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Rewired Metabolism in Drug-resistant Leukemia Cells

A METABOLIC SWITCH HALLMARKED BY REDUCED DEPENDENCE ON EXOGENOUS GLUTAMINE*
  • Claudia Stäubert
    Footnotes
    Affiliations
    From the Department of Molecular Biology, Umeå University, 90187 Umeå, Sweden, the

    Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden, the

    Institute of Biochemistry, Faculty of Medicine, University of Leipzig, 04103 Leipzig, Germany
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  • Hasanuzzaman Bhuiyan
    Footnotes
    Affiliations
    Departments of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, 17177 Stockholm, Sweden, and the
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  • Anna Lindahl
    Affiliations
    Departments of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, 17177 Stockholm, Sweden, and the
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  • Oliver Jay Broom
    Affiliations
    From the Department of Molecular Biology, Umeå University, 90187 Umeå, Sweden, the
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  • Yafeng Zhu
    Affiliations
    Departments of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, 17177 Stockholm, Sweden, and the
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  • Saiful Islam
    Affiliations
    the Departments of Medical Biochemistry and Biophysics, Science for Life Laboratory, Karolinska Institutet, 17177 Stockholm, Sweden
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  • Sten Linnarsson
    Affiliations
    the Departments of Medical Biochemistry and Biophysics, Science for Life Laboratory, Karolinska Institutet, 17177 Stockholm, Sweden
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  • Janne Lehtiö
    Affiliations
    Departments of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, 17177 Stockholm, Sweden, and the
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  • Anders Nordström
    Correspondence
    To whom correspondence should be addressed: Dept. Molecular Biology, SE-90187 Umeå, Sweden. Tel: 46-90-785-25-61; Fax: 090-77-26-30;
    Affiliations
    From the Department of Molecular Biology, Umeå University, 90187 Umeå, Sweden, the

    Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden, the

    Departments of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, 17177 Stockholm, Sweden, and the
    Search for articles by this author
  • Author Footnotes
    * This work was supported by Swedish Research Council Grants 2007-5143 (to A. N.) and 2012-5145 (to J. L.), grants from the Erling-Persson family foundation (to Umeå University), the Swedish Foundation for Strategic Research (to A. N.), the Swedish Cancer Society (to J. L.), and Jane and Dan Olsson Foundation (to A. N.).
    This article contains supplemental Table S1.
    1 Both authors should be considered joint first authors.
Open AccessPublished:February 19, 2015DOI:https://doi.org/10.1074/jbc.M114.618769
      Cancer cells that escape induction therapy are a major cause of relapse. Understanding metabolic alterations associated with drug resistance opens up unexplored opportunities for the development of new therapeutic strategies. Here, we applied a broad spectrum of technologies including RNA sequencing, global untargeted metabolomics, and stable isotope labeling mass spectrometry to identify metabolic changes in P-glycoprotein overexpressing T-cell acute lymphoblastic leukemia (ALL) cells, which escaped a therapeutically relevant daunorubicin treatment. We show that compared with sensitive ALL cells, resistant leukemia cells possess a fundamentally rewired central metabolism characterized by reduced dependence on glutamine despite a lack of expression of glutamate-ammonia ligase (GLUL), a higher demand for glucose and an altered rate of fatty acid β-oxidation, accompanied by a decreased pantothenic acid uptake capacity. We experimentally validate our findings by selectively targeting components of this metabolic switch, using approved drugs and starvation approaches followed by cell viability analyses in both the ALL cells and in an acute myeloid leukemia (AML) sensitive/resistant cell line pair. We demonstrate how comparative metabolomics and RNA expression profiling of drug-sensitive and -resistant cells expose targetable metabolic changes and potential resistance markers. Our results show that drug resistance is associated with significant metabolic costs in cancer cells, which could be exploited using new therapeutic strategies.

      Introduction

      Cancer is a clonal disease progressively producing new subclones displaying altered phenotypic and cytogenetic traits with selection for those that confer growth advantages under specific circumstances (
      • Mullighan C.G.
      • Phillips L.A.
      • Su X.
      • Ma J.
      • Miller C.B.
      • Shurtleff S.A.
      • Downing J.R.
      Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia.
      ,
      • Haffner M.C.
      • Mosbruger T.
      • Esopi D.M.
      • Fedor H.
      • Heaphy C.M.
      • Walker D.A.
      • Adejola N.
      • Gürel M.
      • Hicks J.
      • Meeker A.K.
      • Halushka M.K.
      • Simons J.W.
      • Isaacs W.B.
      • De Marzo A.M.
      • Nelson W.G.
      • Yegnasubramanian S.
      Tracking the clonal origin of lethal prostate cancer.
      • Clappier E.
      • Gerby B.
      • Sigaux F.
      • Delord M.
      • Touzri F.
      • Hernandez L.
      • Ballerini P.
      • Baruchel A.
      • Pflumio F.
      • Soulier J.
      Clonal selection in xenografted human T cell acute lymphoblastic leukemia recapitulates gain of malignancy at relapse.
