1,081–1,420) containing the histone acetyltransferase (HAT) domain, but not other AIB1 regions, associated with SIX1 (Figures S3E and S3F). The observation that the molecular weights of HBO1 (331–611) and AIB1 (581–840) were larger than expected might be due to post-translational modification

of the amino acid regions 331–611 and 581–840. The HATdefective mutant HBO1 (G485A) did not alter the HBO1-SIX1 interaction (Figure S3G). SIX1 (1–183) containing the SIX1 domain (SD) and the homeobox domain (HD) did not interact with HBO1, and the amino acid region 219–253, but not 184–218, of SIX1 was required for the SIX1-HBO1 interaction (Figure S3H). SIX1 (11–284), but not SIX1 (61–284), interacted with AIB1 (Figure S3I), suggesting that the amino acid region 11–60 is necessary for the SIX1-AIB1 interaction. Since SIX1 interacts with HBO1/AIB1, we tested whether SIX1 regulates glycolytic gene transcription via HBO1 and AIB1. HBO1 KO or HBO1 KD decreased mRNA and protein expression of HK2, ALDOA, PGK1, ENO1, and LDHA, but not the other glycolytic genes tested, and AIB1 KO or AIB1 KD decreased that of GLUT1, PFKL, ENO1, PKM2, and LDHA, but not the other glycolytic genes examined, in ZR75-1 or HepG2 cells (Figures 3D, 3E, and S3J–S3M). Importantly, HBO1/AIB1 KO or HBO1/ AIB1 KD abolished or greatly attenuated the ability of SIX1 to promote expression of the corresponding glycolytic genes. The effect of HBO1/AIB1 KO or HBO1/AIB1 KD on glycolytic gene expression could be rescued by HBO1 or AIB1 re-expression in HBO1/AIB1 KO or HBO1/AIB1 KD cells, respectively (Figures 3D, 3E, S3L, and S3M). Moreover, SIX1 (D219–253) or SIX1 (61–284) that fails to interact with HBO1 or AIB1, respectively, did not change or greatly attenuated glycolytic gene expression regulated by HBO1 or AIB1 (Figures S3N and S3O). These data suggest that SIX1 promotes glycolytic gene expression largely through interaction with HBO1. Next, we tested how SIX1 regulates glycolytic gene transcription through HBO1 and AIB1. Like SIX1, HBO1, which acetylates histone H4 lysine 5 (H4K5), H4K8, and H4K12 (Doyon et al., 2006), was recruited to the SIX1 binding sites of HK2, ALDOA, PGK1, ENO1, and LDHA promoters, and AIB1, which acetylates histones H3 and H4, especially H3, was recruited to those of GLUT1, PFKL, ENO1, PKM2, and LDHA promoters (Figures 3F and S3P). Re-ChIP experiments showed that SIX1 associated with HBO1 or AIB1 on the corresponding binding sites (Figures 3G and S3Q). SIX1 KO or SIX1 KD abolished or reduced recruitment of HBO1 and acetylation of H4K5 (H4K5ac), but not H4K8ac and H4K12ac, to the SIX1 binding sites of HK2, ALDOA, PGK1, ENO1, and LDHA promoters, and SIX1 KO or SIX1 KD abrogated or decreased recruitment of AIB1 and acetylation of H3K4ac, but not H3K9ac, H3K14ac, and H3K56ac, to those of GLUT1, PFKL, ENO1, PKM2, and LDHA promoters (Figures 3H and S3R). HBO1 KO or HBO1 KD caused a marked reduction of recruitment of H4K5ac, but not H4K8ac and H4K12ac, to the SIX1/HBO1 binding sites, and AIB1 KO or AIB1 KD led to a dramatic decrease in recruitment of H3K4ac, but not H3K9ac, H3K14ac, and H3K56ac, to the SIX1/AIB1 binding sites. HBO1 or AIB1 KO had no effect on recruitment of SIX1 to these binding

Figure 2. SIX1 Binds the SIX1-Responsive Element to Enhance Glycolytic Gene Promoter Activity (A) Luciferase activity of different glycolytic gene promoter reporters in ZR75-1 cells transfected with Myc-tagged SIX1 or empty vector. Filled circles show the position of the putative SIX1-binding sites, and the ‘‘X’’ shows the mutated SIX1-binding sites. The red letters of each binding region indicate the putative or mutated SIX1-binding sequences. P, putative SIX1-binding site; M, mutant; WT, wild-type. (B) ChIP analysis of SIX1 occupancy on promoters of glycolytic genes in ZR75-1 cells. IgG (immunoglobulin G): normal serum. The different number after each gene represents the regions containing different putative SIX1-binding sites from left to right shown in (A). The graph shows the percentage of input. Data shown are mean ± SD of triplicate measurements that have been repeated 3 times with similar results. Data were analyzed using two-tailed Student’s t test. *p < 0.05, **p < 0.01 versus respective promoter reporter without SIX1 (empty vector) (A). **p < 0.01 versus respective normal IgG (B). See also Figure S2.

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sites. Although the HAT-defective mutant HBO1 (G485A) did not change the SIX1-HBO1 interaction, it failed to promote glycolytic gene expression (Figures S3S and S3T), indicating that the histone acetylase activity is important for HBO1 modulation of glycolytic gene transcription. AIB1 (1–1,080), which lacks histone acetylase activity, also failed to enhance glycolytic gene expression (Figures S3U and S3V). Taken together, these data suggest that SIX1 promotes glycolytic gene transcription through HBO1mediated H4K5ac or AIB1-mediated H3K4ac. SIX1 Is Inhibited by miR-548a-3p, which Reduces Glycolytic Gene Expression To identify potential microRNAs (miRNAs) regulating SIX1, we used two target prediction programs, miRanda and TargetScan. Our analysis predicted several potential SIX1-targeting miRNAs, among which only miR-548a-3p repressed SIX1 protein expression in ZR75-1, HepG2 and HEK293T cells (Figures 4A and 4B). In contrast, miR-548a-3p inhibition enhanced SIX1 protein expression (Figure 4C). miR-548a-3p mimics decreased SIX1 mRNA expression while miR-548a-3p inhibition increased SIX1 mRNA expression (Figure 4D). miR-548a-3p mimics reduced the luciferase reporter activity of SIX1 WT 30 UTR but not mutated 30 UTR, in which the binding sites for miR-548a-3p were mutated (Figure 4E). These results suggest that miR-548a-3p represses SIX1 expression by directly targeting its 30 UTR. Importantly, miR-548a-3p mimics reduced the expression of SIX1-regulated genes except GAPDH (Figure 4F), whereas miR-548a-3p inhibition increased the expression of these genes (Figure 4G). Re-expression of SIX1 with mutated 30 UTR, but not WT 30 UTR, in miR-548a-3p mimics-transfected cancer cells reversed the effects of miR-548a-3p on glycolytic gene expression (Figure 4F). Moreover, SIX1 KO abolished the ability of miR548a-3p to regulate these effects (Figure 4H), indicating that miR-548a-3p inhibits glycolytic gene expression via SIX1. The miR-548a-3p/SIX1 Axis Regulates Aerobic Glycolysis in Cultured Cells Glycolysis involves a series of reactions that metabolizes glucose to pyruvate to produce a net of two ATP from each glucose molecule. Cancer cells consume glucose avidly and produce lactate from pyruvate even in the presence of oxygen. Since the miR-548a-3p/SIX1 axis regulates glycolytic gene

expression, we tested whether this axis modulates the glycolytic phenotype in cultured cells. miR-548a-3p mimics reduced glucose uptake, pyruvate level, lactate production, and ATP level in ZR75-1 and HepG2 cells (Figures 5A and S4A). These effects were reversed by SIX1 re-expression in the miR-548a-3p-transfected cells. miR-548a-3p mimics also displayed decreased extracellular acidification rate (ECAR), which reflects overall glycolytic flux, and increased oxygen consumption rate (OCR), an indicator of mitochondrial oxidative respiration (Figures 5B, 5C, and S4A). Again, SIX1 re-expression in the miR-548a-3ptransfected cells rescued these effects. miR-548a-3p mimics in SIX1 KO ZR75-1 cells had no effects on the glycolytic phenotype (Figures 5D–5F), indicating that miR-548a-3p represses the glycolytic phenotype via SIX1. SIX1 KO ZR75-1 cells or SIX1 KD HepG2 cells had reduced activities of HK, GAPDH, ALDOA, PKM, and LDH (Figures S4B and S4C). SIX1 re-expression in the KO or KD cells rescued these effects. Similar effects of SIX1 on glycolytic activities were observed in HCT116 colorectal cancer cells and A549 lung cancer cells (Figures S4D and S4E), for which many papers report that the Warburg effect exists (Faubert et al., 2013; Liu et al., 2012b). Since SIX1 promotes glycolytic gene expression through HBO1 and AIB1, we tested whether SIX1 modulation of the glycolytic phenotype depends on HBO1 and AIB1. Consistent with HBO1/AIB1 regulation of glycolytic gene expression, HBO1/AIB1 KO or HBO1/AIB1 KD caused reduced glucose uptake, pyruvate level, lactate production, ATP level, and ECAR, and increased OCR (Figures 5G–5L, S4F, and S4G). Importantly, HBO1/AIB1 KO or HBO1/AIB1 KD greatly attenuated the ability of SIX1 to regulate these effects. The miR-548a-3p/SIX1 Axis Regulates Glycolysis under Hypoxia Since hypoxia is a key phenomenon in cancers (Wilson and Hay, 2011), we determined whether the miR-548a-3p/SIX1 axis has a role in regulation of glycolysis under hypoxia. Interestingly, hypoxia stimulated SIX1 expression at both mRNA and protein levels, and decreased miR-548a-3p expression, but did not alter the expression of HBO1 and AIB1 (Figure S4H). Interestingly, under both normoxia and hypoxia a positive feedback loop was formed. Overexpression of HIF-1a increased SIX1 expression, and SIX1 overexpression stimulated HIF-1a expression

Figure 3. SIX1 Promotes Glycolytic Gene Expression through Association with HBO1 and AIB1 (A) Cellular extracts from ZR75-1 cells stably expressing FLAG (control) or FLAG-SIX1 were immunopurified with anti-FLAG affinity columns and eluted with FLAG peptide. The eluates were resolved by SDS-PAGE and silver stained. The differential protein bands were retrieved and analyzed by mass spectrometry. (B) HepG2 or ZR75-1 cells were immunoprecipitated with anti-SIX1 or normal IgG, and the precipitates were analyzed by immunoblot with the indicated antibodies. IP, immunoprecipitation. Nonspecific band is shown (heavy chain). (C) CoIP analysis of ZR75-1 cells treated with or without DNase I. DNA agarose gel electrophoresis serves as a control for DNase I activity. Nonspecific band is shown (heavy chain). (D and E) HBO1/AIB1 WT or KO ZR75-1 cells were transiently transfected with SIX1, HBO1, AIB1, or empty vector (EV). Glycolytic gene expression was measured using qRT-PCR (D) and immunoblot (E). (F) ChIP analysis of SIX1, HBO1, and AIB1 occupancy on glycolytic gene promoters in ZR75-1 cells. Promoter regions of each gene represent the region containing the first SIX1 binding site shown in Figure 2B unless there is only one SIX1 binding site within the gene promoter analyzed. The graph shows the percentage of input. (G) Re-ChIP analysis of the occupancy of SIX1 and HBO1 or AIB1 on the indicated glycolytic gene promoters in ZR75-1 cells. (H) ChIP analysis of SIX1, HBO1, AIB1, and histone H3 or H4 acetylation occupancy on the indicated glycolytic gene promoters in SIX1, HBO1, or AIB1 KO ZR75-1 cells. Data shown are mean ± SD of triplicate measurements that have been repeated 3 times with similar results. Statistical significance was assessed by two-tailed Student’s t test. *p < 0.05 and **p < 0.01 versus respective WT ZR75-1 cells transfected with empty vector (D). **p < 0.01 versus respective normal IgG (F–H). See also Figure S3 and Table S3.

