Glycine Decarboxylase Activity Drives Non-Small Cell Lung Cancer Tumor-Initiating Cells and Tumorigenesis Wen Cai Zhang,1,3 Ng Shyh-Chang,1 He Yang,5 Amit Rai,6 Shivshankar Umashankar,6,7 Siming Ma,1 Boon Seng Soh,1 Li Li Sun,1 Bee Choo Tai,11 Min En Nga,9 Kishore Kumar Bhakoo,12 Senthil Raja Jayapal,13 Massimo Nichane,1 Qiang Yu,2 Dokeu A. Ahmed,4 Christie Tan,4 Wong Poo Sing,10 John Tam,10 Agasthian Thirugananam,14 Monireh Soroush Noghabi,1 Yin Huei Pang,9 Haw Siang Ang,5 Wayne Mitchell,16,17 Paul Robson,1 Philipp Kaldis,13 Ross Andrew Soo,5,8 Sanjay Swarup,6,7 Elaine Hsuen Lim,3,8,15,* and Bing Lim1,18,* 1Stem
Cell and Developmental Biology Biology and Pharmacology Genome Institute of Singapore, 60 Biopolis Street, Singapore 138672 3Department of Respiratory Medicine 4Department of Thoracic Surgery Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore 308433 5Cancer Science Institute of Singapore, National University of Singapore, 28 Medical Drive, Singapore 117456 6Metabolites Biology Lab, Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543 7NUS Environmental Research Institute (NERI), T-Lab Building (TL), National University of Singapore, 5A Engineering Drive 1, Singapore 117411 8Department of Haematology-Oncology 9Department of Pathology 10Department of Thoracic Surgery National University Hospital, 5 Lower Kent Ridge Road, Singapore 119074 11Department of Community, Occupational and Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597 12Translational Molecular Imaging Group (TMIG), Laboratory of Molecular Imaging (LMI), Singapore BioImaging Consortium (SBIC), 11 Biopolis Way, Singapore 138667 13Cell Division and Cancer Laboratory (PRK), Institute of Molecular and Cell Biology, 61 Biopolis Drive, Singapore 138673 14Department of Thoracic Surgery 15Department of Medical Oncology National Cancer Centre, 11 Hospital Drive, Singapore 169610 16Bioinformatics, Experimental Therapeutics Centre, 31 Biopolis Way, Singapore 138669 17Division of Information Sciences, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798 18Beth-Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA *Correspondence:
[email protected] (E.H.L.),
[email protected] (B.L.) DOI 10.1016/j.cell.2011.11.050 2Cancer
SUMMARY
Identification of the factors critical to the tumor-initiating cell (TIC) state may open new avenues in cancer therapy. Here we show that the metabolic enzyme glycine decarboxylase (GLDC) is critical for TICs in non-small cell lung cancer (NSCLC). TICs from primary NSCLC tumors express high levels of the oncogenic stem cell factor LIN28B and GLDC, which are both required for TIC growth and tumorigenesis. Overexpression of GLDC and other glycine/serine enzymes, but not catalytically inactive GLDC, promotes cellular transformation and tumorigenesis. We found that GLDC induces dramatic changes in glycolysis and glycine/serine metabolism, leading to changes in pyrimidine metabolism to regulate cancer cell proliferation. In the clinic, aberrant activation of GLDC correlates with poorer survival in lung
cancer patients, and aberrant GLDC expression is observed in multiple cancer types. This link between glycine metabolism and tumorigenesis may provide novel targets for advancing anticancer therapy. INTRODUCTION Despite numerous advances in our knowledge of cancer (Vogelstein and Kinzler, 2004; Hanahan and Weinberg, 2011), our ability to develop clinically effective therapies based on this understanding has met with limited success. Current therapies can control tumor growth initially, but most patients ultimately relapse. One prominent example is lung cancer, the leading cause of cancer-related mortality with over 1 million deaths each year (Jemal et al., 2011). Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancers. Although NSCLC patients with epidermal growth factor receptor (EGFR) mutations respond to EGFR inhibitors initially, most patients experience a relapse within 1 year (Sequist et al., Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc. 259
2007). These findings underscore the urgent need for both combination therapies and also new approaches to treat cancerous tumors. One such approach may be to target tumor-initiating cells (TICs). Data from leukemias, germ cell tumors, and a number of solid tumors support the notion that cancers are maintained by a subpopulation of self-renewing and evolving TICs. This is also popularly known as the cancer stem cell (CSC) model (Reya et al., 2001; Rosen and Jordan, 2009). Although the validity of the CSC model is an issue of controversy in melanoma (Quintana et al., 2008, 2010; Boiko et al., 2010; Civenni et al., 2011), many other solid tumors appear to follow the CSC model (Ishizawa et al., 2010). Recently it was proposed that at earlier stages of tumorigenesis, rare TIC clones differentiate into nonmalignant progeny to form the bulk of the tumor, whereas at advanced stages, TIC clones constitute the bulk of the tumor (Boiko et al., 2010). Studies with mouse models of lung cancer have also begun to reconcile the connection between the evolving genotype of TIC clones and the surface phenotype of TICs (Curtis et al., 2010). Thus accumulated findings suggest that targeting TICs may be a promising approach for eradicating tumors early. However, progress in the targeting of TICs to improve cancer therapy has been hindered by a lack of understanding of the molecular pathways that are critical to TICs. Recent studies have led to an emerging appreciation of the importance of metabolic reprogramming in cancer (Hsu and Sabatini, 2008; Vander Heiden et al., 2009; Hanahan and Weinberg, 2011). Most recently, the embryonic isoform of pyruvate kinase PKM2, in collaboration with phosphoglycerate mutase, was found to regulate the shift from oxidative phosphorylation to glycolysis in cancer cells (Christofk et al., 2008; Vander Heiden et al., 2010). These findings have led to a resurgence of interest in the Warburg effect—the phenomenon whereby cancer cells, like embryonic cells, preferentially use glycolysis even under aerobic conditions (Warburg, 1956). Besides glycolysis, an arm of metabolism that results in sarcosine production has also been implicated in prostate cancer (Sreekumar et al., 2009). These data suggest that metabolic reprogramming is crucial for tumorigenesis, and much remains to be uncovered. Here we show that glycine metabolism and the metabolic enzyme glycine decarboxylase (GLDC) drive TICs and tumorigenesis in NSCLC. Using CD166 as a surface marker and NOD/SCID Il2rg/ mice as xenotransplantation recipients, we isolated lung TICs from a broad range of primary NSCLC tumors (stages I–III). Primary lung TICs express high levels of LIN28B, GLDC, and many other glycine/serine metabolism enzymes. Both LIN28B and GLDC were required for lung TIC proliferation and tumor growth. Overexpression of GLDC alone, and other glycine/serine enzymes, promotes cellular transformation both in vitro and in vivo. Metabolomic analysis shows that GLDC overexpression induces dramatic changes in glycolysis and glycine metabolism, leading to changes in pyrimidine metabolism for cancer cell proliferation. In human patients, aberrant upregulation of GLDC is significantly associated with higher mortality from lung cancer, and aberrant GLDC expression is observed in multiple cancer types. Our findings establish a link between glycine metabolism and tumorigenesis and may provide novel targets for advancing anticancer therapy. 260 Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc.