      ). Consequently, under therapeutic pressure, following the principles of natural selection, cancer cell populations that are most adaptive or resistant to treatment will be selected for, resulting in relapsing disease often associated with a worse prognosis (
      • Mullighan C.G.
      • Phillips L.A.
      • Su X.
      • Ma J.
      • Miller C.B.
      • Shurtleff S.A.
      • Downing J.R.
      Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia.
      ,
      • Zahreddine H.
      • Borden K.L.
      Mechanisms and insights into drug resistance in cancer.
      ,
      • Greaves M.
      • Maley C.C.
      Clonal evolution in cancer.
      ). Relapse is commonly accompanied by overexpression of the ATP-binding cassette transporter ABCB1 gene product, P-glycoprotein (P-gp)
      The abbreviations used are: P-gp
      P-glycoprotein
      ALL
      acute lymphoblastic leukemia
      AML
      acute myeloid leukemia
      CCS
      charcoal:dextran-stripped fetal bovine serum
      CPT
      carnitine palmitoyltransferase
      DNR
      daunorubicin
      FAO
      fatty acid β-oxidation
      PA
      pantothenic acid
      RNAseq
      RNA sequencing
      TCA
      tricarboxylic acid
      GLUL
      glutamate-ammonia ligase
      PCCB
      propionyl-CoA carboxylase.
      (multidrug resistance protein 1) (
      • Styczynski J.
      • Wysocki M.
      • Debski R.
      • Czyzewski K.
      • Kolodziej B.
      • Rafinska B.
      • Kubicka M.
      • Koltan S.
      • Koltan A.
      • Pogorzala M.
      • Kurylak A.
      • Olszewska-Slonina D.
      • Balwierz W.
      • Juraszewska E.
      • Wieczorek M.
      • Olejnik I.
      • Krawczuk-Rybak M.
      • Kuzmicz M.
      • Kowalczyk J.
      • Stefaniak J.
      • Badowska W.
      • Sonta-Jakimczyk D.
      • Szczepanski T.
      • Matysiak M.
      • Malinowska I.
      • Stanczak E.
      • Wachowiak J.
      • Konatkowska B.
      • Gil L.
      • Balcerska A.
      • Maciejka-Kapuscinska L.
      Predictive value of multidrug resistance proteins and cellular drug resistance in childhood relapsed acute lymphoblastic leukemia.
      ), a drug efflux pump that is a marker for both tumor resistance to chemotherapy and a more aggressive phenotype (
      • Borst P.
      • Schinkel A.H.
      P-glycoprotein ABCB1: a major player in drug handling by mammals.
      ,
      • Chen K.G.
      • Sikic B.I.
      Molecular pathways: regulation and therapeutic implications of multidrug resistance.
      • Amiri-Kordestani L.
      • Basseville A.
      • Kurdziel K.
      • Fojo A.T.
      • Bates S.E.
      Targeting MDR in breast and lung cancer: discriminating its potential importance from the failure of drug resistance reversal studies.
      ). However, P-gp inhibition has been unsuccessful in clinical trials (
      • Borst P.
      • Schinkel A.H.
      P-glycoprotein ABCB1: a major player in drug handling by mammals.
      ,
      • Chen K.G.
      • Sikic B.I.
      Molecular pathways: regulation and therapeutic implications of multidrug resistance.
      ) so it is imperative to identify other targetable molecular mechanisms that are essential for cells with a drug-resistant phenotype to improve the prognosis of relapsing leukemia.
      Metabolic alterations are part of oncogenesis and tumor progression (
      • Galluzzi L.
      • Kepp O.
      • Vander Heiden M.G.
      • Kroemer G.
      Metabolic targets for cancer therapy.
      ), and cancer cell metabolism has therefore attracted interest as a target for therapeutic intervention (
      • Carracedo A.
      • Cantley L.C.
      • Pandolfi P.P.
      Cancer metabolism: fatty acid oxidation in the limelight.
      ,
      • Clendening J.W.
      • Penn L.Z.
      Targeting tumor cell metabolism with statins.
      • Muñoz-Pinedo C.
      • El Mjiyad N.
      • Ricci J.E.
      Cancer metabolism: current perspectives and future directions.
      ). It is assumed that the development of drug resistance in cancer cells is accompanied by metabolic alterations that may be therapeutically targetable (
      • Zhao Y.
      • Butler E.B.
      • Tan M.
      Targeting cellular metabolism to improve cancer therapeutics.
      ).
      So far, only a few studies have analyzed the adaptations of cellular cancer metabolism in a resistance context. One of these studies showed metabolic rewiring to be essential in a lapatinib-resistant breast cancer cell line (
      • Castro-Perez J.M.
      • Roddy T.P.
      • Shah V.
      • McLaren D.G.
      • Wang S.P.
      • Jensen K.
      • Vreeken R.J.
      • Hankemeier T.
      • Johns D.G.
      • Previs S.F.
      • Hubbard B.K.
      Identifying static and kinetic lipid phenotypes by high resolution UPLC-MS: unraveling diet-induced changes in lipid homeostasis by coupling metabolomics and fluxomics.