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(Figure S4I). On the contrary, HIF-1a overexpression repressed miR-548a-3p expression. miR-548a-3p mimics or KO of SIX1, HBO1, or AIB1 repressed the transcription of their corresponding glycolytic genes under both normoxic and hypoxic conditions (Figures S4J–S4M). Consistent with this, miR-548a-3p mimics or KO of SIX1, HBO1, or AIB1 reduced glucose uptake, pyruvate level, lactate production, and ATP level under normoxia and hypoxia (Figures S4N–S4Q). Aerobic Glycolysis Is Critical for miR-548a-3p/SIX1 Axis Modulation of Proliferation of Cultured Cancer Cells We first tested whether the miR-548a-3p/SIX1 axis regulates cancer cell proliferation in cultured cells. miR-548a-3p mimics reduced cell proliferation (Figures 5M and S4R). This effect was reversed by SIX1 re-expression in the miR-548a-3p-transfected cells. We then examined whether glycolysis plays a role in miR-548a-3p/SIX1 axis-mediated regulation of cancer cell proliferation. As expected, glycolytic inhibitors 2-deoxy-D-glucose (2-DG) and 3-bromopyruvate (3-BP) inhibited cancer cell proliferation (Figures 5N, 5O, S4S, and S4T). Importantly, 2-DG and 3-BP greatly reduced the ability of anti-miR-548a-3p and SIX1 to promote cancer cell proliferation. In addition, we tested the effect of SIX1 on cancer cell proliferation and ATP level using galactose or glucose-containing media. Cells grown in galactose depend more on mitochondrial oxidative phosphorylation (OXPHOS) for energy production (Finley et al., 2011). As expected, cancer cells grown in galactose-treated media had similar growth behavior to those grown in high glucose-treated media (Figure S4U). However, SIX1-overexpressing cells grown in glucose grew faster than those grown in galactose. The glycolytic inhibitor 2-DG, but not the OXPHOS inhibitor oligomycin, almost abolished this effect. Consistent with the cell proliferation results, SIX1-overexpressing cells grown in glucose produced more ATP than those grown in galactose (Figure S4U). Again, 2-DG, but not oligomycin, almost abrogated this effect. These data suggest that increased glycolysis by SIX1 drives enhanced ATP production that supports proliferation. Moreover, hypoxia increased cell proliferation and SIX1 KO or SIX1 KD almost abolished hypoxia-stimulated cell proliferation (Figure S4V), suggesting the key role of SIX1 in hypoxia-induced cell proliferation. The miR-548a-3p/SIX1 Axis Regulates Glycolysis and Tumor Growth In Vivo To examine the effects of the miR-548a-3p/SIX1 axis on glycolysis in vivo, we used 18FDG (fluorodeoxyglucose) micro-

PET (positron emission tomography) scans to measure glucose uptake in tumor xenografts in nude mice. The tumors with miR548a-3p inhibitor revealed increased glucose uptake and those with KO of SIX1, HBO1, or AIB1 showed decreased glucose uptake (Figure 6A). SIX1 KO abolished the ability of miR-548a-3p inhibitor to promote glucose uptake. KO of HBO1 or AIB1 greatly reduced the ability of SIX1 to increase glucose uptake. miR548a-3p inhibitor enhanced the expression of their commonly regulated glycolytic genes, ENO1 and LDHA, as well as lactate level. The opposite effects were seen with KO of SIX1, HBO1, or AIB1 (Figures 6B–6D and S5A–S5D). The tumors with higher glycolysis grew faster (Figure 6E). These data suggest that miR-548a-3p regulates glycolysis via SIX1 and that SIX1 modulates glycolysis through HBO1 and AIB1 in nude mice. Next, we tested whether glycolysis plays a role in miR-548a3p/SIX1 axis-mediated regulation of tumor growth in nude mice. As expected, the glycolytic inhibitor 2-DG and KD of LDHA, the enzyme that catalyzes the final step of glycolysis, inhibited tumor growth and lactate level (Figures 6F–6I and S5E–S5H). Importantly, 2-DG and LDHA KD greatly attenuated the ability of anti-miR-548a-3p and SIX1 to promote tumor growth and lactate level, suggesting that glycolysis mediated by the miR-548a-3p/SIX1 axis is critical for cancer cell growth. To examine the physiological relevance of the miR-548a-3p/ SIX1 axis in glycolysis, we used Six1 KO embryos and cancer samples. Six1 KO embryos had decreased glucose uptake and lactate level (Figure 6J). Moreover, patients with breast tumors who had increased glucose uptake assessed by 18FDG PET scans showed decreased miR-548a-3p expression and increased SIX1 expression (Figure 6K). We confirmed the specificity of miR-548a-3p staining by correlation analysis of miR-548a-3p expression in breast tissues examined by miRNA in situ hybridization (MISH) and qRT-PCR, respectively (Figures S5I and S5J), and the specificity of the SIX1 antibody by immunohistochemical (IHC) staining of breast cancer tissues or immunoblot with cell lysates (Figures S5K and S5L). Cancer-Related SIX1 Mutation Increases Its Ability to Promote Glycolytic Gene Expression, Aerobic Glycolysis, and Tumor Growth The Q177R mutation in SIX1 has been reported in tumors (Walz et al., 2015; Wegert et al., 2015). We tested the effect of the cancer-related mutant SIX1 (Q177R) on glycolytic gene expression. SIX1 (Q177R) overexpression in SIX1 KO ZR75-1 cells or Six1 KO MEFs caused increased HK2, GAPDH, PKM2, and LDHA

Figure 4. miR-548a-3p Represses Glycolytic Gene Expression through SIX1 Inhibition (A) Immunoblot analysis of SIX1 expression in HEK293T cells transiently transfected with the indicated miRNAs. NC, nonspecific control for miRNAs. (B and C) Immunoblot analysis of ZR75-1, HepG2, and HEK293T cells transfected with miR-548a-3p (B) or miR-548a-3p inhibitor (C). Histograms show miR-548a-3p expression determined by qRT-PCR. Scramble: negative control for miRNA inhibitor. (D) qRT-PCR analysis of SIX1 expression in cells transfected as in (B) and (C). (E) miRNA luciferase reporter assays in ZR75-1, HepG2, and HEK293T cells transfected with WT or mutated SIX1 reporter and miR-548a-3p. The top panel indicates WT and mutant forms of putative miR-548a-3p target sequences of SIX1 30 UTR. Red font indicates the mutated miR-548a-3p-binding sites within human SIX1 30 UTR. SIX1 WT, wild-type SIX1 30 UTR; SIX1 MUT, mutated SIX1 30 UTR. (F) Immunoblot analysis of glycolytic gene expression in ZR75-1 and HepG2 cells transfected with miR-548a-3p or miR-548a-3p plus SIX1 expression vector with WT or mutated 30 UTR. (G) Immunoblot analysis of glycolytic gene expression in ZR75-1 and HepG2 cells transfected with anti-miR-548a-3p. (H) Immunoblot analysis of glycolytic gene expression in SIX1 WT/KO ZR75-1 cells or Six1 WT/KO MEFs transfected with miR-548a-3p. Data shown are mean ± SD of triplicate measurements that have been repeated 3 times with similar results. Statistical significance was assessed by two-tailed Student’s t test. *p < 0.05, **p < 0.01 versus respective NC or scramble.

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expression, compared with WT SIX1 (Figures 7A and 7B). It should be noted that the overexpression level of WT SIX1 or SIX1 (Q177R) in SIX1 KO ZR75-1 cells or Six1 KO MEFs is similar to the endogenous SIX1 expression level in parental WT cells (Figure S6A). To examine how the SIX1 (Q177R) mutant promotes expression of the glycolytic genes, we performed ChIP experiments on the HK2 and LDHA promoters. SIX1 (Q177R) was recruited to the HK2 and LDHA promoters more strongly than WT SIX1 (Figure 7C). Moreover, SIX1 (Q177R) increased HK2 and LDHA promoter reporter activity more greatly than WT SIX1 (Figure 7D). The cellular localization of SIX1 (Q177R) was similar to that of WT SIX1 (Figure 7E). These data suggest that SIX1 (Q177R) increases its ability to promote glycolytic gene expression through its increased binding to the glycolytic gene promoters. Next, we tested the effect of hypoxia on SIX1 (Q177R)-mediated glycolytic gene transcription. Like SIX1 overexpression, SIX1 (Q177R) overexpression in SIX1 KO ZR75-1 or Six1 KO MEFs under hypoxia resulted in greater glycolytic gene transcription compared with that under normoxia (Figure S6B). Hypoxia increased the interaction between SIX1 and HBO1 or AIB1 (Figure S6C). Similar effects were observed with SIX1 (Q177R). To test the effect of cancer-related SIX1 mutation on glycolysis in vitro, we transfected WT SIX1 or SIX1 (Q177R) into SIX1 KO ZR75-1 or Six1 KO MEFs. SIX1 (Q177R) showed increased glucose uptake, pyruvate level, lactate production, and ATP level compared with WT SIX1 (Figure 7F). SIX1 KO ZR75-1 cells harboring SIX1 (Q177R) grew faster than those harboring WT SIX1 (Figure 7G), and SIX1 (Q177R) had larger tumors than WT SIX1 in nude mice (Figure 7H). As expected, SIX1 (Q177R) had increased HK2 and LDHA expression and lactate level compared with WT SIX1 (Figures 7I and 7J). Previous studies suggested that the Q177R mutation has been shown in kidney tumors in children. By sequencing of both DNA strands from 42 breast tumor tissues, such a mutation was not observed (Figure S6D). In addition, external datasets from TCGA (The Cancer Genome Atlas) with a sample size between 36 and 1,144 cases showed

that there was no Q177R mutation in more than 20 different human cancers, including breast cancer, liver cancer, and colorectal adenocarcinoma (http://www.cbioportal.org). Clinical Relevance of the miR-548a-3p/SIX1 Axis in Breast Cancer In the breast cancer patients we analyzed, miR-548a-3p expression negatively correlated with expression of SIX1, and SIX1 expression positively correlated with PGK1 and LDHA expression (Figure 8A). In contrast, miR-548a-3p negatively correlated with PGK1 and LDHA expression. Like the specificity of miR-548a-3p and SIX1, the specificity of the PGK1 and LDHA antibodies was confirmed (Figures S7A–S7D). The correlation between SIX1 and PGK1 or LDHA was further validated using external datasets from TCGA and Oncomine (Figures S7E and S7F). Data for miR-548a-3p are not available from TCGA and Oncomine. Moreover, IHC analysis showed that expression of HIF-1a, an intrinsic marker for hypoxia, positively correlated with SIX1 expression and the expression of PGK1 and LDHA, the common target genes of HIF-1a and SIX1 (Figure 8A). The association of HIF-1a with SIX1, PGK1, and LDHA was further validated by TCGA datasets (Figure S7G). In addition, IHC analysis revealed that HBO1 expression positively associated with AIB1 expression (Figure S7H). The specificity of the AIB1 and HBO1 antibodies was confirmed (Figures S7I and S7J). Again, the correlation between AIB1 and HBO1 was further confirmed by TCGA datasets (Figure S7K). SIX1 is overexpressed in various human cancers. SIX1 mRNA and/or protein were overexpressed in more than 50% of breast cancer patients and over 60% of liver cancer patients (Ford et al., 1998; Ng et al., 2006; Reichenberger et al., 2005). Datasets from Oncomine indicated that SIX1 mRNA was overexpressed in 38.9% of breast cancer patients and 48.6% of liver cancer patients (Figures S7L and S7M). The clinical significance of miR-548a-3p expression in cancer is unknown. Our analysis showed that miR-548a-3p was significantly downregulated in breast cancer tissues (Figure 8B) and negatively correlated with tumor size, nodal status, and grade (Table S4). Breast

