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1.  Oncogenic K-Ras decouples glucose and glutamine metabolism to support cancer cell growth 
A systems approach using 13C metabolic flux analysis (MFA), non-targeted tracer fate detection (NTFD), and transcriptional profiling was applied to investigate the role of oncogenic K-Ras in metabolic transformation.K-Ras transformed cells exhibit an increased glycolytic rate and lower flux through the oxidative tricarboxylic acid (TCA) cycle.K-Ras transformed cells show a relative increase in glutamine anaplerosis and reductive TCA metabolism.Transcriptional changes driven by oncogenic K-Ras suggest control nodes associated with the metabolic reprogramming of cancer cells.
The ras and myc oncogenes drive pleiotropic changes in cell signaling, nutrient uptake, and intracellular metabolism (Chiaradonna et al, 2006b; Yuneva et al, 2007; Wise et al, 2008; Vander Heiden et al, 2009). Mutated ras proteins, identified in 25% of human cancers (Bos, 1989; Downward, 2003), correlate with an increased rate of glucose consumption, lactate accumulation, altered expression of mitochondrial genes, increased ROS production, and reduced mitochondrial activity (Bos, 1989; Downward, 2003; Vizan et al, 2005; Chiaradonna et al, 2006a; Yun et al, 2009; Baracca et al, 2010; Weinberg et al, 2010). Furthermore, K-Ras transformed cancer cells are dependent upon glucose and glutamine availability, since their withdrawal induces apoptosis and cell-cycle arrest, respectively (Ramanathan et al, 2005; Telang et al, 2006; Yun et al, 2009). However, the precise metabolic effects downstream of oncogenic Ras signaling as well as the mechanisms by which intracellular glucose and glutamine metabolism change have not been completely elucidated.
In this report, we have investigated the reprogramming of central carbon metabolism in cancer cells and its regulation by the K-ras oncogene, applying a systems level approach using 13C metabolic flux analysis (MFA), non-targeted tracer fate detection (NTFD), and transcriptional profiling. These data reveal a coordinated decoupling of glycolysis and the tricarboxylic acid (TCA) cycle. K-Ras transformed mouse and human cells exhibited a high glucose to lactate flux and relatively lower oxidative metabolism of pyruvate. Such changes were supported by increased expression of glycolytic genes as well as several pyruvate dehydrogenase kinases. In contrast to glucose, the contribution of glutamine carbon to TCA cycle intermediates through both oxidative and reductive metabolism was significantly increased upon K-Ras transformation. Despite this increase in glutamine anaplerosis, oxidative TCA flux was significantly decreased. Additionally, we observed elevated levels of glutamine-derived nitrogen in various biosynthetic metabolites in transformed cells, including amino acids, 5-oxoproline, and the nucleobase adenine. Consistent with these changes, we detected increased transcription of genes associated with glutamine metabolism and nucleotide biosynthesis in cells expressing oncogenic K-Ras.
Taken together, these findings indicate an important role of oncogenic K-Ras in cancer cell metabolism. The observed decoupling of glucose and glutamine metabolism enables the efficient utilization of both carbon and nitrogen from glutamine for biosynthetic processes. In accord with these alterations, oncogenic K-Ras induces gene expression changes that may drive this metabolic reprogramming. Finally, these results may enable the identification of metabolic and transcriptional targets throughout the network and allow more effective cancer therapies.
Oncogenes such as K-ras mediate cellular and metabolic transformation during tumorigenesis. To analyze K-Ras-dependent metabolic alterations, we employed 13C metabolic flux analysis (MFA), non-targeted tracer fate detection (NTFD) of 15N-labeled glutamine, and transcriptomic profiling in mouse fibroblast and human carcinoma cell lines. Stable isotope-labeled glucose and glutamine tracers and computational determination of intracellular fluxes indicated that cells expressing oncogenic K-Ras exhibited enhanced glycolytic activity, decreased oxidative flux through the tricarboxylic acid (TCA) cycle, and increased utilization of glutamine for anabolic synthesis. Surprisingly, a non-canonical labeling of TCA cycle-associated metabolites was detected in both transformed cell lines. Transcriptional profiling detected elevated expression of several genes associated with glycolysis, glutamine metabolism, and nucleotide biosynthesis upon transformation with oncogenic K-Ras. Chemical perturbation of enzymes along these pathways further supports the decoupling of glycolysis and TCA metabolism, with glutamine supplying increased carbon to drive the TCA cycle. These results provide evidence for a role of oncogenic K-Ras in the metabolic reprogramming of cancer cells.