      ). Another used computational analyses of transcriptomic and metabolomic data on 59 cell lines from different types of cancer to identify a metabolic consensus phenotype associated with tumor cell chemosensitivity to platinum-based drugs (
      • Araki Y.
      • Andoh A.
      • Tsujikawa T.
      • Fujiyama Y.
      • Bamba T.
      Alterations in intestinal microflora, faecal bile acids and short chain fatty acids in dextran sulphate sodium-induced experimental acute colitis in rats.
      ).
      However, due to the heterogeneity of tumors, merely identifying therapeutic opportunities is not sufficient; it is also necessary to develop methods for predicting which patients will benefit from specific therapeutic regimes. Transcriptional and metabolic changes associated with disease states can be detected using omics technologies, leading to the identification of combinations of prognostic markers such as oncometabolites and transcriptionally regulated metabolic networks. Such indicators could potentially be used to determine when it may be beneficial to treat a particular cancer patient with a drug or drug mixture that is normally used to manage other disease conditions. For example, they may indicate that it would be helpful to treat a patient with fibrates, which are used to reduce blood cholesterol and triglyceride levels (
      • Oosterveer M.H.
      • Grefhorst A.
      • van Dijk T.H.
      • Havinga R.
      • Staels B.
      • Kuipers F.
      • Groen A.K.
      • Reijngoud D.J.
      Fenofibrate simultaneously induces hepatic fatty acid oxidation, synthesis, and elongation in mice.
      ).
      Our combined approach of transcriptomic and metabolomic profiling revealed a central metabolic switch that occurs in daunorubicin (DNR)-resistant P-gp overexpressing leukemia cells. Compared with DNR-sensitive cells, the resistant cells are more dependent on glucose but less dependent on glutamine and fatty acids. We demonstrate how knowledge gained from combined transcriptomic and metabolomic analyses can be exploited to develop new induction treatment strategies involving drugs approved for unrelated indications with relatively low toxicity, which at relevant concentrations, sensitize resistant leukemia cells to DNR treatment.

      DISCUSSION

      To identify and characterize metabolic shifts associated with drug resistance, which could serve as potential markers or targets for individualized therapy, we applied an aggressive selection strategy to obtain a cancerous ALL cell fraction designated CEM/R2 that was capable of tolerating exposure to a clinically relevant DNR concentration (Fig. 1, A and B). We studied these DNR-resistant, P-gp overexpressing ALL cells using global transcriptional and metabolic profiling approaches. From the resulting data, we generated hypotheses regarding the metabolic vulnerability of the resistant cells. Finally, we tested the validity and generality of our hypotheses by performing cell viability assays in both the CEM/R2 cells and a P-gp overexpressing DNR-resistant AML cell line. Our results are summarized graphically in Fig. 6.
      Figure thumbnail gr6
      FIGURE 6.The metabolic rewiring of resistant leukemia cells. Resistant cells depend more on glycolysis and TCA but less on FAO and glutaminolysis. A reduced pantothenic acid uptake capacity might be central to this phenotype because of the importance of PA in allowing cells to maintain adequate CoA levels. The loss of DNAJC15 expression might also reflect a pro-survival signal mediated through a mitochondrial uncoupling mechanism. Green, up-regulated/activation. Red, down-regulated/inhibition.
      RNAseq analyses revealed that transcripts of three genes were present in CEM but not in CEM/R2 cells (supplemental Table S1). One of these genes was DNAJC15, which encodes a methylation-controlled J protein belonging to the HSP40 family. Loss of expression of this protein has been implicated in de novo chemoresistance in ovarian cancer (
      • Shridhar V.
      • Bible K.C.
      • Staub J.
      • Avula R.
      • Lee Y.K.
      • Kalli K.
      • Huang H.
      • Hartmann L.C.
      • Kaufmann S.H.
      • Smith D.I.
      Loss of expression of a new member of the DNAJ protein family confers resistance to chemotherapeutic agents used in the treatment of ovarian cancer.
      ), whereas its overexpression in an ovarian cancer cell line yielded improved chemosensitivity (
      • Witham J.
      • Vidot S.
      • Agarwal R.
      • Kaye S.B.
      • Richardson A.
      Transient ectopic expression as a method to detect genes conferring drug resistance.
      ). Ovarian and breast cancer patients exposed to continuous chemotherapy exhibited lower levels of DNAJC15 protein and enhanced drug resistance (
      • Strathdee G.
      • Davies B.R.
      • Vass J.K.
      • Siddiqui N.
      • Brown R.
      Cell type-specific methylation of an intronic CpG island controls expression of the MCJ gene.
      ,
      • Lindsey J.C.
      • Lusher M.E.
      • Strathdee G.
      • Brown R.
      • Gilbertson R.J.
      • Bailey S.
      • Ellison D.W.
      • Clifford S.C.
      Epigenetic inactivation of MCJ (DNAJD1) in malignant paediatric brain tumours.
      ). In addition, loss of DNAJC15 has been associated with P-gp overexpression and can modulate cellular responses to altered metabolic conditions by enhancing mitochondrial respiration (
      • Hatle K.M.
      • Gummadidala P.
      • Navasa N.