Figure 5. The miR-548a-3p/SIX1 Axis Modulates the Warburg Effect and Cell Proliferation in Cultured Cells (A) ZR75-1 cells were transfected with nonspecific control (NC), miR-548a-3p, or miR-548a-3p plus SIX1. Glucose uptake, pyruvate level, lactate production, and ATP level were determined as described in STAR Methods. Representative immunoblot reveals SIX1 expression. qRT-PCR analysis indicates miR-548a-3p expression. (B and C) ZR75-1 cells were transfected as in (A), and ECAR (B) and OCR (C) were then determined as described in STAR Methods. (D) SIX1 WT or KO ZR75-1 cells were transfected with or without miR-548a-3p and analyzed as in (A). (E and F) ZR75-1 cells were transfected as in (D), and ECAR (E) and OCR (F) were then examined. (G) HBO1 WT or KO ZR75-1 cells were transiently transfected with SIX1 or empty vector and analyzed as in (A). (H and I) HBO1 WT or KO ZR75-1 cells were transfected as in (G), and ECAR (H) and OCR (I) were then assessed. (J) AIB1 WT or KO ZR75-1 cells were transiently transfected with SIX1 or empty vector and analyzed as in (A). (K and L) AIB1 WT or KO ZR75-1 cells were transfected as in (J), and ECAR (K) and OCR (L) were then examined. (M) The proliferation curve of ZR75-1 cells transfected with miR-548a-3p or miR-548a-3p plus Myc-tagged SIX1. Representative immunoblot reveals expression of SIX1. (N) The proliferation curve of ZR75-1 cells transfected with anti-miR-548a-3p and treated with 2.5 mM 2-DG or 100 mM 3-BP as indicated. Representative immunoblot shows SIX1 expression. qRT-PCR analysis indicates miR-548a-3p expression. (O) The proliferation curve of ZR75-1 cells transfected with Myc-tagged SIX1 and treated with 2.5 mM 2-DG or 100 mM 3-BP as indicated. Representative immunoblot reveals expression of Myc-tagged Six1. Data shown are mean ± SD of quintuplicate measurements that have been repeated 3 times with similar results (A for glucose uptake, pyruvate level, lactate production, ATP level, and B–L). Data shown are mean ± SD of triplicate measurements that have been repeated 3 times with similar results (A for qRT-PCR analysis). Data shown are mean ± SD of 3 independent experiments (M–O). Statistical significance was assessed by two-tailed Student’s t test. *p < 0.05, **p < 0.01 versus NC (A–F). *p < 0.05, **p < 0.01 versus WT ZR75-1 cells transfected with empty vector (G–L). *p < 0.05, **p < 0.01 at the final day (M–O). See also Figure S4.

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cancer patients with decreased miR-548a-3p expression had shorter disease-free survival and overall survival (Figure 8C). DISCUSSION Cancer cells frequently display high rates of aerobic glycolysis, a hallmark of cancer (Liberti and Locasale, 2016). This metabolic reprogramming gives cancer cells a growth advantage by providing energy for cancer cell growth. Our study establishes the miR-548a-3p/SIX1 axis as a critical regulatory pathway in the Warburg effect. SIX1 directly promotes the expression of many key glycolytic genes that facilitates the Warburg effect and tumor growth. The upstream regulation of SIX1 expression and function is negatively controlled by miR-548a-3p. Using different cancer cell lines, SIX1 KO cancer cell line, Six1 KO MEFs, Six1 KO mice embryos, and tumor samples, we show that SIX1 regulates glycolytic gene expression, glucose uptake, and the level of lactate, a metabolite that can facilitate tumor growth and metastasis. Our data indicate that SIX1 is a key transcription factor for regulation of the Warburg effect and also indicate a causal role for SIX1 in glycolysis regulation (Figure 8D). SIX1 is overexpressed in various human cancers and its elevated expression is associated with poor clinical outcomes (Wu et al., 2015). In Six1 KO mice, multiple organs fail to develop properly due to the increase in apoptosis and the reduction in cell proliferation (Li et al., 2003; Ozaki et al., 2004; Zheng et al., 2003). Six1 KO mice die shortly after birth. Mutations in SIX1 have been reported in patients with branchio-oto-renal syndrome, a developmental disorder (Ruf et al., 2004). Since SIX1 regulates expression of many glycolytic genes such as HK2 and PKM2 that modulate cell proliferation and/or apoptosis (Liberti and Locasale, 2016), the function of SIX1 in glycolysis at least partly explains these defects induced by SIX1 KO or mutations. However, we cannot exclude the possibility that other genes regulated by SIX1 may also be responsible for these defects. Recently, a hotspot mutation (Q177R) of SIX1 has been reported in approximately 10% of kidney tumors in children (Walz et al.,

2015; Wegert et al., 2015). However, our research data of 42 breast tumor tissues and external datasets of over 20 different cancers from TCGA did not show a Q177R mutation, suggesting that this mutation may be specific for kidney tumors in children. The Q177R mutation has oncogenic gain-of-function phenotypes in terms of the Warburg effect. Since miR-548a-3p inhibits SIX1 expression by directly targeting its 30 UTR, it is most likely that miR-548a-3p also inhibits SIX1 (Q177R) expression. miR-548a-3p expression is downregulated in breast tumors, and its low expression predicts a poor prognosis in breast cancer patients. In contrast to SIX1, miR-548a-3p represses the Warburg effect, causing tumor repression. Cancer cells uses glycolysis more than oxidative respiration (OR) for their energy requirements. miR-548a-3p overexpression and SIX1 KO or SIX1 KD inhibit glycolysis and facilitate OR. The glycolytic inhibitor 2-DG in combination with the PI3K/mTOR inhibitor PF-04691502 was shown to switch lymphoma cells from aerobic glycolysis to OR, and this combination causes strong cytotoxicity toward lymphoma cells but low toxicity to normal lymphocytes (Chen et al., 2016). Since the miR-548a-3p/SIX1 axis is deregulated in cancer, correlates with prognosis, and controls glycolysis, this axis is expected to be an excellent therapeutic target for curing cancer. Potentiation of glycolytic gene transcription by SIX1 is mediated mainly through histone acetyltransferases HBO1 and AIB1. Like miR-548a-3p and SIX1, HBO1 is a key regulator of the Warburg effect. AIB1 was shown to interact with HIF-1a to promote the expression of some glycolytic genes (Zhao et al., 2014). HBO1 and AIB1 have redundant and distinct roles in regulation of glycolytic gene expression. Our study suggests that HBO1-mediated H4K5ac and AIB1-mediated H3K4ac are important for SIX1 modulation of glycolytic gene expression. SIX1 might be directly involved in the process. The exact roles of HBO1 and AIB1 in stimulating gene expression remain to be investigated. Since it is well established that transcription factors can orchestrate the recruitment of histone-modifying enzymes to specific sets of target genes (Thorne et al., 2009),

Figure 6. The miR-548a-3p/SIX1 Axis Modulates the Warburg Effect and Tumor Growth In Vivo (A) Representative FDG microPET images of living nude mice injected with WT or SIX1, HBO1 or AIB1 KO ZR75-1 cells treated with antagomiR-548a-3p, or stably expressing SIX1 or empty vector as indicated. The mouse corresponds to the fourth column in each group (right). Arrows indicate tumor glucose uptake (right). Stripped tumors are shown (left). (B and C) Analysis of the expression of the indicated proteins and miR-548a-3p in representative excised tumor from (A). Representative immunoblot (B) and qRT-PCR (C). The indicated tumor tissue from a single mouse in each group was cut into several pieces and then used for immunoblot and qRT-PCR. Tumors were from the fourth column in each group in (A). (D) Lactate level of representative tumor tissues from (A). Tumor tissues were treated as in (B) and (C). Tumors were from the fourth column in each group in (A). (E) Xenograft tumors were established as in (A) and the growth curve was plotted. (F) ZR75-1 cells stably expressing LDHA shRNA or treated with antagomiR-548a-3p were injected into nude mice. 2-DG was used as indicated. The growth curve was plotted (right). Stripped tumors are shown (left). (G) The expression of the indicated proteins in representative excised tumor from (F) was analyzed as in (B). Tumors were from the fourth column in each group in (F). (H) The expression of miR-548a-3p in representative excised tumor from (F) was analyzed as in (C). Tumors were from the fourth column in each group in (F). (I) Lactate level of representative tumor tissues from (F) was assessed as in (D). Tumors were from the fourth column in each group in (F). (J) Representative FDG microPET images of Six1 WT (+/+), heterozygous (+/), and KO (/) embryos at day 15.5 of gestation. After imaging, embryo tissues were homogenized to measure the lactate levels as described in STAR Methods (n = 9 for WT; n = 9 for heterozygous; n = 5 for KO). The change in lactate level of the embryos was plotted. (K) Representative FDG PET scans and IHC or MISH analysis of 43 breast cancer patients. SIX1 was examined by IHC and miR-548a-3p by MISH. Arrows reveal tumor glucose uptake. Scale bar, 100 mm. The correlation of glucose uptake with SIX1 or miR-548a-3p expression was determined using the Mann-Whitney U test. Case 1 and case 2 refer to two representative samples categorized by low and high expression of miR-548a-3p. Values shown are mean ± SD of measurements of the 3 pieces from each group that have been repeated 3 times with similar results (C). Values shown are mean ± SD of measurements of the five pieces from each group that have been repeated 3 times with similar results (D). p Values were generated by two-tailed Student’s t test (C–F and H–J). **p < 0.01 versus parental ZR75-1 cells (C and D). **p < 0.01 at the final day (E and F). See also Figure S5.