PMCID: PMC3202795  PMID: 21847114
cancer; metabolic flux analysis; metabolism; Ras; transcriptional analysis
2.  Oncogenes induce the cancer-associated fibroblast phenotype 
Cell Cycle  2013;12(17):2723-2732.
Metabolic coupling, between mitochondria in cancer cells and catabolism in stromal fibroblasts, promotes tumor growth, recurrence, metastasis, and predicts anticancer drug resistance. Catabolic fibroblasts donate the necessary fuels (such as L-lactate, ketones, glutamine, other amino acids, and fatty acids) to anabolic cancer cells, to metabolize via their TCA cycle and oxidative phosphorylation (OXPHOS). This provides a simple mechanism by which metabolic energy and biomass are transferred from the host microenvironment to cancer cells. Recently, we showed that catabolic metabolism and “glycolytic reprogramming” in the tumor microenvironment are orchestrated by oncogene activation and inflammation, which originates in epithelial cancer cells. Oncogenes drive the onset of the cancer-associated fibroblast phenotype in adjacent normal fibroblasts via paracrine oxidative stress. This oncogene-induced transition to malignancy is “mirrored” by a loss of caveolin-1 (Cav-1) and an increase in MCT4 in adjacent stromal fibroblasts, functionally reflecting catabolic metabolism in the tumor microenvironment. Virtually identical findings were obtained using BRCA1-deficient breast and ovarian cancer cells. Thus, oncogene activation (RAS, NFkB, TGF-β) and/or tumor suppressor loss (BRCA1) have similar functional effects on adjacent stromal fibroblasts, initiating “metabolic symbiosis” and the cancer-associated fibroblast phenotype. New therapeutic strategies that metabolically uncouple oxidative cancer cells from their glycolytic stroma or modulate oxidative stress could be used to target this lethal subtype of cancers. Targeting “fibroblast addiction” in primary and metastatic tumor cells may expose a critical Achilles’ heel, leading to disease regression in both sporadic and familial cancers.
PMCID: PMC3899185  PMID: 23860382
oncogene; tumor suppressor; RAS; NFkB; TGF-beta; BRCA1; oxidative stress; glycolysis; cancer-associated fibroblast; tumor microenvironment; stromal biomarkers; metabolic symbiosis
3.  Predicting selective drug targets in cancer through metabolic networks 
The authors develop a genome-scale model of cancer metabolism and use it to predict genes that are essential for cancer cell growth. An array of target combinations are then identified that could potentially provide novel selective treatments for specific cancers.
The first genome-scale network model of cancer metabolism is developed and validated by successfully identifying genes essential for cellular proliferation in cancer cell lines.The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new.Combinations of synthetic lethal drug targets are predicted, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection.Potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled.
During tumor development, cancer cells modify their metabolism to meet the requirements of cellular proliferation, thus facilitating the uptake and conversion of nutrients into biomass. Many key metabolic alterations are similar across tumor cells, including changes in glucose metabolism that give rise to the Warburg effect, and an increase in biosynthetic activities (such as nucleotide, lipids and amino-acid synthesis) (DeBerardinis et al, 2008; Tennant et al, 2009; Vander Heiden et al, 2009). The observation that many types of cancer cells adapt their metabolism toward increased proliferation makes flux balance analysis (FBA), a constraint-based modeling (CBM) approach, suitable for modeling cancer metabolism as it assumes that cells are under selective pressure to increase their growth rate (Price et al, 2003).
Building on previous reconstructions of a generic (non-tissue specific) human metabolic network (Duarte et al, 2007; Ma et al, 2007), we develop here the first large-scale FBA model of cancer metabolism that aims to capture the main metabolic alterations that are common across many cancer types. The model reconstruction is based on our recent computational method for the automatic reconstruction of human tissue metabolic models (Jerby et al, 2010), integrating the human metabolic model with cancer gene expression data. The construction of the cancer model focuses on activating a core set of metabolic enzyme-coding genes that are highly expressed across cancer cell lines in the NCI-60 collection, with additional reactions enabling their activation and the biosynthesis of a set of biomass compounds required for cellular proliferation. This generic cancer model enables the successful prediction of the metabolic state of cancer cells across different gene knockdowns and modeling the effects of drug applications on a large scale. As a first demonstration of the predictive performance of the cancer model, we applied it to predict 199 growth-supporting genes whose knockdown is expected to inhibit cellular proliferation, showing that the model predictions indeed match results of shRNA gene silencing experiments (Luo et al, 2008).