      • Bernardo E.
      • Dodge J.
      • Silverstrim B.
      • Fortner K.
      • Burg E.
      • Suratt B.T.
      • Hammer J.
      • Radermacher M.
      • Taatjes D.J.
      • Thornton T.
      • Anguita J.
      • Rincon M.
      MCJ/DnaJC15, an endogenous mitochondrial repressor of the respiratory chain that controls metabolic alterations.
      ,
      • Hatle K.M.
      • Neveu W.
      • Dienz O.
      • Rymarchyk S.
      • Barrantes R.
      • Hale S.
      • Farley N.
      • Lounsbury K.M.
      • Bond J.P.
      • Taatjes D.
      • Rincón M.
      Methylation-controlled J protein promotes c-Jun degradation to prevent ABCB1 transporter expression.
      ). Transcripts encoding the DENN/MADD domain containing 2D protein (DENND2D) were also detected in CEM but not CEM/R2 cells. Little is known about the biochemical function of the DENND2D gene product. However, DENND2D overexpression suppressed the proliferation of non-small cell lung cancer cells in vitro and in vivo by inducing apoptosis (
      • Ling B.
      • Zheng H.
      • Fu G.
      • Yuan J.
      • Shi T.
      • Chen S.
      • Liu Y.
      • Liu Y.
      • Cao Y.
      • Zheng S.
      • Guo S.
      • Han N.
      • Gao Y.
      • Cheng S.
      • Zhang K.
      Suppression of non-small cell lung cancer proliferation and tumorigenicity by DENND2D.
      ), implying that its non-expression in the CEM/R2 cells may represent the loss of a tumor suppressing protein. In keeping with this suggestion, it has been proposed that DENND2D could be a useful marker for predicting the progression and early recurrence of all types of gastric cancer (
      • Kanda M.
      • Shimizu D.
      • Nomoto S.
      • Takami H.
      • Hibino S.
      • Oya H.
      • Hashimoto R.
      • Suenaga M.
      • Inokawa Y.
      • Kobayashi D.
      • Tanaka C.
      • Yamada S.
      • Fujii T.
      • Nakayama G.
      • Sugimoto H.
      • Koike M.
      • Fujiwara M.
      • Kodera Y.
      Prognostic impact of expression and methylation status of DENN/MADD domain-containing protein 2D in gastric cancer.
      ). Finally, GLUL transcripts were only detected in CEM cells. Increased glutaminolysis relative to normal proliferating cells is a key characteristic of proliferating cancer cells (
      • Zhao Y.
      • Butler E.B.
      • Tan M.
      Targeting cellular metabolism to improve cancer therapeutics.
      ,
      • Daye D.
      • Wellen K.E.
      Metabolic reprogramming in cancer: unraveling the role of glutamine in tumorigenesis.
      ). However, although CEM/R2 cells lack GLUL transcripts and exhibit reduced levels of transcripts for the glutamine metabolism genes ASNS, ASS1, and the glutamine transporter gene SLC1A5, it appears that they are less dependent on glutamine metabolism than non-resistant CEM cells (Fig. 2, A and B). This hypothesis was supported by the resistant CEM/R2 and HL60/R10 cell lines' decreased dependence of exogenous glutamine for proliferation (Fig. 2, B and C). Increased GLUL expression was reported to be a prognostic factor predicting a reduced risk of relapse in pre-B ALL (
      • Hoffmann K.
      • Firth M.J.
      • Beesley A.H.
      • Freitas J.R.
      • Ford J.
      • Senanayake S.
      • de Klerk N.H.
      • Baker D.L.
      • Kees U.R.
      Prediction of relapse in paediatric pre-B acute lymphoblastic leukaemia using a three-gene risk index.
      ); conversely, glutamine-independent breast cancer cells were associated with increased expression of mesenchymal markers, a more aggressive mouse xenograft phenotype and resistance to chemotherapeutics (
      • Singh B.
      • Tai K.
      • Madan S.
      • Raythatha M.R.
      • Cady A.M.
      • Braunlin M.
      • Irving L.R.
      • Bajaj A.
      • Lucci A.
      Selection of metastatic breast cancer cells based on adaptability of their metabolic state.
      ). Furthermore, silencing of glutaminase, which catalyzes the first step in glutamine-dependent TCA anaplerosis, induced pyruvate carboxylase activity, demonstrating that glutamine metabolism and glycolysis are linked (
      • Cheng T.
      • Sudderth J.
      • Yang C.
      • Mullen A.R.
      • Jin E.S.
      • Matés J.M.
      • DeBerardinis R.J.
      Pyruvate carboxylase is required for glutamine-independent growth of tumor cells.
      ). These reports paired with our experimental evidence (Figs. 2, B and C, and 4, A and B) strongly support an increased dependence on glycolysis in the resistant cells and prompt us to suggest that reductions in GLUL expression and glutamine dependence may reflect a more general adaptation based on metabolic rewiring that accompanies drug resistance in cancer cells.
