Internalization of Extracellular ATP in Cancer Cells and Development of New
Generations of Anticancer Glucose Transport Inhibitors
A dissertation presented to
the faculty of
the College of Arts and Sciences of Ohio University
In partial fulfillment
of the requirements for the degree
Doctor of Philosophy
Yanrong Qian
December 2014
© 2014 Yanrong Qian. All Rights Reserved.
2
This dissertation titled
Internaliztion of Extracellular ATP in Cancer Cells and Development of New
Generations of Anticancer Glucose Transport Inhibitors
by
YANRONG QIAN
has been approved for
the Department of Chemistry and Biochemistry
and the College of Arts and Sciences by
Xiaozhuo Chen
Associate Professor of Biomedical Sciences
Robert Frank
Dean, College of Arts and Sciences 3
ABSTRACT
QIAN, YANRONG, Ph.D., December 2014, Molecular and Cellular Biology
Internalization of Extracellular ATP in Cancer Cells and Development of New
Generations of Anticancer Glucose Transport Inhibitors
Director of Dissertation: Xiaozhuo Chen
The past decade has witnessed remarkable progress toward understanding the reprogrammed metabolism in cancer, an emerging hallmark as well as an active area of basic, translational, and clinical research. About ninety years ago, Otto Warburg pioneered quantitative investigations of cancer metabolism and discovered that cancer cells exhibit a phenotype of increased glycolysis even under aerobic conditions, known as the Warburg effect. Warburg speculated that the reason for the upregulated glycolysis was for compensating the ATP shortage due to dysfunctions of mitochondria in cancer cells. Despite subsequent progresses, the biological reasons for ATP synthesis by aerobic glycolysis in cancer cells are only partially understood. Intriguingly, intratumoral
(extracellular) ATP levels are 103 to 104 times higher than those in normal tissues. We showed that although extracellular ATP is not known to cross the plasma membrane by itself, extracellular ATP in the range of the intratumoral ATP levels induced large intracellular ATP concentration increase in A549 human lung cancer cells and promoted cancer cell survival. More importantly, we reported that a nonhydrolyzable fluorescent
ATP was internalized by A549 cells through macropinocytosis as visualized by fluorescence microscopy. The induced ATP increase was reduced by the macropinocytosis inhibitor EIPA but persisted even when mitochondrial oxidative 4 phosphorylation and glycolysis were inhibited, without involving transcription or translation. The increases were also observed in several other cancer cell lines, but not in noncancerous cells. Furthermore, extracellular ATP enhanced cancer cell survival under various stress conditions and promoted drug resistance to tyrosine kinase inhibitors that compete with ATP for their anticancer action. Collectively, these results provide the first piece of evidence that extracellular ATP is internalized by cancer cells via macropinocytosis and potentially other endocytic process, which significantly contribute to their growth and to drug resistance. These findings potentially change our understanding of ATP supply and sharing among cancer cells, enhance our understanding of the Warburg effect, and highlight a novel anticancer target. Current understanding of glucose transport and metabolism in cancer, anticancer therapeutics targeting glycolysis and glucose transporters, and daunting challenges are also summarized. Based on the previous discovery on WZB-117, the first generation of glucose transport inhibitor, we screened a library of its derivatives and identified WZB-173 and DRB-18 with higher stabilities and potencies as lead compounds in new generations of novel glucose transport inhibitors. Both compounds can serve as models for further development of glucose transport inhibitors.
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ACKNOWLEDGMENTS
I would like to express my great appreciation to Dr. Xiaozhuo Chen, my advisor, for his inspirational guidance, valuable teaching, strong support, and extraordinary patience during my PhD study in Ohio University. It would be impossible for me to finish this work without his help.
I would also like to express my sincere gratitude to Dr. Shiyong Wu, Dr. Stephen
Bergmeier, and Dr. Fabian Benencia for being on my committee and giving me valuable suggestions on my research. Moreover, I would like to cordially thank Dr. Robert Colvin,
Dr. Yunsheng Li for their critical suggestions and help in my research. I would like to thank Dr. Yi Liu for her help and teaching me basic techniques in the lab. I would like to express my earnest appreciation to Xuan Wang, Yanyang Cao, Lingyu Zhang, Lingying
Tong for their assistance in my research.
In addition, I would like to thank Dr. Weihe Zhang and Dennis Roberts for the design and synthesis of novel glucose transporter inhibitors studied in my work. I would like to thank Dr. Jeff Wiseman and Dr. Athena Chen for their critical review and suggestions on the manuscript for ATP internalization study in Chapter 2. Also, I would like to thank Dr. John Kopchick and Dr. Elahu Gosney Sustarsic for their support and help on realtime PCR in the study of glucose transport inhibitor in Chapter 4.
Furthermore, I would like to express my appreciation of the assistance I received from MCB program, Edison Biotechnology Institution, Department of Chemistry and
Biochemistry. Also, I would like to express my great appreciation to the financial and temporal support in my research granted by 2013-2014 Donald Clippinger Graduate 6
Fellowship, 2013 Student Enhancement Award, 2013 Graduate Student Senate Original
Work Grant from Ohio University, and 2013 American Association for Cancer Research-
Woman In Cancer Research Scholar Award.
Also, I would like to acknowledge Elsevier and Baishideng Publishing Group for permission to include the contents from my publications published in the journals of Free
Radical Biology & Medicine, Cancer Letters, and World Journal of Translational
Medicine in my dissertation.
In addition, I am grateful to Edwin Frebault, Marlene Jenkins, Zongqian Yuan,
Dr. Komal Garg, and all of my friends for their encouragement and support during my
PhD study in Ohio University.
Last but not least, I would like to express my sincere appreciation to my parents,
Xiang’an Qian, Liqin Hu, and all my family members for their endless care, love, support, and encouragement during my PhD study in Ohio University. 7
TABLE OF CONTENTS
Page
Abstract ...... 3 Acknowledgments ...... 5 List of Tables ...... 10 List of Figures ...... 11 Abbreviations ...... 14 Chapter 1 Introduction ...... 19 1.1 Cancer metabolism and the Warburg effect ...... 19 1.2 Original hypothesis and current findings of the Warburg effect ...... 20 1.3 Brief history and current interpretations of the Warburg effect ...... 21 1.4 The Warburg effect in normal cells and cancer cells ...... 23 1.5 ROS balancing and the Warburg effect ...... 24 1.6 Gene regulation and the Warburg effect ...... 26 1.7 Oxygen supply, ATP synthesis and the Warburg effect ...... 30 1.8 Warburg effect at the tumor microenvironment scale ...... 33 1.9 The Warburg effect as a potential target for cancer treatment ...... 36 1.10 Conclusion ...... 43 Chapter 2: Internalization Of Extracellular ATP In Cancer Cells ...... 45 2.1 Introduction ...... 45 2.2. Materials and methods ...... 47 2.2.1 Compounds and cell lines ...... 47 2.2.2 ATP rescue study and inATP measurement ...... 48 2.2.3 Protein analysis, clonogenic and flow cytometry assays of cancer cells ...... 48 2.2.4 Dose- and time-dependence studies of ATP ...... 49 2.2.5 Fluorescence microscopy and ATP localization studies ...... 49 2.2.6 Oligomycin and glucose deprivation assays – time course study ...... 50 2.2.7 Studies with inhibitors of AMPK, transcription, translation ...... 50 2.2.8 Macropinocytosis inhibitor study ...... 50 2.2.9 Drug resistance study ...... 51 2.2.10 Experimental designs and statistical analysis ...... 51 2.3 Results ...... 51 2.3.1 exATP rescued cancer cells under different metabolic stresses and reduced anticancer efficacy of tyrosine kinase inhibitors ...... 51 2.3.2 exATP induced dose- and time- dependent inATP increases in multiple cancer cell lines ...... 55 2.3.3 Nontumorigenic cells displayed profiles of exATP induced inATP increase different from those of cancer cells ...... 56 8
2.3.4 Colocalization of ATP analog and high-molecular-weight (HMW) dextran in A549 cells ...... 58 2.3.5 inATP was increased by exATP even when OXPHOS and/or glycolysis were blocked ...... 60 2.3.6 exATP induced changes in levels and phosphorylation of AMPK ...... 63 2.3.7 inATP increase was not dependent on AMPK, transcription, or translation ... 65 2.3.8 Inhibiting macropinocytosis reduced inATP levels and anticancer activity of TKIs ...... 66 2.4 Discussion ...... 68 Chapter 3 Inhibitors Of Glucose Transport And Glycolysis As Novel Anticancer Therapeutics ...... 76 3.1 Cancer and cancer metabolism ...... 76 3.2 Glucose transport and glucose metabolism in cancer cells – the Warburg effect .. 79 3.3 Anticancer therapeutics targeting glycolysis and its connected pathways ...... 80 3.4 Glucose transporters (GLUTs) and upregulation of GLUTs in cancer ...... 95 3.5 Glucose transporter 1 (GLUT1) inhibitors ...... 101 3.6 Future directions and challenges ...... 105 Chapter 4: Development Of New Generations Of Anticancer Glucose Transport Inhibitors ...... 109 4.1 Introduction ...... 109 4.2 Methods and materials ...... 110 4.2.1 Cell culture ...... 110 4.2.2 Compound preparation ...... 111 4.2.3 Glucose uptake assay ...... 111 4.2.4 Cell viability assay (MTT assay) ...... 112 4.2.5 Compounds stability in serum test ...... 112 4.2.6 Western blot analysis ...... 112 4.2.7 Cell cycle analysis ...... 113 4.2.8 RNA isolation and realtime PCR ...... 114 4.2.9 Statistical analysis ...... 115 4.3 Results ...... 115 4.3.1 WZB-173, a lead compound of a new generation of glucose transport inhibitors, is much more stable than WZB-117 ...... 115 4.3.2 WZB-173 induced cell cycles arrested at G1 phase in A549 human lung cancer cells through the regulation of phosphorylation and total Rb protein ...... 120 4.3.3 DRB series compounds as a new generation of glucose transport inhibitors 124 4.3.4 DRB-18, a lead compound of new generation of glucose transport inhibitors, was much more potent than WZB-117 in NCI-60 cancer cell panels ...... 130 4.4 Disscussion ...... 141 Chapter 5: Future Work ...... 145 5.1 Introduction ...... 145 5. 2 Study of exATP in cancer cells and tumors ...... 146 5.2.1 Mechanism study of ATP internalization ...... 146 9
5.2.2 Identification of sources of ATP increase in intratumoral spaces ...... 154 5.2.3 Mechanism study of exATP-induced drug resistance ...... 157 5.2.4 Studies on exATP-induced metastasis ...... 159 5.3 Development of new generations of glucose transporter inhibitors ...... 160 5.3.1 Optimization study of GLUT1 inhibitors ...... 160 5.3.2 Identification of targets ...... 161 5.3.3 Mechanisms study of GLUT1 inhibitors ...... 161 5.3.4 Animal studies for safety and efficacy ...... 162 5.3.5 Optimization of screening strategy ...... 163 5.3.6 Optimization of the selectivity of GLUT1 inhibitors ...... 164 5.4 Links between ATP internalization and GLUT 1 inhibitors studies ...... 165 References ...... 168 Appendix 1. Structures And Parameters Of DRB Series Compounds ...... 202 Appendix 2. NCI-60 Cancer Cells Panel Test of WZB-117 (10 µM) ...... 213 Appendix 3. NCI-60 Cancer Cells Panel Test of DRB-18 (10 µM) ...... 214 Appendix 4. Publications During My PhD Study In Dr. Xiao Chen’s Lab ...... 215 Appendix 5. Permissions From Journals ...... 217 Permission for Free Radical Biology & Medicine and Cancer Letters (Elsevier) .. 217 Permission for World Journal of Translational Medicine (BPG) ...... 219 10
LIST OF TABLES
Page
Table 1: Therapeutics targeting the Warburg effect in cancers ...... 41
Table 2: Glycolytic inhibitors and compounds that modulate glycolytic metabolism ...95
Table 3: Expression of GLUTs and their major characteristics ...... 99
Table 4: Properties of GLUT1 inhibitors ...... 105
Table 5: Data for DRB series compounds in glucose uptake and cell viability assays in
H1299 human lung cancer cells ...... 125
Table 6: IC50 and GI50 of compounds of DRB series in H1299 human lung cancer cells
...... 128
Table 7: Cell toxicity of compounds in NL-20 human noncancerous lung epithelial cells
...... 130
Table 8: Comparisons between the growth percent of WZB-117 and DRB-18 in NCI-60 cancer cell panels ...... 133
Table 9: The average growth percent (AGP) in each cancer panel and the ratio between the averages for cancer panels treated with WZB-117 and DRB-18 ...... 136
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LIST OF FIGURES
Page
Figure 1: The Warburg effect with its extended functions and regulations ...... 29
Figure 2: Potential drug targets in ATP-sharing model ...... 39
Figure 3: exATP rescued A549 cells treated with WZB-117 and increased their inATP levels ...... 52
Figure 4: exATP reduced cellular stress and rescued A549 cancer cells ...... 53
Figure 5: exATP enhanced the colony formation of A549 cells under stress ...... 54
Figure 6: exATP promoted the drug resistance to TKI sunitinib in both A549 and MCF7 cells ...... 55
Figure 7: exATP induced dose- and time-dependent inATP increases in A549 cells ....56
Figure 8: exATP induced inATP changes in multiple cancer cell lines and their noncancerous counterparts ...... 57
Figure 9: A549 cells internalized HMW-dextran but MCF7 cells did not ...... 59
Figure 10: The structures of nonhydrolyzable fluorescent ATP ...... 59
Figure 11: A549 cells internalized HMW-dextran and nonhydrolyzable fluorescent ATP, which was colocalized with HMW dextran ...... 60
Figure 12: exATP induced inATP increase in A549 cells even when their mitochondrial and /or glycolytic ATP synthesis were blocked ...... 62
Figure 13: NL-20 cells were treated with mitochondrial inhibitor oligomycin in the presence or absence of ATP ...... 63 12
Figure 14: exATP induced changes in phosphorylation and total of AMPK and ACC in
A549 cells in a dose- and time-dependent fashion ...... 64
Figure 15: exATP-induced inATP increase was not dependent upon AMPK, transcription, or translation ...... 65
Figure 16: exATP-induced inATP increase was mediated by macropinocytosis ...... 66
Figure 17: exATP-induced inATP increase was mediated by macropinocytosis and was responsible for drug resistance to TKIs ...... 67
Figure 18: Proposed model for exATP-induced inATP increase ...... 74
Figure 19: Glycolysis and inhibitors / activators of glycolysis as potential anticancer therapeutics ...... 82
Figure 20: Chemical structures of compound WZB-117 and WZB-173 ...... 115
Figure 21: The percentage of glucose uptake and viable cells in A549 and its counterpart
NL-20 cells treated with compound WZB-117 ...... 116
Figure 22: WZB-117 inhibited the proliferation of cancer cells and induces the accumulation of protein in arrested A549 cells ...... 117
Figure 23: WZB-173 (ether bond) was at least six-time more stable than WZB-117 (ester bond) in serum-containing media ...... 118
Figure 24: Glucose uptake and viable cell percentage in A549 cells and NL-20 cells treated with compound WZB-173 ...... 120
Figure 25: Cell cycle arrest after cancer cells treated with compound WZB-173 ...... 121
Figure 26: WZB-173 decreased the phosphorylation and the total levels of Rb protein122 13
Figure 27: Rb mRNA expression in A549 cells was not influenced after WZB-173 treatment for up to 48 hours ...... 123
Figure 28: WZB-117 induced mRNA expression of Glut1 while WZB-173 did not ...124
Figure 29: Correlations between the glucose uptake and cell viability for assayed compounds ...... 127
Figure 30: Glucose uptake IC50 assay and cell growth GI50 assay in H1299 human lung cancer cells ...... 129
Figure 31: Growth percent of NCI-60 cancer cell lines treated by WZB-117 and DRB-18 grouped according to cancer types ...... 138
Figure 32: Diagram for the future studies of ATP study ...... 146
Figure 33: Flowchart for the future work of development of novel GLUT1 inhibitors160
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ABBREVIATIONS
2-DG: 2-deoxy-D-glucose
2-PG: 2-phosphoglycerate
3-BP: 3-bromopyruvate
3-PG: 3-phosphoglycerate
3PO: 3-(3-pyridinyl)-1-(4-pyridinyl)-2-propen-1-one
6-AN: 6-aminocicotinamide
6-P-gluconolactone: 6-phosphogluconolactone
A549: human non-small cell lung cancer
AA: amino acids
ABCs: ATP-binding cassette transporters
ACC: acetyl-CoA carboxylase
Ac-CoA: acetyl-CoA
AD: actinomycin D
AGP: average growth percent
ALD: aldolase
AMPK: AMP-activated protein kinase
ATCC: American Type Culture Collection
BCA: bicinchoninic acid assay
CHO: Chinese hamster ovary cells
CNS: central nervous system 15
Cpd C: compound C
CSCs: cancer stem cells cycloh: cycloheximide
DCA: dichloroacetate ddH2O: distilled and deionized water
DHAP: dihydroxyacetone phosphate
DMEM: Dulbecco's Modified Eagle Medium
ECAR: extracellular acidification rate
ECM: extracellular matrix
EIPA: ethyl isopropyl amiloride
ENO: elonase
ER: estrogen receptor exATP: extracellular ATP
F-1,6-bisP: fructose-1,6-bisphosphate
F-2,6-biP: fructose-2,6-bisphosphte
F6P: fructose-6-phosphate
FITC: fluorescein isothiocyanate
G6P: glucose-6-phophate
G6PD: glucose-6-phosphate dehydrogenase
GADP: glyceraldehyde 3-phosphate
GAPDH: glyceraldehyde-3-phosphate dehydrogenase
GD: glucose deprivation 16
GLUTs: glucose transporters
GLUT1: glucose transporter 1
GPI: glucose-6-phosphate isomerase
GSK-3: glycogen synthase kinase-3
H2O2: hydrogen peroxide
HGF: hepatocyte growth factor
HIF: hypoxia-inducible factors
HK: hexokinase
HMW: high-molecular-weight
HPRT: hypoxanthine phophoribosyltransferase 1
IC50: inhibitor’s efficacy inATP: intracellular ATP
Krasonc: oncogenic form of Kras gene
Kraswt: wild type Kras gene
LDH: lactate dehydrogenase
LDHA: lactate dehydrogenase A
LMW: low-molecular-weight
MCF7: human breast cancer
MCF12A: human nontumorigenic breast cells
MDR: multi-drug resistance
MDSC: myeloid-derived suppressor cells
MSCs: mesenchymal stem cells 17
NADPH: nicotinamide adenine dinucleotide phosphate
NDK: nucleoside-diphosphate kinases
NHI: N-hydroxyindole
NK: natural killer
NL-20: human nontumorigenic lung cells
NSCLC: non-small cell lung cancer
O: oligomycin
OCR: oxygen consumption rate
OXPHOS: mitochondrial oxidative phosphorylation
PCR: polymerase chain reaction
PDH: pyruvate dehydrogenase
PDK: pyruvate dehydrogenase kinase
PEP: phosphoenolpyruvate
PET: Positron Emission Tomography
PFK: phosphofructokinase
PGAM1: phosphoglycerate mutase 1
PGK: phosphoglycerate kinase
PHD: prolyl hydroxylase
PHGDH: 3-phosphoglycerate dehydrogenase
PI: propidium iodide
PK: pyruvate kinase
PKM2: pyruvate kinase M2 18 pO2: oxygen pressure
PPP: pentose phosphate pathway
PR: progesterone receptor
PYR: pyruvate
RB: retinoblastoma protein
RBC: red blood cells
RCC: renal cell carcinoma
Ribose-5-P: ribose-5-phosphate
RKO: human colon cancer cells
ROS: reactive oxygen species
SAICAR: succinylaminoimidazolecarboxamide ribose-5'-phosphate
SAR: structure activity relationship
SCs: stem cells
TBP: TATA box binding protein
RTK: tyrosine kinase receptors
TKI: tyrosine kinase inhibitors
TKTL: transketolase
TKTL1: transketolase-like enzyme 1
TPI: triosephosphate isomerase
VHL: von Hippel-Lindau protein
Xylulose-5-P: D-xylulose-5-phosphate
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CHAPTER 1 INTRODUCTION
This chapter is modified from a peer-reviewed paper published in 2014 in the
Free Radical Biology and Medicine. Yanrong Qian was a coauthor of this paper.
1.1 Cancer metabolism and the Warburg effect
In the United States, one in four deaths are due to cancer (Jemal et al., 2010). In
2013, a total of approximate 1.7 million new cancer cases and more than half-million cancer deaths are expected to occur in the United States (Siegel et al., 2013). In 2012, cancers account for an estimated 8.2 million deaths worldwide (Ferlay et al., 2014).
Thus, the new findings in researches focusing on oncogenesis and anticancer therapeutics have very high impact on people’s health.
Cancer is a group of diseases in which cells with gene mutations grow in an abnormal and uncontrolled way and these cells have the potential to invade surrounding normal tissues or spread to other parts of the body (Hanahan and Weinberg, 2011). The instable genome is traditionally known as one of key hallmarks of cancer including constitutive activation of growth signaling, resistance to cell death, immortality of replication, induction of angiogenesis and activation of invasion and metastasis (Hanahan and Weinberg, 2011).
In the last decade, reprogramming of energy has been recognized as an emerging hallmark of cancer (Hanahan and Weinberg, 2011). Evidences indicate that not only gene mutations but also metabolic reprogramming play important roles in cancer (Cairns et al.,
2011; Kroemer and Pouyssegur, 2008; Levine and Puzio-Kuter, 2010; Schulze and 20
Harris, 2012; Soga, 2013; Yang et al., 2013). In certain cases, the reprogramming of cell metabolism may even participate in the initiation of tumorigenesis (Sundaram et al.,
2013; Taubes, 2012; Yun et al., 2009b). The alterations of metabolism and energetics, within which glucose and adenosine triphosphate (ATP) are prominent players, have been recognized as critical for cancer development in recent years (Hanahan and Weinberg,
2011). Actually, the importance of metabolic alteration in cancer cells was recognized long ago. In the 1920s, Otto Warburg, a German biochemist, observed that unlike normal tissues, cancer cells always show a phenotype of upregulated glycolysis even when oxygen was abundant (Warburg et al., 1927; Warburg, 2010). This phenomenon of so- called aerobic glycolysis became known as the Warburg effect (Bayley and Devilee,
2012; DeBerardinis et al., 2008; Hsu and Sabatini, 2008; Koppenol et al., 2011;
Upadhyay et al., 2013; Vander Heiden et al., 2009; Warburg, 1956).
1.2 Original hypothesis and current findings of the Warburg effect
Warburg hypothesized that existing mitochondrial dysfunction disrupts oxidative phosphorylation (OXPHOS) pathway therefore, cancer cells have to switch from
OXPHOS to glycolysis for ATP generation (Koppenol et al., 2011; Warburg, 1956). As glycolysis is much less efficient than OXPHOS for producing ATP, it has to be greatly upregulated so that sufficient ATP will be synthesized. However, this hypothesis has been challenged in recent years due to findings that upregulated glycolysis in many cancers is not accompanied by detectable mitochondrial defects or OXPHOS disruptions
(Fantin et al., 2006; Moreno-Sanchez et al., 2007). In addition, new evidence revealed 21 that the upregulation of glycolysis is not just for ATP synthesis, but also for synthesis of biomass such as ribonucleotides (Tong et al., 2009) and amino acids (Locasale et al.,
2011) as well as reduced nicotinamide adenine dinucleotide phosphate (NADPH) production (Anastasiou et al., 2011), which can remove reactive oxygen species (ROS) generated by cancer cells’ accelerated metabolism under hypoxic conditions (Anastasiou et al., 2011; Hamanaka and Chandel, 2011). Thus, the Warburg effect appears to be a strategic move made by cancer cells not only to cope with multiple urgent requirements simultaneously for growth, and proliferation in an ever-changing microenvironment under numerous material limitations, such as shortages of oxygen and nutrients; but also to reduce ROS and therefore oxidative stress in cancer cells.
1.3 Brief History And Current Interpretations Of The Warburg Effect
In the early 1920s, after partially elucidating the metabolic pathways of glycolysis and OXPHOS for ATP synthesis, Otto Warburg and his co-workers developed an ex vivo system to measure energy metabolism of cancer tissue slices with a thickness of approximate 200-300 µm isolated from Flexner-Jobling rat liver carcinoma using then newly developed quantitative measurement techniques (Koppenol et al., 2011; Warburg,
1956). He and his coworkers meticulously measured O2 uptake and lactic acid production by the tumor slices and calculated the amount of glucose consumed by cancer slices. He observed that, compared to normal tissues, cancer slices used approximately 10 times more glucose in their energy metabolism and produced a large amount lactate from upregulated glycolysis. Interestingly and surprisingly, the approximately ten-fold 22 upregulation of glycolysis persisted even when the cancer slices were assayed in the presence of normal O2 pressure (Koppenol et al., 2011; Warburg, 1928; Warburg et al.,
1927; Warburg, 2010). From this observation, Warburg concluded that the upregulated and persistent glycolysis was likely to be a forced action taken by cancer cells to switch to glycolysis for producing sufficient ATP to compensate for ATP loss due to dysfunctional OXPHOS resulting from mitochondrial defects (Koppenol et al., 2011;
Warburg, 1956).
In recent decades, it has been recognized that cancer metabolism is an integral part of cancer biology. Research done in the last 10-15 years has confirmed the near- universal prevalence of the Warburg effect in cancers. What was observed and measured by Warburg more than 90 years ago was mostly and quantitatively correct (Koppenol et al., 2011; Warburg, 1956). However, his theory regarding the reason for cancer cells to upregulate glycolysis has been challenged, because in many cancers, aerobic glycolysis is upregulated without mitochondrial dysfunction (no identifiable mitochondrial gene mutations) or OXPHOS disruption (Fantin et al., 2006; Koppenol et al., 2011; Moreno-
Sanchez et al., 2007). In these cancers, OXPHOS continues as normal and produces as much ATP as OXPHOS in normal tissue under the same oxygen pressures (Fantin et al.,
2006; Koppenol et al., 2011; Moreno-Sanchez et al., 2007). Therefore, the upregulation of glycolysis may be a strategic metabolic action made by cancer cells for the purpose of balancing the functional needs of cancer cells, primarily in synthesis of biomass: ribose for RNA and DNA (Tong et al., 2009), amino acids for proteins (Locasale et al., 2011), fatty acids as precursors for components of plasma and intracellular membranes (Lunt 23 and Vander Heiden, 2011; Menendez and Lupu, 2007) as well as reducing equivalents
(NADPH) for reducing ROS and oxidative stress (Anastasiou et al., 2011). Glycolytic
ATP synthesis seems to be of no higher priority because cancer cells, regardless of their oxygen supply, do not suffer an ATP shortage. The debate on the functional roles of upregulated glycolysis in the Warburg effect is ongoing, and interpretation is evolving alongside exciting new findings. Of note, the metabolic reprogramming observed in cancer cells is also found in normal proliferating cells for the same requirements in increased biosynthesis of nucleic acids, amino acids, and fatty acids (Christen and Sauer,
2011; Darzynkiewicz et al., 1981; Hedeskov, 1968; Lunt and Vander Heiden, 2011;
Munyon and Merchant, 1959; Wang et al., 1976).
1.4 The Warburg effect in normal cells and cancer cells
Although the Warburg effect was specifically described for metabolic changes in cancer cells, the phenomenon (aerobic glycolysis) was also observed in rapidly proliferating normal cells such as stimulated lymphocytes and mitotic and proliferating fibroblasts (Christen and Sauer, 2011; Darzynkiewicz et al., 1981; Hedeskov, 1968; Lunt and Vander Heiden, 2011; Munyon and Merchant, 1959; Wang et al., 1976). This dramatic physiological change in normal cells is due to the temporary higher demands in metabolic material and energy for completing the cell proliferation process. The fact that aerobic glycolysis is present in E coli, yeasts, normal proliferating cells as well as almost all cancer cells (Christen and Sauer, 2011; Darzynkiewicz et al., 1981; Hedeskov, 1968;
Lunt and Vander Heiden, 2011; Munyon and Merchant, 1959; Wang et al., 1976), 24 suggests that this is an evolution-selected metabolic strategy conserved among cells to meet special needs during cell proliferation and most cancer cells exploit this strategy because of their constant needs for rapid growth and proliferation.
Because of drastically upregulated glycolysis, more glucose is transported into cancer cells and thus more pyruvate is produced in cancer cells than in normal cells.
Limited by the capacity of OXPHOS and regulated by lactate dehydrogenase (LDH), pyruvate comparable to the amount in normal cells enters the mitochondrial TCA cycle.
A lingering misconception about the Warburg effect is that OXPHOS in cancer cells is greatly reduced compared to normal cells. In fact, OXPHOS in most cancers is normal and a similar amount of ATP is produced by OXPHOS. Different from what Warburg theorized, there is no switch from OXPHOS to glycolysis in cancer cells, rather, glycolysis is upregulated even in the presence of normal oxygen pressure (normoxia) because of higher demands for biosynthesis. Under hypoxia, due to the limited oxygen availability, less pyruvate enters the TCA cycle and thus more pyruvate is converted into lactate. The excess lactate is secreted into the intratumoral space by hypoxic cancer cells
(Koppenol et al., 2011; Vander Heiden et al., 2009).