To identify viable anticancer drug targets, we predicted whether the knockdown of the growth-supporting genes is likely to be toxic to normal cells. Out of the 199 genes that are predicted to be growth supporting in the cancer model, 52 are predicted to have negligible effects on energy production in normal cells. However, the knockdown of the majority of the latter is yet predicted to potentially cause damage to proliferation of normal cells, suggesting that the targeting of these genes would cause similar side effects to those observed with current cytostatic drugs (Partridge et al, 2001). Next, we predicted 342 synthetic lethal drug targets, whose predicted synergy was validated based on (i) comparison with genetic interactions between the corresponding yeast orthologs (Costanzo et al, 2010) and (ii) by analyzing the efficacy of metabolic drugs targeting these genes, finding that drugs that target a single gene (participating in a predicted synthetic lethal pair) indeed have higher efficacy in cell lines in which the synergistic gene is lowly expressed. In contrast to the single targets described above, the knockdown of a third of these synergistic pairs is predicted to leave the proliferation of normal cells intact. Most importantly, the specific targeting of a gene participating in a synergistic pair is especially appealing in tumors in which its interacting gene is specifically inactivated—the targeting of such a gene solely is likely to selectively damage the tumor, without affecting the function of healthy tissues in which the interacting gene in the pair is active. We utilized genomic and transcriptomic data to infer gene inactivation across an array of cancers, which has led to the identification of cancer type-specific targets based on the intersection of this data with our predicted synergistic gene pairs.
In summary, the model presented here lays down a fundamental computational approach for interpreting the rapidly accumulating proteomics (Bichsel et al, 2001) and metabolomics (Fan et al, 2009) data characterizing cancer metabolic alterations. We hope that the publication of this first step will spur further studies aimed at obtaining a systems level understanding of cancer metabolism and at designing new therapeutic means that selectively target them.
The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled.
PMCID: PMC3159974  PMID: 21694718
cancer; metabolic; metabolism; modeling; selectivity
4.  Oncogenes and inflammation rewire host energy metabolism in the tumor microenvironment 
Cell Cycle  2013;12(16):2580-2597.
Here, we developed a model system to evaluate the metabolic effects of oncogene(s) on the host microenvironment. A matched set of “normal” and oncogenically transformed epithelial cell lines were co-cultured with human fibroblasts, to determine the “bystander” effects of oncogenes on stromal cells. ROS production and glucose uptake were measured by FACS analysis. In addition, expression of a panel of metabolic protein biomarkers (Caveolin-1, MCT1, and MCT4) was analyzed in parallel. Interestingly, oncogene activation in cancer cells was sufficient to induce the metabolic reprogramming of cancer-associated fibroblasts toward glycolysis, via oxidative stress. Evidence for “metabolic symbiosis” between oxidative cancer cells and glycolytic fibroblasts was provided by MCT1/4 immunostaining. As such, oncogenes drive the establishment of a stromal-epithelial “lactate-shuttle”, to fuel the anabolic growth of cancer cells. Similar results were obtained with two divergent oncogenes (RAS and NFκB), indicating that ROS production and inflammation metabolically converge on the tumor stroma, driving glycolysis and upregulation of MCT4. These findings make stromal MCT4 an attractive target for new drug discovery, as MCT4 is a shared endpoint for the metabolic effects of many oncogenic stimuli. Thus, diverse oncogenes stimulate a common metabolic response in the tumor stroma. Conversely, we also show that fibroblasts protect cancer cells against oncogenic stress and senescence by reducing ROS production in tumor cells. Ras-transformed cells were also able to metabolically reprogram normal adjacent epithelia, indicating that cancer cells can use either fibroblasts or epithelial cells as “partners” for metabolic symbiosis. The antioxidant N-acetyl-cysteine (NAC) selectively halted mitochondrial biogenesis in Ras-transformed cells, but not in normal epithelia. NAC also blocked stromal induction of MCT4, indicating that NAC effectively functions as an “MCT4 inhibitor”. Taken together, our data provide new strategies for achieving more effective anticancer therapy. We conclude that oncogenes enable cancer cells to behave as selfish “metabolic parasites”, like foreign organisms (bacteria, fungi, viruses). Thus, we should consider treating cancer like an infectious disease, with new classes of metabolically targeted “antibiotics” to selectively starve cancer cells. Our results provide new support for the “seed and soil” hypothesis, which was first proposed in 1889 by the English surgeon, Stephen Paget.