      The results presented herein provide considerable evidence for such metabolic rewiring in resistant cells, including the detected up-regulation of ALDOC transcripts in CEM/R2 cells (Fig. 2A), their slightly increased intracellular lactate levels (Fig. 3A), and their higher sensitivity to glucose depletion (Fig. 4A), all of which suggest a higher rate of glycolysis compared with drug-sensitive CEM cells. In addition, CEM/R2 cells exhibited down-regulation of transcripts involved in FAO, namely ACCA2 and PCCB (Fig. 2A), and reduced levels of palmitate, oleate, and short-chain acyl carnitines. This suggests that the drug-resistant cells have a lower rate of FAO and/or branched-chain amino acid metabolism than their sensitive counterparts (Fig. 3A). In general, carnitines are involved in the transport of fatty acids into the mitochondria. Reductions in their abundance could thus reflect a decreased fatty acid metabolism caused by a lower capability to transport fatty acyl residues inside the mitochondria, implying a reduction in the FAO rate in CEM/R2 cells.
      We analyzed the effect of glucose deprivation on CEM and CEM/R2 as well as HL60 and HL60/R10 cells, revealing that both resistant leukemia cell lines are more heavily affected by glucose removal than their sensitive counterparts (Fig. 4, A and B). Further experimental evidence for a greater FAO dependence in the drug-sensitive CEM cells was provided by the observation of their greater sensitivity to the CPT inhibitor perhexiline (Fig. 4C). CPT-1/2 are responsible for transporting acyl-carnitines into the mitochondria, so enhanced sensitivity to CPT inhibition is likely to reflect a higher demand for fatty acyl residues in the mitochondria. In contrast, perhexiline affected HL60/R10 proliferation but had no effect on HL60 cells (Fig. 4D). This is consistent with the increased levels of carnitines and decreased content of 3-hydroxyadipic acid detected in HL60/R10 compared with HL60 cells (Fig. 3B), suggesting that the former have a higher rate of FAO. It is possible that the concentrations of FAO intermediates or metabolites originating from FAO (e.g. 3-hydroxy fatty acids, dioic fatty acids, and carnitines) in tumor-derived cancer cells could serve as indicators or biomarkers for the usefulness of FAO-inhibiting adjuvant therapies.
      One remarkable difference between the metabolic profiles for CEM and CEM/R2 cells was that the latter exhibited greatly reduced intracellular levels of pantothenic acid, a nutritionally essential substance and precursor of CoA (Fig. 3). We were able to show that this was due to a reduced capacity for PA uptake, which results in a lower intracellular CoA synthesis rate and may represent a metabolic weakness that could provide a therapeutic window (Fig. 5A). This hypothesis was supported by the following experimental observations. First, the peroxisome proliferator-activated receptor α-activating drug fenofibrate, which increases the rates of FAO and fatty acid synthesis (
      • Oosterveer M.H.
      • Grefhorst A.
      • van Dijk T.H.
      • Havinga R.
      • Staels B.
      • Kuipers F.
      • Groen A.K.
      • Reijngoud D.J.
      Fenofibrate simultaneously induces hepatic fatty acid oxidation, synthesis, and elongation in mice.
      ) and is used to reduce blood cholesterol, affected CEM/R2 cell proliferation at lower doses than CEM (Fig. 5B). Second, reducing the availability of pantothenic acid increased the sensitivity of CEM/R2 cells to both fenofibrate and DNR treatment (Fig. 5, G and H). Fenofibrate has been proposed as an anti-cancer agent acting via an anti-angiogenesis mechanism (
      • Panigrahy D.
      • Kaipainen A.
      • Huang S.
      • Butterfield C.E.
      • Barnés C.M.
      • Fannon M.
      • Laforme A.M.
      • Chaponis D.M.
      • Folkman J.
      • Kieran M.W.
      PPARα agonist fenofibrate suppresses tumor growth through direct and indirect angiogenesis inhibition.
      ). Our findings suggest it also acts on cancer cells by accelerating acetyl-CoA consumption and thereby perturbing fatty acid/sterol metabolism. Thus, PA uptake and/or metabolism may provide a therapeutic window that could be exploited via dietary restriction of vitamin B5 or inhibition of PA uptake/CoA metabolism. Finally, CEM cell proliferation was not affected by perhexiline treatment when CEM cells were grown in PA-restricted medium, suggesting that they retain the ability to switch away from FAO when the availability of PA is low, which was not observed for CEM/R2 cells (Fig. 5, E and F).
      In summary, we have shown that combining transcriptomic and metabolomic data with experimental validation of hypotheses generated from the omics data sets is a powerful way of interrogating complex biological systems. We demonstrate that the central metabolism of P-gp overexpressing, DNR-resistant leukemia cells is fundamentally rewired. The key metabolic traits of these resistant cells are a reduced dependence on glutamine, a lower rate of FAO, and a higher demand for glucose accompanied by a decreased pantothenic acid uptake capacity (Fig. 6). However, it remains unclear whether the rewired metabolism is a cause or effect of the acquired resistance. A better understanding of the metabolic cost of resistance could guide the discovery of therapy selection biomarkers and the development of new therapeutic strategies, thereby potentially giving old drugs new tasks.

      REFERENCES

        • Mullighan C.G.