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the observation that HBO1 and AIB1 do not stimulate the expression of GAPDH, which is regulated by SIX1, suggests that SIX1 may interact with another histone-modifying enzyme to promote GAPDH expression. HBO1 can enrich breast cancer stem-like cells (Duong et al., 2013). IHC analysis demonstrates strong HBO1 expression in various human cancers (Iizuka et al., 2009). HBO1 inhibits the transcriptional activity of nuclear factor kB (NF-kB), although HBO1-regulated downstream target genes are unknown (Contzler et al., 2006). However, the role of NF-kB in tumorigenesis is complex, as in some models NF-kB inhibition suppresses, whereas in others it facilitates, tumor development (Pikarsky and Ben-Neriah, 2006). Further studies are required to test whether HBO1 has a context-dependent role in carcinogenesis and to determine whether HBO1 inhibition of NF-kB activity is a negative feedback. AIB1 is overexpressed in many cancers, and its overexpression correlates with poor survival of patients (Zhao et al., 2014). Since HBO1 or AIB1 KO attenuates the ability of SIX1 to promote glycolysis and tumor growth, and SIX1 is necessary for recruitment of HBO1 and AIB1 to glycolytic gene promoters, targeting SIX1 may make cancer therapy more effective than targeting HBO1 or AIB1. However, further investigation of potential side effects of SIX1 inhibition is required, as SIX1 regulates more than 1,900 genes. STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: d d d

d

KEY RESOURCES TABLE CONTACT FOR REAGENT AND RESOURCE SHARING EXPERIMENTAL MODEL AND SUBJECT DETAILS B Human Clinical Samples B Mice B SIX1, HBO1 and AIB1 Knockout Cancer Cell Lines B Cell Lines and Drug Treatments METHOD DETAILS B Plasmids, siRNAs, shRNAs, and Lentiviruses B Transcriptome Sequencing (RNA-Seq) B Quantitative Reverse Transcription-PCR (RT-PCR)

B

Luciferase Reporter Assay Chromatin Immunoprecipitation (ChIP) and re-ChIP B Co-immunoprecipitation and His or GST Pull-down Assays B Mass Spectrometry B Cell Proliferation Assays B Glucose Uptake, Pyruvate, Lactate, ATP, HK, GAPDH, ALDO, PKM and LDH Assays B Extracellular Acidification Rate and Oxygen Consumption Rate Assays B SIX1 Q177R Mutation Screening B miRNA In Situ Hybridization and Immunohistochemistry B PET Imaging of Glucose Uptake in Mice QUANTIFICATION AND STATISTICAL ANALYSIS B Statistical Analysis DATA AND SOFTWARE AVAILABILITY B Data Resources B

d d

SUPPLEMENTAL INFORMATION Supplemental Information includes seven figures and seven tables and can be found with this article online at https://doi.org/10.1016/j.ccell.2018. 01.010. ACKNOWLEDGMENTS This work was supported by the National Key Research And Development Program of China (2017YFA0505602), the National Natural Science Foundation (81330053, 81630067, 81472589, 81672602, 81471466, 81572597, and 81502264) and Beijing Nova Program (Z141102001814055) and Logistics Scientific Research project (BWS16J010). AUTHOR CONTRIBUTIONS Conceptualization, Q.Y. and X.X.; Methodology, L.L., Y. Liang, L.K., Z.Y., J.H., S.J., S.C., W.Y., Q.D., and T.H.; Software, X.X. and L.L.; Validation, X.H., Q.J., Q.S., S.Z., Z.Y., J.H., and S.J.; Formal Analysis, Q.Y., X.X., L.L., and Y. Liang.; Investigation, L.L., Y. Liang, L.K., X.H., Q.J., Q.S., S.Z., S.J., S.C., W.Y., Q.D., and T.H.; Resources, X.X., L.K., T.W., W.Z., Y. Liu, S.G., Y. Li, H.M., and C.Y.; Data Curation, Q.Y., X.X., L.L., and Y. Liang; Writing – Original Draft, Q.Y., L.L., and X.X.; Writing – Review & Editing, Q.Y., X.X., and L.L.; Visualization, Z.Y., J.H., and S.J.; Supervision, Q.Y.; Project Administration, Q.Y.; Funding Acquisition, Q.Y., X.X., T.W., and Z.Y.

Figure 7. Cancer-Related SIX1 Mutation Increases Its Ability to Enhance the Warburg Effect and Tumor Growth (A and B) Expression analysis of SIX1 KO ZR75-1 cells or Six1 KO MEFs infected with lentivirus carrying Myc-tagged SIX1 or SIX1 (Q177R). qRT-PCR (A) and immunoblot (B). (C) ChIP analysis of the occupancy of WT SIX1 and SIX1 (Q177R) on HK2 and LDHA promoters in SIX1 KO ZR75-1 cells infected with Myc-tagged SIX1 or SIX1 (Q177R). Anti-Myc was used for ChIP. Immunoblot shows the expression of WT SIX1 and SIX1 (Q177R). (D) Luciferase activity of HK2 and LDHA promoter reporter in SIX1 KO ZR75-1 cells infected with Myc-tagged SIX1 or SIX1 (Q177R). Immunoblot indicates the expression of WT SIX1 and SIX1 (Q177R). (E) ZR75-1 cells were infected as in (D). Cells were stained with anti-Myc (red). The nuclei were stained with DAPI (blue). Scale bar, 100 mm. (F) SIX1 KO ZR75-1 cells or Six1 KO MEFs were infected with lentivirus carrying Myc-tagged SIX1 or SIX1 (Q177R), and the glucose uptake and the production of pyruvate, lactate, and ATP were then detected. Immunoblot shows the expression of SIX1 or SIX1 (Q177R). (G) SIX1 KO ZR75-1 cells were infected with the indicated constructs as in (F) and cell proliferation was determined. (H) SIX1 KO ZR75-1 cells stably infected with the indicated constructs were injected into nude mice. The growth curve was plotted. (I) Representative immunoblot of the expression of HK2 and LDHA in the representative excised tumor from (H) as analyzed in Figures 6B and 6C. Tumors were from the fourth column in each group in (H). (J) Lactate level of the representative tumor tissue from (H) as analyzed as in Figure 6D. Tumors were from the fourth column in each group in (H). Data shown are mean ± SD of triplicate measurements that have been repeated 3 times with similar results (A–D and G). Data shown are mean ± SD of quintuplicate measurements that have been repeated 3 times with similar results (F). Data were analyzed using two-tailed Student’s t test. **p < 0.01 versus respective empty vector and #p < 0.01 versus Myc-SIX1 (A, C, D, F–H, and J). See also Figure S6.

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DECLARATION OF INTERESTS The authors declare no competing interests. Received: July 14, 2017 Revised: October 26, 2017 Accepted: January 18, 2018 Published: February 15, 2018

of HSIX1: a possible mechanism of breast carcinogenesis. Proc. Natl. Acad. Sci. USA 95, 12608–12613. Greiner, M., Pfeiffer, D., and Smith, R.D. (2000). Principles and practical application of the receiver operating characteristic analysis for diagnostic test. Prev. Vet. Med. 45, 23–41.

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Contzler, R., Regamey, A., Favre, B., Roger, T., Hohl, D., and Huber, M. (2006). Histone acetyltransferase HBO1 inhibits NF-kappaB activity by coactivator sequestration. Biochem. Biophys. Res. Commun. 350, 208–213. Doherty, J.R., and Cleveland, J.L. (2013). Targeting lactate metabolism for cancer therapeutics. J. Clin. Invest. 123, 3685–3692. Dome´nech, E., Maestre, C., Esteban-Martı´nez, L., Partida, D., Pascual, R., Ferna´ndez-Miranda, G., Seco, E., Campos-Olivas, R., Pe´rez, M., Megias, D., et al. (2015). AMPK and PFKFB3 mediate glycolysis and survival in response to mitophagy during mitotic arrest. Nat. Cell Biol. 17, 1304–1316. Doyon, Y., Cayrou, C., Ullah, M., Landry, A.J., Coˆte´, V., Selleck, W., Lane, W.S., Tan, S., Yang, X.J., and Coˆte´, J. (2006). ING tumor suppressor proteins are critical regulators of chromatin acetylation required for genome expression and perpetuation. Mol. Cell 21, 51–64.

Kumar, J.P. (2009). The sine oculis homeobox (SIX) family of transcription factors as regulators of development and disease. Cell. Mol. Life Sci. 66, 565–583. Laclef, C., Hamard, G., Demignon, J., Souil, E., Houbron, C., and Maire, P. (2003). Altered myogenesis in Six1-deficient mice. Development 130, 2239–2252. Liberti, M.V., and Locasale, J.W. (2016). The Warburg effect: How does it benefit cancer cells? Trends Biochem. Sci. 41, 211–218. Liu, D., Li, L., Zhang, X.X., Wan, D.Y., Xi, B.X., Hu, Z., Ding, W.C., Zhu, D., Wang, X.L., Wang, W., et al. (2014). SIX1 promotes tumor lymphangiogenesis by coordinating TGFb signals that increase expression of VEGF-C. Cancer Res. 74, 5597–5607.

Duong, M.T., Akli, S., Macalou, S., Biernacka, A., Debeb, B.G., Yi, M., Hunt, K.K., and Keyomarsi, K. (2013). Hbo1 is a cyclin E/CDK2 substrate that enriches breast cancer stem-like cells. Cancer Res. 73, 5556–5568.

Liu, Y., Cao, Y., Zhang, W., Bergmeier, S., Qian, Y., Akbar, H., Colvin, R., Ding, J., Tong, L., Wu, S., et al. (2012b). A small-molecule inhibitor of glucose transporter 1 downregulates glycolysis, induces cell-cycle arrest, and inhibits cancer cell growth in vitro and in vivo. Mol. Cancer Ther. 11, 1672–1682.

El-Hashash, A.H., Al Alam, D., Turcatel, G., Rogers, O., Li, X., Bellusci, S., and Warburton, D. (2011). Six1 transcription factor is critical for coordination of epithelial, mesenchymal and vascular morphogenesis in the mammalian lung. Dev. Biol. 353, 242–258.

Li, X., Oghi, K.A., Zhang, J., Krones, A., Bush, K.T., Glass, C.K., Nigam, S.K., Aggarwal, A.K., Maas, R., Rose, D.W., et al. (2003). Eya protein phosphatase activity regulates Six1-Dach-Eya transcriptional effects in mammalian organogenesis. Nature 426, 247–254.

Faubert, B., Boily, G., Izreig, S., Griss, T., Samborska, B., Dong, Z., Dupuy, F., Chambers, C., Fuerth, B.J., Viollet, B., et al. (2013). AMPK is a negative regulator of the Warburg effect and suppresses tumor growth in vivo. Cell Metab. 17, 113–124.

Liu, Y., Chu, A., Chakroun, I., Islam, U., and Blais, A. (2010). Cooperation between myogenic regulatory factors and SIX family transcription factors is important for myoblast differentiation. Nucleic Acids Res. 38, 6857–6871.