1.5 ROS Balancing And The Warburg Effect
ROS act as a double-edged sword for cancer cells. An elevated but controlled
ROS level is required for cancer growth and proliferation (Fiaschi and Chiarugi, 2012).
ROS are involved in tumor angiogenesis (Maulik, 2002; Ushio-Fukai and Urao, 2009), in ligand-independent transactivation of receptor tyrosine kinase (Pani et al., 2010; Storz, 25
2005), as well as in promoting invasion and metastasis of cancer cells (Svineng et al.,
2008; Toullec et al., 2010).
However, ROS are also a major contributor to oxidative damage (Blokhina et al.,
2003). Thus the cellular level of ROS must be vigorously maintained within certain ranges so that they will only promote cancer cell growth and proliferation without causing severe oxidative damage and even cell death. ROS production in cancer cells is elevated due to oncogenic stimulation and increased metabolic activities (Fiaschi and
Chiarugi, 2012). The Warburg effect, which leads to the production of NADPH and thus a proper redox status, becomes an important survival mechanism for cancer cells.
One important step of glycolysis reprogramming that leads to The Warburg effect is the switch in isoform of pyruvate kinase (PK), which catalyzes the conversion of phosphoenolpyruvate (PEP) to pyruvate as the last step of glycolysis. Many types of cancer cells use the M2 isoform of pyruvate kinase (PKM2) instead of the M1 isoform of the enzyme (PKM1) as normal tissues do (Christofk et al., 2008a; Christofk et al., 2008b;
Hitosugi et al., 2009). This is surprising because cancer cells drastically upregulate glycolysis; yet PKM2 is less active than PKM1. This paradoxical phenomenon was explained in recent years. The major reasons for upregulating glycolysis in cancers are not only for synthesis of ATP but also for synthesis of biomass (nucleic acids and proteins) and NADPH (Anastasiou et al., 2011; Hamanaka and Chandel, 2011). By using
PKM2, cancer cells upregulate glucose transport and the early steps of glycolysis without overproducing pyruvate. Instead, using the slower PKM2 leads to accumulation of earlier glycolytic intermediates, diverting them to glycolysis-connected subsidiary biosynthesis 26 pathways such as hexosamine, PPP, and amino acids. One major purpose for upregulating glucose transport and early steps of glycolysis appears to be for cell biomass production and achieving metabolic balance among ATP production, biomass synthesis, as well as the control of oxidative stress resulted from ROS generation (Anastasiou et al.,
2011; Hamanaka and Chandel, 2011). The switch to PKM2 results in accumulation of
PEP, which functions as a feedback inhibitor of the glycolytic enzyme triosephosphate isomerase (TPI). This in turn activates PPP, increasing antioxidative metabolism by producing more NADPH, reducing ROS, and amplifying the inhibitory effect of PKM2
(Anastasiou et al., 2011; Hamanaka and Chandel, 2011). In addition, ROS and PKM2 form a negative feedback loop to maintain ROS in a tolerable and functional range
(Figure. 1). PKM2 can be specifically oxidized on cysteine 358 by hydrogen peroxide
(H2O2), an ROS, which leads to reduction in its activity and pyruvate production as well as augmentation of flux of glycolytic intermediates into PPP (Anastasiou et al., 2011;
Hamanaka and Chandel, 2011).
1.6 Gene Regulation And The Warburg Effect
The uncontrollable growth and proliferation of cancer cells as well as abnormal vasculogenesis lead to deficiency of oxygen supply and local hypoxia in tumors (Dang et al., 2008). The resulting condition triggers the increased expression of HIF (Dang et al.,
2008; Gordan and Simon, 2007). There are three members (isoforms) in the HIF family:
HIF1, HIF2, and HIF3 with HIF1 and HIF2 better studied and HIF3’s functions poorly understood. Among the three, HIF1 is the only one that is ubiquitously expressed and the 27 most relevant to cancer (Dang et al., 2008; Gordan and Simon, 2007). HIF1, like all
HIFs, consists of an oxygen-dependent α-subunit and a constitutively expressed β- subunit. Under normoxia, HIF1α is constitutively synthesized and hydroxylated by prolyl hydroxylases (PHDs). Hydroxylated HIF1α is recognized by the von Hippel-Lindau protein (VHL) and its associated ubiquitinase, resulting in proteolytic degradation in proteasomes (Brahimi-Horn et al., 2007; Gordan and Simon, 2007). Under hypoxia, reduced oxygen supply diminishes the activity of PHDs, which are further inhibited by
ROS released from stressed mitochondria that operate under reduced OXPHOS. ROS oxidize and inactivate the ferrous ion located in the active site of PHDs such that they become unable to modify and thus stabilize HIF1α, which binds to HIF1β to form a stabilized HIF1. HIF1 complex then binds and transactivates genes involved in glucose transport, glycolysis, pH regulation, and vasculogenesis, allowing cancer cells to rapidly adapt to hypoxia (Brahimi-Horn et al., 2007; Dang et al., 2008; Semenza, 2003). HIF functions as a master regulator for the initiation and maintenance of the Warburg effect at the level of gene expression. Recently, PKM2 is found to be a PHD-induced coactivator for HIF (Luo et al., 2011), adding another link between the Warburg effect and HIF.
Another well-documented gene that is regulated by HIF and contributes to the
Warburg effect is the MYC proto-oncogene (Liu and Levens, 2006). While it is not directly regulated by ROS, activated MYC, the protein product of the MYC gene, can either work together with HIF or independently in regulating glycolysis and OXPHOS.
The MYC gene is a classical immediate early serum response proto-oncogene under vigorous transcriptional control (Chung and Levens, 2005; Liu and Levens, 2006). 28
Approximately 30% of all human cancers show deregulated MYC gene expression
(Nesbit et al., 1999). MYC is a transcription factor that regulates genes involved in glucose metabolism by binding to and regulating virtually all glycolytic enzyme genes as well as numerous genes involved in mitochondrial biogenesis (Dang et al., 2008; Li et al.,
2005a). One of the key roles of MYC in normal cells is to stimulate glycolytic flux for
OXPHOS (Chung and Levens, 2005; Liu and Levens, 2006). In cancer cells, working together with HIF and PKM2, constitutively active MYC upregulates glycolysis to ensure sufficient metabolic intermediates for synthesis of biomass and reducing equivalents needed by cancer cells (Anastasiou et al., 2011; Hamanaka and Chandel, 2011; Zhang et al., 2007a). Compared to HIF, MYC appears to be more involved in the transcriptional regulation of genes participating in energy generation and cell growth and proliferation.
Both HIF and MYC activate hexokinase 2 (HK2) and pyruvate dehydrogenase kinase 1
(PDK1), leading to augmented glycolytic rates and conversion of glucose to lactate
(Dang et al., 2008). Furthermore, HIF1 and MYC independently activate glucose transporter 1 (GLUT1) and lactate dehydrogenase A (LDHA), resulting in increased glucose influx and higher glycolytic rates (Dang et al., 2008). The roles of HIF1 and
MYC in the regulation of the Warburg effect are schematically shown in Figure 1.
29
Figure 1. The Warburg effect with its extended functions and regulations. Relative amount of glucose consumption and its metabolic products in normal (blue box) and cancer (orange box) under normoxic condition are shown and compared. Cancer cells on average, consume approximately 10 times more glucose than normal cells. Red indicates an elevated level in cancer cells. The enzymes in green function in both normal and cancer cells; and the enzyme in orange functions mainly in cancer cells.
30
1.7 Oxygen Supply, ATP Synthesis And The Warburg Effect
The Warburg effect is a dynamic process, in which the weight of OXPHOS relative to glycolysis in total ATP synthesis is constantly adjusted in response to cancer cells’ microenvironments, particularly oxygen supply rate. Oxygen pressures (pO2) in cancer cells are lower than those in normal cells of the same tissue origin and are different in different tumor types, ranging from very low mmHg to slightly above 10 mmHg as compared to 160 mmHg in the air and approximately 40 mmHg in the vein
(Carreau et al., 2011; Hockel and Vaupel, 2001; Sridhar et al., 1983). Normoxia and hypoxia are relative concepts without absolute standards because hypoxic pO2 in one cancer type may be normoxic in another type. Inside of a single tumor, pO2 is also different from one location to another depending upon the abundance of blood vessels to that location. Even more complicated, pO2 of one location of a tumor can also be changing during tumorigenesis. This is because the vascular structure inside of a tumor is constantly forming and dying, leading to reported phenomena of intermittent and cyclic hypoxia inside tumors (Bhaskara et al., 2012; Cardenas-Navia et al., 2008; Matsumoto et al., 2010; Toffoli and Michiels, 2008). Cancer cells in tumors are heterogeneous with respect to their oxygen supply and ATP synthesis rate. Normoxic cancer cells produce as much as 50% more ATP than normal cells by fully oxidizing a molecule of glucose through OXPHOS (with 36 ATP molecules produced), while simultaneously metabolizing approximately another 10 glucose molecules to lactate through upregulated glycolysis and producing an additional ~20 ATP molecules during the process (Koppenol et al., 2011). By comparison, anoxic cancer cells metabolize about 13 glucose molecules 31 to produce only 26 ATP molecules exclusively through glycolysis. However, a large proportion of cancer cells in tumors lives and grows in varied hypoxic conditions between these two extremes. These heterogeneous cells produce more ATP than anoxic ones but significantly less ATP than normoxic cancer even normal cells (Koppenol et al.,
2011). Exactly how much ATP they can produce depends on their oxygen and glucose availabilities. On average, cancer cells in a tumor produce about 10% more ATP than normoxic normal cells (Koppenol et al., 2011), a value indicative of the heterogeneity of cancer cells within a tumor. While a sub-population of cancer cells has reduced ATP production due to a lack of oxygen and severely depressed OXPHOS rates, these cells do not appear to suffer from a lack of ATP. It is presently unclear as to how these hypoxic cancer cells are capable of securing sufficient levels of ATP to maintain growth and proliferation. One possible explanation is that high ATP-producing normoxic cancer cells and possibly even stromal cells release ATP while low-ATP producing hypoxic cancer cells take up the released ATP from the intratumoral space to supplement their intracellular ATP pool (Figure 2). As a result, the intracellular ATP concentration of hypoxic cancer cells are elevated to such levels that they are capable of performing all the biological functions required for survival, growth, proliferation and even cell movement required for invasion and metastasis (Semenza, 2012; Wong et al., 2011).
Mammalian cells, including cancer cells, are known to release ATP under certain conditions (Ahmad et al., 2005; Chaudry and Gould, 1970; Grygorczyk et al., 2013;
Israel et al., 1976; Pearson and Gordon, 1979). Uptake of ATP by animal cells has been speculated (Chaudry, 1982; Chaudry and Baue, 1980; Pant et al., 1979; Weidemann et al., 32
1969) but has not been experimentally demonstrated. While interstitial ATP concentrations in normal tissues are maintained between 1-1000 nM depending upon tissue type (Corriden et al., 2007; Goldman et al., 2010; Li et al., 2003, 2005b; Trabanelli et al., 2012; Trautmann, 2009), intratumoral ATP levels are in the range of several hundred µM (Falzoni et al., 2013; Michaud et al., 2011; Pellegatti et al., 2008; Wilhelm et al., 2010), which suggests ATP is readily available for use by hypoxic cancer cells.
However, ATP is a charged and thus hydrophilic molecule, unable to cross the cell membrane without the help of a transporter. Since no plasma-membrane-associated ATP transporter has been found, it has long been presumed that extracellular ATP does not enter cells. There has been no direct evidence or identified mechanism for ATP uptake by cancer cells until a recent study demonstrated that normal pancreatic cells transformed with an oncogenic form of Kras gene (Krasonc) drastically upregulated macropinocytosis
(Commisso et al., 2013), a type of endocytosis that engulfs extracellular fluid and nonspecifically takes up extracellular molecules in the fluid. When the macropinocytosis inhibitor EIPA was used to treat nude mice with xenografted tumors of the transformed cells, it substantially reduced tumor growth (Commisso et al., 2013) indicating that the transformed cells use macropinocytosis to take up extracellular nutrients to support their growth in vivo. Because macropinocytosis, commonly named “large-scale fluid drinking”, is nonspecific for the molecules it internalizes (Amyere et al., 2000; Doherty and McMahon, 2009), many extracellular molecules including the highly concentrated
ATP should be taken up by this process. These reports (Ahmad et al., 2005; Chaudry,
1982; Chaudry and Baue, 1980; Chaudry and Gould, 1970; Falzoni et al., 2013; 33
Grygorczyk et al., 2013; Israel et al., 1976; Michaud et al., 2011; Pant et al., 1979;
Pearson and Gordon, 1979; Pellegatti et al., 2008; Weidemann et al., 1969; Wilhelm et al., 2010) and our previous finding of that extracellular ATP increased intracellular ATP levels and increased cancer cell growth and survival (Liu et al., 2012) led to the hypothesis that low ATP-producing hypoxic cancer cells likely solve the problem of ATP deficiency by upregulating macropinocytosis to bypass the lack of an ATP transporter for acquiring extracellular ATP. They internalize intratumoral ATP, hypothetically released from stromal cells and/or normoxic cancer cells (Figure. 2). The uptake of extracellular
ATP also theoretically reduces intracellular ATP synthesis, ROS production and oxidative stress as well as increases survival of cancer cells under conditions of hypoxia.
The hypothesis was tested and the results are reported in the next chapter.
1.8 Warburg Effect At The Tumor Microenvironment Scale
Cancer cells in a tumor nodule are far from a homogeneous population and several levels of heterogeneity exist among cancer cells in tumors. First, cancer cells in tumors are often genetically heterogeneous among tumors in the same individual or even within a single tumor. As tumors grow, cancer cells within a tumor can accumulate additional genetic mutations and create further genetic diversity (Marusyk et al., 2012;
Swanton, 2012). Second, cancer cells in a tumor are also metabolically heterogeneous primarily due to their distances to intratumoral blood vessels, which determines the relative levels of oxygen and nutrient supplies to the cells. Because of the differences in oxygen and nutrient supply, these cancer cells exhibit different rates of mitochondrial 34 respiration and different degrees of reliance on aerobic glycolysis (Koppenol et al.,
2011). Third, a subpopulation of cancer stem cells (CSCs) have been identified and isolated from different cancers. Similar to normal stem cells (SCs), CSCs show full self- renewal capability and the Warburg effect (upregulated aerobic glycolysis) (Kondoh et al., 2007a; Kondoh et al., 2007b; Pacini and Borziani, 2014; Siggins et al., 2008).
Different from SCs, CSCs can differentiate into only non-CSC cancer cells. Forth, the tumor heterogeneity is not only spatial but also temporal. Tumorigenesis is an ever- changing dynamic process. Oxygen and nutrient status of a region in a tumor can change during tumor development and normoxic cancer cells in a tumor at a given time can become hypoxic at another time and vice versa (Bhaskara et al., 2012; Cardenas-Navia et al., 2008; Matsumoto et al., 2010; Toffoli and Michiels, 2008). Genetic and metabolic heterogeneities can further communicate with each other, partially determining the fate of tumor development. These diversities exert differential metabolic pressures on heterogeneous cancer cells in a tumor. As a result, different cancer cells exhibit different levels of the Warburg effect depending upon their oxygen and nutrient status as well as their communications with other cancer cells and stromal cells.
Cancer is a mixed population of cancer cells and stromal cells, which include cells of hematopoietic and mesenchymal origins. All these cancer and non-cancer cells plus the extracellular matrix (ECM) form the tumor microenvironment (Goubran et al., 2014;
Pattabiraman and Weinberg, 2014; Place et al., 2011). Stromal cells of hematopoietic origin include T and B lymphocytes, natural killer (NK) cells as well as macrophages, neutrophils, and myeloid-derived suppressor cells (MDSCs) (Pattabiraman and 35
Weinberg, 2014). The role of T cells is either tumor-promotion (Zou, 2006) or tumor- elimination (Restifo et al., 2012) depending upon the exact tumor microenvironmental context. For example, stimulated T lymphocytes are able to release large amount ATP into extracellular space, potentially modulating cancer metabolism through purinergic receptor-mediated signaling (Antonioli et al., 2013). T cells and macrophages, interacting with cancer cells through cytokines, can launch tumor-protective and tumor growth- promoting inflammatory responses (Coussens and Werb, 2002). Similarly, each of the other constituent cell types of hematopoietic origin may have either a positive or negative effect on tumor development. Stromal cells of mesenchymal origin include fibroblasts, myofibroblasts, mesenchymal stem cells (MSCs), adipocytes and endothelial cells.
Among these cells, adipocytes are found to secret hepatocyte growth factor (HGF) to promote tumor growth (Dirat et al., 2011) and endothelial cells play roles in angiogenesis and cancer cell dissemination (Butler et al., 2010; Karnoub et al., 2007). Thus, all of these stromal cells directly or indirectly affect cancer metabolism and participate in metabolic reprogramming of cancer cells, including regulating the Warburg effect.
Although cancer cells are competing with stromal cells for limited resources such as oxygen and nutrients and energy in the form of ATP, they also form symbiotic and cooperative relationships with one another. The outcome of such overall competition and cooperation results in the formation of a commonly acceptable microenvironment for the best survival of the tumor by transforming normal stromal cells into tumor-friendly stromal cells to serve the needs of cancer cells and tumors. One such example is stimulated lymphocytes release large amounts of ATP into extracellular space (Filippini 36 et al., 1990), potentially creating an ATP-rich environment for both direct energy intake and for purinergic receptor-mediated signaling to regulated metabolisms of cancer cells.
This theory is supported, at least in part, by the observation that intratumoral ATP concentrations are 103 to 104 times higher than those of normal tissues (Falzoni et al.,
2013; Michaud et al., 2011; Pellegatti et al., 2008; Wilhelm et al., 2010). Also, immune stromal cells also use cell surface enzymes CD39 and CD73 to dephosphorylate ATP into
AMP and adenosine, respectively (Antonioli et al., 2013; Regateiro et al., 2013), creating an immunosuppressed environment within tumors. Working in coordination, CD39 and
CD73 create and adjust a "purinergic halo" surrounding immune stromal cells to modulate signaling events mediated by purinergic receptors by regulating the duration, magnitude and composition of the halo (Antonioli et al., 2013; Regateiro et al., 2013).
Through purinergic signaling, immune stromal cells mediate immunological and inflammatory responses such as immunoescape and cancer cell killing impairment in tumors. In addition, CD39/CD73 system is also found overexpressed on the surface of cancer cells (Antonioli et al., 2013), suggesting that this system also utilize high intratumoral ATP concentration to regulate cancer cell metabolism including the
Warburg effect.
1.9 The Warburg Effect As A Potential Target For Cancer Treatment
As presented in the Figure 1, some major characteristics of the Warburg effect are: (i) increased expression of glucose transporters and thus an increased uptake of glucose; (ii) increased PPP-catalyzed NADPH production; (iii) altered activities of 37 glycolytic or glycolysis-related enzymes (such as HIF/MYC induced activation of HK2,
LDHA and PDK1; and the switch from PKM1 to a less active PKM2); (iv) increased lactate production. Some of these characteristics have been or could potentially be targeted for developing therapeutics for cancer treatments (Figure 2 & Table 1). For example, inhibiting glucose transport should lead to shortage of glucose supply to cancer cells, thus slowing down cancer metabolism and biomass synthesis and forcing cancer cells to stop growing and undergo apoptosis. Up to 90% of all cancers substantially upregulate GLUTs and glucose metabolism as demonstrated by PET-scans of cancer patients (Gambhir, 2002; Higashi et al., 1998; Jadvar, 2013; Kelloff et al., 2005;
Kurokawa et al., 2004). Cancer cells are “addicted” to glucose and are more sensitive to changes in glucose transport and glucose supply than normal cells (Liu et al., 2012; Liu et al., 2010). At least twelve glucose transporters (GLUTs) have been identified (Hruz and
Mueckler, 2001; Jung, 1998; Lachaal et al., 1996; Mueckler and Thorens, 2013; Wood and Trayhurn, 2003; Zeng et al., 1996). Among them, GLUT1 (Cho et al., 2013; Kang et al., 2002; Kunkel et al., 2003; Mori et al., 2007; Ravazoula et al., 2003; Younes et al.,
1995) and GLUT3 (Younes et al., 1997) are the most relevant to cancer. In fact, many
GLUT inhibitors have been in studies. More inhibitors for GLUT1 have been developed than for other GLUTs due to its near-universal upregulation in cancer and better knowledge of its protein structure (Figure 2). Reported GLUT1 inhibitors include
GLUT1 antibody (Rastogi et al., 2007), fasentin (Schimmer et al., 2006; Wood et al.,
2008), apigenin (Melstrom et al., 2008; Patel et al., 2007; Shukla and Gupta, 2010), genestein (Li et al., 2012; Nagaraju et al., 2013; Tarkowski et al., 2013; Vera et al., 38
1996), oxime-based inhibitors (Tuccinardi et al., 2013), STF-31 (Chan et al., 2011),
WZB-117 (Liu et al., 2012), and shRNA interfering expression of GLUT1 (Gautier et al.,
2013). While all these GLUT1 inhibitors showed some inhibitory effect in different cultured cancer cell lines, STF-31 (Chan et al., 2011), WZB-117 (Liu et al., 2012), and
GLUT1 RNAi (Gautier et al., 2013) also inhibited cancer growth in vivo. STF-31 inhibited tumor growth in a renal cell carcinoma animal model (Chan et al., 2011); WZB-
117 reduced cancer growth rate by more than 60% in nude mice bearing human lung cancer (A549 cells) (Liu et al., 2012), and RNAi inhibition of GLUT1 prevented myeloproliferation (Gautier et al., 2013). These three in vivo studies clearly demonstrate anticancer efficacy of GLUT1 inhibitors in animal models. 39
Figure 2. Potential drug targets in ATP-sharing model. According to this model, a symbiotic relationship exists among cancer and stromal cells in a tumor. Normoxic cancer cells and stromal cells recruited by hypoxic cancer cells release ATP into intratumoral space, leading to a large intratumoral ATP concentration increase. Highly concentrated intraturmoral ATP is then internalized by hypoxic cancer cells through macropinocytosis and/or other endocytic processes, supplementing the intracellular ATP pool in hypoxic cancer cells. Meanwhile, cancer cells uptake and release of lactate through transporters MCT1 and MCT4. Potential targets for anticancer therapeutic intervention in this model are shown by symbol W.
40
In addition to GLUT inhibitors, drugs targeting enzymes involved in regulation of glycolysis are also in development (Table 1). 2-deoxy-glucose (2-DG) is a hexokinase inhibitor competing with glucose and 2-DG has been widely studied as a potential anticancer drug (Raez et al., 2013). As detailed previously, PKM2 used in cancer cells is less active than PKM1 used in normal tissues (Christofk et al., 2008a; Christofk et al.,
2008b; Hitosugi et al., 2009). Thus, multiple activators of PKM2 have been studied for their ability in reducing upstream PPP-mediated anabolism and suppressing tumorigenesis (Anastasiou et al., 2012; Kung et al., 2012). The activity of LDHA is closely related with NADH consumption. FX-11, as a selective inhibitor of LDHA, induced oxidative stress and inhibited tumor progression (Le et al., 2010). PPP not only produces metabolic intermediates for biomass synthesis, but also generates NADPH as reducing agents. Glucose-6-phosphate dehydrogenase (G6PD) catalyzes the critical step of generating NADPH in PPP. 6-aminocicotinamide (6-AN), as an inhibitor of G6PD, induced oxidative stress and inhibited the growth of cancer cells (Bhardwaj et al., 2012).
AZD3965, as an inhibitor of MCT1, blocked the transport of lactate into cancer cells and therefore inhibited the lactate-fueled respiration in cancer cells (Sonveaux et al., 2008).
Dichloroacetate (DCA), an inhibitor of PDK1, indirectly activated mitochondrial respiration and inhibited cancer growth (Michelakis et al., 2008). A recent clinical trial of
DCA showed some durable anticancer efficacy in the treatment of non-Hodgkin’s lymphoma (Strum et al., 2013). Finally a group of inhibitors suppress tumor growth by targeting PI3K/AKT signaling pathway (Addie et al., 2013; Dumble et al., 2014; Hirai et al., 2010; Lin et al., 2013), which can regulate glycolysis and the Warburg effect by 41 altering levels and activities of key glycolytic proteins and enzymes such as GLUTs and hexokinase (Cairns et al., 2011; DeBerardinis et al., 2008; Kroemer and Pouyssegur,
2008).
Table 1. Therapeutics targeting the Warburg effect in cancers
Process Target Compound Effect Status References (Chan et al., Glucose WZB-117, GLUT1 Inhibits GLUT1 Preclinical 2011; Liu et al., transport STF-31 2012) Clinical (Raez et al., Glycolysis HK 2-DG Inhibits HK trials 2013) discontinued (Anastasiou et Activates PKM2 PKM2 TEPP-46 Preclinical al., 2012; Kung and inhibits PPP et al., 2012) LDHA FX11 Inhibits LDHA Preclinical (Le et al., 2010) Induces (Bhardwaj et al., PPP G6PD 6-AN Preclinical oxidative stress 2012) Inhibits uptake Lactate (Sonveaux et MCT1 AZD3965 of extracellular Phase I transport al., 2008) lactate (Michelakis et Mitochondrial PDK1 DCA Inhibits PDK1 Phase I-II al., 2008; Strum function et al., 2013) AKT signaling Inhibits AKT (Addie et al., AKT AZD5363 Phase I-II pathway activity 2013) (Lin et al., AKT GDC0068 Phase I 2013) Phase I (Dumble et al., AKT GSK2141795 completed 2014) Phase I-II (Dumble et al., AKT GSK2110183 completed 2014) Phase II (Hirai et al., AKT MK-2206 Phase I-II 2010)
42
In Chapter 3, the detailed description about the development of current glycolysis inhibitors and glucose transporter inhibitors is summarized. In Chapter 4, the development of new generations of GLUT1 inhibitors in our lab is described.
Many of above-described agents could inhibit cancer cell growth by decreasing metabolic precursors for glycolysis and synthesis of biomass, reducing equivalents, and generating “absolute nutritional hunger”. Though promising, targeting the Warburg effect may encounter some other challenges. First, CSCs have at least two known features that may interfere cancer therapy targeting glucose metabolism or the Warburg effect. (a)
CSCs are slower cycling compared to the non-CSC cancer cells in the same tumors
(Pattabiraman and Weinberg, 2014). Thus, it is likely that CSCs have lower glucose metabolic rate or reliance on glucose metabolism relative to non-CSC cancer cells. (b)
CSCs overexpress the ATP-binding cassette transporters (ABCs), which play crucial roles in multi-drug resistance (MDR) (Pattabiraman and Weinberg, 2014). As ABCs are
ATP-binding and ATP-consuming, reducing ATP production or ATP internalization processes such as macropinocytosis may contribute to fighting drug resistance and the overall strategy of targeting CSCs. Simultaneous reduction of intratumoral (extracellular)
ATP concentration and intracellular ATP synthesis and creation of an ATP-poor microenvironment should be a novel anticancer and anti-CSC strategy. Second, both normal proliferating cells and cancer cells upregulate aerobic glycolysis (Christen and
Sauer, 2011; Darzynkiewicz et al., 1981; Lunt and Vander Heiden, 2011). Targeting the
Warburg effect (glycolytic proteins and/or enzymes) will not only inhibit cancer cells, but also normal proliferating cells. The latter (lymphocytes under clonal expansion for 43 example) perform some important normal and urgently needed physiological functions.
For this reason, infant and child cancer patients should not be treated with the Warburg effect-targeting therapeutics, as they are growing with large quantities of proliferating cells in their body. For similar reasons, cancer patients undergoing immunotherapy (with potential immune cell clonal expansion going on) should be excluded from the simultaneous anti-Warburg effect therapy. Last, the strategy may not be very effective for those cancers that rely more on glutamine rather than glucose for their metabolic needs. Profiles of glucose metabolism of tumors from cancer patients should be determined before the anti-Warburg effect therapy strategy is adopted.
1.10 Conclusion
Cancer metabolism research in the past decade has substantially enhanced our understanding and changed the interpretations of the Warburg effect. Much more than
Warburg initially speculated and in addition to glycolytic ATP synthesis, aerobic glycolysis also contributes to synthesis of biomass and reducing equivalents and plays a significant and varied role in cancer biology. The connection between the Warburg effect and cancer cell redox homeostasis has been established. The regulation of glycolysis and other glycolysis-connected metabolic pathways are well understood. However, many differences among various cancer types are recognized, with respect to their different genetic mutations; the heterogeneity among cancer cells within a single tumor; and their oxygen and nutritional supplies. Although still in an exploratory stage, targeting the
Warburg effect nevertheless already has yielded promising results. With improved 44 knowledge and better understanding of the Warburg effect, a therapy in combination with oncogenic and metabolic targets with redox manipulation is likely to generate synergistic anticancer effects and become one future anticancer strategy.
45
CHAPTER 2: INTERNALIZATION OF EXTRACELLULAR ATP IN CANCER
CELLS
This chapter is modified from a peer-reviewed paper published in 2014 in Cancer
Letters. Yanrong Qian was the first author of this paper.
2.1 Introduction
Metabolic reprogramming, or deregulation of cellular energetics, is now recognized as a hallmark of cancer (Hanahan and Weinberg, 2011). ATP production by highly upregulated glycolysis in cancer cells even when oxygen is abundant, a phenomenon known as the Warburg effect (Koppenol et al., 2011; Warburg, 1956), is an area of intensive investigation with improved but still incomplete understanding.