RESULTS TICs in Lung Cancer To assess the cellular heterogeneity within NSCLC, we obtained freshly resected lung tumors from 36 human patients with a broad range of stage I–III primary NSCLC (Table S1 available online). Patient lung cancer cells were directly transplanted subcutaneously into NOD/SCID Il2rg/ mice with Matrigel (Quintana et al., 2008). Using this maximally sensitive assay, we estimated by limiting dilution analysis that lung TICs exist with a low frequency of 1 in 4 3 105 cells in unsorted NSCLC tumor cells (n = 36 patients; Figure 1A), consistent with published findings (Ishizawa et al., 2010). To profile the surface phenotype of this subpopulation of lung TICs, we fractionated the NSCLC tumors by fluorescenceactivated cell sorting (FACS; Figure S1A). After excluding hematopoietic and endothelial cells (Lin), we tested a panel of cell-surface markers, including CD166, CD44, CD133, and EpCAM (Figure 1B). We found that CD166 was the most robust marker for enriching the lung TIC subpopulation, compared to CD133, CD44, or EpCAM, allowing us to reliably enrich lung TICs by nearly 100-fold (Figures 1A and 1B). In 12 out of 12 NSCLC patient tumors (lung adenocarcinoma), the CD166+ Lin fraction contained cells that consistently initiated lung tumor formation in vivo. In contrast, CD166Lin tumor cells generally failed to initiate lung tumor formation even after 8 months of observation, although they also expressed carcinoembryonic antigen (CEA), a tumor-specific marker not expressed in normal adult lung cells (Figures 1A, 1B, and S1B). Similar results were observed in lung squamous cell carcinoma and large cell carcinoma (Figure S1C). Although CD166 expression varied across the NSCLC tumors we examined, CD166 was consistently higher in lung tumors than in normal adjacent lung tissues (n = 25 patients; Figures S1D and S1E). CD166+ lung TICs demonstrate a capacity for self-renewal and differentiation in vivo. Serial transplantations showed that only the CD166+ fraction was able to self-renew and initiate primary and secondary xenograft tumors (Figures 1A and S1F). Upon transplantation, CD166+ lung TICs differentiated to form xenograft tumors that phenocopy the complex cytoarchitecture of their parental patient tumors, sharing similar histological morphology by hematoxylin-eosin (H&E) staining and similar tissue distributions of CD166, cytokeratin, E-cadherin, vimentin, smooth muscle actin, and synaptophysin (Figures 1C, S1G, and S1H). Furthermore, we found that transplants with more TICs grow more rapidly, suggesting that lung TIC frequency is correlated with tumor growth rate (Figures 1D and S1I). The self-renewal capacity of CD166+ lung TICs is further corroborated by in vitro assays. We tested the CD166+ fraction for the ability to form tumor spheres, a widely used in vitro technique for assessing self-renewal capacity (Dontu et al., 2003). Although both primary CD166+ and CD166 cells remained viable in vitro, only primary CD166+ but not CD166 cells were able to form compact self-renewing spheres (n = 9 patients; Figures 1E, 1F, and S1J). Using immunofluorescence and flow cytometry, we found that the lung tumor spheres retained high levels of CD166 expression but undetectable CD133 expression
150,000 200,000 300,000 500,000 1,000,000 2,000,000
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1/403,971 (1/255,949 1/637,598)
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Figure 1. CD166+ Fraction Contains TICs from NSCLC Patients (A) Frequency of TICs in unsorted, CD166+, and CD166 subpopulations of cells from 36 NSCLC patients. CI, confidence interval. Lin cells, CD45 CD31 cells. (B) Tumor initiation frequency by various FACS-purified fractions of Lin lung cancer cells isolated from primary xenograft tumors shown in (A). 5 3 104 CD166±, CD44±, CD133±, and EpCAM± cells were tested for tumor initiation in NOD/SCID Il2rg/ mice (n = 12). (C) Histological analysis of patient tumors and primary xenografts derived from patient tumor CD166+ Lin lung cancer cells. Tumors were stained for H&E, CD166, and pan-CK (cytokeratin). Scale bar, 50 mm. (D) Representative tumor-growth curves of xenografts derived from different cell fractions in a lung adenocarcinoma (AdC) patient tumor and the primary xenograft. (E) Phase-contrast images of tumor spheres seeded with CD166+ Lin (top) and CD166 Lin (bottom) cells in lung adenocarcinoma (AdC), squamous cell carcinoma (SCC), and large cell carcinoma (LCC). Scale bar, 50 mm. (F) Quantification of tumor spheres formed by cells from NSCLC patient (AdC, SCC, or LCC) CD166+Lin, CD166Lin, and Lin populations. (G) Frequency of tumorigenesis by single patient-derived tumor sphere cells (n = 3). N.D., not determined. In all panels, error bars represent the standard error of the mean (SEM). See also Figure S1 and Table S1.
in contrast (Figures S1K and S1L). When primary lung tumor spheres were dissociated into single cells and transplanted into NOD/SCID Il2rg/ mice in vivo, we found that as few as 1–5 single cells consistently initiated tumorigenesis (Figures 1G and S1M).
The increased tumor-initiating frequency of lung tumor sphere cells suggests that they are even more highly enriched for lung TICs than the patient tumor CD166+ fraction, and that lung TICs expanded during in vitro culture to form tumor spheres. To test whether CD166 drives tumorigenicity in lung TICs, we Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc. 261
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Figure 2. Lung TICs Express High Levels of GLDC and LIN28B (A) Venn diagram showing strategy for enriching tumorigenic gene expression profile by genome-wide transcriptome analysis. A list of the differentially expressed genes (cutoff threshold of 1.5-fold, p < 0.05) common between P+ versus P, X+ versus X, and S versus X was derived, with the differentially expressed genes of N+ versus N excluded. The gene list was further filtered to select only genes further upregulated or downregulated in S versus X+. N, normal lung tissue (n = 3); P, patient tumor (n = 1); S, tumor sphere (n = 4); X, xenograft tumor (n = 3); +, CD166+; , CD166. Total, n = 11. (B) Graphs of relative expression of candidate lung TIC-associated genes in increasing (left, n = 194) or decreasing (right, n = 295) trends across different CD166+ fraction cells from normal lung tissue (N), primary tumor (P), xenograft tumor (X), and tumor spheres (S) versus nontumorigenic CD166 (X) cells. (C) Top-ranked genes differentially expressed in lung TICs. (D) Enrichment of KEGG pathways by genes differentially expressed in lung TICs. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. (E) Schematic diagram of glycine, serine, and threonine metabolism genes significantly (p < 0.05) upregulated in lung TICs. [, upregulation. See also Figure S2.
knocked down CD166 in two lines of NSCLC patient-derived tumor spheres by retroviral shRNA (Figure S1N). We found that the tumorigenicity of lung TICs in the tumor spheres was not significantly affected by CD166 shRNA, demonstrating that CD166 is an inert cell-surface marker that enriches for lung TICs (Figures S1O–S1Q). Lung TICs Express High levels of Glycine/Serine Metabolism Enzymes To gain a deeper understanding of the molecular basis for the TIC state and its tumorigenic capacity, we sought to obtain 262 Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc.