Finley, L.W., Carracedo, A., Lee, J., Souza, A., Egia, A., Zhang, J., TeruyaFeldstein, J., Moreira, P.I., Cardoso, S.M., Clish, C.B., et al. (2011). SIRT3 opposes reprogramming of cancer cell metabolism through HIF1a destabilization. Cancer Cell 19, 416–428. Ford, H.L., Kabingu, E.N., Bump, E.A., Mutter, G.L., and Pardee, A.B. (1998). Abrogation of the G2 cell cycle checkpoint associated with overexpression

Liu, Y., Nandi, S., Martel, A., Antoun, A., Ioshikhes, I., and Blais, A. (2012a). Discovery, optimization and validation of an optimal DNA-binding sequence for the Six1 homeodomain transcription factor. Nucleic Acids Res. 40, 8227–8239. Micalizzi, D.S., Christensen, K.L., Jedlicka, P., Coletta, R.D., Baro´n, A.E., Harrell, J.C., Horwitz, K.B., Billheimer, D., Heichman, K.A., Welm, A.L., et al. (2009). The Six1 homeoprotein induces human mammary carcinoma cells to

Figure 8. Clinical Relevance of the miR-548a-3p/SIX1 Axis in Breast Cancer (A) Representative IHC of 187 breast cancer patients. SIX1, PGK1, LDHA, and HIF-1a were assessed by IHC, and miR-548a-3p by qRT-PCR. Scale bar, 100 mm. The correlation of miR-548a-3p, PGK1, or LDHA with SIX1, or that of PGK1 or LDHA with miR-548a-3p, was analyzed. The association of HIF-1a with SIX1, PGK1, and LDHA was also determined. Case 1 and case 2 refer to two representative samples categorized by low and high expression of SIX1. The low, medium, and high expression of SIX1, PGK1, LDHA, and HIF-1a was determined as described in STAR Methods. Horizontal lines inside the box represent the median; the bottom and top of the boxes represent the 25th and 75th percentiles. The lines above and below the box represent the upper and lower extremes. The vertical bars represent the range of data. Any outliers are marked with a circle. Data was analyzed by one-way ANOVA with Games-Howell correction. **p < 0.01 versus case 1. (B) miR-548a-3p expression in 187 cancerous breast tissues and matched adjacent normal breast tissues was determined by qRT-PCR. Relative miR-548a-3p expression levels were plotted and compared between normal and cancer tissues (Mann-Whitney U test). (C) The disease-free and overall survival curves related to low and high expression of miR-548a-3p were analyzed in 187 breast cancer patients from (G) using the Kaplan-Meier method. (D) A proposed model underlying the role of the miR-548a-3p/SIX1/HBO1/AIB1 axis in cancer glycolysis and tumor growth. SIX1 activates glycolytic gene transcription through interaction with HBO1 and AIB1 histone acetyltransferases. SIX1 is directly repressed by miR-548a-3p. Thus, the miR-548a-3p/SIX1 axis links glycolytic gene expression to glycolysis and tumor growth. See also Figure S7 and Table S4.

Cancer Cell 33, 1–18, March 12, 2018 17

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undergo epithelial-mesenchymal transition and metastasis in mice through increasing TGF-b signaling. J. Clin. Invest. 119, 2678–2690. Ng, K.T., Man, K., Sun, C.K., Lee, T.K., Poon, R.T., Lo, C.M., and Fan, S.T. (2006). Clinicopathological significance of homeoprotein Six1 in hepatocellular carcinoma. Br. J. Cancer 95, 1050–1055. Ngo, H., Tortorella, S.M., Ververis, K., and Karagiannis, T.C. (2015). The Warburg effect: molecular aspects and therapeutic possibilities. Mol. Biol. Rep. 42, 825–834. Ozaki, H., Nakamura, K., Funahashi, J., Ikeda, K., Yamada, G., Tokano, H., Okamura, H.O., Kitamura, K., Muto, S., Kotaki, H., et al. (2004). Six1 controls patterning of the mouse otic vesicle. Development 131, 551–562. Pikarsky, E., and Ben-Neriah, Y. (2006). NF-kappaB inhibition: a double-edged sword in cancer? Eur. J. Cancer 42, 779–784. Reichenberger, K.J., Coletta, R.D., Schulte, A.P., Varella-Garcia, M., and Ford, H.L. (2005). Gene amplification is a mechanism of Six1 overexpression in breast cancer. Cancer Res. 65, 2668–2675. Ruf, R.G., Xu, P.X., Silvius, D., Otto, E.A., Beekmann, F., Muerb, U.T., Kumar, S., Neuhaus, T.J., Kemper, M.J., Raymond, R.M., Jr., et al. (2004). SIX1 mutations cause branchio-oto-renal syndrome by disruption of EYA1-SIX1-DNA complexes. Proc. Natl. Acad. Sci. USA 101, 8090–8095. Sun, Y., Ding, L., Zhang, H., Han, J., Yang, X., Yan, J., Zhu, Y., Li, J., Song, H., and Ye, Q. (2006). Potentiation of Smad-mediated transcriptional activation by the RNA-binding protein RBPMS. Nucleic Acids Res. 34, 6314–6326. Thorne, J.L., Campbell, M.J., and Turner, B.M. (2009). Transcription factors, chromatin and cancer. Int. J. Biochem. Cell Biol. 41, 164–175.

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Walz, A.L., Ooms, A., Gadd, S., Gerhard, D.S., Smith, M.A., Guidry Auvil, J.M., Meerzaman, D., Chen, Q.R., Hsu, C.H., Yan, C., et al. (2015). Recurrent DGCR8, DROSHA, and SIX homeodomain mutations in favorable histology Wilms tumors. Cancer Cell 27, 286–297. Wegert, J., Ishaque, N., Vardapour, R., Geo¨rg, C., Gu, Z., Bieg, M., Ziegler, B., Bausenwein, S., Nourkami, N., Ludwig, N., et al. (2015). Mutations in the SIX1/ 2 pathway and the DROSHA/DGCR8 miRNA microprocessor complex underlie high-risk blastemal type Wilms tumors. Cancer Cell 27, 298–311. Wilson, W.R., and Hay, M.P. (2011). Targeting hypoxia in cancer therapy. Nat. Rev. Cancer 11, 393–410. Wu, W., Ren, Z., Li, P., Yu, D., Chen, J., Huang, R., and Liu, H. (2015). Six1: a critical transcription factor in tumorigenesis. Int. J. Cancer 136, 1245–1253. Yeung, S.J., Pan, J., and Lee, M.H. (2008). Roles of p53, MYC and HIF-1 in regulating glycolysis—the seventh hallmark of cancer. Cell. Mol. Life Sci. 65, 3981–3999. Zhang, H., Xie, X., Zhu, X., Zhu, J., Hao, C., Lu, Q., Ding, L., Liu, Y., Zhou, L., Liu, Y., et al. (2005). Stimulatory cross-talk between NFAT3 and estrogen receptor in breast cancer cells. J. Biol. Chem. 280, 43188–43197. Zhao, W., Chang, C., Cui, Y., Zhao, X., Yang, J., Shen, L., Zhou, J., Hou, Z., Zhang, Z., Ye, C., et al. (2014). Steroid receptor coactivator-3 regulates glucose metabolism in bladder cancer cells through coactivation of hypoxia inducible factor 1a. J. Biol. Chem. 289, 11219–11229. Zheng, W., Huang, L., Wei, Z.B., Silvius, D., Tang, B., and Xu, P.X. (2003). The role of Six1 in mammalian auditory system development. Development 130, 3989–4000.

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STAR+METHODS KEY RESOURCES TABLE

REAGENT or RESOURCE

SOURCE

IDENTIFIER

anti-GST

GE Healthcare Life Sciences

Cat# RPN1236; RRID: AB_771429

anti-His

GE Healthcare Life Sciences

Cat# 27471001; RRID: AB_771435

anti-Myc

Santa Cruz Biotechnology

Cat# sc-40HRP; RRID: AB_627268

anti-b-actin

Santa Cruz Biotechnology

Cat# sc-47778HRP; RRID: AB_2714189

anti-GPI

Santa Cruz Biotechnology

Cat# sc-33777; RRID: AB_112653

anti-PFKL

Santa Cruz Biotechnology

Cat# sc-292523; RRID: AB_10987636

anti-ENO1

Santa Cruz Biotechnology

Cat# sc-15343; RRID: AB_2099061

anti-AIB1

Santa Cruz Biotechnology

Cat# sc-9119; RRID: AB_647689

anti-AIB1

Santa Cruz Biotechnology

Cat# sc-56854; RRID: AB_1125469

anti-FLAG

Sigma-Aldrich

Cat# A8592; RRID: AB_439702

anti-FLAG M2 agarose

Sigma-Aldrich

Cat# A2220; RRID: AB_10063035

anti-GAPDH

Sigma-Aldrich

Cat# G9295; RRID: AB_1078992

anti-SIX1

Sigma-Aldrich

Cat# HPA001893; RRID: AB_1079991

anti-SIX1

Proteintech

Cat# 10709-1-AP; RRID: AB_2189077

anti-a-Tubulin

Proteintech

Cat# 11224-1-AP; RRID: AB_2210206

anti-GLUT1

Proteintech

Cat# 21829-1-AP; RRID: AB_10837075

anti-ALDOA

Proteintech

Cat# 11217-1-AP; RRID: AB_2224626

anti-PGAM1

Proteintech

Cat# 16126-1-AP; RRID: AB_2160786

anti-PGK1

Proteintech

Cat# 17811-1-AP; RRID: AB_2161218

anti-LDHA

Proteintech

Cat# 19987-1-AP; RRID: AB_10646429

anti-HBO1

Proteintech

Cat# 13751-1-AP; RRID: AB_2266703

anti-HIF-1a

Proteintech

Cat# 20960-1-AP; RID: AB_10732601

anti-HIF-1a

Novus

Cat# NB100-105; RRID: AB_10001154

anti-PKM2

Cell Signaling Technology

Cat# 4053S; RRID: AB_1904096

anti-HK2

Cell Signaling Technology

Cat# 2867S; RRID: AB_2232946

anti-H4K5ac

Millipore

Cat# 07-327; RRID: AB_310523

anti-H4K8ac

Millipore

Cat# 07-328; RRID: AB_11213282

anti-H4K12ac

Millipore

Cat# 07-595; RRID: AB_310740

anti-H3K4ac

Millipore

Cat# 07-539; RRID: AB_673133

anti-H3K9ac

Millipore

Cat# ABE18; RRID: AB_10806219

anti-H3K14ac

Millipore

Cat# 07-353; RRID: AB_310545

anti-H3K56ac

Millipore

Cat# 07-677; RRID: AB_390167

Lentiviral particles for SIX1

This paper

N/A

Lentiviral particles for SIX1 shRNA

This paper

N/A

Lentiviral particles for HBO1 shRNA

This paper

N/A

Lentiviral particles for AIB1 shRNA

This paper

N/A

Lentiviral particles for HIF-1a shRNA

This paper

N/A

Lentiviral particles for PGK1 shRNA

This paper

N/A

Lentiviral particles for LDHA shRNA

This paper

N/A

Chinese PLA General Hospital

N/A

Antibodies

Bacterial and Virus Strains

Biological Samples Human breast cancer tissues

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Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