Interpretations of the functional reasons for upregulated glycolysis in the presence of continued mitochondrial oxidative phosphorylation (OXPHOS) and the relationship between glycolytic synthesis of ATP and other metabolic intermediates in cancer cells are controversial and evolving (Bayley and Devilee, 2012; Israelsen and Vander Heiden,
2010; Koppenol et al., 2011). Being metabolically heterogeneous, some cancer cells in tumors make significantly less ATP than other cancer cells or even normoxic normal cells (Koppenol et al., 2011). However, cancer cells appear to be able to obtain all the
ATP they need regardless of oxygen status. This is puzzling unless previously unrecognized mechanisms for securing ATP exist.
One potential source of ATP for cancer cells is the extracellular ATP (exATP) pool (Abraham et al., 2003). Interstitial ATP concentrations in normal tissues are in the 46 range of 1-1,000 nM (Trabanelli et al., 2012; Trautmann, 2009). In contrast, intratumoral
ATP levels, i.e., exATP levels inside tumors, have recently been measured in the range of several hundred mM or higher (Falzoni et al., 2013; Michaud et al., 2011; Pellegatti et al.,
2008; Wilhelm et al., 2010), or 103 to 104 times of those in normal tissues. However, neither the source of the ATP nor the destination of the molecule is known. Earlier experimental evidence suggests uptake (Chaudry, 1982; Chaudry and Baue, 1980;
Chaudry and Gould, 1970; Pant et al., 1979; Weidemann et al., 1969) and release of ATP in normal animal cells (Israel et al., 1976; Pearson and Gordon, 1979), providing conceptual and biological basis for potential ATP uptake by cancer cells. However, the uptake of exATP by cancer cells has never been demonstrated except by artificial means
(Zhou et al., 2012).
In our recent anticancer therapeutic studies, we observed that exATP significantly increased intracellular ATP (inATP) levels in A549 human lung cancer cells and rescued glucose-deprived cancer cells treated with glucose transporter 1 (GLUT1) inhibitor
WZB-117 (Liu et al., 2012). However, exATP did not rescue A549 cells treated with paclitaxel, a drug with an ATP-independent anticancer mechanism (Liu et al., 2012). One of the possible explanations for these results is that exATP is directly taken up by A549 cells and contributes to inATP concentration increase, playing a significant role in cancer cell growth and survival. Because ATP is charged and therefore hydrophilic, it cannot cross the plasma membrane by itself. However, no plasma membrane-associated ATP transporter has ever been found. Thus, we further speculated that the ATP uptake might be mediated by some types of endocytic processes, bypassing the problem. In the present 47 study, we tested this hypothesis by studying ATP transport mechanisms with a nonhydrolyzable fluorescent ATP. exATP concentrations in the reported intratumoral
ATP range were used to mimic in vivo conditions. To identify the functional significance of the exATP-induced inATP increase, exATP-induced drug resistance was also studied.
The use of a nonhydrolyzable fluorescent ATP for demonstrating ATP internalization and exATP-mediated drug resistance in cancer cells have never been reported. The findings of this study may significantly impact our interpretation of the Warburg effect, expand our knowledge of ATP/energy sharing among cancer cells, and highlight a new target for cancer treatment.
2.2. Materials and methods
2.2.1 Compounds and cell lines
Glut1 inhibitor WZB-117 was used as previously described (Liu et al., 2012; Liu et al., 2010). ATP, oligomycin (O), compound C (Cpd C), cycloheximide (cycloh), sunitinib, paclitaxel, ethyl isopropyl amiloride (EIPA), were from Sigma-Aldrich.
Actinomycin D (AD) and pazopanib were from Calbiochem and LC labs, respectively.
Human non-small cell lung cancer A549, human breast carcinoma MCF7, and their respective human nontumorigenic NL-20 lung cells and MCF12A breast cells, and RKO human colon cancer cells were from ATCC. All these cells were maintained and propagated using ATCC recommended cell culture media and conditions.
48
2.2.2 ATP rescue study and inATP measurement
The cell rescue study was conducted as previously described (Liu et al., 2012). inATP concentration was measured using an ATP-luciferase-based ATPlite luminescence
ATP detection system (Perkin Elmer) by following the assay instructions. Briefly, cells in
96-well non-transparent plates were treated under different conditions. After treatment and media removal, wash, and cell lysis, inATP levels were measured using a Veritas
Microplate Luminometer (Turner BioSystems, Sunnyvale, CA). The relative ATP concentration in mock-treated controls was assigned a value of 100%. Final relative ATP concentrations of the treated samples were calculated by dividing their ATP levels with those of the controls after all the samples were normalized by total protein. Methods for determining absolute inATP concentrations have not been developed and were unnecessary for this study.
2.2.3 Protein analysis, clonogenic and flow cytometry assays of cancer cells
Western blot analyses were performed using the standard protocol. Antibodies against phosphorylated and total AMP-activated protein kinase (AMPK), acetyl-CoA carboxylase (ACC), eIF-2α, and β-actin were from Cell Signaling. β-actin was used as the protein loading control.
Clonogenic assay and flow cytometry analysis of differentially treated A549 cancer cells were performed as described previously (Liu et al., 2012). Cells were treated with 100nM oligomycin and DMEM supplemented with 2 mM glucose (GD, glucose deprivation) with or without 3mM ATP for 24 hours before assays. 49
2.2.4 Dose- and time-dependence studies of ATP
For dose-dependence studies, ATP concentrations in the reported intratumoral
ATP concentration range (Falzoni et al., 2013; Michaud et al., 2011; Pellegatti et al.,
2008; Wilhelm et al., 2010) were specifically chosen and used to treat cancer and nontumorigenic cells for 24 hours. For time-dependence studies, 3 mM ATP-containing cell culture media were used to treat cancer cells for different durations. After treatment, cells were washed, lysed, and their inATP measured.
2.2.5 Fluorescence microscopy and ATP localization studies
Fluorescence microscopy was performed as previously described (Commisso et al., 2013). Briefly, A549 or MCF7 cells were seeded onto glass coverslips. Twenty-four hours after seeding, cells were serum-starved for 15 hours. High-molecular-weight (70
KDa) fluorescent TMR-dextran (Invitrogen), a tracer for visualizing macropinosomes, was added to serum-free medium at a final concentration of 1mg/mL for 30 minutes at
37oC. After incubation, cells were rinsed five times in PBS and fixed in 3.7% formaldehyde for 15 minutes. Coverslips were mounted onto slides using Gold Antifade
Reagent with DAPI (Invitrogen). Images were captured using epi-fluorescence microscope (ECLIPSE E600, Nikon), and analyzed using ImageJ (National Institutes of
Health). For the colocalization study, both TMR-dextran and nonhydrolyzable fluorescent ATP (Jena Bioscience, Germany) were added to serum-free medium at a final concentration of 1mg/ml and 10µM, respectively. The assay was performed the same way as described for dextran. 50
2.2.6 Oligomycin and glucose deprivation assays – time course study
Endogenous ATP synthesis in cancer cells was inhibited by either glucose deprivation (GD) that reduces glycolysis or by oligomycin that blocks OXPHOS in the presence or absence of exATP. Cell culture media with reduced glucose concentrations
(0.5 to 2mM or 2-8% of the glucose concentration in the high glucose cell culture medium) were prepared as previously described (Liu et al., 2012). Oligomycin at 0.25 or
0.5 mM was used to block OXPHOS for 2 to 24 hours. After treatments, inATP levels in the treated cells were measured.
2.2.7 Studies with inhibitors of AMPK, transcription, translation
To determine the role of AMPK, gene expression, and protein synthesis in the inATP increase, AMPK inhibitor compound C (Scaglia et al., 2009; Wu et al., 2007), transcription inhibitor actinomycin D or translation inhibitor cycloheximide was individually added to A549 cells treated with oligomycin in the presence or absence of exATP for various times. After treatment, inATP levels were measured. Cells treated with oligomycin but with or without exATP were used as positive or negative controls.
2.2.8 Macropinocytosis inhibitor study
A549 cells grown in non-transparent black 96-well plates were treated with or without macropinocytosis inhibitor EIPA in the presence or absence of 1mM exATP for various times. After treatment, cells were washed, lysed, and their inATP measured.
51
2.2.9 Drug resistance study
Tyrosine kinase inhibitors (TKIs) sunitinib (Papaetis and Syrigos, 2009) and pazopanib (Olaussen et al., 2009) were used to individually treat A549 cells grown in 96- well plates at various concentrations in the presence or absence of exATP with or without macropinocytosis inhibitor EIPA for 24 hours. After treatment, cell viability of differentially treated cells was measured by the MTT assay. A non-TKI drug paclitaxel
(Xiao et al., 2006) was used as a control.
2.2.10 Experimental designs and statistical analysis
Each experimental condition was performed in triplicate and repeated at least once. Samples were in hexad for MTT assays. Data were reported as mean ± standard deviation and analyzed using one-way ANOVA. P < 0.05 was considered statistically significant. *, P < 0.05; **, P < 0.01 and ***, P < 0.001.
2.3 Results
2.3.1 exATP rescued cancer cells under different metabolic stresses and reduced
anticancer efficacy of tyrosine kinase inhibitors
First, exATP-induced inATP increase and cancer cell rescue were investigated.
When ATP was added to A549 cells treated with Glut1 inhibitor WZB-117 (Liu et al.,
2012), the cells were rescued from cell death in a dose-dependent manner (Figure 3A).
The treated cells displayed significantly elevated inATP levels (Figure 3B). 52
A B
Figure 3. exATP rescued A549 cells treated with WZB-117 and increased their inATP levels. Cancer cells were treated with or without 30µM Glut1 inhibitor WZB-117 (Liu et al., 2012), in the presence or absence of exATP for 24 hours. A. exATP increased cell viability of WZB-117-treated A549 cells measured by MTT assays. Samples were in hexad. B. inATP levels in WZB-117-treated A549 cells in the presence or absence of exATP. Samples were in triplicate. Each experiment was repeated at least once. Data are presented as means ± standard deviations. Assay results were normalized with total protein concentration. The activity of mock-treated samples was assigned as 100%. *, P < 0.05; **, P < 0.01; and ***, P < 0.001.
When A549 cells were treated with the OXPHOS inhibitor oligomycin in the presence of exATP, ATP reversed the upregulation of phosphorylation of metabolic stress marker eIF-2α (Brewer and Diehl, 2000) 24 hours after the treatment (Figure 4A), indicating reduced cell stress. Flow cytometry analysis revealed that addition of exATP enhanced viability of A549 cells, treated with oligomycin and glucose deprivation for 24 hours, from ~39% to ~65% (Figure 4B, bottom left quadrant, P<0.001). The increased cell survival was further confirmed by a clonogenic assay (Figure 5, P<0.001).
53 ! B!
A B ! A!
Figure 4. exATP reduced cellular stress and rescued A549 cancer cells. exATP reversed the upregulation of phosphorylation of metabolic stress marker eIF-2α in A549 cells treated with oligomycin (O) and enhanced viability of A549 cells treated with oligomycin plus glucose deprivation (O+GD). A. Western blot analysis of phosphorylation of stress protein marker eIF-2α in A549 cells treated with 500nM oligomycin (O) with or without 3mM ATP (O + ATP). All samples were run on the same gel and total eIF-2α and β-actin served as controls. Normalized protein levels of samples of 12-hour treatment were assigned as 1. B. Flow cytometry analysis of A549 cells treated with 100nM oligomycin plus 2mM glucose deprivation (O+GD) in the presence or absence of 3mM ATP for 24 hours using FITC Annexin V and propidium iodide staining. ***, P < 0.001.
54
Figure 5. exATP enhanced the colony formation of A549 cells under stress. exATP enhanced the survival of A549 cells treated with oligomycin and glucose deprivation (O+GD) for 24 hours. Cancer cells were treated with 100nM oligomycin and plus 2mM glucose deprivation in the presence or absence of ATP for 24 hours. Then, the cells were seeded and grow for 3 weeks before staining and counting. Data are presented as means ± standard deviations. ***, P < 0.001.
From these results, we speculated that the increased inATP might interfere with drugs that compete with ATP for their anticancer activity. Cell viability studies revealed that exATP at either 1 mM or 3 mM significantly reduced the anticancer activity of sunitinib, a drug functions as an ATP competitor targeting multiple receptor tyrosine kinases (Papaetis and Syrigos, 2009), in A549 and MCF7 cells (Figure 6).
55
Figure 6. exATP promoted the drug resistance to TKI sunitinib in both A549 and MCF7 cells. Cancer cells were treated with 16µM sunitinib (Papaetis and Syrigos, 2009), in the presence or absence of ATP for 24 hours. Cell proliferation (MTT) assays were conducted 24 hours after treatments. Mock-treated samples were assigned as 100%. **, P < 0.01; and ***, P < 0.001.
2.3.2 exATP induced dose- and time- dependent inATP increases in multiple cancer cell
lines
exATP also induced inATP increase in A549 cells without any other treatment
(Figure 7A). When 3 mM ATP was added to A549 cells for different lengths of time, inATP increased more than 50% from 2 to 24 hours after the addition of ATP (Figure
7B). The ATP increase was induced regardless of whether the cells were under stress or not (Figure 3B; Figure 7A-B), indicating that the mechanism(s) for the inATP increase operate under either condition as long as exATP is present.
56
A B
Figure 7. exATP induced dose- and time-dependent inATP increases in A549 cells. A. inATP levels in A549 cells treated with various concentrations of exATP. The assay was performed 24 hours after treatments. B. Time-dependent changes in inATP of A549 cells treated with 3 mM ATP. Mock-treated samples were assigned as 100%. ***, P < 0.001.
Other cancer cell lines such as breast cancer MCF7 and colon cancer RKO cells also demonstrated inATP elevation similar to those found in A549 cells (Figure 8A), indicating that this is a more general phenomenon among cancer cells. The increase was induced by as little as 0.1 mM exATP, while the highest inATP levels were induced at
0.5 to 1.0 mM or higher concentrations in these cancer cell lines.
2.3.3 Nontumorigenic cells displayed profiles of exATP induced inATP increase different
from those of cancer cells
When inATP responses were compared between cancer cells and their nontumorigenic counterparts from the same tissue types, it was found that ATP increase in nontumorigenic cells was induced at different ATP concentrations and the increase was smaller compared with those in cancer cells (Figure 8B-C). This indicates that cancer cells are more responsive to exATP than nontumorigenic cells. 57
A B
C
Figure 8. exATP induced inATP changes in multiple cancer cell lines and their noncancerous counterparts. A. inATP levels in A549, colon cancer RKO, and breast cancer MCF7 cells treated with various concentrations of ATP for 24 hours. B. inATP levels in A549 cancer cells treated with various concentrations of ATP for 24 hours compared with those in identically treated nontumorigenic lung NL-20 cells. C. inATP levels in MCF7 breast cancer cells treated with various concentrations of ATP for 24 hours compared with those in identically treated nontumorigenic breast MCF12A cells. Mock-treated samples were assigned as 100%. *, P < 0.05; **, P < 0.01; and ***, P < 0.001.
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2.3.4 Colocalization of ATP analog and high-molecular-weight (HMW) dextran in A549
cells
After 30 min incubation of A549 cells with fluorescent HMW dextran, the dextran was found internalized by the cells, via macropinocytosis since it is a well- accepted macropinocytosis tracer (Figure 9) (Commisso et al., 2013). Dextran uptake was reduced when macropinocytosis inhibitor EIPA was used to treat A549 cells (Figure 9,
P<0.001). In contrast, MCF7 cells did not take up HMW dextran (Figure 9). When A549 cells were coincubated with the nonhydrolyzable fluorescent ATP (Figure 10) and HMW dextran, the ATP analog colocalized with HMW dextran (Figure 11), indicating that the
ATP analog was taken up by A549 cells via macropinocytosis, the same mechanism that internalized dextran.
59
Figure 9. A549 cells internalized HMW-dextran but MCF7 cells did not. HMW TMR-dextran, a known macropinocytosis tracer (Commisso et al., 2013), was incubated with cancer cells. After incubation and cell processing, the treated cells were examined and photographed. Fluorescence microscopy of A549 and MCF7 cells treated with TMR-dextran (Dex) in the presence or absence of 40µM of EIPA. Dex-treated sample was assigned as 100%. ***, P < 0.001 as >100 cells per group were counted for dextran-internalizing macropinosomes.
Figure 10. The structures of nonhydrolyzable fluorescent ATP.
60
Figure 11. A549 cells internalized HMW-dextran and nonhydrolyzable fluorescent ATP, which was colocalized with HMW dextran. HMW TMR-dextran was incubated with cancer cells with the nonhydrolyzable fluorescent ATP. After incubation and cell processing, the treated cells were examined by fluorescent microscopy and photographed. Inlets were representative internalized ATP analog, dextran, or their merged images. Scale bar was 20µm.
2.3.5 inATP was increased by exATP even when OXPHOS and/or glycolysis were
blocked
Inhibition of ATP synthesis was used to rule out the possibility that the inATP increase was induced by endogenous ATP synthesis, including glycolysis and OXPHOS, in A549 cells. Glucose deprivation alone did not reduce inATP concentration (Figure
12A). In the presence of 3 mM ATP, inATP in glucose-deprived cancer cells increased more than 60% from 4 to 24 hours after the addition of ATP (Figure 12A). This result suggests that the inATP increase is unlikely to be the result of increased glycolysis.
When A549 cells were treated with 500 nM oligomycin, an inhibitor of
OXPHOS, inATP level was reduced by more than 60% from 4 to 24 hours (Figure 12B). inATP levels approximately doubled when 3 mM ATP and oligomycin were added 61 together compared to the oligomycin treatment alone (Figure 12B), suggesting that the inATP increase cannot be accounted for by enhanced OXPHOS, the largest source of
ATP synthesis.
To further block endogenous ATP synthesis, both glucose deprivation and oligomycin were applied to A549 cells with or without 3 mM ATP. Even under these extremely stressful conditions, exATP continued to significantly elevate inATP levels
(Figure 12C). All these results indicate the increased inATP levels induced by exATP were not from endogenous ATP synthesis but from exATP.
In contrast, the large ATP increase was not observed in nontumorigenic NL-20 lung cells treated with oligomycin and exATP at various concentrations (Figure 13), regardless of whether the exATP was at intratumoral or physiological concentrations in normal tissues. Thus, it appears that the ATP increase was much larger in A549 cancer cells.
62
A B
C
Figure 12. exATP induced inATP increase in A549 cells even when their mitochondrial and /or glycolytic ATP synthesis were blocked. A549 were treated with either glucose deprivation (GD), mitochondrial inhibitor oligomycin, or both for various times in the presence or absence of ATP. After treatments, inATP concentrations were measured. Cells without ATP treatment served as controls. The ATP levels of time zero samples were assigned as 100%. A. Comparison of inATP levels of A549 cells treated with GD for various times in the presence or absence of 3 mM ATP. B. inATP levels of A549 cells treated with 500nM oligomycin for various times in the presence or absence of 3 mM ATP. C. inATP levels of A549 cells treated with 2mM GD and 250 nM oligomycin for various times in the presence or absence of 3 mM ATP. *, P < 0.05; ***, P < 0.001.
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Figure 13. NL-20 cells were treated with mitochondrial inhibitor oligomycin in the presence or absence of ATP. After treatments, inATP concentrations were measured. Cells without ATP treatment served as controls. The ATP levels of time zero samples were assigned as 100%. inATP levels of nontumorigenic NL-20 cells treated with 500 nM oligomycin (O) for various times in the presence or absence of ATP.
2.3.6 exATP induced changes in levels and phosphorylation of AMPK
Several approaches were used to probe the mechanisms underlying the exATP- induced inATP increase. AMPK, the master ATP-sensing and regulatory protein (Hardie et al., 2012; Scaglia et al., 2009), was analyzed in A549 cells treated with the same conditions yielding the ATP increase. Western blot analyses showed that exATP at concentrations of 0.75 and 1 mM induced the largest change in AMPK phosphorylation after 24 hours of ATP treatment (Figure 14A). This result correlates with the dose- dependence study that showed that 1 mM exATP induced the largest increase in inATP concentration (Figure 7A; Figure 8A).
The time course of AMPK phosphorylation in the ATP-treated cells displayed a pattern (Figure 14B) that paralleled the observed changes in inATP levels (Figure 7B).
Total and phosphorylated AMPK in A549 cells treated with 3 mM exATP showed a 64 significant and consistent decline after 12 hours (Figure 14B). In addition, both total and phosphorylated ACC, a protein factor working downstream of AMPK, showed trends similar to total and phosphorylated AMPK (Figure 14A-B).
A B
Figure 14. exATP induced changes in phosphorylation and total of AMPK and ACC in A549 cells in a dose- and time-dependent fashion. Cancer cells were treated as described for Figures 7A and B. After treatments, the cells were lysed and their AMPK and AMPK-regulated ACC analyzed by western blots. β- actin served as loading controls. Histograms show the densitometry determinations of the relative intensity of each protein band compared to the mock-treated controls (time or concentration 0). A. Dose-dependent changes in the total or phosphorylated AMPK or ACC in A549 cells treated with various concentrations of ATP for 24 hours. B. Time- dependent changes in AMPK or ACC in A549 cells treated with 3 mM ATP. *, P < 0.05; **, P < 0.01; and ***, P < 0.001.
65
2.3.7 inATP increase was not dependent on AMPK, transcription, or translation
To further ascertain the role of AMPK in the ATP increase, AMPK inhibitor compound C (Scaglia et al., 2009; Wu et al., 2007) was used. The compound C study revealed that the ATP increase persisted despite treatment (Figure 15A).
We went further to determine whether the increases were dependent on gene expression and/or protein synthesis. Studies using the transcription inhibitor actinomycin
D and the translation inhibitor cycloheximide showed that the ATP increase persisted in
A549 cells treated with either inhibitor (Figure 15B), indicating the increase is not dependent on either process.
A B
Figure 15. exATP-induced inATP increase was not dependent upon AMPK, transcription, or translation. Inhibitors of AMPK, transcription, or translation were added individually to A549 cells treated with 500nM oligomycin (O) in the presence or absence of 3 mM ATP for various durations. inATP levels in the treated cells were measured after treatments. Specific inhibitor concentrations used were selected based on published IC50s. A. ATP levels in A549 cells treated with or without 20µM AMPK inhibitor Compound C (Cpd C). B. ATP levels in A549 cells treated with 0.5µM of transcription inhibitor actinomycin D (AD) or 36µM of translation inhibitor cycloheximide (cycloh).
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2.3.8 Inhibiting macropinocytosis reduced inATP levels and anticancer activity of TKIs
When EIPA, a macropinocytosis inhibitor (Commisso et al., 2013; Ivanov, 2008), was added at various concentrations together with 1 mM ATP to A549 cells, inATP levels were reduced in a dose-dependent manner but not to the basal level (Figure 16).
This indicates that macropinocytosis is partially responsible for the ATP increase.
Figure 16. exATP-induced inATP increase was mediated by macropinocytosis. A549 cells in 96-well plates were treated with or without macropinocytosis inhibitor EIPA in the presence or absence of exATP for various durations. After treatments, inATP levels of the treated cells were measured. Mock-treated samples at 4 hours were assigned as 100%. *, P < 0.05; **, P < 0.01; and ***, P < 0.001.
Based on our findings to this point, we speculated EIPA would reduce the efficacy of exATP in blunting its antagonism of TKIs such as sunitinib. When EIPA was added to A549 cells treated with sunitinib and ATP, the viability and inATP levels of
A549 cells were reduced in a dose-dependent manner (Figure 17A-B). ATP also increased drug resistance of other ATP analog TKIs such as pazopanib but not paclitaxel, which works without involving ATP (Figure 17C), confirming our speculation. 67
A B
C
Figure 17. exATP-induced inATP increase was mediated by macropinocytosis and was responsible for drug resistance to TKIs. A549 cells in 96-well plates were treated with or without macropinocytosis inhibitor EIPA or with TKIs and other anticancer drugs in the presence or absence of exATP for various durations. After treatments, inATP levels and viability of the treated cells were measured. Mock-treated samples were assigned as 100%. A. Anticancer activity changes of sunitinib in A549 cells treated with or without EIPA in the presence or absence of ATP for 24 hours and measured with MTT assays. B. inATP changes in A549 cells treated with sunitinib with or without EIPA in the presence or absence of ATP for 24 hours. C. Anticancer activity changes of TKIs and non-TKIs in A549 cells in the presence or absence of ATP as measured with MTT assays. Sunitinib (16µM) and pazopanib (30µM) were TKIs, and paclitaxel (1µM) was a non-TKI. *, P < 0.05; **, P < 0.01; and ***, P < 0.001.
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2.4 Discussion
Cancer cells in tumors are known to produce on average about 10% more ATP than normal cells (Koppenol et al., 2011). However, they are heterogeneous with respect to oxygen supply. Normoxic cancer cells synthesize up to 50% more ATP while severely hypoxic cancer cells synthesize 20-30% less than normal cells (Koppenol et al., 2011). It was also found that exATP concentrations inside tumors (intratumoral ATP concentration), measured in human ovarian carcinoma, melanoma (Falzoni et al., 2013;
Pellegatti et al., 2008), and colorectal carcinoma (Falzoni et al., 2013; Michaud et al.,
2011) are several hundred µM or higher, or ~103-104 times higher than in normal tissues.
The real intratumoral ATP concentration could be even higher because the ATP signals were saturated at ~700 mM in these measurements. All the experimental evidence cited above strongly suggests the possibility that some cancer cells take up exATP to supplement their energy needs. This study, as the first exploratory step, sets out to address two basic questions: what functional roles does exATP-induced inATP increase play in cancer cells and how do cancer cells take up exATP?
First, the functional significance of exATP-induced inATP increase in cancer cells was examined. exATP significantly increased the survival of cancer cells under various metabolic stress conditions, including inhibition of glucose transport (Figure 3A-
B), blocking of ATP synthesis (Figure 4A-B; Figure 5), and treatment with sunitinib
(Figure 6). Sunitinib is a tyrosine kinase inhibitor and an ATP competitor that works by binding to the ATP binding site of several receptor tyrosine kinases (Papaetis and
Syrigos, 2009). Thus, this result strongly suggests that exATP reduces the anticancer 69 activity of sunitinib by increasing inATP levels. A similar but smaller effect of sunitinib treatment was observed in a breast cancer cell line MCF7 (Figure 6), indicating that the
ATP effect on TKIs such as sunitinib is fairly general among cancer cell lines. These results demonstrate for the first time that exATP, at intratumoral ATP concentrations, substantially increased cancer cell survival and drug resistance to sunitinib.
Cancer cells grown under normal conditions also responded to exATP. Compared to nontumorigenic cells of the same tissues, cancer cell lines exhibited higher relative inATP concentrations at all exATP concentrations examined, even including with-no- extracellular-ATP treatment (Figure 8B-C). This is consistent with previous findings that cancer cells have higher inATP concentrations (Koppenol et al., 2011) and demonstrates the higher responsiveness of cancer cells to exATP at intratumoral concentrations than normal cells. Differences between A549 and NL-20 cells and between MCF7 cells and
MCF12A cells in exATP-induced inATP level increase may be due, at least in part, to their different rates of ATP internalization.
To address the second question, we did ATP uptake studies and the results revealed that HMW dextran, a well-accepted macropinocytosis tracer (Commisso et al.,
2013; Ivanov, 2008), was taken up by A549 cells (Figure 9), indicating that A549 cells exhibit the phenotype of macropinocytosis. Treatment with the well-accepted macropinocytosis inhibitor EIPA (Commisso et al., 2013; Ivanov, 2008) led to significant reduction of internalized dextran (Figure 9), further supporting the notion that the internalization mechanism is macropinocytosis. The same experimental conditions did not induce uptake of HMW dextran in MCF7 cells (Figure 9). These results are consistent 70 with a recent report that the macropinocytosis phenotype in animal cells is correlated with the oncogenic Kras genotype of the cells (Commisso et al., 2013). A549 cells express an oncogenic Kras gene (Krasonc) (Choi et al., 2010; Krypuy et al., 2006), whereas MCF7 cells express a wild type Kras (Kraswt) (Lee et al., 2009). The absence of macropinocytosis and the presence of large exATP-induced inATP increases in MCF7 cells suggest that MCF7 cells use mechanisms different from macropinocytosis for the induced inATP increase.
In similarly-treated A549 cells, the nonhydrolyzable fluorescent ATP and HMW dextran were colocalized (Figure 11), indicating that the ATP analog was taken up by
A549 cells by the same mechanism for HMW dextran: macropinocytosis. Shades of merged colors of the colocalized ATP analog and dextran (Figure 11) suggest that they were taken up in different ratios as two separate chemical entities. This was further confirmed by the observation that nonhydrolyzable fluorescent ATP, without dextran, was also internalized by A549 cells (data not shown). Similarities in structure and size between the ATP analog and ATP strongly suggest that regular ATP can also be taken up by the same process, since macropinocytosis is nonspecific for the molecules it internalizes and can internalize molecules as large as proteins (Commisso et al., 2013).
This is the first time that exATP (ATP analog in this case) is shown to be internalized by cancer cells. A nonhydrolyzable fluorescent ATP is currently the best surrogate available for ATP, as ATP or radioactive ATP is too unstable and easily hydrolyzed while the ATP analog used in this study is nonhydrolyzable for its first phosphoanhydride bond and the bond linking ATP and the fluorescent group is also very stable (Figure 10). The finding 71 that Krasonc A549 cells show macropinocytosis is significant because up to 20% of all human cancers express oncogenic Kras mutations (Arrington et al., 2012), which are known to upregulate glucose metabolism (Ying et al., 2012; Yun et al., 2009b).