a molecular signature for lung TICs. To do this, we performed genome-wide transcriptome analysis on CD166 Lin tumor cells, CD166+ Lin tumor cells, and lung tumor spheres, in increasing order of lung TIC frequency (Figure 2A). As a negative control, we also profiled CD166+ versus CD166 cells from normal adjacent lung tissues (n = 3 patients; Table S1). This led us to a profile of genes that are upregulated and downregulated in lung TICs, compared to non-TICs (Figure 2B). Lung TIC-associated genes include the oncogenic stem cell factor LIN28B, embryonic lung transcription factors like PEA3 and the trachealess homolog NPAS1 (Viswanathan et al., 2009;
Liu et al., 2003; Levesque et al., 2007), as well as cell-cycle regulators like CCNB1 and GADD45G (Figure 2C). The highestranking genes were validated by qRT-PCR (Figure S2A). KEGG pathway analysis of the lung TIC-gene profile showed that the top enriched pathways were ‘‘cell cycle,’’ ‘‘DNA replication,’’ ‘‘glycine, serine, and threonine metabolism,’’ ‘‘pyrimidine metabolism,’’ ‘‘MAPK signaling pathway,’’ and ‘‘p53 signaling pathway’’ (Figure 2D). Within the glycine, serine, and threonine metabolism pathway, we found that glycine/serine metabolism enzymes like GLDC, glycine C-acetyltransferase (GCAT), serine hydroxymethyltransferase (SHMT1), phosphoserine phosphatase (PSPH), and phosphoserine aminotransferase (PSAT1) were all upregulated in lung TICs (Figures 2E and S2B–S2D). In particular, GLDC was one of the most highly upregulated genes in multiple analyses of lung TIC-enriched populations, at both the mRNA and protein levels (Figures 2C and S2C). GLDC is a key component of the highly conserved glycine cleavage system in amino acid metabolism that catalyzes the breakdown of glycine to form CO2, NH3, and 5,10-methylene-tetrahydrofolate (CH2-THF) to fuel one-carbon metabolism (Kume et al., 1991). GLDC Is an Oncogene that Promotes Tumorigenesis and Cellular Transformation High expression of GLDC and LIN28B in lung TIC-enriched populations, but not in CD166 lung cancer cells and CD166+ normal lung cells, suggests that these two genes drive tumorigenicity in lung TICs. To test this hypothesis, we knocked down GLDC and LIN28B in lung tumor spheres with shRNAs (Figure S3A) and compared their growth both in vitro and in vivo. We found that both GLDC and LIN28B were necessary for cell proliferation in sphere culture, as well as anchorage-independent colony formation in soft agar (Figures 3A and S3B). Importantly, tumorigenicity was also significantly reduced upon knockdown of either GLDC or LIN28B (Figures 3B and S3C). A549 lung adenocarcinoma cells showed similar results (Figures S3D–S3G). Our results suggest that lung TICs and lung tumorigenesis are dependent on GLDC. This led us to ask what oncogenes upregulate GLDC. Because the E2F pathway upregulates many metabolic genes during cell proliferation, we examined the expression of GLDC over the course of the cell cycle in both normal human lung fibroblasts (HLFs) and the transformed A549 cells after synchronization by serum starvation. Our results showed that GLDC is insensitive to cell-cycle progression in both normal HLFs and transformed A549 cells, suggesting that GLDC is not regulated by cell-cycle or E2F signals (Figure 3C). We then examined GLDC levels in MCF10A cells after transformation by oncogenic KRASG12D, PIK3CAE545K, and MYCT58A. Our results show that all three oncogenes induce GLDC by 20-fold, suggesting that oncogene-induced GLDC transcription is common to the cellular transformation process mediated by oncogenic Ras, PI3K, and Myc (Figure 3D). To test whether aberrant GLDC upregulation is sufficient to drive cellular transformation, as has been shown for LIN28B (Viswanathan et al., 2009), we overexpressed GLDC in NIH/ 3T3 cells (Figure S3H). We found that GLDC overexpression significantly increased colony formation by 3T3 cells under normal culture conditions (Figures 3E and 3F). To test for cellular transformation in vitro, we cultured the 3T3 cells overexpressing
GLDC under anchorage-independent conditions and found that GLDC transforms 3T3 cells readily with a rate exceeding that of LIN28B (Figures 3G and S3I). Upon transplantation into NOD/ SCID Il2rg/ mice, 3T3 cells overexpressing GLDC consistently formed tumors in 6/6 transplants, and 3T3 cells overexpressing LIN28B formed tumors in 3/6 transplants, whereas 3T3 cells overexpressing the empty control vector never formed tumors (Figures S3J–S3L). To test whether GLDC can also transform normal primary HLF and normal primary human bronchial epithelial (NHBE) cells, we overexpressed GLDC in HLF and NHBE cells (Figures S3M and S3O). Both HLF and NHBE cells showed a dramatic increase in cell proliferation upon overexpression of GLDC alone (Figures 3H–3J and S3P). Surprisingly we found that GLDC also transforms HLF and NHBE cells readily in vitro (Figures 3K and S3Q). However, perhaps because primary adult HLF and NHBE cells are not immortalized, GLDC-overexpressing HLF and NHBE cells do not form tumors upon transplantation (Figures S3N and S3R). In contrast, CD166 lung tumor cells, which also could not form tumors in vivo, could now initiate tumorigenesis at a low frequency upon overexpression of GLDC (Figure 3L). Collectively, our results show that GLDC is an oncogene that is both necessary and sufficient to promote tumorigenesis. GLDC Promotes Tumorigenesis through Its Metabolic Activity Although GLDC is a metabolic enzyme, it remained unclear whether GLDC promotes tumorigenesis through a metabolismdependent or -independent mechanism. To address this question, we engineered a series of four point mutations within or near the evolutionarily conserved catalytic active site of the GLDC enzyme to disrupt its metabolic activity (Figure 4A). These point mutations comprised three nonlethal GLDC mutations found in human patients with nonketotic hyperglycinemia (H753P, P769L, G771R; Figures S4A and S4B) and one mutation K754A that is predicted to abrogate the covalent bond with the critical pyridoxal-50 -phosphate cofactor (Nakai et al., 2005; Kure et al., 2006). When we overexpressed these four GLDC mutants in 3T3 cells, none of them could lead to tumorigenesis in vivo, whereas wild-type GLDC could, even though all of them were expressed at high levels similar to that in transformed A549 cells (Figure 4B). Thus the metabolic activity of GLDC is required for its tumorigenic function. In addition, the upregulation of many other upstream enzymes in the glycine/serine pathway in lung TICs further supports the idea that metabolic activity in the glycine/serine pathway is responsible for promoting tumorigenesis (Figure 2E). To test this idea, we also overexpressed PSAT1, PSPH, SHMT1, SHMT2, and GCAT in 3T3 cells and transplanted them in vivo to test for cellular transformation and tumorigenesis (Figure 4C). By 2 months, we found that three other glycine/serine enzymes— PSAT1, PSPH, and SHMT2—could also transform 3T3 cells to form tumors in vivo (Figure 4D). Interestingly, we noted that PSAT1, PSPH, and SHMT2 overexpression only led to a slight upregulation of GLDC protein (Figure 4E), suggesting that their tumorigenic activity is due to increased glycine/serine metabolism, rather than indirect upregulation of GLDC. These findings indicate that increased metabolism in the glycine/serine pathway Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc. 263
Tumor spheres
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Figure 3. GLDC and LIN28B Are Necessary and Sufficient for Malignant Growth (A) Proliferation curve of tumor sphere (TS) cells with shRNA knockdown of either GLDC (GD-sh) or LIN28B (28B-sh). (B) Quantitative mass analysis of xenograft tumors formed 30 days after transplanting 100,000 tumor sphere cells with either GLDC knockdown (GD-sh) or LIN28B knockdown (28B-sh). (C) Western blot analysis of endogenous GLDC during the cell cycle in synchronized normal human HLFs and transformed A549 cells. HLF or A549 cells were serum-starved for 72 hr followed by release into serum-containing medium with samples collected at indicated time points. Expression of GLDC, FOS (early
264 Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc.