PMCID: PMC3865048  PMID: 23860378
oncogene; oxidative stress; glycolysis; reverse Warburg effect; RAS; inflammation; NFkB; cancer associated fibroblast; tumor microenvironment; HaCaT; MCT1; MCT4; caveolin-1; TOMM20; mitochondrial metabolism; wound healing; response to injury; field cancerization; metabolic parasite; autophagy; senescence; oncogenic stress; stromal biomarkers
5.  Convergence of Mutation and Epigenetic Alterations Identifies Common Genes in Cancer That Predict for Poor Prognosis  
PLoS Medicine  2008;5(5):e114.
The identification and characterization of tumor suppressor genes has enhanced our understanding of the biology of cancer and enabled the development of new diagnostic and therapeutic modalities. Whereas in past decades, a handful of tumor suppressors have been slowly identified using techniques such as linkage analysis, large-scale sequencing of the cancer genome has enabled the rapid identification of a large number of genes that are mutated in cancer. However, determining which of these many genes play key roles in cancer development has proven challenging. Specifically, recent sequencing of human breast and colon cancers has revealed a large number of somatic gene mutations, but virtually all are heterozygous, occur at low frequency, and are tumor-type specific. We hypothesize that key tumor suppressor genes in cancer may be subject to mutation or hypermethylation.
Methods and Findings
Here, we show that combined genetic and epigenetic analysis of these genes reveals many with a higher putative tumor suppressor status than would otherwise be appreciated. At least 36 of the 189 genes newly recognized to be mutated are targets of promoter CpG island hypermethylation, often in both colon and breast cancer cell lines. Analyses of primary tumors show that 18 of these genes are hypermethylated strictly in primary cancers and often with an incidence that is much higher than for the mutations and which is not restricted to a single tumor-type. In the identical breast cancer cell lines in which the mutations were identified, hypermethylation is usually, but not always, mutually exclusive from genetic changes for a given tumor, and there is a high incidence of concomitant loss of expression. Sixteen out of 18 (89%) of these genes map to loci deleted in human cancers. Lastly, and most importantly, the reduced expression of a subset of these genes strongly correlates with poor clinical outcome.
Using an unbiased genome-wide approach, our analysis has enabled the discovery of a number of clinically significant genes targeted by multiple modes of inactivation in breast and colon cancer. Importantly, we demonstrate that a subset of these genes predict strongly for poor clinical outcome. Our data define a set of genes that are targeted by both genetic and epigenetic events, predict for clinical prognosis, and are likely fundamentally important for cancer initiation or progression.
Stephen Baylin and colleagues show that a combined genetic and epigenetic analysis of breast and colon cancers identifies a number of clinically significant genes targeted by multiple modes of inactivation.
Editors' Summary
Cancer is one of the developed world's biggest killers—over half a million Americans die of cancer each year, for instance. As a result, there is great interest in understanding the genetic and environmental causes of cancer in order to improve cancer prevention, diagnosis, and treatment.
Cancer begins when cells begin to multiply out of control. DNA is the sequence of coded instructions—genes—for how to build and maintain the body. Certain “tumor suppressor” genes, for instance, help to prevent cancer by preventing tumors from developing, but changes that alter the DNA code sequence—mutations—can profoundly affect how a gene works. Modern techniques of genetic analysis have identified genes such as tumor suppressors that, when mutated, are linked to the development of certain cancers.
Why Was This Study Done?
However, in recent years, it has become increasingly apparent that mutations are neither necessary nor sufficient to explain every case of cancer. This has led researchers to look at so-called epigenetic factors, which also alter how a gene works without altering its DNA sequence. An example of this is “methylation,” which prevents a gene from being expressed—deactivates it—by a chemical tag. Methylation of genes is part of the normal functioning of DNA, but abnormal methylation has been linked with cancer, aging, and some rare birth abnormalities.
Previous analysis of DNA from breast and colon cancer cells had revealed 189 “candidate cancer genes”—mutated genes that were linked to the development of breast and colon cancer. However, it was not clear how those mutations gave rise to cancer, and individual mutations were present in only 5% to 15% of specific tumors. The authors of this study wanted to know whether epigenetic factors such as methylation contributed to causing the cancers.
What Did the Researchers Do and Find?