Several lines of evidence suggest that the exATP-induced inATP increase is a vigorously regulated process. First, exATP induced inATP increase in a dose-dependent fashion within an ATP concentration range from 0.1 to ~1 mM in different cancer cell lines (Figure 7A; Figure 8A). It may not be a coincidence that this range overlaps with the measured intratumoral ATP concentrations. Second, inATP concentrations were maintained in a relatively narrow range over time (4-24 hours) in the presence of a specific exATP concentration with or without other treatment (Figure 7B; Figure 12A-B).
Since AMPK is the master regulator of endogenous ATP synthesis and AMPK phosphorylation (activation) is required for ATP synthesis (Hardie et al., 2012; Scaglia et al., 2009), total and phosphorylated AMPK in ATP-treated A549 cells were investigated.
Phosphorylation levels of AMPK varied over different exATP concentrations and during the 24 hours treatment period with a fixed ATP concentration. Phosphorylation levels of
AMPK were found to be highest (Figure 14A-B) when the inATP concentrations of the corresponding concentration or time points were also highest (Figure 7A-B). These matched changes can be accounted for by at least two mechanisms: (i) higher AMPK phosphorylation was triggered by the need for ATP synthesis, or (ii) AMPK phosphorylation was triggered by and a passive consequence of higher inATP concentration. To differentiate between these two possibilities, AMPK inhibitor compound C was used to inhibit AMPK activity in the presence of exATP, resulting in 72 augmentation of inATP concentration, not reduction (Figure 15A). This suggests mechanism (ii) is correct. The observed decline of total and phosphorylated AMPK over exATP concentrations or treatment time (Figure 14A-B) also implies that the inATP increase is not dependent on the level of AMPK or even AMPK phosphorylation. This conclusion is consistent with a previous report that showed phosphorylation of AMPK in human umbilical vein endothelial cells was induced by exATP and the phosphorylation was not driven by the AMP:ATP ratio of the cells (da Silva et al., 2006). This finding is also consistent with reports that AMPK and AMPK phosphorylation declined in long- term physical exercises in muscle cells when other ATP producing mechanisms were upregulated (Durante et al., 2002; Winder et al., 2003). Taken together, all these suggest that under the conditions examined, AMPK did not upregulate but maintain or downregulate endogenous ATP synthesis. These data also imply that at least a significant portion of the increased inATP was not generated intracellularly but came from the internalized exATP. Overall, we showed that the increased inATP was not dependent on either gene expression or protein synthesis, glycolysis or OXPHOS. Instead, it was derived, at least in part, from macropinocytosis-mediated ATP internalization as illustrated by the colocalization study.
Once we identified macropinocytosis as a mechanism for moving exATP into
A549 cells (Figure 9; Figure 11; and Figure16), we went back to study if the drug resistance observed earlier (Figure 6) was mediated by the same mechanism. Indeed,
EIPA treatment reduced inATP levels (Figure 17B) and increased sunitinib’s anticancer efficacy (Figure 17A) in a dose-dependent manner. These results strongly suggest that the 73 increased drug resistance is through macropinocytosis-mediated inATP increase. This conclusion was further supported by an ATP effect on another ATP competitor TKI pazopanib (Olaussen et al., 2009), but not on paclitaxel (Figure 17C), a non-TKI whose anticancer mechanism does not involve ATP (Xiao et al., 2006). All these results support the hypothesis that the exATP-induced drug resistance is mediated by an increase in inATP level resulting from, at least in part, macropinocytosis. Because the study was done at intratumoral ATP levels (Falzoni et al., 2013; Michaud et al., 2011; Pellegatti et al., 2008; Wilhelm et al., 2010), these observed effects are of in vivo significance. Thus, the discovery that exATP reduces the anticancer efficacy of some TKIs may have a profound impact on how to reduce drug resistance and enhance anticancer efficacy of these drugs.
Based on all the data reported in this study, a hypothetical mechanism for exATP- induced inATP increase in cancer cells is proposed (Figure 18). In cancer cells, due to gene mutations and metabolic reprogramming, mechanisms different from those of normal cells are present for upregulating inATP concentrations. Macropinocytosis appears to play an important role in exATP uptake, contributing to growth, survival and drug resistance to TKIs of cancer cells. Other mechanisms, such as other endocytic processes, may also be involved in the induced ATP increase. More studies are needed to validate this model. Our findings substantially expands the traditional view that ATP cannot cross plasma membrane by itself and there is no ATP transporter associated with the plasma membrane, by providing an alternative for ATP entry of cells. This model 74 does not exclude the possibility that other non-endocytic mechanisms are also involved in the inATP increase.
Figure 18. Proposed model for exATP-induced inATP increase. In this hypothetical model, exATP is internalized by cancer cells mediated through macropinocytosis and other presently unknown mechanism(s) including other endocytic processes. Once inside cells, internalized exATP elevates inATP concentration ([inATP]), and promotes cell growth, survival and drug resistance to TKIs through increased inATP concentration.
These data also imply the existence of a previously under-appreciated cooperative relationship among cancer cells in tumors involving ATP-sharing. Our findings provide new insights on how heterogeneous cancer cell populations in tumors secure their 75 energy/ATP supply, opening the door to novel approaches to study the Warburg effect and cancer energy metabolism, highlighting new targets for more effectively combating cancer and drug resistance.
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CHAPTER 3 INHIBITORS OF GLUCOSE TRANSPORT AND GLYCOLYSIS AS
NOVEL ANTICANCER THERAPEUTICS
This chapter is modified from a peer-reviewed paper published in 2014 in the
World Journal of Translational Medicine. Yanrong Qian was the first author of this paper.
3.1 Cancer and cancer metabolism
Cancer has long been considered a group of diseases caused by genetic mutations and genetic mutations only. However, in recent decades, extensive biochemical and biological studies have convincingly demonstrated that cancers exhibit significantly reprogrammed metabolism, which plays important roles in tumorigenesis (Cairns et al.,
2011; Kroemer and Pouyssegur, 2008; Levine and Puzio-Kuter, 2010; Schulze and
Harris, 2012; Soga, 2013; Yang et al., 2013). In some cases, altered metabolism may be not only the consequence of genetic mutations, but also a contributing factor or cause of tumorigenesis (Sundaram et al., 2013; Taubes, 2012; Yun et al., 2009b). Cancer metabolic reprogramming and altered energetics have been recognized now as a hallmark of cancer (Hanahan and Weinberg, 2011).
The importance of metabolism in cancer was actually recognized long time ago.
In the1920s, the German biochemist Otto Warburg, studied glucose metabolism in cancer tissues. He found that, unlike in normal tissue, incubated cancer samples always switched from mitochondrial oxidative phosphorylation (OXPHOS) to cytosolic glycolysis even when oxygen was abundant (Bayley and Devilee, 2012). This phenomenon of so called 77 aerobic glycolysis has been known as the Warburg effect (Hsu and Sabatini, 2008;
Upadhyay et al., 2013; Vander Heiden et al., 2009; Warburg, 1956). Warburg went so far as to claim that the altered glucose metabolism was the cause of cancer; this hypothesis is called the Warburg theory of cancer. He speculated that due to some mitochondrial dysfunctions, mitochondria could not synthesize ATP and thus cells have to switch cytosolic glycolysis, leading to cancer formation (Koppenol et al., 2011; Warburg, 1956).
Biological studies in recent decades have found that Warburg’s view on the cause of the switch was largely incorrect: many cancers switch to glycolysis even without any mitochondrial defects. New biological and biochemical studies in the past decades revealed that the switch from OXPHOS to glycolysis is not just for ATP synthesis but also for biomass synthesis (DeBerardinis et al., 2008; Upadhyay et al., 2013), production of NADPH (Anastasiou et al., 2011; Upadhyay et al., 2013), a reducing agent needed to remove ROS generated by cancer cells’ accelerated metabolism, as well as synthesis of amino acids (Locasale et al., 2011; Upadhyay et al., 2013). The Warburg effect appears to be a strategic move made by cancer cells to deal with multiple requirements for growth, survival, and proliferation in a microenvironment with numerous constraints.
Altered cancer metabolism has also been recognized as a potential target for cancer therapeutics. Glucose transport and glucose metabolism are significantly upregulated in cancer as revealed by the PET scan and other detection methods (Burt et al., 2001; Gambhir, 2002; Jadvar, 2013; Kelloff et al., 2005; Kurokawa et al., 2004). The reliance of cancer cells on glucose indicates that they are addicted to the Warburg effect or glucose (Bui and Thompson, 2006; Gatenby and Gillies, 2004; Kim and Dang, 2006). 78
As a result, cancer cells are more sensitive than normal cells to changes in glucose concentration and will die before normal cells (Bui and Thompson, 2006; Gatenby and
Gillies, 2004; Kim and Dang, 2006; Liu et al., 2012). The recognition of this vulnerability of cancer cells has led to targeting glucose transport and metabolism as a new anticancer strategy. Furthermore, although targeted anticancer drugs inhibit one or more proteins or enzymes, cancers demonstrate the ability to escape inhibition using redundant signaling pathway(s). It has been proposed that targeting a signaling pathway or a metabolic process, rather than a protein in a pathway, may be more effective in preventing drug resistance and prolonging treatment effectiveness (Jones et al., 2008;
Vogelstein et al., 2013). Potential targets for this proposed new approach include glucose transport and glycolysis, the predominant glucose metabolic changes found in cancer cells.
It should be emphasized that targeting cancer metabolism is not actually an entirely novel strategy. Some of the earliest chemotherapy drugs, such as methotrexate, also target metabolism and show significant efficacy (Abolmaali et al., 2013; Chabner and Roberts, 2005; Longo-Sorbello and Bertino, 2001). As we have accumulated more knowledge about cancer metabolism, we should be able to develop more successful anticancer-metabolism drugs. In the following sections, recently developed glucose transport and glycolysis inhibitors will be described.
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3.2 Glucose transport and glucose metabolism in cancer cells – the Warburg effect
In normal cells under aerobic conditions, OXPHOS is used to make ATP, the universal energy currency in all living organisms. OXPHOS is used because it is the most efficient way for making ATP. For each molecule of glucose, ~34 molecules of ATP can be produced by OXPHOS (Koppenol et al., 2011). However, OXPHOS can proceed only when oxygen is present and abundant, a condition called normoxia. When oxygen is lacking, a condition called hypoxia, cells are forced to shift to anaerobic glycolysis to maintain ATP synthesis and energy metabolism (Altenberg and Greulich, 2004). Due to rapid growth and proliferation, a large proportion of the cancer cells in a tumor are in a hypoxic condition and thus use glycolysis to make ATP and other essential biomass molecules such as ribonucleotides. The phenomenon of OXPHOS-to-glycolysis shift in cancer cells is called the Warburg effect (Hsu and Sabatini, 2008; Koppenol et al., 2011;
Upadhyay et al., 2013; Vander Heiden et al., 2009; Warburg, 1956). Although the
Warburg effect was observed more than 80 years ago, its interpretation is still controversial and evolving. Warburg thought that the effect was caused by mitochondrial dysfunctions and the effect is a forced alternative strategy for ATP synthesis. However, research in recent decades largely disagrees with this interpretation. Recently, it has been found that the switch in cancer cells is primarily for the synthesis of biomass (e.g. of
RNA precursor and others) (DeBerardinis et al., 2008), the reducing agent NADPH
(Anastasiou et al., 2011), which is needed for clearing ROS, and the amino acid serine
(Locasale et al., 2011). ATP synthesis seems not to be a rate-limiting factor. This conclusion is very different from Warburg’s and is based on the observation that although 80 cancer cells upregulate all glycolytic enzymes, they switch pyruvate kinase (PK), the last enzyme in the glycolytic pathway, from a form with higher activity (PKM1) to that with lower activity, PKM2 (Christofk et al., 2008a; Christofk et al., 2008b; Hitosugi et al.,
2009; Wong et al., 2013). This change suggests that cancer cells do not want all the glucose obtained from the upregulated glucose transport to be converted to pyruvate, but rather diverts some glucose metabolic intermediates to other connected metabolic pathways, such as pentose phosphate pathway (PPP) for synthesis of biomass and reducing agents (Anastasiou et al., 2011; DeBerardinis et al., 2008; Locasale et al., 2011;
McCarthy, 2013). This also suggests that ATP synthesis is not the top priority of the upregulation of glucose transport and metabolism. On the other hand, since glycolysis is about 18 times less efficient compared to OXPHOS, cancer cells must drastically upregulate glycolysis to compensate for the low ATP production.
3.3 Anticancer therapeutics targeting glycolysis and its connected pathways
Currently, the Warburg effect is a very active cancer research area (Hsu and
Sabatini, 2008). Targeting glucose metabolism and transport, has been proposed as an effective anticancer strategy (Cairns et al., 2011; Kroemer and Pouyssegur, 2008).
Glycolysis, the key process of increased glucose metabolism in cancer cells, has been targeted both in vitro and in vivo (Kroemer and Pouyssegur, 2008; Pelicano et al., 2006).
Glycolysis genes are overexpressed in various cancers (Altenberg and Greulich, 2004). In addition to higher potentials for invasiveness and metastasis (Fantin et al., 2006), the glycolytic switch in cancer also increases cancer’s sensitivity to external interference 81 because of their higher dependence on aerobic glycolysis (Bui and Thompson, 2006;
Gatenby and Gillies, 2004; Kim and Dang, 2006; Liu et al., 2012).
Glucose deprivation, a method traditionally used to reduce glucose concentration in cultured cells for metabolic studies, has been used frequently in cancer research
(Aykin-Burns et al., 2009; Saito et al., 2009; Yun et al., 2009a; Zhao et al., 2008).
Glucose deprivation limits glucose supply, forcing cancer cells to slow down proliferation or undergo apoptosis (Kretowski et al., 2013; Shim et al., 1998; Singh et al.,
1999). Blocking glucose transport or glycolysis is similar to glucose deprivation, suggesting the possibility of restricting glucose supply with glucose transport or glycolysis inhibitors as an anticancer strategy.
Various inhibitors of glycolytic enzymes have shown significant anticancer efficacy. Most of the reported glycolysis inhibitors are summarized (Figure 19; Table 2).
The enzymes targeted include hexokinase (HK), phosphofructokinase (PFK), pyruvate kinase (PK), lactate dehydrogenase (LDH), and pyruvate dehydrogenase kinase (PDK).
Related studies revealed that these inhibitors induced apoptosis in cancer cells (Bhardwaj et al., 2012; Kim et al., 2007; Liu et al., 2010; Wong et al., 2008; Zhai et al., 2013).
Moreover, inhibition of glycolysis has been shown to overcome drug resistance in multiple cancer cells associated with mitochondrial respiratory defect and hypoxia (Xu et al., 2005b). Although numerous attempts to block glycolysis by using various inhibitors in cancer cells and in animal models have been made, developing clinically effective and safe glucose metabolism-targeting therapeutics is still a challenging task. 82
Glucose--
Extracellular-space- GLUTs- WZB117,-FasenMn,-etc.- Cytosol-- Glucose-- PPP- HK- G6PD- 2"DG,-3"BP--- 6"P"gluconolactone-- G6P-- GPI- Glycolysis- 6"AN--- F6P-- PFK2- 3PO,-N4A,-YZ9- F"1,6"bisP-- ALD- TKTL1- Xylulose"5"P- Glyceraldehyde"3"P-- GAPDH- Oxythiamine-- 1,3"Diphophoglycerate- PHGDH- PGK- 3"Phosphonooxypyruvate- 3"PG- PGAM1- PGMI"004A,-MJE3-- 2"PG- serine- ENO- Phosphoenolpyruvate- PKM2- ML265- Pyruvate- DCA- LDHA- FX11,-Quinoline-3"sulfonamides-
Lactate- PDH- PDK- HK2- Lonidamine- OXPHOS-
Figure 19. Glycolysis and inhibitors / activators of glycolysis as potential anticancer therapeutics. Enzymes are in red and their respective inhibitors are in blue. PPP, pentose phosphate pathway; OXPHOS, oxidative phosphorylation, shown in green.
83
Hexokinase (HK) as the first enzyme in glycolysis phosphorylates glucose to glucose-6-phophate (G6P) irreversibly, which is a rate-limiting step. In cancer cells, type
II HK (HK2) is bound to mitochondria, facilitating a high glycolytic flux rate and preventing cancer cell from apoptosis (Pedersen et al., 2002). HK2 is required for tumor initiation and maintenance and the systemic deletion of HK2 is therapeutic in mice bearing tumors (Patra et al., 2013). Thus, targeting HK2 may be an effective anticancer strategy.
2-deoxy-D-glucose (2-DG) is one of the most widely studied HK inhibitors. 2-DG is a glucose analog with a hydrogen group instead of a hydroxyl group in position 2 of glucose. Due to its structural similarity, 2-DG competes with glucose and inhibits HK with a Ki of 0.25mM (Bachelard, 1972). The product 2-deoxy-D-glucose-6-phosphate made from 2-DG cannot be processed in the following glycolytic steps and therefore blocks glycolysis, leading to ATP depletion, cell cycle arrest and cell death (Aft et al.,
2002; Zhang et al., 2006). Synergistic studies combining 2-DG and other anticancer drugs, such as adriamycin and paclitaxel, indicated that 2-DG is effective in vivo in combination with other drugs (Maschek et al., 2004). 2-DG sensitizes glioblastoma cells to other anticancer treatments and radiation (Dearling et al., 2007; Dwarakanath and Jain,
2009; Egler et al., 2008; Singh et al., 2005). Though effective, 2-DG is relatively toxic with side effects when administered to patients (Raez et al., 2013; Singh et al., 2005).
This is at least in part because 2-DG has to be used at high concentrations, around and higher than 5 mM, in order to compete with blood glucose (Strandberg et al., 2013). 84
3-bromopyruvate (3-BP) is another HK inhibitor, which has been shown to inhibit the progression of tumors in vivo (Kim et al., 2007; Ko et al., 2001; Ko et al., 2004). 3-
BP also increases the total ROS in tumor cells (Ihrlund et al., 2008; Kim et al., 2008). A recent study demonstrated that 3-BP inactivates ABC transporters, restoring drug sensitivity in malignant cells (Nakano et al., 2011). 3-BP has also been studied in combination with various anticancer drugs for synergistic effects, and it has been found to be effective in vitro (Xu et al., 2005a) and in vivo (Cao et al., 2008b), although with some hepatotoxicity (Jae et al., 2009). However, 3-BP inhibits other enzymes, such as
GAPDH, as well (Ganapathy-Kanniappan et al., 2013). Up to now, no clinical trials have been reported for 3-BP. This may be attributed to its low target specificity and relatively high toxicity.
Lonidamine specifically inhibits mitochondria-bound HK2, which is present mostly in cancer cells but not in normal cells (Floridi et al., 1981). It effectively inhibits the cell growth, decreasing lactate and ATP generation, in cancer cells (Fanciulli et al.,
1996; Floridi et al., 1998). Meanwhile, the combination of lonidamine with other anticancer agents reverts drug resistance and is effective in the treatment of various cancer cells in both pre-clinical and phase II/III studies (De Lena et al., 2001; Di Cosimo et al., 2003; Fanciulli et al., 1996). However, the combination of lonidamine and epirubicine resulted in no improvement in patients’ survival (Berruti et al., 2002).
Though lonidamine has been widely studied, its hepatotoxicity resulted in the termination of several clinical trials (Granchi and Minutolo, 2012; Price et al., 1996). These studies of the HK2 inhibitors suggest that, although HK2 is a potential target, being the first and the 85 rate-limiting step of glycolysis, inhibition of HK2 may result in severe side effects.
However, the combination of HK2 inhibitors and other anticancer drugs may still be an alternative approach for HK2-overexpressing tumors.
Phosphofructokinase (PFK) has two isoforms. PFK1 promotes the chemical reaction of fructose-6-phosphate (F6P) to fructose-1,6-bisphosphate (F-1,6-bisP), while
PFK2 catalyzes the synthesis of fructose-2,6-bisphosphte (F-2,6-biP) and reverses it back to F6P (Dunaway et al., 1988). In tumor cells, PFK2 is ubiquitously and constitutively active to produce F-2,6-biP (Atsumi et al., 2002; Bando et al., 2005; Chesney et al.,
1999). PFK2 is also inducible by hypoxia in vivo (Atsumi et al., 2002; Minchenko et al.,
2003), which is known as a microenvironment for tumor cell (Minchenko et al., 2002).
Thus, targeting PFK may be a good anticancer strategy.
3-(3-pyridinyl)-1-(4-pyridinyl)-2-propen-1-one (3PO) is the most specific known
PFK2 inhibitor with a Ki of 25µM (Clem et al., 2008; Granchi and Minutolo, 2012). 3PO suppresses glucose uptake and glycolytic flux in multiple cancer cell lines, with IC50 values ranging from 1.4 to 24µM (Clem et al., 2008). Animal studies show that 3PO inhibits tumor growth in vivo (Clem et al., 2008). In addition, a chromene derivative,
N4A, mimics F6P and is a competitive inhibitor of PFK2, with a Ki of 1.29µM (Seo et al., 2011). Its derivative, YZ9, has a Ki as low as 0.094µM (Seo et al., 2011). These inhibitors were shown to inhibit the proliferation of Hela cells (human cervical cancer cells) and T47D cells, (human adenocarcinoma cells) in vitro (Seo et al., 2011). Using high-throughput screening and structure activity relationship (SAR) studies, Brooke et al. identified derivatives of 5-triazolo-2-arylpyridazinone as a novel group of inhibitors of 86
PFK2, with the lowest IC50 of 2.6µM (Brooke et al., 2014). Although these inhibitors with extremely low IC50s are potent and promising in vitro, in vivo studies are required to assess their toxicity in animals.
3-phosphoglycerate dehydrogenase (PHGDH) catalyzes the first step of the serine biosynthesis pathway (Figure 19). The increased serine synthesis flux attributed to
PHGDH is essential to the viability of a subset of cancer cells in which the enzyme is overexpressed (Liu et al., 2013; Locasale et al., 2011; Possemato et al., 2011). Through negative-selection RNAi screening using a human breast cancer xenograft model,
Possemato et al. showed that PHGDH is required for tumorigenesis in vivo (Possemato et al., 2011). Meanwhile, using a metabolomics approach with isotope labeling, Locasale et al. showed that glycolytic flux is diverted into serine and glycine metabolism in cancer cells. This suggests that cancer cells use this specific pathway to promote oncogenesis
(Locasale et al., 2011). The PHGDH gene was found to be amplified recurrently in both breast cancers and melanoma (Locasale et al., 2011; Mullarky et al., 2011; Possemato et al., 2011). In addition, the protein levels of PHGDH are elevated in 70% of estrogen receptor (ER)-negative breast cancers (Possemato et al., 2011). Suppression of PHGDH in cancer cell lines with overexpressed PHGDH, but not in these without, causes a reduction in serine synthesis as well as cell proliferation (Locasale et al., 2011;
Possemato et al., 2011). So far, no PHGDH inhibitors have been reported, although it appears to be a good target.
Phosphoglycerate mutase 1 (PGAM1) catalyzes 3-phosphoglycerate (3-PG) to 2- phosphoglycerate (2-PG). In human cancer cells, loss of TP53 leads to upregulation of 87
PGAM1 (Hitosugi et al., 2012). In addition, Tyr26 phosphorylation of PGAM1 stabilizes the active conformation of the enzyme (Hitosugi et al., 2013). These regulations of
PGAM1 contribute to the increased glycolysis and the rapid biosynthesis in cancer cells
(Hitosugi et al., 2012; Hitosugi et al., 2013).
Inhibition of PGAM1 by shRNA increased 3-PG and decreased 2-PG levels and inhibited the proliferation of cancer cells (Hitosugi et al., 2012). Through in situ proteome reactivity profiling, PGAM1 inhibitor MJE3 was identified (Evans et al., 2005).
MJE3 inhibits PGAM1 activity with an IC50 of 33µM and reduces the proliferation of breast cancer cells in vitro (Evans et al., 2005). PGMI-004A, an alizarin derivative, is another inhibitor of PGAM1 with an IC50 of 13µM, and it leads to significantly decreased glycolysis, pentose phosphate pathway (PPP) flux and biosynthesis, resulting in attenuated cancer cell proliferation and tumor growth in vivo (Hitosugi et al., 2012).
Pyruvate kinase (PK) irreversibly catalyzes the conversion of phosphoenolpyruvate (PEP) to pyruvate coupled with the generation of ATP. PKM2 is the isoform highly expressed in embryonic cells and cancer cells during fast proliferation
(Mazurek, 2011). The switch of PKM2 to PKM1 was able to inhibit tumor growth in vivo
(Christofk et al., 2008a). PKM2 is inactive as a dimer and highly active as a tetramer.
Regulation of the transition between the dimer and the tetramer forms depends on the F-
1,6-bisP level (Mazurek et al., 2005) or the phosphorylation of tyrosine residue 105 of
PKM2, which is induced by oncogenic signals in cancer cells (Hitosugi et al., 2009).
Meanwhile, PKM2 activity is further influenced by serine and succinylaminoimidazolecarboxamide ribose-5'-phosphate (SAICAR), which adds 88 additional complexity to how PKM2 is regulated in cells and suggests that the modulation of PKM2 activity enables cancer cells to adapt their unique metabolic patterns to their specific pathological conditions (Gui et al., 2013; Hitosugi et al., 2009).
In tumor cells, the lower activity of PKM2 results in accumulation of upstream glycolytic metabolites for biosynthesis through PPP (Christofk et al., 2008b; Mazurek et al., 2002). In addition, the presence of histidine-phosphorylated PGAM1 has been found to correlate with the expression of PKM2 in both cancer cell lines and tumors (Vander
Heiden et al., 2010). In fact, cancer cells with low PKM2 activity allow PEP to transfer its phosphate group to the histidine of PGAM1 and generate pyruvate. This alternate glycolytic pathway bypasses the activity of PKM2 and decouples ATP production from pyruvate generation, facilitating the high rate of glycolysis to support the biosynthesis observed in many proliferating cancer cells (Vander Heiden et al., 2010). This decoupled
ATP production also suggests that ATP may not be the limiting factor for fast proliferation in cancer cells because cancer cells have access to increased interstitial ATP
(Commisso et al., 2013; Pellegatti et al., 2008; Qian et al., 2014).
Recently, Israelsen et al. demonstrated that PKM2 is not necessary for the proliferation of tumor cells and variable PKM2 expression was found in human tumors
(Israelsen et al., 2013). These results suggest that varied PKM2 activity supports the different metabolic requirements of various cancer cells, each with unique metabolic conditions (Israelsen et al., 2013). Though the role of varied expression of the PKM2 isoform in cancer cells is still controversial, ongoing studies focus on both inhibitors and activators of PKM2 to inhibit cancer cell growth both in vitro and in vivo. 89
Shikonin and alkannin are potent PKM2 inhibitors. Both compounds lower PKM2 activity and decrease glycolysis in MCF-7 human breast cancer cells and A549 human lung cancer cells (Chen et al., 2011). TT-232, a synthetic heptapeptide, interferes with the cellular location of PKM2 in tumor cells and induces apoptosis (Stetak et al., 2007).
However, the selectivity of these inhibitors is not very high for PKM2 and side effects were observed (Chen et al., 2011; Szende and Keri, 2003).
In fact, PKM2 was found to be less active than PKM1 (Christofk et al., 2008a), indicating that cancer cells prefer to use a less active PK to regulate glycolysis and balance their metabolic needs. Thus, in order to inhibit cancer cell growth more effectively, activators, not inhibitors of PKM2, should be used.
Activators of PKM2, such as N, N’-diarylsulfonamides, thieno-pyrrole- pyridazinones and tetrahydroquinoline-6-sulfonamides, have been identified and studied through high throughput screening and SAR exploration (Boxer et al., 2010; Jiang et al.,
2010; Walsh et al., 2011). These compounds showed potent PKM2 activation activity with a highest AC50 of 38nM (Boxer et al., 2010). Kung et al. reported a series of quinolone sulfonamides with a unique allosteric binding mode, which activate PKM2 in
A549 lung carcinoma cells (Kung et al., 2012). The activation of PKM2 reduces carbon flow to serine biosynthesis, which has been known to promote oncogenesis (Kung et al.,
2012; Locasale et al., 2011). This study suggests that targeting PKM2 confers metabolic stress to cancer cells and attenuates the unique metabolic pattern of cancer cells. Among these compounds, ML265 (or TEPP-46), a potent activator of PKM2 with an AC50 of
92nM, was found to activate PKM2 by inducing the tetramerization of PKM2 90
(Anastasiou et al., 2012; Walsh et al., 2010). ML265 has been shown to reduce tumor size, weight, and occurrence in animal models (Anastasiou et al., 2012; Walsh et al.,
2010). Recently, Xu et al. described a structurally novel series of small molecule 3-
(trifluoromethyl)-1H-pyrazole-5-carboxamides as potent PKM2 activators in vitro (Xu et al., 2014). Moreover, Guo et al. identified 2-((1H-benzo[d]imidazol-1-yl)methyl)-4H- pyrido[1,2-a]pyrimidin-4-ones as novel PKM2 activators with a novel binding mode
(Guo et al., 2013). However, their results also suggested that activation of PKM2 alone was insufficient to significantly alter the cancer metabolism (Guo et al., 2013). Although the complex roles of PKM2 in tumorigenesis remain to be elucidated, potent and selective activators of PKM2 may be valuable tools for solving the puzzle of PKM2 and combating cancer.