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Figure 4. GLDC Promotes Tumorigenesis through Its Metabolic Activity (A) Crystal structure of T. thermophilus GLDC near the catalytic active site. The labeled bacterial residues H703b, K704b (purple), P729b, and G731b are homologous to H753, K754, P769, and G711 of human GLDC. Residues implicated in human nonketotic hyperglycinemia are shown (red). PLP, pyridoxal-50 phosphate cofactor (green). (B) GLDC protein expression and tumor formation efficiency of 3T3 cells overexpressing wild-type or mutant GLDC. Four point mutations were tested: H753P, K754A, P769L, and G771R. Incidence of tumor formation was determined 2 months after injection with 1.5 3 106 cells per mouse (n = 8). A549 cells served as a positive control. WT, wild-type. (C) Gene expression in 3T3 cells overexpressing GLDC, PSPH, PSAT1, GCAT, SHMT1, and SHMT2, relative to 3T3 cells with the empty vector, as determined by qRT-PCR. (D) Tumor formation efficiency of 3T3 cells overexpressing GLDC, PSPH, PSAT1, GCAT, SHMT1, SHMT2, or the empty vector. Incidence of tumor formation was determined 2 months after injection with 1.5 3 106 cells per mouse (n = 6). (E) GLDC protein expression of 3T3 cells overexpressing GLDC, PSPH, PSAT1, GCAT, SHMT1, and SHMT2. A549 cells served as a positive control. b-actin was used as a loading control. In all panels, error bars represent SEM. See also Figure S4.
due to GLDC or other glycine/serine enzymes can exert a potent tumorigenic effect. GLDC Regulates Glycine Metabolism, with Effects on Glycolysis and Pyrimidines Given that GLDC promotes tumorigenesis through a metabolism-dependent mechanism, we performed metabolomic anal-
ysis to gain deeper mechanistic insights into the GLDC-driven metabolism changes that lead to tumorigenesis. We used liquid chromatography-mass spectrometry (LC-MS) to perform metabolomics profiling of HLF cells and 3T3 cells overexpressing GLDC, as well as A549 lung adenocarcinoma cells with retroviral knockdown of GLDC, relative to empty vector controls. We found that glycine-related metabolites, glycolysis intermediates,
serum response), and CDK1 (E2F target) were tested. Normal growing, unsynchronized cells (Cyc) were used as a control. HSP90 was used as a loading control. CDK1, cyclin-dependent kinase 1; HSP90, heat shock protein 90. (D) Expression of endogenous GLDC in MCF10A cells transformed by oncogenic KRASG12D, PIK3CAE545K, MYC, or MYCT58A, by qRT-PCR. (E) Colony formation assay in adherent conditions by seeding 500 3T3 cells overexpressing either GLDC (3T3-GD) or LIN28B (3T3-28B). (F) Quantitative analysis of colony formation efficiency under adherent conditions as shown in (E). (G) Quantitative analysis of soft agar colony formation by 5,000 3T3 cells overexpressing either GLDC (3T3-GD) or LIN28B (3T3-28B). Colonies were stained with INT on day 28. (H) Proliferation curve of HLF cells overexpressing GLDC (HLF-GD), LIN28B (HLF-28B), or the empty vector (HLF). (I) Colony formation assay in adherent conditions seeding 1,000 HLF cells overexpressing GLDC (HLF-GD), LIN28B (HLF-28B), or the empty vector (HLF). (J) Quantitative analysis of colony formation efficiency under adherent conditions as shown in (I). (K) Quantitative analysis of soft agar colony formation by 5,000 HLF cells overexpressing either GLDC (HLF-GD), LIN28B (HLF-28B), or the empty vector (HLF). (L) Tumor formation by CD166 lung tumor cells 3 months after overexpression of GLDC. CD166 tumor cells from xenografts were sorted by FACS and infected with retrovirus expressing either the empty vector (CD166) or GLDC (CD166 GD), followed by transplantation into mice 24 hr after infection (n = 12 for each group). In all panels, error bars represent SEM. *p < 0.05, **p < 0.01. See also Figure S3.
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and many pyrimidines were significantly perturbed by both GLDC overexpression and knockdown (p < 0.05; Figures 5A–5D). For glycine-related metabolites, we found that sarcosine (N-methylglycine) levels increased significantly upon GLDC overexpression and dropped significantly upon GLDC knockdown, indicating that GLDC promotes sarcosine synthesis or accumulation (Figure 5A). Consistent with this observation, betaine aldehyde in the betaine-sarcosine-glycine pathway for glycine synthesis also showed the same pattern of changes (Figure 5A). Glycine levels decrease with GLDC overexpression and increase with GLDC knockdown, in agreement with the fact that GLDC breaks down glycine irreversibly. In contrast, serine levels increase with GLDC overexpression and decrease with GLDC knockdown, suggesting that GLDC promotes serine synthesis or uptake (Figure 5A). Surprisingly, GLDC perturbation also led to dramatic changes in glycolysis and other amino acids (Figures 5B, 5C, and S5A). Our data suggest that GLDC promotes glycolysis, leading to the increased synthesis or accumulation of glucose-1phosphate, phosphoenolpyruvate, pyruvate, and lactate (Figures 5B and 5C). In fact many of the upstream glycine/serine metabolism enzymes that we found upregulated in lung TICs, such as PSAT1, PSPH, and SHMT1/2, channel glycolytic intermediates into de novo serine and glycine biosynthesis (Figure 2E), suggesting that GLDC is working in a concerted fashion with these enzymes to promote the glycolysis-serine-glycine flux. This is supported by our finding that GLDC does not significantly promote glycine uptake (Figures S5B and S5C) but promotes glycolysis instead (Figures 5B and 5C). Finally, our metabolomics analysis also revealed that GLDC promotes the synthesis or accumulation of pyrimidines, including thymidine, deoxyuridine, thymine, uracil, and cytosine (Figure 5D). The GLDC-catalyzed reaction converts glycine into CH2-THF (Kume et al., 1991). CH2-THF contains the methylene group that fuels de novo thymidine synthesis from deoxyuridine in concert with pyrimidine biosynthesis and hence nucleotide synthesis during cell proliferation (Tibbetts and Appling, 2010). Recent studies suggest that early oncogenesis involves aberrant activation of cell proliferation, which then leads to a crisis of nucleotide deficiency and replication stress (Bester et al., 2011). Our observations on pyrimidine synthesis suggest that upregulation of GLDC could promote cellular transformation by overcoming this deficiency to progress onward in early oncogenesis. To test whether any of the metabolite changes induced by GLDC can mimic GLDC’s effects on cancer cells, we analyzed whether an increased exogenous supply of specific metabolites could rescue GLDC retroviral knockdown in A549 cells. We found that 10 mM of sarcosine could significantly rescue the proliferation defect upon GLDC knockdown, with little effect on control A549 cells (Figure 5F), indicating that increased sarcosine-glycine metabolite flux can rescue the effects of reduced GLDC enzyme. To further test whether the production of CH2-THF is necessary for GLDC’s effects on proliferation, we tested whether the antifolate drug methotrexate could specifically abrogate GLDC-induced proliferation by reducing the tetrahydrofolate (THF) cofactor needed to produce CH2-THF for pyrimidine synthesis. Our results show that low doses of methotrexate specifically abrogated GLDC-induced proliferation in 3T3 266 Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc.