The researchers first identified 56 of the 189 candidate cancer genes as likely tumor suppressors and then determined that 36 of these genes were methylated and deactivated, often in both breast and colon (laboratory-grown) cancer cells. In nearly all cases, the methylated genes were not active but could be reactivated by being demethylated. They further showed that, in normal colon and breast tissue samples, 18 of the 36 genes were unmethylated and functioned normally, but in cells taken from breast and colon cancer tumors they were methylated.
In contrast to the genetic mutations, the 18 genes were frequently methylated across a range of tumor types, and eight genes were methylated in both the breast and colon cancers. The authors found by reviewing the genetics and epigenetics of those 18 genes in breast and colon cancer that they were either mutated, methylated, or both. A literature review showed that at least six of the 18 genes were known to have tumor suppressor properties, and the authors determined that 16 were located in parts of DNA known to be missing from cells taken from a range of cancer tumors.
Finally, the researchers analyzed data on cancer cases to show that methylation of these 18 genes was correlated with reduced function of these genes in tumors and with a greater likelihood that a cancer will be terminal or spread to other parts of the body.
What Do These Findings Mean?
The researchers considered only the 189 candidate cancer genes found in one previous study and not other genes identified elsewhere. They also did not consider the biological effects of the individual mutations found in those genes. Despite this, they have demonstrated that methylation of specific genes is likely to play a role in the development of breast and/or colon cancer cells either together with mutations or independently, most likely by turning off their tumor suppression function.
More broadly, however, the study adds to the evidence that future analysis of the role of genes in cancer should include epigenetic as well as genetic factors. In addition, the authors have also shown that a number of these genes may be useful for predicting clinical outcomes for a range of tumor types.
Additional Information.
Please access these Web sites via the online version of this summary at
A December 2006 PLoS Medicine Perspective article reviews the value of examining methylation as a factor in common cancers and its use for early detection
The Web site of the American Cancer Society has a wealth of information and resources on a variety of cancers, including breast and colon cancer is a nonprofit organization providing information about breast cancer on the Web, including research news
Cancer Research UK provides information on cancer research
The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins publishes background information on the authors' research on methylation, setting out its potential for earlier diagnosis and better treatment of cancer
PMCID: PMC2429944  PMID: 18507500
6.  Roles of microRNA on cancer cell metabolism 
Advanced studies of microRNAs (miRNAs) have revealed their manifold biological functions, including control of cell proliferation, cell cycle and cell death. However, it seems that their roles as key regulators of metabolism have drawn more and more attention in the recent years. Cancer cells display increased metabolic autonomy in comparison to non-transformed cells, taking up nutrients and metabolizing them in pathways that support growth and proliferation. MiRNAs regulate cell metabolic processes through complicated mechanisms, including directly targeting key enzymes or transporters of metabolic processes and regulating transcription factors, oncogenes / tumor suppressors as well as multiple oncogenic signaling pathways. MiRNAs like miR-375, miR-143, miR-14 and miR-29b participate in controlling cancer cell metabolism by regulating the expression of genes whose protein products either directly regulate metabolic machinery or indirectly modulate the expression of metabolic enzymes, serving as master regulators, which will hopefully lead to a new therapeutic strategy for malignant cancer. This review focuses on miRNA regulations of cancer cell metabolism,including glucose uptake, glycolysis, tricarboxylic acid cycle and insulin production, lipid metabolism and amino acid biogenesis, as well as several oncogenic signaling pathways. Furthermore, the challenges of miRNA-based strategies for cancer diagnosis, prognosis and therapeutics have been discussed.
PMCID: PMC3563491  PMID: 23164426
MicroRNA; Cell metabolism; MiRNA biomarker
7.  Phosphoglycerate Dehydrogenase: Potential Therapeutic Target and Putative Metabolic Oncogene 
Journal of Oncology  2014;2014:524101.
Exemplified by cancer cells' preference for glycolysis, for example, the Warburg effect, altered metabolism in tumorigenesis has emerged as an important aspect of cancer in the past 10–20 years. Whether due to changes in regulatory tumor suppressors/oncogenes or by acting as metabolic oncogenes themselves, enzymes involved in the complex network of metabolic pathways are being studied to understand their role and assess their utility as therapeutic targets. Conversion of glycolytic intermediate 3-phosphoglycerate into phosphohydroxypyruvate by the enzyme phosphoglycerate dehydrogenase (PHGDH)—a rate-limiting step in the conversion of 3-phosphoglycerate to serine—represents one such mechanism. Forgotten since classic animal studies in the 1980s, the role of PHGDH as a potential therapeutic target and putative metabolic oncogene has recently reemerged following publication of two prominent papers near-simultaneously in 2011. Since that time, numerous studies and a host of metabolic explanations have been put forward in an attempt to understand the results observed. In this paper, I review the historic progression of our understanding of the role of PHGDH in cancer from the early work by Snell through its reemergence and rise to prominence, culminating in an assessment of subsequent work and what it means for the future of PHGDH.