Lactate dehydrogenase (LDH) catalyzes the chemical conversions of pyruvate to lactate and NADH to NAD+ simultaneously. Upregulation of LDHA under c-Myc control promotes aerobic glycolysis and the growth of tumor cells (Shim et al., 1997).
Increased expression of LDHA was identified in clinical samples of multiple tumor types
(Rong et al., 2013; Yao et al., 2013). Inhibition of LDHA expression in fumarate hydratase deficient cells by RNA interference inhibited cell proliferation and tumorigenesis in vivo (Garber, 2006; Xie et al., 2011). Thus, LDHA is a potential anticancer target with multiple inhibitors already developed (Granchi et al., 2010).
Oxamate competes with pyruvate for LDHA binding with a Ki of 136µM
(Thornburg et al., 2008). However, oxamate also works as an inhibitor of aspartate aminotransferase with an even lower Ki of 28µM (Thornburg et al., 2008). Thus, oxamate 91 is a non-specific inhibitor of LDHA. FX-11, 3-dihydroxy-6-methyl-7-(phenylmethyl)-4- propylnaphthalene-1-carboxylic acid, competing with NADH as a selective inhibitor of
LDHA, inhibited the growth of xenograft tumors (Le et al., 2010).
Galloflavin, a new LDHA inhibitor, reduced ATP generation, lactate production, and inhibited growth of human breast cancer cells. However, other mechanisms in addition to inhibition of LDHA were involved in cell death induced by galloflavin
(Farabegoli et al., 2012). Moorhouse et al. used a fragment-based click-chemistry- supported approach to synthesize a series of bifunctional inhibitors of LDHA. In this approach, the structures of both natural substrates pyruvate and NADH were mimicked and linked together in a bifunctional inhibitor. The lead compound has an IC50 of 14.8µM
(Moorhouse et al., 2011). Numerous LDHA inhibitors have been identified by ARIAD
Pharmaceuticals and Genentech recently, however, these inhibitors need to be tested in vitro and in vivo in due course (Dragovich et al., 2013; Fauber et al., 2013; Kohlmann et al., 2013; Vanderporten et al., 2013). Ward et al. used fragment-based lead generation as well as X-ray crystallography to develop very potent inhibitors of LDHA. The lead compound has a remarkable IC50 of 0.27µM (Ward et al., 2012). However, these potent
LDHA inhibitors still need to be tested both in vitro and in vivo to demonstrate their potentials as anticancer therapeutics.
Granchi et al. designed and synthesized a series of N-hydroxyindole (NHI)-based compounds as competitive human LDHA inhibitors (Granchi et al., 2011). Some representative compounds were tested and shown to possess anti-proliferation activity in multiple human cancer cell lines (Granchi et al., 2010; Granchi et al., 2011). NHI-1, one 92 of these inhibitors, working with gemcitabine is active against pancreatic cancer cells synergistically (Maftouh et al., 2014). Interestingly, glycosylation of these NHI-based
LDHA inhibitors increased potencies and improved cell permeability in cancer cells
(Calvaresi et al., 2013). Linking the glucose and the LDHA inhibitor facilitates the dual- targeting strategy.
Recently, Billiard et al. showed that quinoline 3-sulfonamides inhibit LDHA and reverse aerobic glycolysis in multiple cancer cell lines (Billiard et al., 2013).
Interestingly, compound 1, an LDHA inhibitor in this study, also activates PKM2, if not directly, then at least in part due to the accumulation of F-1,6-bisP caused by LDHA inhibition. Unfortunately, because of low in vivo clearance rates and low oral bioavailability, the quinolone 3-sulfonamides are unsuitable for in vivo use (Billiard et al., 2013). In sum, though several LDHA inhibitors have been identified, further efforts are needed to test their anticancer effects in vivo as well as in clinical trials.
Pyruvate dehydrogenase kinase (PDK) favors glycolysis over mitochondrial oxidative phosphorylation (OXPHOS) by blocking the activity of pyruvate dehydrogenase (PDH) by phosphorylating it (Harris et al., 2002). Under normoxic conditions, pyruvate is taken up by mitochondria and converted to acetyl-CoA in a step catalyzed by PDH. Acetyl-CoA is an important component of the citric acid cycle and
OXPHOS. In studies in cancer cells, PDK1 expression was induced by HIF-1 in hypoxic conditions and shown to lead to increased glycolysis and suppressed OXPHOS (Kim et al., 2006; Papandreou et al., 2006). The expression of PDK1 is associated with poor prognosis in head-and-neck squamous cancer (Wigfield et al., 2008). Also, the 93 upregulation of PDK in cancer was associated with a more aggressive phenotype (McFate et al., 2008). For these reasons, PDK has been considered an attractive and promising anticancer target.
Dichloroacetate (DCA), an analog of pyruvate, has been identified as a PDK inhibitor and has been studied widely for its ability to inhibit lactate production and cancer growth (Bonnet et al., 2007; Michelakis et al., 2008; Papandreou et al., 2011;
Stacpoole et al., 1988; Whitehouse and Randle, 1973). DCA is effective in suppressing the growth of cancer cells both in vitro and in vivo (Cao et al., 2008a; Sun et al., 2010;
Wong et al., 2008; Xie et al., 2011). Several human clinical trials of DCA are on-going.
A phase II clinical trial for malignant glioblastoma has been completed and shows that
DCA can be used safely in patients with glioblastoma, suggesting that DCA is a promising anticancer agent and inhibiting glycolysis is a potent and effective anticancer strategy (Langbein et al., 2008). In addition, several clinical trials combing DCA and other anticancer drugs or therapies are in progress (Table 2).
Pentose phosphate pathway (PPP), a metabolic pathway branched off from glycolysis, provides metabolic intermediates for biosynthesis and NADPH for clearing
ROS in cells. At the first step of PPP, glucose-6-phosphate dehydrogenase (G6PD) catalyzes the conversion of G6P to 6-phophogluconolactone, coupled with generation of
NADPH. G6PD has been shown to be overexpressed in cancer cells (Langbein et al.,
2008; Ramos-Montoya et al., 2006). Therefore, inhibition of G6PH is an attractive strategy to alter cancer metabolism and attenuate cancer growth. 6-aminocicotinamide (6-
AN) is an inhibitor of G6PD that induces oxidative stress and sensitizes cancer cells to 94 drugs (Bhardwaj et al., 2012; Budihardjo et al., 1998; Varshney et al., 2003). Recently,
Preuss et al. used high-throughput screening to identify several hit compounds as novel inhibitors of G6PD with IC50s of <4µM (Preuss et al., 2013). These G6PD inhibitors reduced the viability of MCF10-AT1 mammary carcinoma cells with an IC50 of ~25µM compared to ~50µM for MCF10-A non-carcinoma cells (Preuss et al., 2013). However, its in vivo efficacy remains to be investigated.
The enzyme transketolase (TKTL) is critical for both PPP and glycolysis
(Langbein et al., 2008; Langbein et al., 2006). Transketolase-like enzyme 1 (TKTL1) has been shown to be increased in tumor cells (Chen et al., 2009; Kayser et al., 2011; Zhang et al., 2008). Down-regulation of TKTL1 inhibited cancer cell proliferation, tumor growth and metastasis (Coy et al., 2005; Hu et al., 2007; Zhang et al., 2007b). Thus, inhibiting TKTL1 is a potential anticancer strategy. Oxythiamine inhibits TKTL and the growth of cancer cells both in vitro and in vivo (Boros et al., 1997; Rais et al., 1999).
Also, oxythiamine interrupted signaling dynamics in pancreatic cancer cells (Wang et al.,
2013), and attenuated tumor cell metastasis (Yang et al., 2010). Further studies on oxythiamine are of interest.
95
Table 2. Glycolytic inhibitors and compounds that modulate glycolytic metabolism
Compound Target protein Status References 2-DG Inhibits HK Phase I-completed (Jul 2008) NCT00096707 Phase I/II-terminated (Mar 2011) NCT00633087 3-BP Inhibits HK Pre-clinical (Kim et al., 2007) Lonidamine Inhibits Phase II/III-terminated NCT00237536 mitochondrial HK2 (Aug / Dec 2006) NCT00435448 3PO Inhibits PFK2 Pre-clinical (Clem et al., 2008) N4A, YZ9 Inhibits PFK2 Pre-clinical (Seo et al., 2011) PGMI-004A Inhibits PGAM1 Pre-clinical (Hitosugi et al., 2012) MJE3 Inhibits PGAM1 Pre-clinical (Evans et al., 2005) TT-232 Inhibits PKM2 Phase II-completed (Mar 2008) NCT00422786 Phase II-terminated (Oct 2010) NCT00735332 Shikonin/ Inhibits PKM2 Pre-clinical (Chen et al., 2011) alkannin ML265 Activates PKM2 Pre-clinical (Anastasiou et al., (TEPP-46) 2012; Walsh et al., 2010) FX11 Inhibits LDHA Pre-clinical (Le et al., 2010) Quinoline 3- Inhibit LDHA Pre-clinical (Billiard et al., sulfonamides 2013) DCA Inhibits PDK Phase I-ongoing NCT00566410 Phase I-ongoing NCT01111097 Phase II-completed (Aug 2009) NCT00540176 (6-AN) Inhibits G6PD Pre-clinical (Budihardjo et al., 1998) Oxythiamine Inhibits TKTL1 Pre-clinical (Rais et al., 1999) Notes: www.clinicaltrial.gov for identifier numbers.
3.4 Glucose transporters (GLUTs) and upregulation of GLUTs in cancer
Up to 90% of cancers demonstrate a phenotype of increased glucose uptake, as revealed by PET scan and other detection methods (Czernin and Phelps, 2002; Gambhir,
2002; Higashi et al., 1998; Kelloff et al., 2005). Cancer cells also show an increased dependence on glucose as a source of energy and biosynthesis precursor for cell growth, while normal cells utilize lipids, amino acids and glucose in a more balanced fashion (Bui and Thompson, 2006; Fantin et al., 2006). Increased glucose uptake in cancer is achieved 96 primarily by upregulation of glucose transporters (GLUTs) (Cooper et al., 2003; Liu et al., 2010; Medina and Owen, 2002; Younes et al., 1996) although the recent finding that animal cells transformed with a mutated (oncogenic) Kras (Krasonc) gene exhibit macropinocytosis (Commisso et al., 2013) raises the possibility that macropinocytosis and other endocytosis may contribute significantly to glucose uptake in cancer cells.
Current research finds that upregulation of GLUTs can be attributed to oncogenic alterations in cancer cells (Dang and Semenza, 1999).
GLUTs (SLC2A) are plasma membrane-associated transporters that facilitate glucose transport across the cell membrane down the glucose concentration gradients
(Mueckler and Thorens, 2013). Up to now, at least 14 different isoforms of GLUTs have been identified in human cells (Table 3) (Mueckler and Thorens, 2013). All GLUTs share a common and highly conserved (97%) transmembrane domain composed of twelve membrane-spanning helices with less conserved and asymmetric extracellular and cytoplasmic domains (Jung, 1998; Lachaal et al., 1996; Zeng et al., 1996). Different isoforms of GLUTs are structurally and functionally related proteins and divided into 3 classes according to the similarity of their amino acid sequences (Mueckler and Thorens,
2013). They are expressed in various cell types based on cells’ unique physiological requirements for glucose (Table 3) (Medina and Owen, 2002). This differential need and thus transport of glucose is achieved by varied affinities of the GLUTs for glucose
(Medina and Owen, 2002; Wood and Trayhurn, 2003).
GLUTs that are most relevant to cancer are GLUT1 and GLUT3 (Macheda et al.,
2005; Medina and Owen, 2002; Szablewski, 2013). GLUT1 is a basal glucose transporter 97 expressed in almost all cell types (Hruz and Mueckler, 2001) and is upregulated in almost all cancer types examined (Cooper et al., 2003; Liu et al., 2010; Medina and Owen, 2002;
Younes et al., 1996). PET scans and other analytical methods have revealed membranous overexpression of GLUT1 and increase in glucose uptake by cancer cells (Higashi et al.,
1998). GLUT1 expression level is correlated with the grade, proliferative activity, differentiation, and known prognostic markers in various cancers (Cho et al., 2013;
Higashi et al., 1998; Ravazoula et al., 2003; Younes et al., 1995). Clinical studies also have shown that high levels of GLUT1 expression correlate with poor prognosis and survival (Cho et al., 2013; Kang et al., 2002; Kunkel et al., 2003; Mori et al., 2007).
Therefore, targeting GLUT1 in cancer cells is an effective strategy to block basal glucose uptake and therefore to kill the cancer cells. The discoveries of GLUT1 inhibitors will be discussed in next session. In 2014, the crystal structure of human GLUT1 has been elucidated and reported in Nature (Deng et al., 2014). This discovery will undoubtedly facilitate further development of GLUT1 inhibitors with higher potency and specificity in the future.
GLUT3, normally, is expressed primarily in the tissues with high energy demand to supplement GLUT1 (Cooper et al., 2003; Medina and Owen, 2002). GLUT3 is overexpressed in various cancers compared with their non-cancerous tissues (Macheda et al., 2005; Medina and Owen, 2002; Szablewski, 2013; Younes et al., 1997). However,
GLUT3-specific inhibitor has not been reported yet. GLUT2 is expressed in the liver, pancreatic islet cells, and retina cells (Medina and Owen, 2002; Watanabe et al., 1999).
GLUT2 has low affinity and high capacity for glucose (Efrat, 1997; Eisenberg et al., 98
2005). GLUT2 also has high affinity for fructose (Gould et al., 1991). Abnormal levels of
GLUT2 expression were detected in gastric, breast, and pancreatic cancers (Godoy et al.,
2006; Noguchi et al., 1999; Seino et al., 1993). In addition, GLUT4, GLUT5 and
GLUT12 have been found abnormally expressed in various cancers (Chandler et al.,
2003; Godoy et al., 2006; Kurata et al., 1999; Macheda et al., 2005; Szablewski, 2013).
Transport of glucose from the extracellular space into the cytoplasm is the first rate-limiting step for glycolysis (Gatenby and Gillies, 2004). Glucose metabolism is drastically upregulated in cancer (Warburg, 1956). Thus, inhibition of aerobic glycolysis by blocking glucose uptake may be more efficient than inhibiting glycolytic enzymes in cells. Therefore, GLUTs are potential targets for anticancer therapies. All known glucose transporters and their major characteristics are summarized in Table 3.
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Table 3. Expression of GLUTs and their major characteristics
Protein Expression Affinity Major Features Expression in (glucose) cancer GLUT1 Ubiquitous (abundant in High Constitutive basal Over-expressed brain and erythrocytes) glucose uptake GLUT2 Liver, retina, pancreatic Low Glucose sensing, Abnormal islet cells fructose transport GLUT3 Brain High Supplements GLUT1 Over-expressed in brain GLUT4 Muscle, fat, heart High Insulin responsive Abnormal GLUT5 Intestine, testis, kidney, Very low Fructose transport Abnormal erythrocytes GLUT6 Spleen, leukocytes, brain Low Sub-cellular U.D. redistribution GLUT7 Liver, intestine, colon, High Glucose and fructose N.D. testis, prostate transport GLUT8 Testis, brain High Sub-cellular Over-expressed redistribution, multisubstrates GLUT9 Liver, kidney, pancreatic High Multisubstrates U.D. cells GLUT10 Liver, pancreas High Glucose transport N.D. GLUT11 Heart, muscle Low Inhibited by fructose N.D. GLUT12 Heart, prostate, muscle, High Insulin-reponsive Abnormal fat, intestine HMIT Brain No H+/myo-inositol N.D. transport GLUT14 Testis N.D. N.D. N.D. Notes: HMIT stands for H+/myo-inositol transporter; N.D. stands for not determined; U.D. stands for undetectable. This table is modified and updated from Table 1 in (Medina and Owen, 2002). Due to the space limit, the references cited in this table can be found in Table 3-2 below.
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Table 3: continued
Protein Expression Affinity to Major Features Expression in glucose cancer GLUT1 (Mueckler et (Burant and Bell, (Mueckler et al., (Godoy et al., al., 1985) 1992; Gould et al., 1985) 2006; Medina and 1991; Nishimura Owen, 2002) et al., 1993) GLUT2 (Medina and (Burant and Bell, (Efrat, 1997; (Godoy et al., Owen, 2002; 1992; Gould et al., Medina and Owen, 2006; Kurata et al., Watanabe et al., 1991) 2002) 1999; Medina and 1999) Owen, 2002; Noguchi et al., 1999; Seino et al., 1993) GLUT3 (Kayano et al., (Burant and Bell, (Kayano et al., (Kurata et al., 1988) 1992; Gould et al., 1988; Medina and 1999; Medina and 1991) Owen, 2002) Owen, 2002) GLUT4 (Fukumoto et (Burant et al., (Fukumoto et al., (Szablewski, 2013) al., 1989) 1992; Keller et al., 1989) 1989; Nishimura et al., 1993) GLUT5 (Concha et al., (Burant et al., (Burant et al., 1992) (Godoy et al., 1997; Kayano et 1992) 2006; Medina and al., 1990) Owen, 2002) GLUT6 (Doege et al., (Doege et al., (Joost and Thorens, (Godoy et al., 2000a) 2000a) 2001) 2006) GLUT7 (Joost and (Li et al., 2004) (Li et al., 2004) N.D. Thorens, 2001; Li et al., 2004) GLUT8 (Doege et al., (Doege et al., (Joost and Thorens, (Goldman et al., 2000b) 2000b) 2001) 2006) GLUT9 (Evans et al., (Manolescu et al., (Joost and Thorens, (Godoy et al., 2009; Phay et 2007a) 2001) 2006) al., 2000) GLUT10 (McVie-Wylie (Dawson et al., (Dawson et al., N.D. et al., 2001) 2001) 2001) GLUT11 (Doege et al., (Doege et al., (Doege et al., 2001) N.D. 2001) 2001) GLUT12 (Rogers et al., (Rogers et al., (Rogers et al., (Chandler et al., 2002) 2003) 2002) 2003) HMIT (Uldry et al., No (Uldry et al., 2001) N.D. 2001) GLUT14 (Wu and N.D. N.D. N.D. Freeze, 2002) Notes: HMIT stands for H+/myo-inositol transporter; N.D. stands for not determined; UD stands for undetectable.
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3.5 Glucose transporter 1 (GLUT1) inhibitors
Due to the wide expression of GLUT1 and its involvement in different types of cancers (Hruz and Mueckler, 2001; Kunkel et al., 2003; Manolescu et al., 2007b; Zhao and Keating, 2007), targeting GLUT1 is a promising anticancer approach. However,
GLUT1 was not targeted therapeutically until recently. Anti-GLUT1 antibody has been shown to be effective in reducing cancer cell growth in vitro (Rastogi et al., 2007). Up to now, several groups of small-molecule GLUT1 inhibitors have been reported, which are described individually below.
Cytochalasin B and phloretin are the first two identified GLUT1 inhibitors
(Krupka, 1985). Both bind with GLUT1 with high affinity. Cytochalasin B is a mycotoxin while phloretin is natural flavonoid. Cytochalasin B binds to intracellular domain of GLUT1. Phloretin binds to intracellular and extracellular domains of GLUT1
(Salas-Burgos et al., 2004). However, cytochalasin B has other anticancer mechanisms, such as blocking cytokinesis (Chao and Liu, 2006) and is too toxic to be used in cancer treatment. Phloretin has been shown to inhibit GLUT2 (Walker et al., 2005; Wu et al.,
2009) and bind to estrogen receptor as an estrogen antagonist (Lerner et al., 1963).
Fasentin was first identified as a sensitizer for the death receptor stimuli FAS and has been shown to inhibit glucose uptake (Wood et al., 2008). Its anticancer mechanism involves the alteration of genes associated with nutrient and glucose metabolism.
Docking studies suggest fasentin interacts with a unique site on the central transport channel of GLUT1, different from phloretin and cytochalasin B (Wood et al., 2008).
Fasentin is not a GLUT1-specific inhibitor because it can inhibit both GLUT1 and 102
GLUT4 and its IC50 on GLUT1 is higher than 300µM. No in vivo study has been reported for Fasentin.
Genistein is a dietary-derived isoflavone product present in plants and has been shown to inhibit tyrosine kinases and therefore exhibit therapeutic effects against a variety of health disorders (Behloul and Wu, 2013; Li et al., 2012; Nagaraju et al., 2013;
Tarkowski et al., 2013). Genistein is also reported to be a potent inhibitor of GLUT1
(Perez et al., 2011; Vera et al., 1996). It inhibits the transport of hexose through GLUT1 in human HL-60 cells and Chinese hamster ovary (CHO) cells overexpressing GLUT1 in a dose-dependent fashion (Vera et al., 1996). Though binding studies demonstrated that genistein directly binds to the external surface of GLUT1, altering the binding of glucose to the external surface site of GLUT1 and therefore interferes with its transport activity
(Perez et al., 2011), genistein does not appear to be specific for GLUT1 and its tyrosine kinase inhibitory activity should not be neglected. A phase II clinical trial of genistein in patients with bladder cancer has been completed. However, the primary purpose of this study was to identify genistein’s effects on tyrosine kinases, not GLUT1.
Using high-throughput pairwise screening approach, two potent pyrrolidinone- derived GLUT1 inhibitory compounds were identified (Ulanovskaya et al., 2011). These compounds inhibit glucose transport mediated by erythrocyte membrane-derived vesicles
with an IC50 of 5µM (Ulanovskaya et al., 2011). However, no in vivo study has been reported for these compounds.
A group of synthetic oxime-based novel GLUT1 inhibitors have been reported recently (Tuccinardi et al., 2013). Some of these compounds are potent in inhibiting 103 glucose transport and cell proliferation in H1299 human lung cancer cells with the lowest
IC50 of 8.5µM (Tuccinardi et al., 2013). A detailed computer simulation study revealed the potential binding site for these compounds on GLUT1, which appears to be consistent with that reported for genistein (Afzal et al., 2002). The result and basic structure of these novel compounds provide bases for designing next-generation GLUT1 inhibitors and suggests further investigations in vivo.
STF-31 is a lead molecule of the 3-series, a group of compounds selectively kills von Hippel-Lindau (VHL)-deficient renal cell carcinomas (RCCs) (Chan et al., 2011).
Deficiency of VHL, a tumor suppressor, leads to aberrant HIF stabilization and therefore diminished mitochondrial activity and high dependence of glucose uptake and glycolysis in cancer cells. STF-31 was shown to inhibit more than 50% of the glucose uptake and cell growth of VHL-deficient RCCs after a prolonged incubation (48-72 hour). Also,
STF-31 is effective in inhibiting tumor growth in tumor-bearing mice. Though it was claimed that STF-31 binds to GLUT1 directly, the rapid inhibitory effects (in a range of minutes) of GLUT1 inhibition induced by STF-31 was not shown. It is possible that the mechanisms of STF-31’s inhibitory effects of glucose transport and glycolysis in VHL- deficient RCCs were secondary. Moreover, though GLUT2 has been proved not as a target of STF-31, More investigations on the GLUT1-specific inhibitory effects of STF-
31 are needed to exclude other possible GLUTs inhibitory activities.
WZB-117, as a novel small-molecule GLUT1 inhibitor, is the lead compound of a series of polyphenol as basal glucose transport inhibitors reported by our lab in collaboration of Dr. Bergmeier’s lab (Liu et al., 2012; Liu et al., 2010; Zhang et al., 104
2010). As a specific GLUT1 inhibitor, WZB-117 has an IC50 of 10µM in inhibiting the growth of A549 human lung cells (Liu et al., 2012). The specificity of its inhibition on
GLUT1 has been tested in human red blood cells (RBC), which only express GLUT1 but not other glucose transporters. However, whether WZB-117 inhibits other GLUTs remains to be elucidated. The computational docking study demonstrated that WZB-117 binds to Asn34, Arg126, and Trp412 in the central channel of GLUT1 protein through three hydrogen bonds (Liu et al., 2012). In the crystal structure of human GLUT1 reported in Nature this year, both Asn34 and Arg126 have been found conserved (Deng et al., 2014; Liu et al., 2012). The anticancer efficacy and the safety of WZB-117 were tested in nude mice. Synergistic effects of WZB-117 and anticancer drugs were reported.
Due to the ester bonds in the structure, WZB-117 is not very stable in esterase-containing human blood and serum. Therefore, new generations of GLUT1 inhibitors with higher stability and efficacy derived from WZB-117 need to be synthesized and studied. The data of the continuing study is reported in Chapter 4.
Comparison among GLUT1 inhibitors described above is summarized in Table 4.
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Table 4. Properties of GLUT1 inhibitors
Inhibitor Features Binding sites Specif Status References -icity Cytochalasin B mycotoxin Intracellular low In vitro (Scherlach et al., domain 2010) Phloretin Natural Intra- & extra- low Animal (Wu et al., 2009) flavonoid cellular domain study Fasentin Synthesis Central transport low In vitro (Wood et al., channel 2008) Genistein Dietary- External surface low Phase II NCT00118040 derived Completed (Perez et al., 2011; isoflavone Vera et al., 1996) Pyrrolidinone Synthesis N.D. N.D. In vitro (Ulanovskaya et derived al., 2011) GLUT1 inhibitors Oxime-based Synthesis Intracellular N.D. In vitro (Tuccinardi et al., GLUT1 region 2013) inhibitors 3-series / Synthesis central transport Low Animal (Chan et al., 2011) STF-31 channel study WZB-117 Synthesized central transport N.D. Animal (Liu et al., 2012) polyphenol channel study N.D.: not determined.
3.6 Future directions and challenges
From numerous examples discussed above, it can be concluded that targeting glucose transport and metabolism offers several advantages. (a) It targets a protein, enzyme or process that is significantly altered or upregulated in cancer compared to those in normal cells. The differences between cancer and normal cells potentially provides a therapeutic window by which cancer cells can be effectively inhibited without harming patients’ normal cells. (b) Targeting GLUTs, especially GLUT1 which is widely overexpressed in cancers, is equivalent to inhibiting the entire process of glycolysis, leaving cancer cells fewer options for production of sufficient amount of ATP, NADPH, 106 serine, etc. It may also be harder for cancer cells to bypass GLUT inhibition, leading to stronger and longer-lasting inhibition. To compensate for the shortage of glucose, cancer cells will have to use either other glucose transport mechanisms or other energy molecules, such as glutamine for biosynthesis and energy. Although this is possible, it is more difficult than merely bypassing the inhibition of a single enzyme in the middle of a signaling pathway. (c) Cancer cells are addicted to glucose (Bui and Thompson, 2006;
Kim and Dang, 2006), and thus more sensitive to glucose concentration changes triggered by GLUT inhibition than are normal cells. Cancer cells more readily enter cell cycle arrest or apoptosis from glucose shortage than normal cells (Liu et al., 2012).
However, there are also some weaknesses associated with the strategy of glucose transport inhibition. These include (i) GLUTs are expressed by both cancer and normal cells. Inhibiting cancer cells’ GLUTs inevitably inhibits normal cells that also use
GLUTs for their functions. The identification of a therapeutic window is absolutely essential for the success of this anticancer strategy. Fortunately, key organs in the body such as the brain and heart can use ketone bodies as a substitute for glucose (Cotter et al.,
2013; Veech, 2004). Therefore, GLUT inhibition should not result in significant energy shortage for these vital organs. (ii) Cancer cells’ reliance on glucose is not absolute.
Some cancer cells use glutamine (Hensley et al., 2013; Son et al., 2013) and others can shift from glucose metabolism to glutamine metabolism (Burgess, 2013; DeBerardinis and Cheng, 2010), bypassing glucose transport inhibition. Drugs targeting other metabolic pathways such as glutamine transport / metabolism or targeting cancer cell growth signaling may be used together with GLUT inhibitors to shut down cancer cells’ 107 energy metabolism and cell growth more effectively, leading to cancer cell death. These approaches need to be tested in cancer cells first and then in animal tumor models.
Recently, we have observed that our GLUT1 inhibitor WZB-117 (Liu et al., 2012) more effectively inhibits cancer cell lines that express the wild type Kras gene (Kraswt cells) than Krasonc cancer cell lines. Although the reason for the difference is unclear, we speculate this may be associated with the “leakiness” of cancer cells to extracellular glucose and ATP. We base this on the findings discussed in chapter 2 and a recent finding published in a 2013 Nature paper that Krasonc genotype is associated with a phenotype of macropinocytosis (Commisso et al., 2013), a type of endocytosis that non- specifically takes up extracellular molecules as large as proteins (Doherty and McMahon,
2009). In theory, Krasonc-induced macropinocytosis should be able to take up glucose or
ATP as well. Thus, to further enhance cancer treatment efficacy by GLUT inhibitors, it is imperative to ascertain not only which GLUT is upregulated in the targeted cancer, but also the genotype (such as Kras status) of the cancer. We also observed that WZB-117 was less effective in cancer cell lines with higher glycogen content. It is possible that higher intracellular glycogen content confers some degree of resistance to glucose transport inhibitors. In theory, a longer duration of GLUT inhibition should be able to exhaust intracellular glycogen storage and change GLUT inhibitor-insensitive cells into sensitive ones. These new findings may enhance GLUT inhibitors’ success in treating specific cancer types.