and HLF cells, with little effect on control 3T3 and HLF cells (Figure 5E). Furthermore, methotrexate in combination with GLDC shRNA killed transformed A549 cells much more effectively than either alone (Figure 5E), suggesting that a combination of antifolates with a GLDC inhibitor could completely shut off glycine catabolism to treat cancer cells more effectively. Using these metabolic data, we constructed a model of how aberrant GLDC expression might reprogram glycolysis and glycine metabolism fluxes in cancer cells to promote cancer cell proliferation and tumorigenesis (Figure 5G). Prognostic Significance of Aberrant GLDC Expression in NSCLC Patients To assess whether our experimental findings on GLDC are relevant to human lung cancer patients in the clinic, we used tissue microarray immunohistochemistry to examine the prognostic significance of GLDC expression, tumor size, tumor grade, and cancer stage in clinical tumor samples from cohorts of NSCLC patients (n = 143) (Figures 6A and S6; Table S2). Subdistribution hazard ratio (SHR) analysis showed that patients with high or grade 3+ GLDC expression have a 3-fold higher risk of lung cancer mortality compared to patients with low or grade 0 GLDC expression, even when adjusted for cancer stage (SHR = 3.01, 95% confidence interval [CI]: 1.48–6.10, p = 0.002) (Figure 6B). Cumulative mortality analysis also showed that high GLDC expression (grade 3+) is significantly associated with higher cumulative incidence of mortality across 143 NSCLC lung cancer patients, even when adjusted for cancer stage (p = 0.005) (Figure 6C). CD166 expression was not significantly associated with higher mortality in lung cancer patients—which was not unexpected given that only 1 in 5 3 103 CD166+ cells are tumorigenic (Figures S6A–S6C). Indeed, coimmunostaining of lung tumors revealed that GLDC+ cells mostly form a subset of CD166+ cells, and that not all CD166+ cells are GLDC+ (Figures 6D and S6D). LIN28B immunohistochemistry was also not significantly correlated with lung cancer patient mortality (Figures S6A–S6C), although western blots revealed that lung TICs express a second LIN28B isoform that is indiscernible from immunohistochemistry staining, thus rendering our LIN28B staining results inconclusive (Figure S6E). Our immunohistochemistry results on clinical tumor samples are consistent with the idea that lung TICs constitute the bulk of the tumors in late stages of malignancy and demonstrate that aberrant activation of GLDC is significantly associated with human mortality in NSCLC patients—further supporting its role as a metabolic oncogene in human NSCLC. Aberrant GLDC Expression in Other Cancers To check whether aberrant GLDC expression is specific to NSCLC, we examined a variety of other cancers. Surprisingly GLDC is also aberrantly upregulated in subsets of primary tumors from other cancers, especially ovarian and germ cell tumors (Figure 7A; Table S3). Further analysis of 606 human cancer cell lines showed that 158 (26.1%) cancer cell lines overexpress GLDC, including lines from ovarian, germ cell, cervical, lung, lymphoma, prostate, bladder, and colon cancer (Figure 7B; Table S4). To test whether GLDC is also required for growth by one of these GLDC-overexpressing cell lines, we knocked
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Figure 5. Metabolomics of Cells upon GLDC Overexpression and Knockdown (A–D) Relative fold change in levels of (A) glycine-related metabolites, (B) glycolysis intermediates, and (D) pyrimidines in 3T3 cells with GLDC overexpression (3T3-GD/Ctrl), HLF cells with GLDC overexpression (HLF-GD/Ctrl), and A549 cells with GLDC knockdown (A549-GD-sh/Ctrl), as determined by LC-MS metabolomics. (C) Lactate production by 3T3 cells with GLDC overexpression or A549 cells with GLDC knockdown. (E) Effects of the antifolate drug methotrexate on colony formation after GLDC overexpression or knockdown. 3T3 and HLF cells overexpressing GLDC were plated at clonal density and exposed to varying concentrations of methotrexate for 8 days. A549 cells with GLDC knockdown were plated in soft agar at clonal density and exposed to varying concentrations of methotrexate for 14 days. (F) Effects of sarcosine on soft agar colony formation after GLDC knockdown in A549 cells. One thousand cells were seeded in soft agar at clonal density and exposed to 10 mM sarcosine for 14 days. (G) Model of metabolic flux changes induced by GLDC. In all panels, error bars represent SEM. See also Figure S5.
Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc. 267
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Figure 6. GLDC Is a Prognostic Indicator for Mortality in NSCLC Patients (A) GLDC immunohistochemistry staining in a NSCLC tumor microarray (n = 143). Representative images shown for human primary lung adenocarcinomas (AdC) immunostained with GLDC. Staining intensity grade is indicated in the upper right corner. The boxed regions in the upper images are shown at higher magnification in the lower images. Scale bar, 100 mm. (B) Subdistribution hazard ratios for each GLDC staining intensity grade, adjusted for American Joint Committee on Cancer (AJCC) staging. CI, confidence interval. (C) Cumulative incidence of lung cancer mortality adjusted for AJCC staging, for patients with each GLDC staining intensity grade. (D) Coimmunofluorescence staining of CD166 (red) and GLDC (green) on primary lung cancer patient tumors, counterstained with DAPI (blue). Representative cases with coexpression of high levels of CD166 and high levels of GLDC (left panel) and low levels of CD166 and low levels of GLDC (right panel) are shown. Higher magnification inset is shown in bottom left corner. Scale bar, 50 mm. See also Figure S6 and Table S2.
268 Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc.
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Figure 7. GLDC Is Aberrantly Expressed in Other Cancers (A) Log2-transformed fold changes in GLDC expression of patient tumors versus normal adjacent tissues across different cancers. Data are normalized and aggregated from 51 GEO datasets containing 84 sets of tumor expression data (tumor versus normal) with 2,020 tumor samples and 671 normal samples. Fold change cutoff was set at 1.5 by yellow line. (B) Normalized GLDC expression across various cancer cell lines (n = 606). Yellow line indicates the mean value (250) of GLDC expression intensities between patient lung tumors and normal lung tissues. (C) qRT-PCR for GLDC and LIN28B in CACO2 colon cancer cells expressing shRNA against GLDC (GD-sh) or LIN28B (28B-sh). (D) Proliferation curve of CACO2 cells expressing shRNA against GLDC (GD-sh) or LIN28B gene (28B-sh) described in (C). Cell numbers were measured on days 2, 4, and 6. (E) Tumor formation in mice upon injecting 2.5 3 104 CACO2 colon cancer cells with GLDC knockdown (CACO2-GD-sh) or LIN28B knockdown (CACO2-28B-sh). Mice were assessed by week 13 (n = 6). In all panels, error bars represent SEM. See also Figure S7 and Table S3 and S4.