2-deoxy-D-glucose (2-DG)

Sigma-Aldrich

Cat# D8375

3-bromopyruvate (3-BP)

Sigma-Aldrich

Cat# 16490

Oligomycin

Sigma-Aldrich

Cat# 75351

Magna ChIP G Assay Kit

Millipore

Cat# 17-409

XF Glycolysis Stress Test Kit

Agilent Technologies

Cat# 103020

XF Cell Mito Stress Test Kit

Agilent Technologies

Cat# 103015

Glucose Uptake Colorimetric Assay kit

Biovision

Cat# K676

Pyruvate Colorimetric Assay kit

Biovision

Cat# K609

Chemicals, Peptides, and Recombinant Proteins

Critical Commercial Assays

Lactate Colorimetric Assay Kit II

Biovision

Cat# K627

ATP Colorimetric Assay kit

Biovision

Cat# K354

Hexokinase Colorimetric Assay Kit

Biovision

Cat# K789

GAPDH Activity Assay Kit

Biovision

Cat# K680

Aldolase Activity Colorimetric Assay Kit

Biovision

Cat# K665

Pyruvate Kinase Activity Colorimetric Assay Kit

Biovision

Cat# K709

Lactate Dehydrogenase Activity Assay Kit

Biovision

Cat# K726

Deposited Data RNA sequencing raw and analyzed data

This paper

GEO: GSE93925

RNA sequencing data from human breast cancer cells

The Cancer Genome Atlas (TCGA)

https://tcga-data.nci.nih.gov/

Human embryonic kidney HEK293T cells (N/A)

ATCC

ATCC # CRL-3216

Human breast cancer ZR75-1 cells (Female)

ATCC

ATCC #: CRL-1500

Human liver cancer HepG2 cells (Male)

ATCC

ATCC #: HB-8065

Human colon cancer HCT116 cells (Male)

ATCC

ATCC #: CCL-247

Experimental Models: Cell Lines

Human lung cancer A549 cells (Male)

ATCC

ATCC #: CRM-CCL-185

Human ZR75-1 SIX1 KO cells (Female)

Genloci Biotech

N/A

Human ZR75-1 HBO1 KO cells (Female)

Genloci Biotech

N/A

Human ZR75-1 AIB1 KO cells (Female)

Genloci Biotech

N/A

Six1-/- MEFs (N/A)

This paper

N/A

Shanghai Model Organisms Center

N/A

Experimental Models: Organisms/Strains Six1 KO Mice Oligonucleotides shRNAs or siRNA targeting sequence, see Table S5

This paper

N/A

Primers for real-time PCR, see Table S6

This paper

N/A

Primers for ChIP, see Table S7

This paper

N/A

Recombinant DNA pGL4-GLUT1 promoter deletion mutants

This paper

N/A

pGL4-HK2 promoter deletion mutants

This paper

N/A

pGL4-PFKL promoter deletion mutants

This paper

N/A

pGL4-ALDOA promoter deletion mutants

This paper

N/A

pGL4-GAPDH promoter deletion mutants

This paper

N/A

pGL4-PGK1 promoter deletion mutants

This paper

N/A

pGL4-ENO1 promoter deletion mutants

This paper

N/A

pGL4-PKM2 promoter deletion mutants

This paper

N/A

pGL4-LDHA promoter deletion mutants

This paper

N/A

pGL4-SIX1-3’-UTR-WT and mutant

This paper

N/A

Flag-SIX1 and its mutants

This paper

N/A (Continued on next page)

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Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

Myc-SIX1 and its mutants

This paper

N/A

GST-SIX1

This paper

N/A

pCDH-SIX1

This paper

N/A

pSIH-SIX1, HBO1, AIB1, HIF-1a, PGK1 and LDHA

This paper

N/A

His-HBO1 and its deletion mutants

This paper

N/A

Myc-HBO1 and its mutants

This paper

N/A

His-AIB1 deletion mutants

This paper

N/A

Flag-AIB1 and its deletion mutants

Dr. Chundong Yu Lab

N/A

Wave 2.2.0

Seahorse Bioscience

N/A

SPSS 13.0

IBM

N/A

Seahorse XFe 96 Extracellular Flux Analyzer

Seahorse Bioscience

N/A

Animal PET Scanner

Philips Corp.

N/A

Software and Algorithms

Other

CONTACT FOR REAGENT AND RESOURCE SHARING Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Qinong Ye ([email protected]). EXPERIMENTAL MODEL AND SUBJECT DETAILS Human Clinical Samples Forty three and one hundred and eighty seven cases of primary breast carcinomas used for analyses of 18FDG PET scans and clinical outcomes, respectively, were obtained from Chinese PLA General Hospital, with the informed consent of patients and with the approval of the Institutional Review Committees of Chinese PLA General Hospital. Similar experiments performed previously were used to estimate sample size. For patients used for 18FDG PET scan analysis, all cases were female with 39-68 years of age (mean age: 52.7 years). For patients used for clinical outcome analysis, all cases were female with 26-84 years of age (mean age: 53.5 years) and the follow-up time was 1-76 months (mean: 64.3 months). Normal distribution was performed using SPSS13.0. Out of 187 breast cancer specimens, 42 cancer tissues were available for DNA isolation and sequencing. Mice All animal studies conformed to the relevant regulatory standards and were approved by the Institutional Animal Care Committee of Beijing Institute of Biotechnology. Six1 knockout mice were generated by CRISPR/Cas9 (Shanghai Model Organisms Center, Inc.). The guide RNA targeting exon 1 of SIX1 gene was designed. The guide RNA sequence is GTGGCTGAAAGCGCACTACG. A mixture of plasmids encoding Cas9 and SIX1 guide RNA was microinjected into the fertilized C57BL/6 eggs, and the transgenic embryos were planted into pseudopregnant recipients. Founder lines of successful mutation of the SIX1 gene cluster were identified through PCR genotyping of tail DNA. PCR products were further verified through DNA sequencing. The genotyping primers were as follows: Forward primer, 5’-GATGCTGCCGTCGTTTGGTTTTA-3’; Reverse primer, 5’-GGGTGGCGGCGGGTAGGAAG -3’. The positive female founder mice and wild-type male mice were bred to get F1 SIX1 heterozygote mice. Male SIX1 heterozygote mice and female SIX1 heterozygote mice were then crossed to obtain SIX1 homozygote mice. As previously reported (El-Hashash et al., 2011; Laclef et al., 2003), mice with homozygous deletion of SIX1 die shortly after birth. For mouse embryo genotype identification, genomic DNA was prepared from the tail tips of 14-day-old embryos and the SIX1 mutation was identified by PCR amplification, DNA sequencing and immunoblot. For 18FDG microPET scans, seven week-old female or male nude mice were subcutaneously inoculated in the dorsal left flank with 5 3 106 ZR75-1 or HepG2 cells. For miRNA study, cells were treated with antagomiR-548a-3p or antagomiR-NC, a negative control, for three days, and then harvested for further study. 2-DG (500 mg/kg) was administered to mice intraperitoneally every other day. Growth was recorded by caliper measurements at indicated times. One average-sized tumor tissue from each group was chosen and cut into several pieces. Every piece was then weighed. For further studies, the pieces were lysed in corresponding extraction buffer. The three pieces from each group were used for immunoblot and qRT-PCR, and the five pieces from each group for measurement of lactate. Other tumor tissues were stored in liquid nitrogen or fixed in 4% paraformaldehyde.

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SIX1, HBO1 and AIB1 Knockout Cancer Cell Lines SIX1, HBO1 and AIB1 knockout cancer cells were generated by CRISPR/Cas9 (Genloci Biotechnologies Inc.). CRISPRs were designed using a CRISPR design web tool (http://crispr.mit.edu). The sgRNA (single guide RNA) sequences targeted by SIX1, HBO1 and AIB1 CRISPR are CCTGCACAAGAACGAGAGCGTAC, CCGACGATCTGCTCGAGTCACCC and TGATGTATATTCAAG ATGAGTGG, respectively. The sgRNAs were cloned into the pGK1.1/CRISPR/Cas9 vector (Genloci Biotechnologies Inc.). Cells were transfected with the sgRNA vectors, expanded and screened for mutations at nuclease target sites by PCR amplification of genomic sequences, followed by DNA sequencing and immunoblotting. The CRISPR cell lines were clonal. Rescue experiments were performed to avoid off-target effect. Cell Lines and Drug Treatments Human embryonic kidney HEK293T cells, human breast cancer ZR75-1 cells (Female), human liver cancer HepG2 cells (Male), human colorectal cancer HCT116 cells (Male) and human lung cancer A549 cells (Male) were purchased from American Type Culture Collection (ATCC), and have previously been tested for mycoplasma contamination. The information on the sex of HEK293T cells and MEFs is not available due to their isolation from fetus. Cells were routinely cultured in DMEM containing 25 mM glucose (Invitrogen) and 10% FBS (Hyclone) at 37 C. Lipofectamine 2000 reagent and Lipofectamine RNAiMAX were used for transfections of plasmids and siRNAs, respectively, according to the manufacturer’s instructions (Invitrogen). For plasmid transfection, cells were seeded to 70–90% confluent at the time of transfection. Plasmids and Lipofectamine 2000 reagent were diluted in DMEM. The diluted plasmids were mixed with the diluted Lipofectamine 2000. The mixtures were incubated for 5 min at room temperature and added to cells in each dish. The transfected cells were collected after 24–48 hr. For siRNA transfection, siRNA and Lipofectamine RNAiMAX reagent were diluted in DMEM without serum, and the contents were mixed gently. The mixtures were incubated for 10–20 min at room temperature. The incubated mixtures of siRNA and RNAiMAX were then added to cells in each dish. Cells were incubated for 48–72 hr. In galactose study, cells were cultured in DMEM without glucose supplemented with 10 mM galactose (Invitrogen) and 10% FBS. Cells were treated with 2.5 mM 2-DG, 100 mM 3-BP or 0.1mM oligomycin at indicated times. METHOD DETAILS Plasmids, siRNAs, shRNAs, and Lentiviruses The eukaryotic expression vectors encoding FLAG- or MYC-tagged proteins or untagged proteins were generated by inserting PCR-amplified fragments into pcDNA3 (Invitrogen). Prokaryotic plasmids encoding GST- or His-fusion proteins were constructed in pGEX-KG (Amersham Pharmacia Biotech) and pET28a (Novagen), respectively. The glycolytic gene promoter luciferase reporters were made by inserting PCR-amplified promoter fragments from genomic DNA into the pGL4-Basic vector (Promega). The mutants for the FLAG-, MYC- or GST-tagged proteins as well as the luciferase reporters were made by recombinant PCR. The cDNA target sequences of siRNAs and/or shRNAs for SIX1, HBO1, AIB1, LDHA and PGK1 were listed in Table S5. Lentiviral vectors for gene overexpression were obtained by inserting PCR-amplified gene fragments into pCDH (System Biosciences). Lentiviral shRNA vectors were constructed by cloning short hairpin RNA fragments into pSIH-H1-Puro (System Biosciences). Lentiviruses were produced by cotransfection of HEK293T cells with recombinant lentivirus vectors and pPACK Packaging Plasmid Mix (System Biosciences) using Megatran reagent (Origene), and were used to infect target cells according to the manufacturers’ instructions. Transcriptome Sequencing (RNA-Seq) A minimum of 3 mg of total RNA was oligo (dT) selected using the Dynabeads mRNA purification kit (Invitrogen). The mRNAs isolated from total RNA were fragmented into short fragments with a fragmentation buffer (Ambion). Double-stranded cDNA was synthesized with these short fragments as templates. The cDNA was end-repaired, ligated to Illumina adapters, size selected on agarose gel (approximately 250 bp) and PCR amplified. The cDNA library was sequenced on an Illumina HiSeq 2000 sequencing platform (BerryGenomics). The gene expression levels for each transcript were estimated as the number of reads per kilobase of exon model per million mapped reads (RPKM) using only uniquely mapped reads in exonic regions. A gene is considered significantly differentially expressed if its expression differs between any two samples with the fold change > 2 and the p value < 0.05 as calculated by Cufflinks. The RNA-Seq data are available at the Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo/, accession number GSE93925). Quantitative Reverse Transcription-PCR (RT-PCR) Total RNA was isolated using TRIzol reagent according to the manufacturer’s instructions (Invitrogen). The samples were homogenized with TRIzol Reagent, vortexed for 1 min with 200 mL chloroform and centrifuged at 1.3 3 104 rpm for 10 min at 4 C, thereby building two phases. The upper aqueous phase (containing RNA) was precipitated with isopropanol at – 20 C for 1 h and centrifuged at 1.2 3 104 rpm for 15 min. The RNA pellets were washed with 70% (v/v) ethanol and 100% (v/v) ethanol in succession, air-dried, and dissolved in 100–200 ml of nuclease-free water. Two micrograms of total RNA was reverse transcribed into first strand cDNA with oligo (dT) primers using Moloney murine leukemia virus reverse transcriptase (Promega). One microliter of the first strand cDNA synthesis reaction mixture was used for PCR amplification in a total volume of 50 ml. qPCR was performed in triplicates in a 20 ml reaction mixture containing 10 ml of SYBR Premix Ex Taq Master Mix (23) (Takara), 0.5 mM of each of the primers and 10 ng cDNA. The relative expression was calculated by the comparative Ct method. The primers used for real-time PCR analysis were listed in Table S6.