        • Phillips L.A.
        • Su X.
        • Ma J.
        • Miller C.B.
        • Shurtleff S.A.
        • Downing J.R.
        Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia.
        Science. 2008; 322: 1377-1380
        • Haffner M.C.
        • Mosbruger T.
        • Esopi D.M.
        • Fedor H.
        • Heaphy C.M.
        • Walker D.A.
        • Adejola N.
        • Gürel M.
        • Hicks J.
        • Meeker A.K.
        • Halushka M.K.
        • Simons J.W.
        • Isaacs W.B.
        • De Marzo A.M.
        • Nelson W.G.
        • Yegnasubramanian S.
        Tracking the clonal origin of lethal prostate cancer.
        J. Clin. Investig. 2013; 123: 4918-4922
        • Clappier E.
        • Gerby B.
        • Sigaux F.
        • Delord M.
        • Touzri F.
        • Hernandez L.
        • Ballerini P.
        • Baruchel A.
        • Pflumio F.
        • Soulier J.
        Clonal selection in xenografted human T cell acute lymphoblastic leukemia recapitulates gain of malignancy at relapse.
        J. Exp. Med. 2011; 208: 653-661
        • Zahreddine H.
        • Borden K.L.
        Mechanisms and insights into drug resistance in cancer.
        Front. Pharmacol. 2013; 4: 28
        • Greaves M.
        • Maley C.C.
        Clonal evolution in cancer.
        Nature. 2012; 481: 306-313
        • Styczynski J.
        • Wysocki M.
        • Debski R.
        • Czyzewski K.
        • Kolodziej B.
        • Rafinska B.
        • Kubicka M.
        • Koltan S.
        • Koltan A.
        • Pogorzala M.
        • Kurylak A.
        • Olszewska-Slonina D.
        • Balwierz W.
        • Juraszewska E.
        • Wieczorek M.
        • Olejnik I.
        • Krawczuk-Rybak M.
        • Kuzmicz M.
        • Kowalczyk J.
        • Stefaniak J.
        • Badowska W.
        • Sonta-Jakimczyk D.
        • Szczepanski T.
        • Matysiak M.
        • Malinowska I.
        • Stanczak E.
        • Wachowiak J.
        • Konatkowska B.
        • Gil L.
        • Balcerska A.
        • Maciejka-Kapuscinska L.
        Predictive value of multidrug resistance proteins and cellular drug resistance in childhood relapsed acute lymphoblastic leukemia.
        J. Cancer Res. Clin. Oncol. 2007; 133: 875-893
        • Borst P.
        • Schinkel A.H.
        P-glycoprotein ABCB1: a major player in drug handling by mammals.
        J. Clin. Investig. 2013; 123: 4131-4133
        • Chen K.G.
        • Sikic B.I.
        Molecular pathways: regulation and therapeutic implications of multidrug resistance.
        Clin. Cancer Res. 2012; 18: 1863-1869
        • Amiri-Kordestani L.
        • Basseville A.
        • Kurdziel K.
        • Fojo A.T.
        • Bates S.E.
        Targeting MDR in breast and lung cancer: discriminating its potential importance from the failure of drug resistance reversal studies.
        Drug Resistance Updates. 2012; 15: 50-61
        • Galluzzi L.
        • Kepp O.
        • Vander Heiden M.G.
        • Kroemer G.
        Metabolic targets for cancer therapy.
        Nat. Rev. Drug Discov. 2013; 12: 829-846
        • Carracedo A.
        • Cantley L.C.
        • Pandolfi P.P.
        Cancer metabolism: fatty acid oxidation in the limelight.
        Nat. Rev. Cancer. 2013; 13: 227-232
        • Clendening J.W.
        • Penn L.Z.
        Targeting tumor cell metabolism with statins.
        Oncogene. 2012; 31: 4967-4978
        • Muñoz-Pinedo C.
        • El Mjiyad N.
        • Ricci J.E.
        Cancer metabolism: current perspectives and future directions.
        Cell Death Dis. 2012; 3: e248
        • Zhao Y.
        • Butler E.B.
        • Tan M.
        Targeting cellular metabolism to improve cancer therapeutics.
        Cell Death Dis. 2013; 4: e532
        • Castro-Perez J.M.
        • Roddy T.P.
        • Shah V.
        • McLaren D.G.
        • Wang S.P.
        • Jensen K.
        • Vreeken R.J.
        • Hankemeier T.
        • Johns D.G.
        • Previs S.F.
        • Hubbard B.K.
        Identifying static and kinetic lipid phenotypes by high resolution UPLC-MS: unraveling diet-induced changes in lipid homeostasis by coupling metabolomics and fluxomics.
        J. Proteome Res. 2011; 10: 4281-4290
        • Araki Y.
        • Andoh A.
        • Tsujikawa T.
        • Fujiyama Y.
        • Bamba T.
        Alterations in intestinal microflora, faecal bile acids and short chain fatty acids in dextran sulphate sodium-induced experimental acute colitis in rats.
        Eur. J. Gastroenterol. Hepatol. 2001; 13: 107-112
        • Oosterveer M.H.