down GLDC in CACO2 cells. Indeed we found that GLDC knockdown reduced their proliferation and tumorigenic potential upon transplantation, suggesting that GLDC may act as an oncogene in other cancer cells as well (Figures 7C–7E). To examine the possibility that GLDC is a housekeeping gene for cell proliferation, we also knocked down GLDC in normal HLFs (Figure S7A). We found that HLF proliferation was unaffected by retroviral knockdown of GLDC (Figures S7B and S7C). Furthermore we observed that GLDC is highly expressed only in a few normal tissues, including postmitotic liver cells, kidney cells, placenta cells, and olfactory bulb neurons (Figure S7D). Altogether our observations in both experimental and clinical settings suggest
that human GLDC is not a housekeeping gene required for cell proliferation but rather an oncogenic metabolic enzyme aberrantly upregulated in NSCLC and possibly several other human cancers. DISCUSSION TIC State in Lung Cancer Our work sheds new light on the nature of the TIC state and the role of metabolic reprogramming in tumorigenesis. In this study, we isolated a subpopulation of TICs from NSCLC patients using the marker CD166 and showed that both the oncogenic stem cell Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc. 269
factor LIN28B and the glycine metabolism enzyme GLDC drive the tumorigenicity of lung cancer TICs. Our data showed that CD166 enriched for TICs in primary NSCLC, and that CD166 served as an inert surface marker. In contrast, our results on CD133 are different from the results reported by Eramo et al. (2008) even though both studies used the same CD133 antibody. This is most likely due to differences in the xenotransplantation assays, which tend to underestimate the true frequency of TICs. We employed a more sensitive mouse xenotransplantation assay using NOD/SCID Il2rg/ mice instead of SCID mice, and we directly transplanted primary tumor cells with Matrigel instead of expanding the tumor cells in vitro. Previous studies have demonstrated that using a more sensitive mouse xenotransplantation assay dramatically improves our understanding of TICs (Quintana et al., 2008). Our present study supports this notion, leading us to CD166 as a new marker for the lung TIC-containing fraction. In normal physiology, CD166 is expressed predominantly during embryonic development, including the embryonic upper airway, primitive cardiac cells, and mesenchymal stem cells (Avril-Delplanque et al., 2005; Murakami et al., 2007; Hennrick et al., 2007; Sabatini et al., 2005). Expression of CD166 in the embryonic lung is consistent with our observation that CD166+ lung TICs express high levels of embryonic lung transcription factors like PEA3 and the trachealess homolog NPAS1, as well as the oncogenic stem cell factor LIN28B (Liu et al., 2003; Levesque et al., 2007; Viswanathan et al., 2009). Interestingly, mouse Lin28 is also expressed in the embryonic lung during normal development (Yang and Moss, 2003). These observations suggest that the TIC state in lung cancer is similar to the embryonic lung progenitor state in many aspects. GLDC Is a Metabolic Oncogene Our results demonstrate that multiple components in the glycine/ serine pathway are also oncogenes. In addition to embryonic lung factors, lung TICs also express high levels of GLDC, GCAT, SHMT1/2, PSPH, and PSAT1, suggesting that TICs rely on glycine/serine metabolism for tumorigenesis. Overexpression of catalytically active GLDC, as well as PSAT1, PSPH, and SHMT2, could induce cellular transformation in 3T3 cells to form tumors, whereas retroviral knockdown of GLDC significantly reduces the tumorigenicity of lung cancer cells. We further observed that GLDC+ cells mostly form a subset of CD166+ cells in lung tumors. PSAT1, PSPH, and SHMT1/2 lie upstream of GLDC in the glycine/serine pathway, diverting glycolytic flux from 3-phosphoglycerate through serine to glycine. GLDC is an oxidoreductase that catalyzes the irreversible rate-limiting step of glycine catabolism, by breaking down each glycine molecule in the glycine cleavage system to produce NADH, CO2, NH3, and CH2-THF (Kume et al., 1991). CH2-THF fuels the one-carbon/ folate metabolism pool, which in turn supplies methylene groups for biosynthesis (Tibbetts and Appling, 2010). Consistent with these facts, we found that GLDC regulates many metabolites in glycolysis and the glycine/serine pathway, leading to specific changes in pyrimidine synthesis. Pyrimidine derivatives like thymidine, in turn, are required for nucleotide synthesis in cell proliferation. Recent studies suggest that early oncogenesis 270 Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc.
involves aberrant activation of cell proliferation, which then leads to a crisis of nucleotide deficiency and replication stress (Bester et al., 2011)—a crisis that GLDC upregulation could overcome for continued progression in tumorigenesis. Interestingly, we found that GLDC also increases the levels of N-methylglycine or sarcosine, an oncometabolite implicated in prostate cancer (Sreekumar et al., 2009). Furthermore, we observed that GLDC promotes glycolysis. Combined with our findings on LIN28, which has been shown to promote glucose uptake and glycolysis (Zhu et al., 2010, 2011), GLDC might be cooperating with LIN28 as well as PSAT1, PSPH, and SHMT1/2 to divert the glycolytic flux to glycine and produce CH2-THF. These observations support the notion that the Warburg effect promotes biosynthesis for tumorigenesis (Hsu and Sabatini, 2008; Vander Heiden et al., 2009). GLDC and Glycine Metabolism Are Relevant to Human Cancer Patients From the prognostic perspective, aberrant GLDC expression is significantly correlated with the survival rates of NSCLC patients. This is consistent with the model that TIC clones expand to constitute the bulk of the tumor in advanced stages of malignancy (Boiko et al., 2010). Aberrantly increased GLDC is also widespread in many other human cancers, including lymphoma, ovarian, germ cell, cervical, prostate, bladder, and colon cancer, whereas most normal adult human tissues express very low levels of GLDC. Our experimental data further suggest that in cancers that rely on GLDC and glycine metabolism, the highly toxic antifolate drug methotrexate might be initially effective because it targets TICs, although our data suggest an even more effective chemotherapy could be potentially achieved by combining an antifolate drug with a GLDC inhibitor or by searching for a glycine cleavage complex-specific antifolate drug— much like the search for kinase-specific inhibitors in targeted cancer therapy. Our study links a glycine metabolism enzyme to lung cancer and tumorigenesis. Recently several metabolic enzymes have been linked to cancer in patients, supporting the status of metabolic reprogramming as a new hallmark of cancer (Hanahan and Weinberg, 2011). In particular, the pyruvate kinase M2 isoform PKM2, isocitrate dehydrogenase IDH1/2, and phosphoglycerate dehydrogenase PHGDH have been implicated in multiple cancers (Christofk et al., 2008; Parsons et al., 2008; Dang et al., 2009; Locasale et al., 2011; Possemato et al., 2011). Regardless of the controversy over the frequency of TICs at different stages of malignancy, our approach shows that characterizing the unique molecular basis that defines cancer cells with tumorigenic capacity may nevertheless provide novel drug targets for advancing cancer therapy. EXPERIMENTAL PROCEDURES Tumor Cell Preparation NSCLC tumors were collected from patients according to protocols approved by the Ethics Committee of the National University of Singapore. Samples were washed, dissociated, and incubated in DNase and collagenase/dispase. After incubation, cell clusters and red blood cells were removed. Then single cells were resuspended and ready for transplantation. See the Extended Experimental Procedures for more details.