e4 Cancer Cell 33, 1–18.e1–e7, March 12, 2018

Please cite this article in press as: Li et al., Transcriptional Regulation of the Warburg Effect in Cancer by SIX1, Cancer Cell (2018), https://doi.org/ 10.1016/j.ccell.2018.01.010

Luciferase Reporter Assay Luciferase reporter assays were performed according to the manufacturer’s instructions (Promega). Briefly, cells were seeded in 24well plates. For analysis of glycolytic gene promoter activity, cells were transfected with 1 mg of promoter luciferase reporter, 0.5 mg of empty vector, SIX1, or SIX1 mutant expression vector, and 0.1 mg of b-galactosidase reporter. For analysis of SIX1 3’-UTR activity, cells were transfected with 1 mg of WT SIX1 3’-UTR or mutated SIX1 3’-UTR luciferase reporter, 0.5 mg of miR-548a-3p, and 0.1 mg of b-galactosidase reporter. Twenty four hours after transfection, the cells were harvested in 13 lysis buffer and subjected to a single freeze-thaw cycle to ensure complete lysis. Cell lysates were transferred to the microcentrifuge tubes, vortexed for 3 min and then centrifuged at 1.2 3 104 rpm for 5 min at 4 C. Ten microliters of supernatants were mixed with 10 ml of the Luciferase Assay Reagent per tube and measured for the luciferase activity using the luminometer. For b-galactosidase activity assay, the supernatants were transferred to a 96-well plate and incubated in the Assay buffer for 1 h at 37 C. Reaction was stopped and OD values were measured at 420 nm using a microplate reader. Chromatin Immunoprecipitation (ChIP) and re-ChIP ChIP assay was performed using the Magna ChIP G Assay Kit (Millipore) according to the manufacturer’s instructions. Briefly, cells were cross-linked with 37% formaldehyde, pelleted, and resuspended in lysis buffer. The cells were sonicated and centrifuged to remove the insoluble material. The supernatants were collected and incubated overnight with indicated antibodies and Protein G magnetic beads. The beads were washed, and the precipitated chromatin complexes were collected, purified, and de-crosslinked at 62 C for 2 h, followed by incubation at 95 C for 10 min. The precipitated DNA fragments were quantified through RT-PCR analysis. For re-ChIP, complexes were eluted from the primary immunoprecipitation by incubation with 10 mM DTT at 37 C for 30 min and diluted 1:50 in re-ChIP buffer (150 mM NaCl, 1% Triton X-100, 2 mM EDTA, 20 mM Tris-HCl, pH 8.1) followed by re-immunoprecipitation with the second antibodies. Samples were analyzed by real-time PCR with primers listed in Table S7. Co-immunoprecipitation and His or GST Pull-down Assays Co-immunoprecipitation (Co-IP) was performed as previously described (Sun et al., 2006). For transfection-based coimmunoprecipitation assays, 293T cells were transfected with the indicated plasmids using Lipofectamine 2000 (Invitrogen), lysed in 500 ml of lysis buffer (50 mM Tris at pH 8.0, 500 mM NaCl, 0.5% Nonidet P-40, 1 mM dithiothreitol, and protease inhibitor tablets from Roche Applied Science), and immunoprecipitated with anti-FLAG or Myc-agarose beads (Sigma-aldrich) overnight at 4 C. The beads were washed three times with the lysis buffer and eluted in SDS sample buffer. The eluted immunocomplexes were separated by SDS-PAGE, followed by Western blotting with indicated antibodies according to the standard procedures. For detecting endogenous protein interactions, cells were lysed in 500 ml of lysis buffer and immunoprecipitated with indicated antibody or control serum (Santa Cruz Biotechnology). After extensive washing with the lysis buffer, the immunoprecipitates were resolved by SDS-PAGE, followed by Western blot analysis. For His or GST pull-down assays, His- or GST-fusion proteins were expressed and purified according to the manufacturers’ instructions (QIAGEN and Amersham Pharmacia). His- or GST-fusion proteins were expressed in Escherichia coli (BL21). After induction with 0.5 mM IPTG at 20 C for over 20 hr, Escherichia coli were collected, resuspended in lysis buffer and sonicated. Precipitates were removed from the lysates through centrifugation and supernatants were loaded on nickel beads (QIAGEN) or glutathione-Sepharose beads (Amersham Pharmacia) balanced with lysis buffer for 4 hr at 4 C. The beads were collected and washed 3 times with lysis buffer. GST- or His -fusion proteins were eluted from their respective beads with reduced glutathione and imidazole, respectively. Purified GST-fusion proteins were incubated with His-fusion protein bound to nickel beads (QIAGEN) or cell lysates were incubated with GST fusion protein bound to GST beads for 4 hr at 4 C. After washing, the adsorbed proteins were analyzed by immunoblot. Mass Spectrometry The FLAG-tagged Six1 complex was obtained by immunoprecipitation with anti-FLAG from 108 ZR75-1 cells stably expressing FLAG-Six1 according to the manufacturer’s instructions (Sigma-Aldrich). Cells were lysed in IP buffer (20mM Tris at PH 8.0, 0.25M NaCl, 0.5% NP-40, 5mM EDTA) and immunoprecipitated with anti-FLAG agarose beads (Sigma-aldrich) for 4 hr at 4 C. The beads were washed four times with IP buffer and eluted with FLAG peptide. The eluted proteins were resolved on gradient SDS-PAGE, silver stained, and subjected to mass spectrometry (MS) sequencing and data analysis. In-solution and in-gel digestion were performed according to a previously published method (Jin et al., 2003). Briefly, gel bands were minced and destained with 50% acetonitrile in 50 mM ammonium bicarbonate. Proteins were reduced with 10 mM DTT at 56 C, followed by alkylation with 55 mM iodoacetamide at room temperature in the dark. Trypsin digestion was performed overnight at 37 C with gentle shaking. Peptides were extracted using 1% trifluoroacetic acid in 50% acetonitrile. Samples were vacuum-dried and reconstituted in 0.1% formic acid for subsequent MS analysis. The treated samples were examined by nanoLC-MS/MS (nanoACQUITY UPLC and SYNAPT G2 HD mass spectrometer, Waters). MS/MS data were obtained with Data Dependent Analysis mode and processed with PLGS 2.4 software (Waters), and the resulting peak list was searched against the NCBI database with the MASCOT search engine. Cell Proliferation Assays Cell proliferation was determined by the CCK-8 Kit (Dojindo Laboratories) according to the manufacturer’s instructions. Briefly, ten microliters of CCK-8 solution was added to cultured cells in each well, followed by incubation at 37 C for 1 hr. The OD values were measured at 450 nm using a microplate reader. Cancer Cell 33, 1–18.e1–e7, March 12, 2018 e5

Please cite this article in press as: Li et al., Transcriptional Regulation of the Warburg Effect in Cancer by SIX1, Cancer Cell (2018), https://doi.org/ 10.1016/j.ccell.2018.01.010