        • Grefhorst A.
        • van Dijk T.H.
        • Havinga R.
        • Staels B.
        • Kuipers F.
        • Groen A.K.
        • Reijngoud D.J.
        Fenofibrate simultaneously induces hepatic fatty acid oxidation, synthesis, and elongation in mice.
        J. Biol. Chem. 2009; 284: 34036-34044
        • Islam S.
        • Kjällquist U.
        • Moliner A.
        • Zajac P.
        • Fan J.B.
        • Lönnerberg P.
        • Linnarsson S.
        Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq.
        Genome Res. 2011; 21: 1160-1167
        • Islam S.
        • Kjällquist U.
        • Moliner A.
        • Zajac P.
        • Fan J.B.
        • Lönnerberg P.
        • Linnarsson S.
        Highly multiplexed and strand-specific single-cell RNA 5′ end sequencing.
        Nat. Protoc. 2012; 7: 813-828
        • Zajac P.
        • Islam S.
        • Hochgerner H.
        • Lönnerberg P.
        • Linnarsson S.
        Base preferences in non-templated nucleotide incorporation by MMLV-derived reverse transcriptases.
        PloS One. 2013; 8: e85270
        • Langmead B.
        • Trapnell C.
        • Pop M.
        • Salzberg S.L.
        Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
        Genome Biol. 2009; 10: R25
        • Anders S.
        • Huber W.
        Differential expression analysis for sequence count data.
        Genome Biol. 2010; 11: R106
        • Stock W.
        • Johnson J.L.
        • Stone R.M.
        • Kolitz J.E.
        • Powell B.L.
        • Wetzler M.
        • Westervelt P.
        • Marcucci G.
        • DeAngelo D.J.
        • Vardiman J.W.
        • McDonnell D.
        • Mrózek K.
        • Bloomfield C.D.
        • Larson R.A.
        Dose intensification of daunorubicin and cytarabine during treatment of adult acute lymphoblastic leukemia: results of Cancer and Leukemia Group B Study 19802.
        Cancer. 2013; 119: 90-98
        • Bogason A.
        • Quartino A.L.
        • Lafolie P.
        • Masquelier M.
        • Karlsson M.O.
        • Paul C.
        • Gruber A.
        • Vitols S.
        Inverse relationship between leukaemic cell burden and plasma concentrations of daunorubicin in patients with acute myeloid leukaemia.
        Br. J. Clin. Pharmacol. 2011; 71: 514-521
        • Jönsson K.
        • Dahlberg N.
        • Tidefelt U.
        • Paul C.
        • Andersson G.
        Characterization of an anthracycline-resistant human promyelocyte leukemia (HL-60) cell line with an elevated MDR-1 gene expression.
        Biochem. Pharmacol. 1995; 49: 755-762
        • Kung H.N.
        • Marks J.R.
        • Chi J.T.
        Glutamine synthetase is a genetic determinant of cell type-specific glutamine independence in breast epithelia.
        PLoS Genet. 2011; 7: e1002229
        • Nordström A.
        • Want E.
        • Northen T.
        • Lehtiö J.
        • Siuzdak G.
        Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics.
        Anal. Chem. 2008; 80: 421-429
        • Tserng K.Y.
        • Jin S.J.
        Metabolic origin of urinary 3-hydroxy dicarboxylic acids.
        Biochemistry. 1991; 30: 2508-2514
        • Tein I.
        Disorders of fatty acid oxidation.
        Handbook Clin. Neurol. 2013; 113: 1675-1688
        • Roe D.S.
        • Roe C.R.
        • Brivet M.
        • Sweetman L.
        Evidence for a short-chain carnitine-acylcarnitine translocase in mitochondria specifically related to the metabolism of branched-chain amino acids.
        Mol. Genet. Metab. 2000; 69: 69-75
        • Violante S.
        • Ijlst L.
        • Ruiter J.
        • Koster J.
        • van Lenthe H.
        • Duran M.
        • de Almeida I.T.
        • Wanders R.J.
        • Houten S.M.
        • Ventura F.V.
        Substrate specificity of human carnitine acetyltransferase: implications for fatty acid and branched-chain amino acid metabolism.
        Biochim. Biophys. Acta. 2013; 1832: 773-779
        • Kerner J.
        • Minkler P.E.
        • Lesnefsky E.J.
        • Hoppel C.L.
        Fatty acid chain-elongation in perfused rat heart: synthesis of stearoylcarnitine from perfused palmitate.
        FEBS Lett. 2007; 581: 4491-4494
        • Castro-Perez J.
        • Previs S.F.
        • McLaren D.G.
        • Shah V.
        • Herath K.
        • Bhat G.
        • Johns D.G.
        • Wang S.P.
        • Mitnaul L.
        • Jensen K.
        • Vreeken R.
        • Hankemeier T.
        • Roddy T.P.
        • Hubbard B.K.
        In vivo D2O labeling to quantify static and dynamic changes in cholesterol and cholesterol esters by high resolution LC/MS.
        J. Lipid Res. 2011; 52: 159-169
        • Shridhar V.
        • Bible K.C.
        • Staub J.