In summary, glucose transport and glycolysis inhibitors have been shown to be promising anticancer agents that warrant further basic science and clinical investigation. 108
Improvement in inhibitor’s efficacy (IC50), selectivity of the target, and identification of therapeutic windows, all while taking into account specific cancer’s genotype and phenotype, are needed for such inhibitors to become effective anticancer therapeutics.
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CHAPTER 4: DEVELOPMENT OF NEW GENERATIONS OF ANTICANCER
GLUCOSE TRANSPORT INHIBITORS
All the data in this chapter are unpublished at the time of dissertation defense.
4.1 Introduction
Cancer metabolism has been found recently to be essential for full understanding of oncogenesis. Abnormal glucose metabolism, also known as Warburg effect, has become an active research area and a new target for cancer therapy. Studies showed that more than 90% of cancers have upregulated glucose uptake as well as increased dependence on glucose as a source of bio-energy and biosynthesis precursor for cell growth, compared to normal cells (Bui and Thompson, 2006; Garber, 2006; Gottlieb and
Tomlinson, 2005; Warburg, 1956). In other words, cancer cells are addicted to glucose
(Hsu and Sabatini, 2008; Kim and Dang, 2006). This unique feature has already been utilized as Positron Emission Tomography (PET) scan in the clinical diagnoses and prognoses of cancers (Czernin and Phelps, 2002; Gambhir, 2002). Though the reasons for upregulated glucose uptake in cancer cells have not been completely known, numerous studies have shown that the increased expression of glucose transporters on the cancer cell membranes facilitates the increased glucose uptake in cancer cells (Liu et al., 2010).
Glucose transport, mediated by glucose transporters (GLUTs), is the rate-limiting step leading to glycolysis that is drastically upregulated in cancer cells (Gatenby and Gillies,
2004). Thus, targeting glucose transporters in cancer cells has been proposed as a novel and effective anticancer strategy (Kroemer and Pouyssegur, 2008; Liu et al., 2012; Liu et al., 2010; Zhang et al., 2010). 110
We have shown that small compound inhibitors targeting glucose transport are very effective in inhibiting cancer cell proliferation both in vitro and in vivo (Liu et al.,
2012; Liu et al., 2010; Zhang et al., 2010). However, exactly how those glucose transport inhibitors reduce cancer cell proliferation is not completely known. In addition, our previously reported GLUT inhibitors, although effective in inhibiting cancer cell growth, are not very chemically stable. Therefore, we designed, synthesized, and screened new generations of novel glucose transport inhibitors with more stable chemical structures and higher potency of inhibiting glucose transport and cancer cell growth. Also, we further studied the anticancer mechanisms of WZB-173, the lead compound of a new generation of glucose transport inhibitors.
4.2 Methods and Materials
4.2.1 Cell culture
Various cancer cell lines, including A549, human epithelial non-small lung carcinoma, and H1299, human epithelial non-small cell lung cancer, were used to test the efficacy and mechanism(s) of compound WZB-173 and derivatives in inhibiting glucose uptake and cancer cell growth. A549 and H1299 cancer cells were cultured in standard
Dulbecco’s Modified Eagle Medium with 10% fetal bovine serum and 1% penicillin in incubator with 5% CO2 and humid environment at 37°C. NL-20, noncancerous counterpart of A549 and H1299, were cultured as suggested by ATCC.
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4.2.2 Compound preparation
Compounds were designed, synthesized and prepared as 50µM stock in DMSO in
Dr. Stephen C. Bergmeier’s lab, Department of Chemistry and Biochemistry, Ohio
University. The compounds were stored at -20°C before use. DMSO was used as solvent and mock in each experiment.
4.2.3 Glucose uptake assay
By measuring the amount of the radioactive glucose uptake in cell, the glucose uptake ability was analyzed. Here 2-deoxy-D-[3H] glucose was used as the labeled marker. After seeded in 24-well plates, cells were washed with serum-free Dulbecco’s
Modified Eagle Medium for two times and incubated for 2 hours to decrease the possible influence caused by serum (Blackburn et al., 1999; Lee et al., 1998). Then, cells were washed with Krebs-Ringer-Phosphate buffer for three times and incubated for 30 minutes to be prepared for glucose uptake. Then cells were added with compounds and incubated for 10 minutes at 37°C. The mixture composed of 2-deoxy-D-[3H] glucose and regular glucose was added to initiate glucose uptake. Thirty minutes later, the cells were washed by cold phosphate buffered saline for three times to stop glucose uptake. During this process, the radioactive glucose remaining outside of cells was washed away. Then, 0.2N
NaOH was added to lyse cells. The radioactive glucoses inside the cells were transferred into scintillation vials for counting using LS 6500 Scintillation Counter (Beckman
Coulter). 112
4.2.4 Cell viability assay (MTT assay)
MTT assay is a colorimetric method to test cell proliferation ability. MTT is a chemical named Thiazolyl Blue Tetrazolium Bromide, which is widely used to test the viable ability of cells. The principle is that the live cells can utilize the yellow tetrazolium salt to form a purple formazan product and by measuring the absorbance value of the solution of the purple formazan at 570nm wavelength, the activity of the survival cells can be quantitatively determined. In this experiment, 5,000 cells were seeded in each well in 96-well plate and cultured with or without compounds for 48 hours. Ten µl of MTT was added into each well. After four-hour incubation, the medium was removed and 100
µl of dissolving solution was added. Then, the absorbance of the solution in each sample was measured.
4.2.5 Compounds stability in serum test
Compound WZB-117 and WZB-173 were incubated in serum-containing cell culture media for 0, 1, 2, 4, 6, 9, 12, 24, 48, 72 hours before the cell viability assays. Due to the existence of esterase in serum, the ester bonds in WZB-117 would be hydrolyzed and lead to the instability of this compound and therefore the lack of inhibitory effect.
The media from previous incubation were used to treat the cells as described above.
4.2.6 Western blot analysis
Compound-treated cells were washed with phosphate buffered saline for three times and lysed with protein lysis buffer. After sonication, cell lysates were centrifuged at 113
14,000 rpm at 4°C for 10 minutes. The supernatants were collected and their protein concentrations were measured by bicinchoninic acid (BCA) assay. Equal amount of (30
µg) total protein were separated by SDS-PAGE with a regular western detection stacking gel (Invitrogen), and then transferred to a nitrocellulose membrane. Then, specific antibodies for phosphorylated Rb and total Rb protein were used to detect the protein on the membrane. β-actin or tubulin was used as loading control. After being washed three times in TBST and the development of film (Kodak) by using enhanced chemiluminescence, the protein bands on the blot membranes were visualized, scanned, and analyzed.
4.2.7 Cell cycle analysis
Cell cycle is composed of four phases, G1 (Gap 1), S (DNA synthesis phase), G2
(Gap 2) and M (mitosis phase). By using flow cytometry, the distribution of cell stages can be measured and analyzed according to different amount of DNA in an individual cell. Usually, cell cycles are arrested when cells are exposed to certain cellular stress, such as glucose deprivation. Therefore, the distributions of phases of the cells treated with compounds were analyzed. Reduced glucose concentration Dulbecco’s Modified
Eagle Medium, which contains 2mM glucose (8% of normal medium, which contains
25mM glucose), were used as positive control, known as glucose deprivation (GD). Cells were treated separately with reduced glucose medium, normal medium with or without compounds for 48 hours after synchronization (serum-starved for 24 hours) (Liu et al.,
2012), then washed with cold phosphate buffered saline and resuspended in 70% cold 114 ethanol for overnight to be fixed. After ethanol was removed, the cells were treated with a mixture of propidium iodide, DNase-free RNase A and phosphate buffered saline at
37 °C for 30 minutes. The propidium iodide was used to label DNA, while DNase-free
RNase A to eliminate RNA, which would ruin the analysis result. The DNA contents of cells were measured by flow cytometry and the percentages of cells in different cell cycle phases were analyzed by ModFit software.
4.2.8 RNA isolation and realtime PCR
A549 cells were treated with compounds or glucose deprivation for 0, 1, 2, 3, 4, 6,
9, 12, 18, 24, 48 hours, respectively. RNA from these cells was isolated using RNeasy total RNA extraction kit (Qiagen) and the quality of RNA was confirmed by NanoDrop
2000C Spectrophotometer (Thermo Scientific). cDNA was synthesized using Maxima
First Strand cDNA Synthesis Kit (Bio-Rad). The transcriptions of human RB
(Retinoblastoma 1), SLC2A1 (Glut1) were quantified using Bio-Rad iCycler with
Maxima SYBR Green/Fluorescein qPCR Master Mix (Thermo Scientific). Reactions are in duplicate. The expression of TBP (TATA box binding protein) and HPRT
(hypoxanthine phosphoribosyltransferase 1) were found to be stable and used as housekeeping controls for normalization of target mRNA. The primer sets for human RB,
Glut1, TBP and HPRT were designed in the lab and synthesized by Sigma. The temperature optimization and efficiency of the primers sets were tested before the quantification tests. Statistical analysis was conducted with qBasePLUS and GraphPad
Prism 5 (GraphPad Software). 115
4.2.9 Statistical analysis
All the samples in the experiments were triplicate unless mentioned separately.
The average and standard deviation were reported in the results. Student’s t-test was used to analyze data. Significance will be set at p<0.05. *, P<0.05; **, P<0.01; ***, P<0.001.
4.3 Results
4.3.1 WZB-173, a lead compound of a new generation of glucose transport inhibitors, is
much more stable than WZB-117
According to our previous studies, we investigated WZB-117 as lead compound inhibiting the growth of cancer cells by inhibiting glucose uptake (Liu et al., 2012; Zhang et al., 2010). The chemical structure of WZB-117 is shown in Figure 20.
WZB-117 WZB-173
Figure 20. Chemical structures of compound WZB-117 and WZB-173. WZB-117 has ester bond, while WZB-173 has ether bond.
Compound WZB-117 inhibited glucose uptake in A549 human lung cancer cells
(Figure 21A). In addition, the growth of A549 cancer cells was inhibited after cells were 116 treated with WZB-117 (30µM) for 48 hours (Figure 21B). Interestingly, NL-20 cells, the noncancerous counterpart of A549, maintained a higher viability after treatment (Figure
21B). The fact that WZB-117 inhibited the growth of A549 lung cancer cells with less effect on its counterpart cell NL-20 suggested that WZB-117 had the potential to be used as a novel anticancer agent that has significantly less toxicity to normal cells.
%) *
*** ** ellviability ( C
Figure 21. The percentage of glucose uptake and viable cells in A549 and its counterpart NL-20 cells treated with compound WZB-117. A. Glucose uptake in A549 cells (n=3) was inhibited by compound WZB-117 (30µM). B. Percentage of viable A549 cells (n=6) was decreased after treated with compound WZB- 117 (30µM) after 48hr, while NL-20 had higher percentage of viable cells after WZB- 117 treatment. The data are presented as mean ± standard deviation. **, P<0.01; ***, P<0.001.
The increase of total numbers of A549 cells treated with WZB-117 was significantly inhibited after 24-hour treatment (Figure 22A). The inhibitory effect remained until 72 hours, the longest time point in this study. The protein level per cell was increased significantly after A549 cells being treated with WZB-117 for 24 hours and longer (Figure 22B). This result is consistent with our previous finding that WZB-
117 arrested cell cycles and inhibited the proliferation of cancer cells (Liu et al., 2012). 117
However, WZB-117 is not very chemically stable because that its ester bonds are very vulnerable to the esterases in the blood under physiologically conditions (Figure 20).
A B **
* * **
Figure 22. WZB-117 inhibited the proliferation of cancer cells and induces the accumulation of protein in arrested A549 cells. A. Total cell numbers of A549 cells treated with or without WZB-117 (50µM) for indicated length of time. B. Cellular proteins of A549 cells after WZB-117 treatment (50µM). The data are presented as mean ± standard deviation (n=3). *, P<0.05; **, P<0.01.
Therefore, we designed, synthesized, and screened a new generation of WZB-117 analogs with ether bonds (which are five times more stable in the serum) and identified
WZB-173 as the lead compound due to its higher stability (Figure 20; Figure 23) and high potency in inhibiting glucose uptake as well as cancer cell proliferation (Figure
24A-B).
The stability assay showed that WZB-117 with ester bond is not very stable in serum-containing media (Figure 20; Figure 23). After 12-hour incubation in serum- containing media, WZB-117 lost the inhibitory effect on the growth of H1299 human 118 lung cancer cells. In contrast, WZB-173 possesses ether bonds (Figure 20). Even after 72- hour incubation, WZB-173 still maintained its full cancer cell inhibitory activity (Figure
23). This may be an under-estimation of the duration of the activity because no longer incubation was performed.
***
WZB-117 Cellviability (%)
NS
WZB-173 Cellviability (%)
Figure 23. WZB-173 (ether bond) was at least six-time more stable than WZB-117 (ester bond) in serum-containing media. The compounds WZB-117, or WZB-173 (30µM) were incubated in cell culture media with serum (10%) for indicated time lengths (hours) as shown in x-axis before the cell viability assays. The incubation decreased effective compound concentration proportionally to the incubation times and to compounds' relative stability in the serum- containing media. The compound-containing media were then incubated with H1299 cells for 48 hours for cell viability assays. After 12-hour incubation in serum-containing media, WZB-117 lost the inhibitory effect on the growth of H1299 human lung cancer cells. In contrast, even after 72-hour incubation, WZB-173 still maintained its full inhibitory activity. The data are presented as mean ± standard deviation (n=6). ***, P<0.001; NS, no significant difference.
119
The result of glucose uptake assay showed that compound WZB-173 inhibited glucose uptake in A549 human lung cancer cells in a dose-dependent fashion (Figure
24A). The IC50 of WZB-173 in glucose uptake assay was about 1µM. The growth of
A549 cancer cells was inhibited when cells were treated with WZB-173 (30µM) for 48 hours. The GI50 of WZB-173 in A549 cell viability assay was about 10µM. More importantly, its counterpart normal cells, NL-20, showed higher viable cell numbers after the WZB-173 treatment (Figure 24B). The GI50 of WZB-173 in NL-20 cells, noncancerous lung cells, was about 30µM, approximately three times higher than in
A549 human lung cancer cells. Therefore, A549 cancer cells were more sensitive to
WZB-173 than its counterpart normal NL-20 cells, which is consistent with our previous study on WZB-117 (Liu et al., 2012). This result showed the WZB-173 has less cytotoxicity towards normal cells than cancer cells and it could be used as a potential anticancer agent in future studies.
120
* ***
** *** *** (%) viability Cell
Figure 24. Glucose uptake and viable cell percentage in A549 cells and NL-20 cells treated with compound WZB-173. A. Glucose uptake in A549 cells (n=3) was inhibited by compound WZB-173, which showed a dose-dependent effect. B. Viable A549 cells (n=6) were decreased sharply after being treated with WZB-173 (30µM) for 48 hours, but NL-20 had a higher survival rate. The data are presented as mean ± standard deviation. *, P<0.05; **, P<0.01; ***, P<0.001.
4.3.2 WZB-173 induced cell cycles arrested at G1 phase in A549 human lung cancer cells
through the regulation of phosphorylation and total Rb protein
To investigate the mechanisms by which WZB-173 inhibited the growth of cancer cells, we tested the cell cycle distribution of cancer cells after the treatment of compound
WZB-173 for 48 hours. The cell cycles were arrested at G1 phase in A549 human lung cancer cells treated with compound WZB-173 (30µM) for 48 hours (Figure 25). Low- glucose media (2mM glucose equals to 8 % of regular glucose concentration) was used as a positive control. A similar distribution of G1-phase arrest was induced in A549 cancer cells grown in low-glucose media (Figure 25). These results suggested that WZB-173 121 might have inhibited the growths and cell cycles of A549 cells through the same mechanisms as that of low-glucose media (Figure 25).
**
*** ***
Figure 25. Cell cycle arrest after cancer cells treated with compound WZB-173. A549 human lung cancer cells were arrested in G1 phase after being treated with compound WZB-173 (30µM) for 48hr. DMSO was used as negative control and low- glucose medium (2mM glucose equals to 8% of regular glucose concentration) was used as positive control. The data are presented as mean ± standard deviation (n=3). *, P<0.05; **, P<0.01; ***, P<0.001.
To study the mechanism(s) of G1 cell cycle arrest induced by WZB-173 in A549 cancer cells, the phosphorylation and total level of Rb protein were studied by using
Western blot (Figure 26). Rb, the retinoblastoma protein coded by RB gene, is a tumor suppressor protein, whose dysfunction leads to cancers (Murphree and Benedict, 1984).
Rb prevents cell progression along the cell cycle through G1 into S phase if the cell is not ready to divide (Das et al., 2005). The phosphorylation of Rb allows cell to progress in cell cycle through the G1/S checkpoint and divide into two daughter cells. The Western blot analyses showed that the phosphorylation levels and the total levels of Rb were reduced when A549 human lung cancer cells were treated with WZB-173 or glucose- 122 deprived media for 24 or 48 hours, suggesting that the mechanism of WZB-173-induced
G1 cell cycle arrest could be through the reduction of protein level and phosphorylation of Rb, a mechanism previously reported (Hahm and Singh, 2007). However, exactly how the reduction of total and phosphorylation of Rb was induced by WZB-173 in A549 cells was unknown.
Figure 26. WZB-173 decreased the phosphorylation and the total levels of Rb protein. WZB-173 (30µM) inhibited the phosphorylation of Rb. DMSO was used as negative control and low glucose concentration medium (2mM glucose equals to 8% of regular glucose concentration) was used as positive control.
In order to determine whether the decreased levels of Rb were regulated at transcriptional level or at translational level, real time PCR were used to measure the mRNA level of Rb in A549 cells treated with WZB-173 from 1 to 48 hours. The results showed that the mRNA levels of Rb were not affected when A549 cells were treated with
WZB-173 (Figure 27). The similar results were observed in A549 cells treated with
WZB-117 or glucose-deprived media as positive controls. Therefore, the decreased Rb 123 phosphorylation and total protein levels were likely to be due to translational changes but not transcriptional regulations.
Figure 27. Rb mRNA expression in A549 cells was not influenced after WZB-173 treatment for up to 48 hours. Rb mRNA levels were normalized by TBP (TATA box binding protein) and HPRT (hypoxanthine phosphoribosyltransferase 1) as housekeeping genes. DMSO was used as negative control. 2mM low-glucose medium or WZB-117 (30µM) was used as positive controls. The data is presented as mean ± standard deviation (n=2).
Glut1 mRNA levels were also tested in A549 human lung cancer cells treated with WZB-173 or WZB-117. Interestingly, the increase of the transcription of Glut1 gene in A549 treated with WZB-117 was induced at 3 hours (Figure 28). However, there was no significant change of the Glut1 mRNA level in A549 cells treated with WZB-173 within 24 hours, which is similar to the Glut1 mRNA level in A549 treated by low- glucose media (Figure 28). Therefore, it appears that WZB-173 and WZB-117 had different effects on the Glut1 mRNA level changes but the reason for this difference is presently unknown. 124
* ** ** * * * * * * *
Time (h)
Figure 28. WZB-117 induced mRNA expression of Glut1 while WZB-173 did not. Glut1 mRNA expressions were tested in A549 cells treated by WZB-117 or WZB-173 for different length of time. Glut1 mRNA levels were normalized by TBP (TATA box binding protein) and HPRT (hypoxanthine phosphoribosyltransferase 1) as housekeeping genes. DMSO was used as negative control. 2mM low-glucose medium was used as positive control. The data is presented as mean ± standard deviation (n=2). *, P<0.05; **, P<0.01.
4.3.3 DRB series compounds as a new generation of glucose transport inhibitors
Further studies on the mechanisms of WZB-173 in inhibiting the growth of cancer cells are needed. In the mean time, new generations of WZB-117 or WZB-173 derivatives as novel glucose transport inhibitors were designed, synthesized and screened.
The new compounds were named as the DRB series. The glucose uptake assays and cell viability assays were conducted to study the structure and activity relationships (SAR) in order to improve the inhibitory efficacies of novel compounds on both glucose uptake and cancer cell growth. The assay results are presented in Table 5. The structures of these compounds were attached in Appendix 1.
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Table 5. Data for DRB series compounds in glucose uptake and cell viability assays in H1299 human lung cancer cells.
Compound Glucose uptake (%) Cell viability (%) Mock 100.0±4.0 100.0±6.0 WZB-117 10.7±1.0 35.0±6.0 DRB-1 79.6±6.4 44.9±4.1 DRB-5 31.8±2.4 63.6±4.6 DRB-6 8.2±0.5 71.3±5.2 DRB-7 11.5±1.6 66.0±12.2 DRB-8 17.9±1.8 13.8±2.8 DRB-9 11.3±1.8 16.7±11.5 DRB-10 82.6±6.3 39.2±7.9 DRB-11 22.9±5.8 110.5±9.9 DRB-12 43.9±4.1 121.0±11.3 DRB-13 39.3±5.4 122.7±8.6 DRB-14 88.3±3.4 83.7±8.3 DRB-15 82.0±3.5 72.9±12.1 DRB-16 100.2±3.8 68.5±3.2 DRB-17 15.2±1.2 45.0±7.0 DRB-18 18.3±4.5 22.5±7.1 DRB-19 48.5±6.0 89.6±7.1 DRB-20 26.8±2.2 109.5±3.7 DRB-21 18.9±2.9 32.5±6.1 DRB-22 36.6±4.5 103.0±6.6 DRB-23 25.1±2.0 58.3±12.8 DRB-24 67.9±5.6 83.0±14.0 DRB-25 78.3±10.9 97.1±12.1 DRB-26 28.1±2.7 79.5±8.5 DRB-27 80.0±1.0 66.6±7.8 DRB-28 45.2±5.3 95.0±16.9 DRB-29 14.8±2.4 81.0±8.0 DRB-30 85.6±4.7 56.2±4.2 DRB-31 67.2±3.5 53.3±5.5 126
Table 5: continued DRB-32 24.9±1.4 69.7±5.3 DRB-33 52.2±6.5 74.3±10.1 DRB-34 70.6±2.8 67.1±5.4 DRB-35 11.3±0.9 139.9±10.7 DRB-36 59.1±1.7 87.0±9.0 DRB-37 94.7±8.5 91.2±7.6 DRB-38 60.5±3.6 74.0±14.0 DRB-39 20.8±1.5 62.0±12.0 DRB-40 72.5±4.8 75.3±10.0 DRB-41 57.8±4.6 78.0±9.5 DRB-42 35.8±5.8 93.9±11.1 DRB-43 75.9±1.6 77.9±7.4 DRB-44 47.6±10.9 29.1±11.7 DRB-45 49.0±1.5 72.5±11.2 DRB-46 78.6±5.8 48.0±3.0 DRB-47 72.6±7.8 77.0±9.0 KKB-1 13.9±1.6 103.5±5.4 KKB-2 6.3±0.3 104.1±8.4 TWB-1 7.3±1.5 51.3±3.6 JDB-1 75.4±6.8 80.3±11.8 JDB-2 60.3±2.0 65.2±5.6 Note: Compounds were tested at 30µM. DMSO-treated cells served as negative control (100%). Data are presented as mean ± standard deviation.
In order to identify the best compound in DRB series, the correlations between the glucose uptake and cell viability activities of these compounds were determined (Figure
29). The compounds at the lower left corner with color labels are these compounds with the highest potency in inhibiting both glucose uptake and cancer cell viability. Also, both activities of these compounds may be directly linked. 127
120
100
80
60
40
D-18 D-21 D-9 Glucoseuptake (%) 20 D-17
D-8 TWB1 0 0 25 50 75 100 125 150 Cell viability (%)
Figure 29. Correlations between the glucose uptake and cell viability for assayed compounds. At lower left corner, the colored squares corresponding to the colored labels are the compounds with highest activities among all the compounds tested (n=48). D-8, DRB-8; D-9, DRB-9; D-17, DRB-17; D-18, DRB-18; D-21, DRB-21; TWB1, TWB-1.
After the identification of new generations of glucose uptake inhibitors in DRB series, IC50s and GI50s of these DRB compounds were calculated and listed in Table 6.
The IC50 and GI50 test results for DRB-18, the lead compound for the new generation of glucose uptake inhibitors are shown in Figure 30.
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Table 6. IC50 and GI50 of compounds of DRB series in H1299 human lung cancer cells.
Glucose uptake Cell viability Compound IC50 (µM) GI50 (µM) WZB-117 9.6 ± 1.0 25.9 ± 6.8 DRB-17 15.6 ± 1.9 24.2 ± 3.7 DRB-18 20.1 ± 2.8 25.7 ± 4.6 DRB-21 17.7 ± 1.0 > 30 TWB-1 4.3 ± 1.5 > 30 Notes: Compounds were tested at a series of doses. DMSO-treated cells served as negative control (100%). Data were presented as mean ± standard deviation.
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A B
Cell viability (%) viability Cell
Figure 30. Glucose uptake IC50 assay and cell growth GI50 assay in H1299 human lung cancer cells. A. Glucose uptake IC50 assay. H1299 cells were rinsed by serum-free DMEM for three times and KRP buffer for three times. Different doses of DRB-18 were added and incubated with cells for 10 minutes. 3H-glucose was then added and the glucose uptake was initiated. At the end of the assay, the cells were rinsed by cold PBS and lysed and the radioactivities were counted. The radioactivity of each sample stands for the uptake of glucose in cells (n=3). The mock treatment was set as 100%. The IC50 was calculated by using the software Prism 6. B. Cell growth GI50 assay. H1299 cells were seeded one night before the assay. DRB-18 was prepared in cell culture medium in the range of doses shown in the figure. H1299 cells were incubated in the fresh-prepared medium with DRB-18 for 48 hours. At the end of the cell growth assay, MTT were added and incubated with cells for 4 hours. The absorbance of each sample at wavelength of 570nm was counted. The absorbance of each sample stands for the viability of cells (n=6). The mock treatment was set as 100%. The GI50 was calculated by using the software Prism 6.
The toxicities of these compounds were tested in NL-20 cells, noncancerous lung
epithelial cells, as counterparts of A549 and H1299 human lung cancer cells. The
toxicities were quite high as presented in Table 7. On the other hand, the correlation
between a compound’s toxicity in a cell line and its toxicity in vivo has been found to be
relatively poor and animal study of the compound is needed for the final determination of
the cytotoxicity of the compound towards normal cells in the body. For example, Taxol, 130 an anticancer drug widely used worldwide, was found to be quite toxic in a cellular assay in 1964 (Walsh and Goodman, 1999) and more toxic than our GLUT inhibitors in our assay (data not shown).
Table 7. Cell toxicity of compounds in NL-20 human noncancerous lung epithelial cells.
NL-20 cell viability Compound (30µM) WZB-117 63±4.0 DRB-8 0±0.8 DRB-9 0±0.6 DRB-17 0±0.7 DRB-18 0±0.7 DRB-21 0±0.7 TWB-1 0±0.4 Notes: Compounds were tested at 30µM. DMSO-treated cells served as negative control (100%). Data were presented as mean ± standard deviation.
4.3.4 DRB-18, a lead compound of new generation of glucose transport inhibitors, was
much more potent than WZB-117 in NCI-60 cancer cell panels
Since DRB-18 is the lead compound of a new generation of glucose uptake inhibitors, it was tested for its anticancer activity in the NCI-60 cancer cells panel in a single-dose test (10µM) in comparison with WZB-117. The result is shown in Table 8 and Appendix 2&3. As shown in the table, the red color indicates the improved growth inhibition of DRB-18 on the tested cancer cell lines compared with WZB-117, while the green color indicates the decreased inhibition of growth. The growth percent were 131 decreased in 57 out of 60 DRB-18 treated cancer cell lines. Among nine cancer types,
DRB-18 showed strong inhibition in all cell lines of six cancer types. These cancer types are leukemia, CNS (central nervous system) cancer, melanoma, ovarian cancer, renal cancer, prostate cancer, and breast cancer. The average of growth rates of NCI-60 cancer cell lines decreased from 60.11% of WZB-117 to 24.61% of DRB-18. Therefore, DRB-
18 is much more potent than WZB-117.
Importantly, the trends of inhibitions of various cancer cell lines among cancer panels are very similar for both WZB-117 and DRB-18. For example, among several ovarian cancer cell lines, the growth percent of OVCAR-5 treated with WZB-117 was
95.10% as the highest. When treated with DRB-18, the same cell line showed a 73.62% growth percent also as the highest among all the ovarian cancer cell lines tested. The same phenomenon can be found in several other cancer types, such as, EKVX and NCI-
H226 in non-small cell lung cancer (NSCLC), SF-295 in CNS cancer, HT29 in colon cancer, and A498 in renal cancer. On the other hand, the cancer cells with the strongest inhibition in each cancer type also showed a very similar trend, that the WZB-117-treated cancer cells with the lowest growth percent within a given cancer type remained the lowest growth percent when treated with DRB-18. For example, in ovarian cancer cells, the growth percent of OVCAR-3 treated with WZB-117 was 22.49% as the lowest. When treated with DRB-18, the same cell line exhibited a 10.94% growth percent as the lowest among the ovarian cancer cell lines tested as well. The same phenomenon can be found in several other cancer types, such as, NCI-H460 and NCI-H522 in non-small cell lung cancer (NSCLC), LOX IMVI in melanoma, ACHN, SN12C, UO-31 in renal cancer, and 132
PC-3 in prostate cancer. These correlations between the two NCI-60 cancer panel studies strongly suggested that WZB-117 and DRB-18 have similar inhibition trends in various cancer types and these two compounds are likely to inhibit these cancer cell lines by binding to the same target, GLUT1, and use similar inhibitory mechanism.