Flow Cytometry A list of antibodies used can be found in Table S5. Cells were FACS-sorted using a FACSAria (BD). Flow cytometry was performed using a LSR II flow cytometer, and data were analyzed with CELLQuest Pro software (BD). Animals and Transplantation of Tumor Cells NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice (Jackson Laboratories) at 4–6 weeks old were subcutaneously transplanted with single-cell suspensions in serum-free medium and Matrigel (BD) (1:1). Tumor Sphere Culture Cells were grown in DMEM/F12 containing ITS (BD Biosciences) and supplemented with 50 ng/ml EGF and 20 ng/ml basic fibroblast growth factor (bFGF) (Invitrogen), using nontreated cell culture plates (Nunc). Fresh medium was replenished every 3 days.
(E.H.L.). We gratefully acknowledge assistance from Y.P.R. Yip, S.L. Long, and J. Xu for collection of lung tissues. We are grateful to the Biopolis Shared Facilities Histopathology Laboratory staff for their support with immunohistochemistry and image analysis. We thank Z.M. Li for assistance with making transformed breast cell lines. We greatly acknowledge V. Gaddemane, C.S. Gan, and T. Hennessy from Agilent Technologies, Singapore for their support in acquiring and analyzing the mass spectrometry data for the differential analysis of the metabolites. We thank W.L. Tam and F. McKeon for comments on the manuscript. Received: February 22, 2011 Revised: August 11, 2011 Accepted: November 17, 2011 Published online: January 5, 2012 REFERENCES
cDNA Microarray Analysis Total RNA was extracted by Trizol (Invitrogen) and purified by RNeasy Mini Kit (QIAGEN). Lung primary tumors (one patient), tumor xenografts (three patients), tumor spheres (four patients), and normal human adult lung tissues (three patients) were used. RNA was processed and hybridized to HumanRef-8 v3.0 Beadarrays (Illumina), and the microarray data were normalized and analyzed as described previously (Chua et al., 2006). A fold-change cut-off threshold of 1.5 was applied to generate the lung TIC gene signature after four comparisons: primary tumor CD166+ versus CD166 (P+/P), xenograft tumor CD166+ versus CD166 (X+/X), spheres versus xenograft tumor CD166+ (S/X+), and normal lung CD166+ versus CD166 (N+/N). After intersecting the differentially expressed genes (DEGs) of P+/P, X+/X, and S/X+ and excluding DEGs intersecting with N+/N, DAVID Bioinformatics Resources 6.7 was applied for KEGG pathway analysis of the final list of DEGs (Huang et al., 2009). Metabolomics Metabolites were extracted by centrifugation of culture media at 14,000 rpm for 30 min at 4 C. Metabolomic profiling was performed through UPLC/MS using a Zorbax Eclipse Plus-C18 column on the Agilent 1200 RRLC and an Agilent 6530 Accurate Mass QTOF. Mass spectrometry was performed on an Agilent 6530 Accurate Mass Q-TOF mass spectrometer operating in positive ion mode with 2 GHz extended dynamic range mode. See Extended Experimental Procedures for more details. Statistical Analysis Differences were compared using two-tailed Student’s t test. p values < 0.05 were considered statistically significant. All analyses were performed with SPSS 18.0 (SPSS). Lung TIC frequencies were estimated using ELDA software (Hu and Smyth, 2009). Fisher’s exact test was used to assess the association between GLDC, CD166, or LIN28B and clinicopathological parameters. The effect of GLDC, CD166, or LIN28B expressions on lung cancer mortality was modeled using competing risks regression and quantified based on the SHR (Fine and Gray, 1999). ACCESSION NUMBERS The GEO accession number for human datasets is GSE33198.
Avril-Delplanque, A., Casal, I., Castillon, N., Hinnrasky, J., Puchelle, E., and Pe´ault, B. (2005). Aquaporin-3 expression in human fetal airway epithelial progenitor cells. Stem Cells 23, 992–1001. Bester, A.C., Roniger, M., Oren, Y.S., Im, M.M., Sarni, D., Chaoat, M., Bensimon, A., Zamir, G., Shewach, D.S., and Kerem, B. (2011). Nucleotide deficiency promotes genomic instability in early stages of cancer development. Cell 145, 435–446. Boiko, A.D., Razorenova, O.V., van de Rijn, M., Swetter, S.M., Johnson, D.L., Ly, D.P., Butler, P.D., Yang, G.P., Joshua, B., Kaplan, M.J., et al. (2010). Human melanoma-initiating cells express neural crest nerve growth factor receptor CD271. Nature 466, 133–137. Christofk, H.R., Vander Heiden, M.G., Harris, M.H., Ramanathan, A., Gerszten, R.E., Wei, R., Fleming, M.D., Schreiber, S.L., and Cantley, L.C. (2008). The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature 452, 230–233. Chua, S.W., Vijayakumar, P., Nissom, P.M., Yam, C.Y., Wong, V.V.T., and Yang, H. (2006). A novel normalization method for effective removal of systematic variation in microarray data. Nucleic Acids Res. 34, e38. Civenni, G., Walter, A., Kobert, N., Mihic-Probst, D., Zipser, M., Belloni, B., Seifert, B., Moch, H., Dummer, R., van den Broek, M., and Sommer, L. (2011). Human CD271-positive melanoma stem cells associated with metastasis establish tumor heterogeneity and long-term growth. Cancer Res. 71, 3098–3109. Curtis, S.J., Sinkevicius, K.W., Li, D.A., Lau, A.N., Roach, R.R., Zamponi, R., Woolfenden, A.E., Kirsch, D.G., Wong, K.K., and Kim, C.F. (2010). Primary tumor genotype is an important determinant in identification of lung cancer propagating cells. Cell Stem Cell 7, 127–133. Dang, L., White, D.W., Gross, S., Bennett, B.D., Bittinger, M.A., Driggers, E.M., Fantin, V.R., Jang, H.G., Jin, S., Keenan, M.C., et al. (2009). Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature 462, 739–744. Dontu, G., Abdallah, W.M., Foley, J.M., Jackson, K.W., Clarke, M.F., Kawamura, M.J., and Wicha, M.S. (2003). In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells. Genes Dev. 17, 1253– 1270.
SUPPLEMENTAL INFORMATION
Eramo, A., Lotti, F., Sette, G., Pilozzi, E., Biffoni, M., Di Virgilio, A., Conticello, C., Ruco, L., Peschle, C., and De Maria, R. (2008). Identification and expansion of the tumorigenic lung cancer stem cell population. Cell Death Differ. 15, 504–514.
Supplemental Information includes Extended Experimental Procedures, seven figures, and six tables and can be found with this article online at doi:10.1016/ j.cell.2011.11.050.
Fine, J.P., and Gray, R.J. (1999). A proportional hazards model for the subdistribution of a competing risk. J. Am. Stat. Assoc. 94, 496–509.
ACKNOWLEDGMENTS
Hanahan, D., and Weinberg, R.A. (2011). Hallmarks of cancer: the next generation. Cell 144, 646–674.
This work is supported by grants from Biomedical Research Council (BMRC) and Agency for Science, Technology and Research (A*STAR) (B.L.) and grants from the Singapore Cancer Syndicate and Singapore Lung Cancer Consortium
Hennrick, K.T., Keeton, A.G., Nanua, S., Kijek, T.G., Goldsmith, A.M., Sajjan, U.S., Bentley, J.K., Lama, V.N., Moore, B.B., Schumacher, R.E., et al. (2007). Lung cells from neonates show a mesenchymal stem cell phenotype. Am. J. Respir. Crit. Care Med. 175, 1158–1164.
Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc. 271
Hsu, P.P., and Sabatini, D.M. (2008). Cancer cell metabolism: Warburg and beyond. Cell 134, 703–707. Hu, Y.F., and Smyth, G.K. (2009). ELDA: extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays. J. Immunol. Methods 347, 70–78. Huang, W., Sherman, B.T., and Lempicki, R.A. (2009). Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57. Ishizawa, K., Rasheed, Z.A., Karisch, R., Wang, Q.J., Kowalski, J., Susky, E., Pereira, K., Karamboulas, C., Moghal, N., Rajeshkumar, N.V., et al. (2010). Tumor-initiating cells are rare in many human tumors. Cell Stem Cell 7, 279–282. Jemal, A., Bray, F., Center, M.M., Ferlay, J., Ward, E., and Forman, D. (2011). Global cancer statistics. CA Cancer J. Clin. 61, 69–90. Kume, A., Koyata, H., Sakakibara, T., Ishiguro, Y., Kure, S., and Hiraga, K. (1991). The glycine cleavage system. Molecular cloning of the chicken and human glycine decarboxylase cDNAs and some characteristics involved in the deduced protein structures. J. Biol. Chem. 266, 3323–3329. Kure, S., Kato, K., Dinopoulos, A., Gail, C., DeGrauw, T.J., Christodoulou, J., Bzduch, V., Kalmanchey, R., Fekete, G., Trojovsky, A., et al. (2006). Comprehensive mutation analysis of GLDC, AMT, and GCSH in nonketotic hyperglycinemia. Hum. Mutat. 27, 343–352. Levesque, B.M., Zhou, S.T., Shan, L., Johnston, P., Kong, Y.P., Degan, S., and Sunday, M.E. (2007). NPAS1 regulates branching morphogenesis in embryonic lung. Am. J. Respir. Cell Mol. Biol. 36, 427–434. Liu, Y.R., Jiang, H.Y., Crawford, H.C., and Hogan, B.L.M. (2003). Role for ETS domain transcription factors Pea3/Erm in mouse lung development. Dev. Biol. 261, 10–24. Locasale, J.W., Grassian, A.R., Melman, T., Lyssiotis, C.A., Mattaini, K.R., Bass, A.J., Heffron, G., Metallo, C.M., Muranen, T., Sharfi, H., et al. (2011). Phosphoglycerate dehydrogenase diverts glycolytic flux and contributes to oncogenesis. Nat. Genet. 43, 869–874. Murakami, Y., Hirata, H., Miyamoto, Y., Nagahashi, A., Sawa, Y., Jakt, M., Asahara, T., and Kawamata, S. (2007). Isolation of cardiac cells from E8.5 yolk sac by ALCAM (CD166) expression. Mech. Dev. 124, 830–839. Nakai, T., Nakagawa, N., Maoka, N., Masui, R., Kuramitsu, S., and Kamiya, N. (2005). Structure of P-protein of the glycine cleavage system: implications for nonketotic hyperglycinemia. EMBO J. 24, 1523–1536. Parsons, D.W., Jones, S., Zhang, X.S., Lin, J.C.H., Leary, R.J., Angenendt, P., Mankoo, P., Carter, H., Siu, I.M., Gallia, G.L., et al. (2008). An integrated genomic analysis of human glioblastoma multiforme. Science 321, 1807– 1812. Possemato, R., Marks, K.M., Shaul, Y.D., Pacold, M.E., Kim, D., Birsoy, K., Sethumadhavan, S., Woo, H.K., Jang, H.G., Jha, A.K., et al. (2011). Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature 476, 346–350. Quintana, E., Shackleton, M., Sabel, M.S., Fullen, D.R., Johnson, T.M., and Morrison, S.J. (2008). Efficient tumour formation by single human melanoma cells. Nature 456, 593–598.
272 Cell 148, 259–272, January 20, 2012 ª2012 Elsevier Inc.
Quintana, E., Shackleton, M., Foster, H.R., Fullen, D.R., Sabel, M.S., Johnson, T.M., and Morrison, S.J. (2010). Phenotypic heterogeneity among tumorigenic melanoma cells from patients that is reversible and not hierarchically organized. Cancer Cell 18, 510–523. Reya, T., Morrison, S.J., Clarke, M.F., and Weissman, I.L. (2001). Stem cells, cancer, and cancer stem cells. Nature 414, 105–111. Rosen, J.M., and Jordan, C.T. (2009). The increasing complexity of the cancer stem cell paradigm. Science 324, 1670–1673. Sabatini, F., Petecchia, L., Tavian, M., Jodon de Villeroche´, V., Rossi, G.A., and Brouty-Boye´, D. (2005). Human bronchial fibroblasts exhibit a mesenchymal stem cell phenotype and multilineage differentiating potentialities. Lab. Invest. 85, 962–971. Sequist, L.V., Joshi, V.A., Ja¨nne, P.A., Muzikansky, A., Fidias, P., Meyerson, M., Haber, D.A., Kucherlapati, R., Johnson, B.E., and Lynch, T.J. (2007). Response to treatment and survival of patients with non-small cell lung cancer undergoing somatic EGFR mutation testing. Oncologist 12, 90–98. Sreekumar, A., Poisson, L.M., Rajendiran, T.M., Khan, A.P., Cao, Q., Yu, J.D., Laxman, B., Mehra, R., Lonigro, R.J., Li, Y., et al. (2009). Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 457, 910–914. Tibbetts, A.S., and Appling, D.R. (2010). Compartmentalization of mammalian folate-mediated one-carbon metabolism. Annu. Rev. Nutr. 30, 57–81. Vander Heiden, M.G., Cantley, L.C., and Thompson, C.B. (2009). Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324, 1029–1033. Vander Heiden, M.G., Locasale, J.W., Swanson, K.D., Sharfi, H., Heffron, G.J., Amador-Noguez, D., Christofk, H.R., Wagner, G., Rabinowitz, J.D., Asara, J.M., and Cantley, L.C. (2010). Evidence for an alternative glycolytic pathway in rapidly proliferating cells. Science 329, 1492–1499. Viswanathan, S.R., Powers, J.T., Einhorn, W., Hoshida, Y., Ng, T.L., Toffanin, S., O’Sullivan, M., Lu, J., Phillips, L.A., Lockhart, V.L., et al. (2009). Lin28 promotes transformation and is associated with advanced human malignancies. Nat. Genet. 41, 843–848. Vogelstein, B., and Kinzler, K.W. (2004). Cancer genes and the pathways they control. Nat. Med. 10, 789–799. Warburg, O. (1956). On the origin of cancer cells. Science 123, 309–314. Yang, D.H., and Moss, E.G. (2003). Temporally regulated expression of Lin-28 in diverse tissues of the developing mouse. Gene Expr. Patterns 3, 719–726. Zhu, H., Shah, S., Shyh-Chang, N., Shinoda, G., Einhorn, W.S., Viswanathan, S.R., Takeuchi, A., Grasemann, C., Rinn, J.L., Lopez, M.F., et al. (2010). Lin28a transgenic mice manifest size and puberty phenotypes identified in human genetic association studies. Nat. Genet. 42, 626–630. Zhu, H., Shyh-Chang, N., Segre`, A.V., Shinoda, G., Shah, S.P., Einhorn, W.S., Takeuchi, A., Engreitz, J.M., Hagan, J.P., Kharas, M.G., et al; DIAGRAM Consortium; MAGIC Investigators. (2011). The Lin28/let-7 axis regulates glucose metabolism. Cell 147, 81–94.