        • Avula R.
        • Lee Y.K.
        • Kalli K.
        • Huang H.
        • Hartmann L.C.
        • Kaufmann S.H.
        • Smith D.I.
        Loss of expression of a new member of the DNAJ protein family confers resistance to chemotherapeutic agents used in the treatment of ovarian cancer.
        Cancer Res. 2001; 61: 4258-4265
        • Witham J.
        • Vidot S.
        • Agarwal R.
        • Kaye S.B.
        • Richardson A.
        Transient ectopic expression as a method to detect genes conferring drug resistance.
        Int. J. Cancer. 2008; 122: 2641-2645
        • Strathdee G.
        • Davies B.R.
        • Vass J.K.
        • Siddiqui N.
        • Brown R.
        Cell type-specific methylation of an intronic CpG island controls expression of the MCJ gene.
        Carcinogenesis. 2004; 25: 693-701
        • Lindsey J.C.
        • Lusher M.E.
        • Strathdee G.
        • Brown R.
        • Gilbertson R.J.
        • Bailey S.
        • Ellison D.W.
        • Clifford S.C.
        Epigenetic inactivation of MCJ (DNAJD1) in malignant paediatric brain tumours.
        Int. J. Cancer. 2006; 118: 346-352
        • Hatle K.M.
        • Gummadidala P.
        • Navasa N.
        • Bernardo E.
        • Dodge J.
        • Silverstrim B.
        • Fortner K.
        • Burg E.
        • Suratt B.T.
        • Hammer J.
        • Radermacher M.
        • Taatjes D.J.
        • Thornton T.
        • Anguita J.
        • Rincon M.
        MCJ/DnaJC15, an endogenous mitochondrial repressor of the respiratory chain that controls metabolic alterations.
        Mol. Cell. Biol. 2013; 33: 2302-2314
        • Hatle K.M.
        • Neveu W.
        • Dienz O.
        • Rymarchyk S.
        • Barrantes R.
        • Hale S.
        • Farley N.
        • Lounsbury K.M.
        • Bond J.P.
        • Taatjes D.
        • Rincón M.
        Methylation-controlled J protein promotes c-Jun degradation to prevent ABCB1 transporter expression.
        Mol. Cell. Biol. 2007; 27: 2952-2966
        • Ling B.
        • Zheng H.
        • Fu G.
        • Yuan J.
        • Shi T.
        • Chen S.
        • Liu Y.
        • Liu Y.
        • Cao Y.
        • Zheng S.
        • Guo S.
        • Han N.
        • Gao Y.
        • Cheng S.
        • Zhang K.
        Suppression of non-small cell lung cancer proliferation and tumorigenicity by DENND2D.
        Lung Cancer. 2013; 79: 104-110
        • Kanda M.
        • Shimizu D.
        • Nomoto S.
        • Takami H.
        • Hibino S.
        • Oya H.
        • Hashimoto R.
        • Suenaga M.
        • Inokawa Y.
        • Kobayashi D.
        • Tanaka C.
        • Yamada S.
        • Fujii T.
        • Nakayama G.
        • Sugimoto H.
        • Koike M.
        • Fujiwara M.
        • Kodera Y.
        Prognostic impact of expression and methylation status of DENN/MADD domain-containing protein 2D in gastric cancer.
        Gastric Cancer. 2014 (10.1007/s10120-014-0372-0)
        • Daye D.
        • Wellen K.E.
        Metabolic reprogramming in cancer: unraveling the role of glutamine in tumorigenesis.
        Semin. Cell Dev. Biol. 2012; 23: 362-369
        • Hoffmann K.
        • Firth M.J.
        • Beesley A.H.
        • Freitas J.R.
        • Ford J.
        • Senanayake S.
        • de Klerk N.H.
        • Baker D.L.
        • Kees U.R.
        Prediction of relapse in paediatric pre-B acute lymphoblastic leukaemia using a three-gene risk index.
        Br. J. Haematol. 2008; 140: 656-664
        • Singh B.
        • Tai K.
        • Madan S.
        • Raythatha M.R.
        • Cady A.M.
        • Braunlin M.
        • Irving L.R.
        • Bajaj A.
        • Lucci A.
        Selection of metastatic breast cancer cells based on adaptability of their metabolic state.
        PloS One. 2012; 7: e36510
        • Cheng T.
        • Sudderth J.
        • Yang C.
        • Mullen A.R.
        • Jin E.S.
        • Matés J.M.
        • DeBerardinis R.J.
        Pyruvate carboxylase is required for glutamine-independent growth of tumor cells.
        Proc. Natl. Acad. Sci. U.S.A. 2011; 108: 8674-8679
        • Panigrahy D.
        • Kaipainen A.
        • Huang S.
        • Butterfield C.E.
        • Barnés C.M.
        • Fannon M.
        • Laforme A.M.
        • Chaponis D.M.
        • Folkman J.
        • Kieran M.W.
        PPARα agonist fenofibrate suppresses tumor growth through direct and indirect angiogenesis inhibition.
        Proc. Natl. Acad. Sci. U.S.A. 2008; 105: 985-990