In the mean time, six cancer cell lines, including EKVX (80.20%), NCI-H226
(85.73%), SF-295 (74.19%), OVCAR-5 (73.62%), and A498 (82.16%), from five different cancer types were inhibited no more than 30%, suggesting that DRB-18 doesn’t have a general toxicity against all cancer cells. This also suggests that DRB-18 may not be very toxic towards all normal cells and DRB-18’s cytotoxicity is selective.
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Table 8. Comparisons between the growth percent of WZB-117 and DRB-18 in NCI-60 cancer cell panels.a
Panel / Cell Line WZB-117 DRB-18 Leukemia CCRF-CEM 29.50 9.13 HL-60(TB) 30.20 8.41 K-562 73.81 12.28 MOLT-4 47.49 -10.49 RPMI-8226 61.50 15.98 SR No data -33.00
Non-Small Cell Lung Cancer A549/ATCC 50.57 21.00 EKVX 80.29 80.20 HOP-62 50.91 40.47 HOP-92 65.50 -11.02 NCI-H226 75.56 85.73 NCI-H23 68.81 3.70 NCI-H322M 85.64 17.56 NCI-H460 36.97 2.22 NCI-H522 29.42 12.52
Colon Cancer COLO 205 63.87 90.20 HCC-2998 92.50 22.67 HCT-116 37.67 24.45 HCT-15 43.36 7.28 HT29 97.42 49.09 KM12 50.82 -1.46 SW-620 73.54 25.91
CNS Cancer SF-268 30.80 28.29 SF-295 89.49 74.19 SF-539 36.71 25.84 SNB-19 67.28 29.51 SNB-75 58.61 41.09 U251 46.96 21.89
Melanoma LOX IMVI 32.36 2.86 MALME-3M 90.75 -3.38 M14 53.26 25.33 MDA-MB-435 71.71 30.89 SK-MEL-2 90.66 33.34 SK-MEL-28 61.39 31.94 SK-MEL-5 47.40 32.75 134
Table 8: continued UACC-257 81.10 46.15 UACC-62 74.29 38.58
Ovarian Cancer IGROV1 27.92 24.24 OVCAR-3 22.49 10.94 OVCAR-4 60.64 27.78 OVCAR-5 95.10 73.62 OVCAR-8 54.18 23.62 NCI/ADR-RES 43.39 15.42 SK-OV-3 80.03 54.67
Renal Cancer 786-0 49.49 23.02 A498 114.14 82.16 ACHN 36.80 0.11 CAKI-1 54.81 37.37 RXF 393 74.35 21.16 SN12C 33.81 -27.78 TK-10 95.62 52.33 UO-31 33.28 11.90
Prostate Cancer PC-3 33.54 7.21 DU-145 52.18 23.37
Breast Cancer MCF7 75.02 9.21 MDA-MB-231/ATCC 66.40 -52.18 HS 578T 67.15 42.70 BT-549 48.17 39.89 T-47D 56.77 11.29 MDA-MB-468 92.95 32.53
Mean 60.11 24.61 Range 91.65 142.38 Note: a, The growth percent was done in a single dose of 10µM. Red color indicates the increased growth inhibition, while green indicates the decreased inhibition compared to WZB-117. The viable cells at the beginning and the end of the assay were assigned as 0% and 100%, separately. Negative data means the number of viable cells were less than the number of cells at the starting point of the assay.
135
The average growth percent (AGP) of cancer panels treated with DRB-18 are much lower compared to that of WZB-117, indicating the higher potency of DRB-18 as an anticancer reagent (Table 9). The ratio in Table 9 equals the AGP of each cancer type treated by WZB-117 divided by the AGP of the same cancer types treated by DRB-18.
The mean ratio (2.4) as shown in bold equals the AGP of 60 cancer cell lines treated with
WZB-117 divided by the AGP of 60 cancer cell lines treated with DRB-18. The ratios highlighted in red are the ratios above mean (2.4), suggesting the higher potency of DRB-
18 in inhibiting the growth of these specific cancers types than WZB-117. For example, in the panel of leukemia, the ratio is as high as 6.9, suggesting that DRB-18 have very high potency and specificity in general inhibition of the growth of leukemia compared to other cancer types.
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Table 9. The average growth percent (AGP) in each cancer panel and the ratio between the averages for cancer panels treated with WZB-117 and DRB-18.
Cancer Panel WZB-117 DRB-18 Ratioa (Cell Line Number) Leukemia (5) 48.5 7.1 6.9 NSCLC (9) 60.4 28.0 2.2 Colon Cancer (7) 65.6 31.2 2.1 CNS Caner (6) 55.0 36.8 1.5 Melanoma (9) 67.0 26.5 2.5 Ovarian Cancer (7) 54.8 32.9 1.7 Renal Cancer (8) 61.5 25.0 2.5 Prostate Cancer (2) 42.9 15.3 2.8 Breast Cancer (6) 67.7 13.9 4.9 Mean 60.1 24.6 2.4b Note: a, The ratio equals the AGP of a specific cancer panel treated with WZB-117 divided by the AGP of corresponding cancer panels treated with DRB-18. b, The ratio (2.4) equals the AGP of 60 cancer cell lines treated with WZB-117 divided by the AGP of 60 cancer cell lines treated with DRB-18. The ratios above 2.4 were highlighted in red color.
The grwoth percent of NCI-60 cancer cell lines treated by WZB-117 and DRB-18 were grouped based on cancer types in Figure 31. In these nine panels, the links between each cell line indicated the trend of changed potency of DRB-18 in the inhibition of cell growth compared to that of WZB-117. The slopes of these lines were almost all negative and parallaled, suggeting the improvement of the potency and a similar mechanism of inhibiting cancer cell growth shared by both compounds. The increased potency of DRB-
18 may be attributed to the prolonged stability compared to WZB-117.
Interestingly, two cancr cell lines showed postive slopes, indicating the decreased inhibition of DRB-18 compared to that of WZB-117. For instance, the grwoth percent of
NCI-H226 in NSCLC increaed from 75.56% to 85.73% and COLO 205 increased from 137
63.87% to 90.20% in colon cancer (Table 8; Figure 31). Taking into consideration that the growth percent of these cells treated by WZB-117 was very high already, these cell lines may not be very dependent on GLUT1, and therefore not sensitive to GLUT1 inhibitors. These resutls indirectly suggetted the selectivity of both WZB-117 and DRB-
18 on GLUT1 and that there is no general toxicity caused by either comopound.
By comparing the inhibition of growth percent among all cancer types, we found that DRB-18, as an effetive GLUT1 inhbitor, is very potent in the inhibition of several cancer types, especially leukemia (Table 8; Table 9; and Figure 31). This is consistant with previous reports that GLUT1 inhbitors are very effectvive in inhibiting leukemia cells (Akers et al., 2011) and renal cancer cells(Chan et al., 2011). 138
100 Leukemia 80 CCRF-CEM 60 HL-60(TB) K-562 40 MOLT-4 20 RPMI-8226 Growth percet (%) Growth 0 WZB-117 DRB-18 -20
NSCLC 100 A549/ATCC EKVX 80 HOP-62 HOP-92 60 NCI-H226 40 NCI-H23 NCI-H322M 20 NCI-H460 NCI-H522 0 Growth percent (%) Growth WZB-117 DRB-18 -20
Colon Cancer
100 COLO 205 80 HCC-2998 60 HCT-116 HCT-15 40 HT29 20 KM12 SW-620 0 Growth percent (%) Growth WZB-117 DRB-18 -20
139
CNS Cancer 100
80 SF-268 SF-295 60 SF-539 SNB-19 40 SNB-75 20 U251
Growth percent (%) Growth 0 WZB-117 DRB-18 -20
Melanoma 100 LOX IMVI 80 MALME-3M M14 60 MDA-MB-435 SK-MEL-2 40 SK-MEL-28 SK-MEL-5 20 UACC-257
Growth percent (%) Growth 0 WZB-117 DRB-18 -20
Ovarian Cancer
100
80 IGROV1 OVCAR-3 60 OVCAR-4 OVCAR-5 40 OVCAR-8 NCI/ADR-RES 20 SK-OV-3
Growth percent (%) Growth 0 WZB-117 DRB-18 -20
140
Renal Cancer 120 100 786-0 80 A498 ACHN 60 CAKI-1 40 RXF 393 SN12C 20 TK-10 0 Growth percent (%) Growth -20 WZB-117 DRB-18 -40
Prostate Cancer 100 80
60 PC-3 40 DU-145 20
Growth percent (%) Growth 0 WZB-117 DRB-18
Breast Cancer 100 80 MCF7 MDA-MB-231/ATCC 60 HS 578T 40 BT-549 T-47D 20 MDA-MB-468 0 WZB-117 DRB-18 -20 Growth percent (%) Growth -40 -60
Figure 31. Growth percent of NCI-60 cancer cell lines treated by WZB-117 and DRB-18 grouped according to cancer types. In each panel, the same cell line was linked through a line, indicating the trend of changes. 141
4.4 Disscussion
We have screened new generations of novel glucose transport inhibitors synthesized by Dr. Bergmeier’s lab and identified WZB-173 and DRB-18 as two lead compounds with higher stability (Figure 23) and potency in the inhibition of glucose uptake and growth of cancer cells (Figure 24; Table 5; and Table 8).
As a lead compound in the new generation of glucose uptake inhibitors, WZB-
173 is much more stable than previous compound WZB-117 in the serum-containing medium (Figure 20; Figure 23). It is also likely to be much more stable than WZB-117 in vivo. Glucose uptake assays and cell viability assays provided additional evidence to support that WZB-173 has higher stability, higher anticancer efficacy and milder toxicity to normal cells, compared to WZB-117 (Figure 24). The results from cell cycle analysis, western blots and real time PCR assays suggested that WZB-173 induces cell cycle arrest through the down-regulation of Rb at the protein and phosphorylation levels (Figure 25;
Figure 26; Figure 27). Rb is a tumor suppressor that regulates cell cycle at the G1/S checkpoint (Das et al., 2005). However, how the reduction of protein and phosphorylation of Rb was induced by WZB-173 in A549 cells remains unknown. It is possible that the WZB-173-mediated decrease of total protein Rb was due to its increased proteasomal degradation (Hahm and Singh, 2007). In addition, WZB-117 induced the increase of mRNA of Glut1 in treated A549 cells, while WZB-173 did not (Figure 28), suggesting that different mechanisms may be involved in the inhibition of cancer cell growth by these two compounds. 142
Due to the potent inhibitory activities on the glucose uptake and cancer cell growth, DRB-18 was identified as one of lead compounds of DRB series, a new generation of small-molecule glucose uptake inhibitors (Table 5; Figure 29). The IC50 and GI50 of DRB-18 were experimentally estimated (Table 6; Figure 30).
As a lead compound, DRB-18 showed significantly enhanced potency in the NCI-
60 cancer panels than WZB-117 in the inhibition of all cancer types cells (Table 8; Table
9; Figure 31). DRB-18 had increased inhibition of growth in 57 out of 60 cancer cells tested compared with WZB-117 (Table 8; Figure 31). The increased cell-killing activity was possibly attributed to the improved stability and efficacy of DRB-18. The change from ester bonds in WZB-117 to amine bonds in DRB-18 contributes to the stability of the compound. In the mean time, WZB-117 and DRB-18 have similar structures (Figure
20; Appendix 1) and the data in NCI-60 cancer panels study showed the similarity of the trend of the inhibitory effects of both compounds in multiple cancer types (Figure 31), suggesting DRB-18 may inhibit the growth of cancer cells through inhibiting GLUT1, the same mechanism as WZB-117 does.
Furthermore, MDA-MB-231, a metastatic triple-negative and Krasonc breast cancer cell line, was resistant to WZB-117 (Table 8). The inhibition of the growth of
MDA-MB-231 was 66.40% when treated by 10µM WZB-117. In contrast, the growth of
MDA-MB-231 cells was significantly decreased to -52.18% by DRB-18 at 10µM (Table
8). Triple-negative breast cancer cells, which lack estrogen receptor (ER), progesterone receptor (PR) and Her2/neu receptor, are known to be more aggressive and resistant to chemotherapies targeting the three receptors (Albergaria et al., 2011). As a Krasonc breast 143 cancer cell line, MDA-MB-231 may also have the phenotype of macropinocytosis for internalization extracellular ATP and other components to promote survival and drug resistance, as discussed in Chapter 2. Therefore, potential anti-triple-negative-breast- cancer drugs are of great value. However, more studies are needed to elucidate the detailed mechanism(s) of DRB-18 inhibiting MDA-MB-231 cells growth.
To further delineate the mechanism(s) by which compound WZB-173, DRB-18 and other novel small-molecule glucose transporters inhibit the growth of cancer cells, various studies are needed in the future. Red blood cells and their derived vesicles, which only express GLUT1, can be utilized to identify the target of compounds (Liu et al.,
2012). Since the crystal structure of human GLUT1 has been elucidated at very high resolution (Deng et al., 2014), the docking study of novel glucose transport inhibitors on human GLUT1 can be done to verify the binding of compounds to GLUT1 using computational analysis. Glycolytic capacity assays in cancer cells treated with compounds can be used to study the inhibition of glycolysis induced by the inhibition of glucose transport (Liu et al., 2012). Also, according to the results of previous studies, the possible mechanisms inhibiting the growth of cancers cells, such as the induction of apoptosis, autophagy and ER stress, which were known as induced by the inhibiting the glucose uptake, can be studied (Liu et al., 2012).
In summary, the studies described in this chapter show significant improvements in both stability and anticancer potency of two new compounds (Figure 23; Figure 31).
They will facilitate the on-going development of WZB-117 analogs targeting glucose transport in cancer cells with even higher anticancer potency. This work will also 144 contribute to the improved understanding of the Warburg effect in cancer cells and targeting the upregulated glucose transport as an effective anticancer therapy.
145
CHAPTER 5: FUTURE WORK
5.1 Introduction
Despite progress made in research of the Warburg effect, the biological reasons for ATP synthesis by aerobic glycolysis in cancer cells are only partially understood.
Intriguingly, intratumoral (extracellular) ATP levels are found to be 103 to 104 times higher than those in normal tissues (Pellegatti et al., 2008). In Chapter 2, we showed that extracellular ATP (exATP) in the range of the intratumoral ATP levels induced large intracellular ATP (inATP) concentration increase (Figure 7; Figure 8) and promoted survival of A549 human lung cancer cells (Figure 3-6). Moreover, this study provide first pieces of evidence that exATP is internalized by cancer cells via macropinocytosis
(Figure 9; Figure 11; Figure 16), which significantly contributes to their growth and drug resistance (Figure 17). These findings potentially change our understanding of ATP supply and ATP sharing among cancer cells, also highlighting a novel anticancer target.
In Chapter 3, we summarized glycolysis inhibitors and glucose transport inhibitors reported up to now. In Chapter 4, we presented WZB-173 and DRB-18 as two lead compounds of novel glucose transporter inhibitors with higher stability (Figure 23) and potency (Table 8-9; Figure31) compared to WZB-117, the previous reported GLUT1 inhibitor from Dr. Bergmeier’s and our labs (Liu et al., 2012; Zhang et al., 2010).
Although we have shown the significance and potentials of these studies, numerous questions remain to be answered. In the following sections, the future work based on these early findings will be discussed.
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5. 2 Study of exATP in cancer cells and tumors
The following is a diagram for the proposed future ATP studies.
inATP homeostasis
Sources of exATP internalization Drug exATP in vitro and in vivo resistance
Metastasis
Figure 32. Diagram for the future studies of ATP study.
5.2.1 Mechanism study of ATP internalization
5.2.1.1 exATP may be internalized through non-macropinocytosis endocytosis
Although we have shown that A549 human lung cancer cells internalized exATP through macropinocytosis (Figure 9; Figure 11), other presently unknown processes may also be involved in the internalization. We hypothesize that other endocytic processes, 147 such as endocytosis, internalize exATP into A549 cancer cells. To test this hypothesis, we will use low-molecular-weight (LMW) fluorescent dextran (3,000 Da), a tracer of non-macropinocytotic endocytosis (Whalley et al., 1995), and fluorescent nonhydrolyzable ATP with a different color to demonstrate the co-localization in A549 cells under fluorescence microscope. Internalization and colocalization of fluorescent
ATP with LMW dextran suggest the presence and functionality of non-macropinocytotic endocytosis. Also, luminescence ATP measurement assays and fluorescent microscopy will be used to confirm the results with the application of siRNA knockdown the expression of endocytic proteins, such as clathrin (Ivanov, 2008), and several endocytosis inhibitors, such as Chlorpromazine and Filipin (Ivanov, 2008).
5.2.1.2 exATP negatively regulates intracellular ATP synthesis, including glycolysis and mitochondrial oxidative phosphorylation in A549 cancer cells
Although we have shown that the exATP was internalized resulting in the increase of inATP in A549 cancer cells even when both glycolysis and mitochondrial oxidative phosphorylation (OXPHOS) were blocked (Figure 12), whether or how exATP affects internal ATP syntheses is presently unknown. We hypothesize that exATP negatively regulates intracellular ATP synthesis, including glycolysis and mitochondrial oxidative phosphorylation in A549 cancer cells. This hypothesis is proposed based on the consideration that if cancer cells have plenty ATP supply from outside (Pellegatti et al.,
2008; Qian et al., 2014), no high levels of internal ATP synthesis would be necessary. To test this hypothesis, Seahorse metabolic analyzer, as a carbohydrate metabolism 148 measurement instrument (Wu et al., 2007), will be used to detect the changes of extracellular acidification rate (ECAR), an indicator of glycolysis rate, and oxygen consumption rate (OCR), an indicator of OXPHOS, if any, induced by exATP treatment.
To confirm these results, the activities or the expression levels of glycolytic enzymes can be measured by using metabolic assays or Western blots. For example, phosphoglycerate mutase 1 (PGAM1) is a recently identified alternative enzyme for pyruvate kinase (PK) that converts PEP to pyruvate (Vander Heiden et al., 2010). The difference between these two enzymes is that the reaction conducted by PK produces a molecule of ATP, whereas
PGAM1 does not (Vander Heiden et al., 2010). Since exATP-treated cancer cells exhibit increased inATP levels (Figure 7), the activity of PGAM1 and/or the expression of
PGAM1 may be increased to reduce the internal ATP synthesis through glycolysis.
Meanwhile, the activities and levels of PK may be decreased. To test this, different amounts of extracellular ATP will be added to A549 cells and the activities and expression levels of PGAM1 and PK at different time points will be measured for comparison. Up to now, why PGAM1, the alternative enzyme of PK, is present and how it is regulated remains largely unknown. If our hypothesis is validated, it will be the first time to identify the regulatory mechanism of PGAM1 by exATP.
5.2.1.3 Purinergic receptor signaling is involved in the exATP-mediated inATP increase and other processes
ATP is not only an energy currency in all higher organisms, but also an important signaling molecule (Idzko et al., 2014). Therefore, we hypothesize that purinergic 149 receptor signaling is involved in the exATP-mediated inATP increase and other processes. To test this hypothesis, ATP-related purinergic receptor inhibitors, such as suramin (Tatur et al., 2007), will be used to block the exATP-induced perinergic receptors signaling and the inATP levels of the cancer cells will be measured. The release of Ca2+ is usually an intermediate step as the downstream signal of activated purinergic receptors and an upstream signal relay for functional effects in cells (Tatur et al., 2007).
Therefore, by using BAPTA, a Ca2+ chelator (Zamora et al., 2012), to block the Ca2+ release in the cancer cells treated with exATP, our hypothesis can be tested by measuring the inATP levels in cells. To confirm the results, siRNA knockdown of purinergic receptors, as a second method, will also be used.
5.2.1.4 ATP internalization is a well-regulated pulsatory process
During the study of exATP-induced inATP increase, we observed fairly reproducible fluctuations of inATP levels at various time points in A549 cells (data not shown). More noticeable, when A549 cells were treated with oligomycin and exATP for about 8 hours, we almost always observed a relatively large peak of inATP increase (data not shown). This unique and prominent phenomenon has constantly been observed during the entire ATP study. This phenomenon has never been reported. However, it was difficult to explain why the peak existed and how it was regulated then. Interestingly, we also found out that the inATP increase was always within a concentration range under various conditions (Figure 7; Figure 8; Figure 12), suggesting that the increase of inATP is vigorously regulated. Here, we hypothesize that ATP internalization is a well-regulated 150 pulsatory process instead of a steady one. The mechanisms of regulation of ATP homeostasis within the cancer cells may be through the regulations of more or less / faster or slower endocytosis / macropinocytosis processes, and/or through the regulation of purinergic receptor signaling, etc. To study the pulsatory process inATP increase, inATP measurement at multiple time points, minutes in interval, not in hours as was done previously, for A549 cells treated with various doses of exATP will be needed. The kinetics of inATP increase in A549 cells induced by exATP can be measured and calculated. The inATP concentration ranges of A549 cells treated with various exATP doses will be measured. The inATP increase induced by exATP could be detected in seconds after ATP addition (data not shown). Therefore, the interval between every two adjacent time points of measurement at the initial stages of inATP increase should be within minutes, not hours. At every moment, the inATP concentration is a total sum of several dynamic processes including ATP synthesis, ATP hydrolysis, ATP internalization and ATP release. The pulsatory phenotype suggested that the balance of all these processes for reaching equilibrium of inATP levels is a well-regulated process for the purpose of maintaining inATP homeostasis.
5.2.1.5 Cancer cells with plenty inATP may release ATP
Furthermore, if the inATP increase is a well-regulated and dynamic process, it is possible that the cancer cells may release extra inATP into extracellular spaces when inATP is more than cancer cells can consume. To test this hypothesis, after A549 cancer cells treated with extracellular glucose at different concentrations, or glucose deprivation 151
(GD) or oligomycin, which would alter intracellular ATP synthesis rates and affect inATP levels (Qian et al., 2014), the exATP released from these treated cells into the culture media will be examined.
5.2.1.6 Lung cancer cell lines internalize exATP the way as A549 cells do
Based on the finding that A549 human non-small cell lung cancer cell line internalized exATP (Figure 11), we speculate that other lung cancer cell lines also internalize exATP as A549 cells do. To test this hypothesis, we propose to use other lung cancer cell lines, such as H1299, a second non-small cell lung cancer cell line, to study the internalization of exATP in the same assays as we did in A549 cells. Additional lung cancer cell lines may also be used. The completion of the study will enable us to understand if exATP internalization is a general phenomenon among lung cancer cells.
5.2.1.7 Other cancer types internalize exATP the way A549 cells do
One step further, we also speculate that other types of human cancer cell lines also internalize exATP as A549 cells do. To test this hypothesis, multiple cancer cell lines, such as MCF7, a human breast cancer cell line, MDA-MB-231, a metastatic triple- negative human breast cancer cell line, and RKO, a human colon cancer cell line, will be used to study exATP internalization as we did in A549 cells. The completion of the study will show if exATP internalization is a general phenomenon among various human cancer types. If this is positively confirmed, more cancer cell lines from other cancer types may be included in this study. 152
5.2.1.8 Some exATP internalization is initiated by Kras mutation status
A549 cancer cells have a Krasonc mutation (Choi et al., 2010; Krypuy et al., 2006), which has been proved to induce internalization of extracellular molecules such as proteins (Commisso et al., 2013). We speculate that Krasonc caused exATP internalization through macropinocytosis in Krasonc-carrying cancer cells. To test this hypothesis, siRNA of Krasonc knock down and Kras inhibitors will be used in exATP internalization studies. The completion of the study will enable us to understand if Krasonc is the cause of macropinocytosis in A549 cells and other types of cancer cells.
5.2.1.9 exATP internalization is stimulated by exATP as energy molecule
When A549 cells were treated by exATP, the cells’ inATP increased (Figure 7;
Figure 8). As we know, nucleoside-diphosphate kinases (NDKs) are enzymes converting
ATP to GTP or vise versa (Lacombe et al., 2000). Since GTP is required as an energy supplier for endocytosis (Huotari and Helenius, 2011), it is possible that some of the increased inATP would be converted into GTP to stimulate endocytosis (Dhani et al.,
2008). Therefore, we hypothesize that exATP stimulates the endocytic process as an energy molecule. To test this hypothesis, various doses of exATP and HMW dextran will be applied to the cells and the numbers of macropinosomes will be counted under the microscope and analyzed. Also, the intracellular GTP levels of cells with the same treatment will be measured and analyzed.
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5.2.1.10 Internalized exATP are accumulated in lysosomes and released into cytosols
Based on the finding that A549 cells internalize exATP through macropinocytosis
(Figure 11), we speculate that internalized exATP is accumulated into lysosomes and then released into cytosol afterward (Huotari and Helenius, 2011; Luzio et al., 2007;
Zhang et al., 2007c). Although the pH within lysosome is at 4.6-5.0 (Luzio et al., 2007),
ATP could be accumulated inside of lysosomes (Zhang et al., 2007c). To test if internalized exATP is located in lysosomes, we propose to use a lysosome tracers/markers (Kazmi et al., 2013) combined with nonhydrolyzable fluorescent ATP analog to localize and visualize the accumulation of internalized exATP. How to study the release of internalized ATP from lysosome needs to be further discussed.
5.2.1.11 exATP is also internalized in vivo in real tumors
Based on the finding that the ATP level in intratumoral space is much higher than that in normal tissues (Pellegatti et al., 2008), and that A549 cells internalized exATP through macropinocytosis in vitro (Qian et al., 2014), we speculate that internalized exATP is also internalized through macropinocytosis in vivo. To test this hypothesis, we propose to conduct tumor-bearing nude mice study for ATP internalization in vivo. HMW
Dextran and/or fluorescent nonhydrolyzable ATP will be injected into the tumor grown on nude mice. The tumors will be surgically removed from the sacrificed mice, fixed, sliced, and mounted on glass slides. The numbers of macropinosomes, as fluorescent spots in cancer cells on each tumor slice, will be counted and analyzed. The completion of the study will not only strongly confirm the study presented in Chapter 2, but also 154 prove that exATP internalization happens in vivo, which will have a great impact in current research of the Warburg effect.
5.2.2 Identification of sources of ATP increase in intratumoral spaces
5.2.2.1 High intratumoral ATP in interstitial spaces may come from normoxic cancer cells
It is well known that there are heterogeneity and interactions among hypoxia and normoxia cancer cells and stromal cells (Marusyk et al., 2012). The cancer cells in tumors are heterogeneous (Marusyk et al., 2012). Immune cells, stromal cells, and endothelial cells are also present in the tumors (Marusyk et al., 2012). Due to varied distances between cancer cells and the blood vessels in a tumor, the supply of oxygen and glucose or other nutrients to different cancers cells in the same tumor are different
(Marusyk et al., 2012; Swanton, 2012).
A simple calculation for ATP production in normoxic and hypoxia cancer cells can be informative and revealing. For example, consider cancer cells take up 10 molecules of glucose. One of the ten glucoses will undergo OXPHOS and produce 36
ATP (Koppenol et al., 2011). Meanwhile, about 9 molecules of glucose undergo glycolysis and produce lactate as well as 18 ATP (Koppenol et al., 2011). Therefore, normoxic cancer cells can approximately produce about 36+18=54 molecules of ATP from 10 glucose molecules (Koppenol et al., 2011). In contrast, extremely hypoxic cancer cells can produce only about 18 molecules of ATP from 10 glucose molecules because their OXPHOS cannot properly function without oxygen. Therefore, the hypoxic cancer 155 cells may need much more exATP compared with its normoxic counterparts and depending upon the severity of hypoxia.
Actually, it has been reported that stretched A549 cancer cells released inATP to extracellular space (Grygorczyk et al., 2013). And functional ATP synthases have been identified on the plasma membrane of A549 cancer cells and produced exATP
(Deshpande et al., 2012; Lu et al., 2009; Wen-Li et al., 2012). Inhibition of the ecto-ATP synthesis inhibited cancer cell proliferation and induced apoptosis (Deshpande et al.,
2012; Wen-Li et al., 2012). Therefore, normoxic cancer cells may produce more ATP than they can consume and share them with hypoxic cancer cells that are short of ATP.
To test this hypothesis, inATP levels in normoxic and hypoxic cancer cells will be compared first. Then the exocytic and endocytic processes will be detected in cancer cells under normoxia and hypoxia. For the same passage of cancer cells, the normoxic and hypoxic culture conditions will be switched and the same assays will be conducted. We speculate that the inATP levels and endocytic process will be also switched along with the change in oxygen status.
5.2.2.2 High intratumoral ATP in interstitial spaces may come from necrotic cancer cells
Due to the extreme hypoxia and nutrient-defective in the center of the tumor sphere, the cancer cells there usually undergo necrosis, which lead to the loss of cell membrane integrity and release of intracellular components, including inATP into extracellular space (Proskuryakov et al., 2003). Thus, we speculate that the high intratumoral ATP in interstitial spaces in a tumor may also come from necrotic cancer 156 cells. To test this hypothesis, 3-D culture for cancer cell spheres under different hypoxic and nutrient-deprived conditions will be applied and the exATP from the spheres’ culture medium will be measured and compared.