Glucose Uptake, Pyruvate, Lactate, ATP, HK, GAPDH, ALDO, PKM and LDH Assays Glucose Uptake Colorimetric Assay Kit, Pyruvate Colorimetric Assay kit, Lactate Assay Kit II, ATP Colorimetric Assay Kit, Hexokinase Colorimetric Assay Kit, GAPDH Activity Assay Kit, Aldolase Activity Colorimetric Assay Kit, Pyruvate Kinase Activity Colorimetric Assay Kit, and Lactate Dehydrogenase Activity Assay Kit were used to determine glucose uptake, levels of pyruvate, lactate and ATP, and activities of HK, GAPDH, ALDO, PKM and LDH, respectively, according to the manufacturer’s protocols (Biovision). For glucose uptake assay, cells were seeded into 10-cm plates, transfected or infected with indicated constructs, and incubated in DMEM supplemented with 10% FBS for 48 hr. The transfected cells were harvested and the cell number was determined. Ten thousand cells were then plated into a 96-well plate, and incubated for 10 hr, at which time cell number for each group was very similar. Cells were washed 3 times with PBS and then starved for glucose by preincubating with 100 ml Krebs-Ringer-Phosphate-HEPES (KRPH) buffer containing 2% BSA for 40 min. Ten microliter of 10 mM 2-DG was added and incubated for 20 min. Cells were lysed with 90 ml of extraction buffer and then frozen/thawed once and heated at 85 C for 40 min. The cell lysate was neutralized by adding 10 ml of neutralization buffer. After centrifugation at 1.23104 rpm for 5 min, the supernatant was used for determination of glucose uptake (Biovision). The glucose uptake was measured at 412 nm in a microplate reader. The results were normalized to cell number. For pyruvate activity assay, cells were transfected or infected as in glucose uptake assay. Cells (53105) were collected and extracted with 4 volume of the Pyruvate Assay Buffer (Biovision). The cells were centrifuged at 1.23104 rpm for 10 min at 4 C to remove insoluble material. After centrifugation, the supernatant was assayed by Pyruvate Colorimetric Assay kit (Biovision). The reaction mixture was incubated for 30 min at room temperature, protected from light and measured at 570 nm in a microplate reader. Data were normalized to cell number. For measurement of lactate production, cells were transfected or infected, and harvested as in glucose uptake assay. One hundred thousand cells were then plated into a 12-well plate and incubated in DMEM containing 10% FBS for 10 hr. To measure the secretion of lactate, the media were removed and the cells were incubated in DMEM without FBS. After incubation for 1 hr, the supernatant was collected for measurement of lactate production (Biovision). The reaction mixture was incubated for 30 min at room temperature and protected from light. The lactate levels were measured at 450 nm in a microplate reader and normalized with cell number. For measurement of the lactate levels of mouse tumor, 10 mg of tumor tissues were isolated and homogenized in the Assay Buffer (Biovision). The samples were centrifuged and the soluble fractions were measured and normalized to protein concentrations. For ATP level analysis, cells were transfected or infected as in glucose uptake assay. Cells (53105) were collected and extracted in 100 ml of the ATP Assay Buffer (Biovision). The cells were centrifuged at 1.23104 rpm for 5 min and the supernatant was used for ATP determination. The reaction mixture was incubated for 30 min at room temperature, protected from light, and measured at 570 nm in a microplate reader. Values were normalized to cell number. For hexokinase activity assay, cells were transfected or infected as in glucose uptake assay. Cells (53105) were harvested and homogenized in 100 ml of Hexokinase Assay Buffer (Biovision) for 10 min. The cells were centrifuged at 1.23104 rpm for 5 min and the supernatant was assayed by Hexokinase Colorimetric Assay Kit (Biovision). The reaction mixture was incubated at room temperature for 20-60 min and measured at 450 nm in a microplate reader. Results were normalized to cell number. For GAPDH or aldolase activity assay, cells were transfected or infected as in glucose uptake assay. Cells (53105) were collected and homogenized in 100 ml GAPDH or Aldolase Assay Buffer (Biovision) for 10 min. The cells were centrifuged at 1.23104 rpm for 5 min and the supernatant was analyzed by GAPDH or Aldolase Activity Assay Kit (Biovision). The reaction mixture was incubated at 37 C for 10-60 min and measured at 450 nm in a microplate reader. Data were normalized to cell number. For pyruvate kinase activity assay, cells were transfected or infected as in glucose uptake assay. Cells (53105) were harvested and extracted with 4 volume of the Pyruvate Kinase Assay Buffer (Biovision). The cells were centrifuged at 1.23104 rpm for 10 min to get clear extract. After centrifugation, the supernatant was assayed by Pyruvate Kinase Activity Assay Kit (Biovision). The reaction mixture was incubated for 10-20 min at room temperature, protected from light, and measured at 570 nm in a microplate reader. Results were normalized to cell number. For lactate dehydrogenase activity assay, cells were transfected or infected as in glucose uptake assay. Cells (23105) were collected and homogenized in 100 ml of the Lactate Dehydrogenase Assay Buffer (Biovision). The cells were centrifuged at 1.23104 rpm for 15 min and the supernatant was assessed by Lactate Dehydrogenase Activity Assay Kit (Biovision). The reaction mixture was incubated at 37 C for 30 min, protected from light and measured at 450 nm in a microplate reader. Values were normalized to cell number. Extracellular Acidification Rate and Oxygen Consumption Rate Assays The extracellular acidification rate (ECAR) and cellular oxygen consumption rate (OCR) were measured using the Seahorse XFe 96 Extracellular Flux Analyzer (Seahorse Bioscience). Experiments were performed according to the manufacturer’s instructions. ECAR and OCR were measured using Seahorse XF Glycolysis Stress Test Kit and Seahorse XF Cell Mito Stress Test Kit (Agilent Technologies), respectively. Briefly, cells were transfected or infected as in glucose uptake assay. The transfected cells were harvested and the cell number was counted. Ten thousand cells per well were then seeded into a Seahorse XF 96 cell culture microplate for 10 hr, at which time cell number for each group was very similar. The cells were used for measurement of ECAR and OCR. After baseline measurements, for ECAR, glucose, the oxidative phosphorylation inhibitor oligomycin, and the glycolytic inhibitor 2-DG were sequentially injected into each well at the indicated time points; and for OCR, oligomycin, the reversible inhibitor of oxidative phosphorylation FCCP (p-trifluoromethoxy carbonyl cyanide phenylhydrazone), and the mitochondrial complex I inhibitor rotenone plus the mitochondrial complex III inhibitor antimycin A (Rote/AA) were sequentially injected. Data were analysed by Seahorse XF-96 Wave software. OCR is reported in pmols/minute and ECAR in mpH/minute. The results were normalized to cell number. e6 Cancer Cell 33, 1–18.e1–e7, March 12, 2018

Please cite this article in press as: Li et al., Transcriptional Regulation of the Warburg Effect in Cancer by SIX1, Cancer Cell (2018), https://doi.org/ 10.1016/j.ccell.2018.01.010

SIX1 Q177R Mutation Screening Genomic DNA was isolated from 42 breast cancer tissues using the blood/tissue/cell genomic DNA Extraction Kit (Tiangen, DP304) according to the manufacturer’s instructions. In brief, tissues were digested in lysis solution mixed with proteinase K and incubated at 58 C until being dissolved. The detergent buffer was added during lysis and mixed with binding buffer and ethanol for subsequent DNA binding. The DNA binds to the silica-based membrane in the Spin Column and impurities are removed by thorough washing with wash buffers. The genomic DNA was then eluted in elution Buffer and subjected to PCR. Approximately 300 bp of PCR fragment containing the SIX1 Q177 site was first amplified using genomic DNA and re-amplified with the first amplified PCR product as the template using the following primers. The forward primer sequence was 5’-CACCATCTGGGACGGCGAGGA-3’, and the reverse primer sequence 5’-GGACTTGGTGGCTGGTGCCTG-3’. Both strands of the final PCR products were sequenced. miRNA In Situ Hybridization and Immunohistochemistry For patients used for 18FDG PET scan analysis, miRNA in situ hybridization (MISH) on paraffin tissue sections with probes specific for human miR-548a-3p was performed according to the manufacturer’s instructions (Exonbio). The sequence of the miR-548a-3p probe, complementary to miR-548a-3p, is 5’-GCAAAAGTAATTGCCAGTTTTG-3’. Both 5’ and 3’ ends of the probe were labeled by digoxin. A U6 probe 5’- GAACGCTTCACGAATTTGCGTGTCATCCTTGCGCA-3’ was used as a positive control. A scramble probe 5’-GTGTAACACGTCTATACGCCCA-3’ was used as a negative control. Briefly, paraffin-embedded tissue slides were deparaffined, rehydrated and pretreated with 3% H2O2 for 15 min to quench endogenous peroxidase activity. The slides were preincubated with miRNA Hybridization solution at 55 C for 1 hr, followed by hybridization with DIG-labeled miR-548a-3p probe at 42 C for 48 hr. The slides were washed 3 times at 42 C for 2 min and stained with 3, 3’-Diaminobenzidine (DAB). Slides were counterstained with hematoxylin, dehydrated in the increased concentrations of ethanol series, cleared in xylene and mounted with neutral resin. Immunohistochemistry (IHC) of formalin-fixed paraffin-embedded samples was performed as described previously (Zhang et al., 2005). Briefly, the formalin-fixed paraffin sections were deparaffinized, rehydrated, and pretreated with 3% H2O2 for 20 min. The antibody-binding epitopes of the antigens were retrieved by microwave treatment, and the sections were then preincubated with 10% goat serum to block nonspecific binding. Rabbit anti-SIX1 (HPA001893, Sigma-Aldrich), rabbit anti-PGK1 (17811-1-AP, Proteintech), rabbit anti-LDHA (19987-1-AP, Proteintech), mouse-anti-AIB1 (sc-56854, Santa Cruz Biotechnology), rabbit anti-HBO1 (13751-1-AP, Proteintech), and mouse anti-HIF-1a (NB100-105, Novus), diluted at 1: 50, 1: 100, 1:100, 1:200, 1:200 and 1:50 respectively, were used as the primary antibodies. The specimens were incubated with the primary antibodies for 1 hr at room temperature, followed by the addition of biotinylated anti-rabbit or anti-mouse secondary antibody and streptavidin-horseradish peroxidase. DAB was used as a chromogen, and hematoxylin was used for counterstaining. The miR-548a-3p, SIX1, PGK1, LDHA, AIB1, HBO1 and HIF-1a score was generated by multiplying the percentage of stained cells (0 - 100%) by the intensity of the staining (low, 1+; medium, 2+; strong, 3+). Thus, the score is between 0-3. The optimal cutoff value of the IHC scores were estimated using receiver operating characteristic (ROC) curve analysis as previously described (Greiner et al., 2000). For correlation analysis, we defined score <0.25, 0.25%score %0.75 and score >0.75 as low, medium and high SIX1, PGK1, LDHA, AIB1, HBO1, or HIF-1a, respectively. For PET scan analysis, we defined score %0.75 and score >0.75 as low and high SIX1 and miR-548a-3p, respectively. When real-time PCR was used for miR-548a-3p quantification (the score is between 0-5), we defined score %2.1 and score >2.1 as low and high miR-548a-3p. PET Imaging of Glucose Uptake in Mice PET imaging of mice was performed using an animal PET scanner (Philips Corp.). Mice were injected intravenously with 3.7 MBq (100 mCi) of 18F radio-labeled fluorodeoxyglucose (18FDG) after anesthetization with pentobarbital. Five-minute emission scans were performed to obtain attenuation correction data in the prone position at 60 minutes after injection, and delay scans of 10 minutes were acquired at 2 hours. For each mouse, radioactivity was calibrated against a known aliquot of the injected tracer and presented as percent injected dose of tissue. QUANTIFICATION AND STATISTICAL ANALYSIS Statistical Analysis Trial experiments or similar experiments done previously were used to assess sample size with adequate statistical power. Statistical significance in the preclinical experiments was assessed by two-tailed Student’s t-test. The correlation of expression among miR-548a-3p, SIX1, PGK1 and LDHA was determined using Spearman’s Rank Correlation test. Estimation of disease-free survival and overall survival was performed using the Kaplan-Meier method, and differences between survival curves were determined with the log-rank test. All statistical tests were two-sided. Statistical calculations were performed using SPSS 13.0. In all assays, p < 0.05 was considered statistically significant. DATA AND SOFTWARE AVAILABILITY Data Resources The accession number for the transcriptome sequencing data reported in this paper is GEO Datasets: GSE93925.

Cancer Cell 33, 1–18.e1–e7, March 12, 2018 e7