5.2.2.3 High intratumoral ATP in interstitial spaces may come from stromal cells
Within a tumor, cancer cells and stromal cells, such as immune cells, endothelial cells, coexist in a unique tumor environment (Marusyk et al., 2012). Therefore, it is possible that the high intratumoral ATP in interstitial spaces may also come from stromal cells, such as endothelial cells and T lymphocytes, which have been reported to release
ATP into extracellular spaces under various conditions (Coussens and Werb, 2002). For example, stimulated T lymphocytes, in addition to its interaction with cancer cells through cytokines, also release large amount ATP to modulate cancer metabolism through purinergic receptor signaling (Antonioli et al.). In the first intratumoral paper published by Italian scientists (Pellegatti et al., 2008), immune-deficient nude mice were used to detect the high exATP concentrations in interstitial spaces in tumors. If immune cells were one of the resources of the increased ATP in intratumoral space, the real exATP level would even be higher because nude mice have a defect in T lymphocytes
(Cordier and Haumont, 1980).
Meanwhile, endothelial cells during acute inflammation increase release of ATP into extracellular space (Bodin and Burnstock, 1998; Milner et al., 1990). In fact, tumors usually have inflammation locally (Coussens and Werb, 2002), which may stimulate the 157 release of ATP from endothelial cells into interstitial spaces to form a high ATP-level tumor microenvironment.
In addition, cancer-associated fibroblasts interact with cancer cells and accelerate tumor growth and metastasis through ROS stress, autophagy and aerobic glycolysis
(Pavlides et al., 2012). Therefore, we speculate that these cancer-associated fibroblasts may produce exATP, which may be internalized by cancer cells to support their growth and metastasis.
The strategies for how to test these hypotheses remain to be formulated. The completion of this study will identify the sources of high exATP in tumor interstitial space, suggest potential anticancer targets for blocking the increase of exATP, and imply the possible diagnostic and prognostic strategies for cancers by measuring locally high exATP levels in tumor environment.
5.2.3 Mechanism study of exATP-induced drug resistance
5.2.3.1 Mechanism study of exATP-induced drug resistance to TKIs
In Chapter 2, we have shown that exATP rescued A549 cells treated by tyrosine kinase inhibitors (TKIs), including sunitinib and pazopanib (Figure 6; Figure 17C), whose anticancer mechanism is competition between the TKIs and inATP for the ATP binding sites of tyrosine kinase receptors (RTKs) and therefore inhibit their downstream cell growth-promoting signaling (Papaetis and Syrigos, 2009). Since the exATP induced inATP increase in A549 cells (Figure 7; Figure 17B), the TKIs’ anticancer effect would be reduced, leading to drug resistance. A possible mechanism by which exATP induced 158 drug resistance to TKIs in A549 cells is that the increased inATP compete with TKIs’ binding for ATP binding sites on RTKs and therefore enhance the phosphorylation of
RTKs and their downstream cell growth signaling. Another possible mechanism is that the increased inATP may promote the general phosphorylation of key proteins in cell growth signaling in cancer cells. To test these hypotheses, the phosphorylation and total proteins of RTKs and key proteins in cell growth signaling will be measured by Western blots.
5.2.3.2 Mechanism study of exATP-induced drug resistance to anticancer drugs
Moreover, ATP-binding cassette transporters (ABCs) have been reported to play significant roles in multi-drug resistance (MDR) in cancer cells’ drug resistance (Han and
Zhang, 2004). The activities of ABC are highly dependent on the binding and hydrolysis of ATP (Han and Zhang, 2004). Therefore, the increased inATP induced by exATP may enhance the activities of ABC in cancer cells and therefore play critical roles in exATP- induced drug resistance in cancer cells. To test this hypothesis, the ABC inhibitors will be used in cancer cells treated with TKI and other anticancer drugs and the viability of these cancer cells will be measured by using MTT assays and clonogenic assays. Since ABC inhibitors may have the direct cell inhibitory effect, ABC inhibitor-treated cancer cells will be used as control in this study. The site-specific mutagenesis for ATP binding site of ABCs will be used to confirm the results. The completion of this study will further the understanding on drug resistance in cancer cells and suggest new targets to overcome with the drug resistance in cancer treatment. 159
5.2.4 Studies on exATP-induced metastasis
During the ATP internalization study, we have shown that exATP promoted survival and drug resistance of cancer cells (Figure 6; Figure 17). Meanwhile, we also observed weaker attachment of exATP-treated cancer cells to cell culture dishes than non-treated cancer cells (data not shown), which suggested that the exATP-treated cells have the tendency to leave from the original location and move to another place. The invasion and metastatic processes require energy (Nieman et al., 2011) and hypoxic cancer cells are responsible for invasion and metastasis (Sullivan and Graham, 2007).
Therefore, we speculate that exATP may promote invasion and metastasis of cancer cells.
5.2.4.1 exATP may promote detachment and invasion of cancer cells
To test the hypothesis that exATP promote detachment, cell adhesion will be measured for cancer cells treated with or without exATP (Lee et al., 2014). The trans- well assays will be used to compare the invasion capabilities of cancer cells treated with or without exATP (Liang et al., 2014). Also, the clonogenic assays for the floating cancer cells in cell culture will be conducted to confirm the results. Furthermore, the same assays can be performed under hypoxic conditions. We anticipate the effects caused by exATP would be more pronounced under hypoxia (Schumacher et al., 2013; Sullivan and
Graham, 2007).
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5.2.4.2 exATP may promote metastasis of cancer cells in vivo
To test if exATP may promote metastasis of cancer in vivo, infusion exATP in breast cancer-bearing mice will be used to study the lung metastasis (Que et al., 2008).
The completion of this study will not only expand our understanding on exATP’s effects on cancer cells, but also imply potential targets for prevention of cancer progress and metastasis.
5.3 Development of new generations of glucose transporter inhibitors
Op miza on of GLUT inhibitors -- SAR study
Stability and IC50& GI50 tests
Iden fica on of target(s) -- RBC and vesicle studies
Mechanism study of GLUT1 inhibitors
Toxicity and efficacy study in vivo -- Animal studies
Figure 33. Flowchart for the future work of development of novel GLUT1 inhibitors. If the goal of finding potent inhibitors is not achieved during the process, a new round of SAR study will be conducted to produce compounds with higher potency, specificity, and less toxicity than earlier compounds.
5.3.1 Optimization study of GLUT1 inhibitors
To optimize the WZB-117-derived GLUT inhibitors, the inhibition of glucose transport in cancer cells and the viability of the compound-treated cancer cells will be examined (Table 5). In addition, the stability of compounds in cell culture medium, an in 161 vitro substitute for in vivo, will be investigated in serum as described in Chapter 4 (Figure
23). As demonstrated in Chapter 4, the group of DRB series compounds with very stable amine bonds was the most promising and they also showed some correlation between the inhibition of glucose uptake and cell viability (Figure 29). In the future, the development of amine-bond WZB-117 derivatives should be a major focus.
5.3.2 Identification of targets
To determine if the target of novel glucose transporter inhibitor is GLUT1, red blood cells (RBC) and their derived vesicles, which express GLUT1 as their sole glucose transporter, will be used (Liu et al., 2012). The docking for novel GLUT inhibitor in human GLUT1 protein will be performed by in computational software to identify the theoretical binding sites of the inhibitor on GLUT1 (Liu et al., 2012). The result of WZB-
117 binding to GLUT1 central channel will be used as a starting point and for comparison. After confirming the amino acid residues involved in the compound-GLUT1 interaction at the theoretical binding sites, the site-specific in vitro mutagenesis will be made to generate numerous GLUT1 protein mutants to study the binding of novel inhibitors to GLUT1. The completion of this work will help identify narrow-spectrum inhibitors specifically targeting GLUT1.
5.3.3 Mechanisms study of GLUT1 inhibitors
To elucidate the mechanism(s) by which novel compounds inhibit the growth of cancer cells, various studies will be conducted. Glycolytic capacity assay in cancer cells treated with compounds will be performed (Liu et al., 2012). According to previous 162 studies, GLUT1 inhibitors would induce glucose deprivation, ER stress, ROS increase, cell cycle distribution, programmed cell death, senescence, and autophage (Chen et al.,
2014; Liu et al., 2012). Thus, same assays will be performed to study the possible mechanisms inhibiting the growth of cancers cells. Antibodies corresponding to various protein factors involved these processes will be used to separately detect the changes in activation or expression of the protein factors with western blot analysis. GLUT1 antibody, various glucose transport inhibitors, such as fasentin (Wood et al., 2008), phloretin (Krupka, 1985) and glucose deprivation (Liu et al., 2010) will be used as positive controls in these studies. Thus, WZB-173, DRB-18 and other compounds can be further developed into new anticancer therapeutics.
5.3.4 Animal studies for safety and efficacy
To investigate the inhibition of the growth of cancer in nude mice by using novel compounds, nude mouse models with human cancer xenografts will be used to determine the safety and efficacy of the novel compounds in vivo. First, the safety and drug toxicity studies will be done to determine the proper dose range for compound injection. During the nude mice experiment, the tumor volume, food intake, body weight, and blood glucose level will be measured and analyzed weekly for the entire study (Liu et al.,
2012). After the mice are sacrificed, potential biomarkers, such as the mRNA and protein of GLUT1, will be measured in tumor samples by realtime PCR, western blot and immumohistochemistry staining, separately. The studies on the novel compounds in cancers will provide us with additional data that may lead a better understanding of the 163 relationship between glucose transport and growth of cancer cells in vitro and in vivo.
Meanwhile, the effective glucose uptake inhibitors can be used as a new approach to study basal glucose transport and glucose metabolism, which is critical for the survival of cancer cells. If our goal can be accomplished, this proposed work will provide us with not only a deeper understanding on how the inhibition of glucose transport leads to the inhibition of cancer cell growth, but also a new anticancer strategy in vivo.
5.3.5 Optimization of screening strategy
How to choose the cell lines as models for optimization of GLUT1 inhibitors is very important for the success of the process. NCI-60 cancer panel results (Table 8; Table
9; Figure 31) provide us with some strong evidence and clues for selecting the candidates of cancer types and cancer cell lines in future study. Unlike other cancer types, all leukemia cancer cell lines in the NCI-60 panel cells were strongly inhibited by DRB-18
(Table 8; Table 9; Figure 31). Therefore, leukemia may be a good cancer target for
GLUT1 inhibitors and they may be good model candidates for target identification, and animal studies.
The selection of assays and assay conditions largely determine the quality of the data generated from it. For example, under hypoxia, glucose uptake and cell viability assays will be more effective and informative in screening GLUT1 inhibitors than performing the assays under normoxic conditions.
An interesting question arises concerning what a “good” compound is. The definition of a good compound as an effective GLUT1 inhibitor need to have the 164 following features in current assay system: (1) high glucose-uptake-inhibitory effect in both cancer cells overexpressing GLUT1 and RBCs, (2) high cell-viability-inhibitory effect, (3) high stability, (4) low toxicity to normal cells.
It is difficult to tell whether a broad-spectrum GLUT inhibitor is better than a specific GLUT inhibitor targeting a specific type of glucose transporter. Pan-GLUT inhibitor, such as CG-5, has been reported (Lai et al., 2014). Broad-spectrum GLUT inhibitors will be multi-GLUT-targeting, resulting in a general inhibitory effect on most cancer cells. On the other hand, a specific GLUT inhibitor will inhibit one specific type of GLUTs. The high specificity of the inhibitor more effectively blocks glucose transport in these cancer cells overexpressing and heavily relying on a specific type of GLUTs, leading to strong inhibition of cancer cells without causing severe side effects in normal cells.
5.3.6 Optimization of the selectivity of GLUT1 inhibitors
Although the brain and heart, the most important organs in human body and are highly dependent on glucose, they can also utilize ketone bodies as alternative energy sources for metabolism and survival (Hasselbalch et al., 1994; Kodde et al., 2007).
Since red blood cells (RBCs) express GLUT1 as their only glucose transporter
(Liu et al., 2012), RBCs have to solely depend on GLUT1 for glucose transport.
Therefore, GLUT1 inhibitors will be more toxic to RBCs. Thus, how to distinguish red blood cells from cancer cells are of high value in GLUT1 inhibitor studies, especially clinically. Another concern is how to overcome hemolysis in RBCs (Chan et al., 2011). 165
Therefore, novel delivery strategy of GLUT1 inhibitors can be explored. For example, the high ATP and low pH condition in intratumoral spaces (6.2-6.9 in intratumoral extracellular spaces compared to 7.3-7.4 in normal extracellular spaces)
(Calorini et al., 2012; Pellegatti et al., 2008) can be used for selective drug delivery. Also,
GLUT1 inhibitor can be linked to antibodies binding cancer biomarkers to improve the selective delivery of GLUT1 inhibitors to cancer cells in vivo.
5.4 Links between ATP internalization and GLUT 1 inhibitors studies
The increased stability of DRB-18 enhances the inhibition of glucose uptake and therefore the inhibition of cancer cell growth. For example, the MDA-MB-231 triple- negative human breast metastatic cancer cells were very resistant to WZB-117 but very sensitive to DRB-18 (Table 8; Figure 31). MDA-MB-231 cells have higher intracellular glycogen content and respond to ATP depletion faster than other cancer cell lines
(Bensaad et al., 2014; Pelletier et al., 2012; Rousset et al., 1981), theoretically making them more resistant to WZB-117, which is an unstable GLUT1 inhibitor. Since cancer cells are addictive to glucose (Bui and Thompson, 2006; Gatenby and Gillies, 2004; Kim and Dang, 2006), the depletion of glucose or inhibition of glycolysis, lead to shortage of
ATP (Liu et al., 2012) and other metabolic deficiencies (Locasale et al., 2011; Tong et al., 2009) and restore drug sensitivity (Nakano et al., 2011). We speculate that the higher glycogen content within the MDA-MB-231 cells can provide the cells with extra glucose storage, making them less dependent on extracellular glucose supply and thus less sensitive to WZB-117 treatment. The stability of DRB-18 drastically enhances the 166 duration of the inhibitory effect on glucose transport and therefore, the storage of glycogen within MDA-MB-231 cells would be exhausted during the inhibition by DRB-
18. To test this hypothesis, cell viability assays, ATP measurement assays, and glycogen measurement assays can be used to study the effect of DRB-18 on cell viability of MDA-
MB-231 cells and their glycogen levels. DAB, an inhibitor of glycogen phosphorylase will also be used to block the conversion of glycogen to glucose inside the cells to study the contribution of glycogen for the ATP level and survival of cancer cells treated with
DRB-18 (Pelletier et al., 2012). WZB-117 will be used as control for comparison with
DRB-18.
In Chapter 4, the DRB series compounds showed various patterns of inhibitory effects on glucose transport and cell viabilities in H1299 human lung cancer cells (Figure
29). If the chart is divided in four quadrants, the compounds would be grouped into four categories according to their different activities. For example, the lower left quadrant contains those compounds with high inhibitory effects in both glucose uptake and cell viability assays. Thus, those compounds should be good candidates as GLUT1 inhibitors for target identification and animal studies. In contrast, the up right quadrant contains the compounds with low inhibitory activity in both assays. Thus, those compounds were not of interest in this study. However, the compounds located at up left quadrant had low inhibitory activity on glucose uptake but high on cell viabilities. These compounds might kill the cancer cells through mechanism(s) other than inhibiting glucose transport. Thus, those compounds are not of interest of the study, either. On the other hand, the compounds in the lower right quadrant had high inhibitory effects on glucose uptake but 167 low on cell viabilities. They might still be good candidates as GLUT1 inhibitors because the inhibitory effects can be partially reduced by other possible glucose supply in the cancer cell tested, such as macropinocytosis, other endocytosis, and glycogen storage, etc. Both macropinocytosis and other endocytosis were observed in H1299 human lung cancer cells during the study (data now shown). More studies are needed for identifying the roles of these compensatory effects in compound studies.
Macropinocytosis and glucose transport complement with each other (Commisso et al., 2013). A single block of either macropinocytosis or glucose transport may not be sufficient to completely block the energy intake in some cancer cells. Using the combination of macropinocytosis and glucose transport inhibitors may drastically reduce the energy intake of cancer cells, destroy the ROS balance, deplete the anabolic metabolites, and therefore efficiently inhibit the growth of cancer cells. These two strategies are similar in that they both targeting cancer energy metabolism. Combining with these energy transport inhibitors to generate synergistic effects, other anticancer drugs may be more effective in treating cancers (Cao et al., 2008b; Liu et al., 2010; Xu et al., 2005a) and inducing less drug resistance than being used alone (Nakano et al., 2011).
The cocktail medicine/therapy may be widely used to treat cancers in the future, in a fashion similar to the cocktail therapy for HIV (Ascierto and Marincola, 2011).
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APPENDIX 1. STRUCTURES AND PARAMETERS OF DRB SERIES COMPOUNDS
HPLC FW Compound Structure Purity (g/mol) # (%)
O N N N 279.34 DRB-1 -
Cl
O O 425.69 DRB-5 91
Cl Cl OH OH Cl
NO2 O
O O 337.71 DRB-6 99
OH Cl
NO2
O OH 295.68 DRB-7 100
OH Cl
Br Br
O O 514.59 DRB-8 95
OH OH Cl
O O 384.85 DRB-9 100
OH OH 203
O N N N OH 311.34 DRB-10 - HO
378.46 DRB-11 100 O O OH OH
HO OH 382.41 DRB-12 100 HO OH OH OH
F OH 336.4 DRB-13 95 OH
Cl
100 O2N NO2 446.79 DRB-14 O O
OH OH F
O
N H O NH O 510.47 DRB-15 100 OAc
OAc O 204
F
O
N H O NH O 426.39 DRB-16 - OH
OH O Cl
O
N H O NH 410.85 DRB-17 97 OH
OH
Cl
N H NH 382.88 DRB-18 100 OH
OH
F
O OH N H O NH 398.34 DRB-19 100
OH
HO OH 205
Cl
O OH N H O NH 414.8 DRB-20 100
OH
HO OH F
N H NH 366.43 DRB-21 100 OH
OH
Cl
O
N H O NH 410.85 DRB-22 100
OH
OH Cl
N H NH 382.88 DRB-23 100
OH
OH F Cl N 246.67 DRB-24 100 N H 206
F
O
N H O NH 394.4 DRB-25 100
OH
OH F
N H NH 366.43 DRB-26 100
OH
OH F O
N H O NH 366.34 DRB-27 97 OH
OH F
N H NH 338.38 DRB-28 97 OH
OH Cl
O
N H O NH Cl 451.69 DRB-29 98 OH
OH Cl 207
N
N OH 316.35 DRB-30 100 HO
O N O N 404.46 DRB-31 100
O O F
O
N H O NH Cl 435.23 DRB-32 97 OH
OH Cl Cl
O
N H O NH F 418.78 DRB-33 100 OH
OH F F
O
N H O NH F 402.32 DRB-34 98 OH
OH F 208
Cl
O OH
N H O NH 382.8 DRB-35 97
OH
Cl
O
N H O NH OH 382.8 DRB-36 100
OH Cl
O
N H O NH O 526.92 DRB-37 98 OAc
OAc O Cl
O
N H O NH O 442.85 DRB-38 100 OH
OH O 209
F
O OH
N H O NH 366.34 DRB-39 99
OH
Cl
N H NH OH 354.83 DRB-40 95
OH Cl
N H NH O 414.88 DRB-41 97 OH
OH O F
N H NH O 398.43 DRB-42 99 OH
OH O 210
Cl
N H NH F 390.81 DRB-43 - OH
OH F Cl
N H 97 NH 423.72 DRB-44 Cl OH
OH Cl F
N H NH OH 338.38 DRB-45 99
OH OH
N H NH 320.38 DRB-46 99 OH
Cl
OH
N H NH 354.83 DRB-47 98
OH
211
Cl
O
N H O NH Br 540.59 DRB-48 98 OH
OH Br Cl
O
N H O NH NO2 472.79 DRB-49 98 OH
OH NO2
O O 348.39 KKB-1 100
OH OH O
O O 362.38 KKB-2 100
OH OH O OH
O O 376.36 TWB-1 97
OH OH 212
Cl O O
O O O 428.86 JDB-1 -
OH Cl OH
O O O 400.85 JDB-2 -
OH
Note: This table is prepared and provided by Dennis Roberts.
213
APPENDIX 2. NCI-60 CANCER CELLS PANEL TEST OF WZB-117 (10 µM)
214
APPENDIX 3. NCI-60 CANCER CELLS PANEL TEST OF DRB-18 (10 µM)
Developmental Therapeutics Program NSC: D-781082 / 1 Conc: 1.00E-5 Molar Test Date: Jun 23, 2014
One Dose Mean Graph Experiment ID: 1406OS08 Report Date: Jul 10, 2014
Panel/Cell Line Growth Percent Mean Growth Percent - Growth Percent Leukemia CCRF-CEM 9.13 HL-60(TB) 8.41 K-562 12.28 MOLT-4 -10.49 RPMI-8226 15.98 SR -33.00 Non-Small Cell Lung Cancer A549/ATCC 21.00 EKVX 80.20 HOP-62 40.47 HOP-92 -11.02 NCI-H226 85.73 NCI-H23 3.70 NCI-H322M 17.56 NCI-H460 2.22 NCI-H522 12.52 Colon Cancer COLO 205 90.20 HCC-2998 22.67 HCT-116 24.45 HCT-15 7.28 HT29 49.09 KM12 -1.46 SW-620 25.91 CNS Cancer SF-268 28.29 SF-295 74.19 SF-539 25.84 SNB-19 29.51 SNB-75 41.09 U251 21.89 Melanoma LOX IMVI 2.86 MALME-3M -3.38 M14 25.33 MDA-MB-435 30.89 SK-MEL-2 33.34 SK-MEL-28 31.94 SK-MEL-5 32.75 UACC-257 46.15 UACC-62 38.58 Ovarian Cancer IGROV1 24.24 OVCAR-3 10.94 OVCAR-4 27.78 OVCAR-5 73.62 OVCAR-8 23.62 NCI/ADR-RES 15.42 SK-OV-3 54.67 Renal Cancer 786-0 23.02 A498 82.16 ACHN 0.11 CAKI-1 37.37 RXF 393 21.16 SN12C -27.78 TK-10 52.33 UO-31 11.90 Prostate Cancer PC-3 7.21 DU-145 23.37 Breast Cancer MCF7 9.21 MDA-MB-231/ATCC -52.18 HS 578T 42.70 BT-549 39.89 T-47D 11.29 MDA-MB-468 32.53 Mean 24.61 Delta 76.79 Range 142.38
150 100 50 0 -50 -100 -150
215
APPENDIX 4. PUBLICATIONS DURING MY PHD STUDY IN DR. XIAO CHEN’S
LAB
The following are the papers that I have published in the past five years of my PhD study in Dr. Xiaozhuo Chen’s lab in Ohio University.
ATP internalization study:
Qian Y, Wang X, Liu Y, Li Y, Colvin R, Tong L, Wu S, and Chen X. (2014) Extracellular ATP is internalized by macropinocytosis and induces intracellular ATP increase and drug resistance in cancer cells. Cancer Lett. 351(2): 242-51. PMID: 24973521.
Chen X, Qian Y, Wu S. The Warburg effect: evolving interpretations of an established concept. Free. Radic. Biol. Med. PMID: 25277420 (2014, accepted)
Glucose transporter inhibitors study:
Qian Y, Wang X, and Chen X. (2014) Inhibitors of glucose transport and glucose metabolism as novel anticancer therapeutics. World J. Transl. Med. 3(2): 37-57. doi: 10.5528/wjtm.v3.i2.37.
Liu Y, Cao Y, Zhang W, Bergmeier S, Qian Y, Akbar H, Colvin R, Ding J, Tong L, Wu S, Hines J, and Chen X. (2012) A small molecule inhibitor of glucose transporter 1 down- regulates glycolysis, induces cell cycle arrest, and inhibits cancer cell growth in vitro and in vivo. Mol. Cancer Ther. 11(8):1672-82. PMID: 22689530.
Tuccinardi T, Granchi C, Iegre J, Paterni I, Bertini S, Macchia M, Martinelli A, Qian Y, Chen X, and Minutolo F. (2013) Oxime-based inhibitors of glucose transporter 1 displaying antiproliferative effects in cancer cells. Bioorg. Med. Chem. Lett. 23(24):6923- 7. PMID: 24200808.
Ren Y, Yuan C, Qian Y, Gallucci J, Chai H, Chen Xiao, Goetz M, and Kinghorn D. (2014) Constituents of an Extract of Cryptocarya rubra Housed in a Repository with Cytotoxic and Glucose Transport Inhibitory Effects. J. Nat. Prod. 77(3):550-6. PMID: 24344605.
216
α-PGG, obesity and diabetes study:
Liu X, Malki A, Cao Y, Li Y, Qian Y, Wang X, Chen X. Glucose- and triglyceride- lowering dietary penta-O-galloyl-a-D-glucose reduces expression of PPARγ, C/EBPα, and induces p21-mediated G1 phase cell cycle arrest and inhibits adipogenesis in 3T3-L1 preadipocytes. (2014, submitted)
Cao Y, Himmeldirk K, Qian Y, Ren Y, and Chen X. (2014) Biological functions of penta-O-galloyl-D-glucose and its derivatives. J. Nat. Med. 68(3):465-72. PMID: 24532420.
Cao Y, Li Y, Kim J, Ren Y, Himmeldirk K, Liu Y, Qian Y, Liu F, and Chen X. (2013) Orally efficacious small molecule 6-chloro-6-deoxy-1,2,3,4-tetra-O-galloyl-a-D- glucopyranose (6Cl-TGQ) selectively and potently stimulates insulin receptor and reduces blood glucose levels in type 1 and type 2 diabetes animals. J. Mol. Endocrinol. 51(1): 15-26. PMID: 23549408. 217
APPENDIX 5. PERMISSIONS FROM JOURNALS
Permission for Free Radical Biology & Medicine and Cancer Letters (Elsevier)
Both Free Radical Biology & Medicine and Cancer Letters belong to Elsevier.
Qian Y, Wang X, Liu Y, Li Y, Colvin R, Tong L, Wu S, and Chen X. (2014) Extracellular ATP is internalized by macropinocytosis and induces intracellular ATP increase and drug resistance in cancer cells. Cancer Lett. 351(2): 242-51. PMID: 24973521.
Chen X, Qian Y, Wu S. The Warburg effect: evolving interpretations of an established concept. Free. Radic. Biol. Med. PMID: 25277420 (2014, accepted)
“Authors can use either their accepted author manuscript or final published article for inclusion in a thesis or dissertation.” This is cited from the link below: http://www.elsevier.com/journal-authors/author-rights-and-responsibilities#author-use
From: Yanrong Qian [email protected] Subject: Ask for permission Date: August 18, 2014 at 3:12 PM To: [email protected]
Hi,
This is Yanrong Qian. I am a graduate student working on my dissertation. Also, I am an author of a paper we submitted to FRBM. I searched for the copyright policy on Elsevier website and found out that, as an author, I can include this paper, if accepted, in my dissertation. Therefore, I am wondering if I still need to apply for permission for that or not.
I will wait for your reply sincerely. Thank you very much!
Yanrong
PhD candidate MCB Program Ohio University Athens, OH 45701
218
Reply:
From: Permissions Helpdesk [email protected] Subject: RE: Ask for permission Date: August 18, 2014 at 3:51 PM To: Yanrong Qian [email protected]
Dear Yanrong:
Permission is covered by the rights you retain as an Elsevier journal author as outlined at http://www.elsevier.com/journal-authors/author-rights-and-responsibilities, which include Inclusion in a thesis or dissertation, provided that proper acknowledgement is given to the original source of publication. As this is a retained right, no written permission from Elsevier is necessary. If you have any questions, please let me know. Best of luck with your dissertation.
Regards, Hop
Hop Wechsler Permissions Helpdesk Manager Elsevier 1600 John F. Kennedy Boulevard Suite 1800 Philadelphia, PA 19103-2899 Tel: +1-215-239-3520 Mobile: +1-215-900-5674 Fax: +1-215-239-3805 E-mail: [email protected] Contact the Permissions Helpdesk: +1-800-523-4069 x 3808 [email protected]
219
Permission for World Journal of Translational Medicine (BPG)
World Journal of Translational Medicine belongs to Baishideng Publishing Group (BPG).
Qian Y, Wang X, and Chen X. (2014) Inhibitors of glucose transport and glucose metabolism as novel anticancer therapeutics. World J. Transl. Med. 3(2): 37-57. doi: 10.5528/wjtm.v3.i2.37.
“BPG applies the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non- commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. ” This is cited from the link below: http://www.wjgnet.com/bpg/subscribe.htm
From: Yanrong Qian
Hi,
This is Yanrong Qian. I am a graduate student working on my dissertation. Also, I am the first author of the following paper we submitted to WJTM.
Inhibitors of glucose transport and glycolysis as novel anticancer therapeutics Yanrong Qian, Xuan Wang and Xiaozhuo Chen. World J Transl Med 3(2):37- 57. Published online 2014 August 12. doi: 10.5528/wjtm.v3.i2.37.
I searched for the copyright policy on the BPG website and couldn’t find the policy about if, as an author, I can include this paper, in my dissertation. Therefore, I am wondering if I can apply for permission for that or not.
I will wait for your reply sincerely. Thank you very much!
Yanrong
PhD candidate MCB Program Ohio University Athens, OH 45701
220
Reply: Dear Dr. Qian,
See the website: http://www.wjgnet.com/bpg/subscribe.htm
Best regards,
Xiu-Xia Song, Vice Director, Editorial Office
Baishideng Publishing Group Inc E-mail: [email protected] Help desk: http://www.wjgnet.com/esps/helpdesk.aspx http://www.wjgnet.com
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