PMCID: PMC4276281  PMID: 25574168
8.  Energy transfer in “parasitic” cancer metabolism 
Cell Cycle  2011;10(24):4208-4216.
It is now widely recognized that the tumor microenvironment promotes cancer cell growth and metastasis via changes in cytokine secretion and extra-cellular matrix remodeling. However, the role of tumor stromal cells in providing energy for epithelial cancer cell growth is a newly emerging paradigm. For example, we and others have recently proposed that tumor growth and metastasis is related to an energy imbalance. Host cells produce energy-rich nutrients via catabolism (through autophagy, mitophagy and aerobic glycolysis), which are then transferred to cancer cells, to fuel anabolic tumor growth. Stromal cell derived L-lactate is taken up by cancer cells and is used for mitochondrial oxidative phosphorylation (OXPHOS), to produce ATP efficiently. However, “parasitic” energy transfer may be a more generalized mechanism in cancer biology than previously appreciated. Two recent papers in Science and Nature Medicine now show that lipolysis in host tissues also fuels tumor growth. These studies demonstrate that free fatty acids produced by host cell lipolysis are re-used via β-oxidation (β-OX) in cancer cell mitochondria. Thus, stromal catabolites (such as lactate, ketones, glutamine and free fatty acids) promote tumor growth by acting as high-energy onco-metabolites. As such, host catabolism via autophagy, mitophagy and lipolysis may explain the pathogenesis of cancer-associated cachexia and provides exciting new druggable targets for novel therapeutic interventions. Taken together, these findings also suggest that tumor cells promote their own growth and survival by behaving as a “parasitic organism.” Hence, we propose the term “parasitic cancer metabolism” to describe this type of metabolic-coupling in tumors. Targeting tumor cell mitochondria (OXPHOS and β-OX) would effectively uncouple tumor cells from their hosts, leading to their acute starvation. In this context, we discuss new evidence that high-energy onco-metabolites (produced by the stroma) can confer drug resistance. Importantly, this metabolic chemo-resistance is reversed by blocking OXPHOS in cancer cell mitochondria, with drugs like Metformin, a mitochondrial “poison.” In summary, parasitic cancer metabolism is achieved architecturally by dividing tumor tissue into at least two well-defined opposing “metabolic compartments:” catabolic and anabolic.
PMCID: PMC3272257  PMID: 22033146
mitochondria; cancer metabolism; autophagy; mitophagy; aerobic glycolysis; lipolysis; oxidative phosphorylation; beta-oxidation; Metformin; drug discovery; drug resistance; chemo-resistance; Warburg effect; oncometabolite; parasite; metabolic compartments
9.  Targeting Cancer Metabolism 
The understanding that oncogenes can have profound effects on cellular metabolism and the discovery of mutations and alterations in several metabolism-related enzymes (IDH1, IDH2, SDH, FH, PKM2) has renewed interest in cancer metabolism and renewed hope of taking therapeutic advantage of cancer metabolism. Otto Warburg observed that aerobic glycolysis was a characteristic of cancer cells. More than 50-years later, we understand that aerobic glycolysis and uptake of glutamine and glycine allow cancer cells to produce energy (ATP) and the nucleotides, amino acids and lipids required for proliferation. Expression of the MYC oncogene drives the increase in cellular biomass facilitating proliferation. PKM2 expression in cancer cells stimulates aerobic glycolysis. Amongst intermediary metabolism enzyme, mutations in succinate dehydrogenase (SDH) occur in gastointestinal stromal tumors and result in a pseudohypoxic metabolic milieu. Fumarate hydratase (FH) mutations lead to a characteristic renal cell carcinoma. Isocitrate dehydrogenase (IDH1/2) mutations have been found in leukemias, gliomas, prostate cancer, colon cancer, thyroid cancer and sarcomas. These recently recognized oncogenic metabolic lesions may be selective targets for new anticancer therapeutics.
PMCID: PMC3475613  PMID: 23071355
Cancer metabolism; IDH1/2; PKM2; MYC; succinate dehydrogenase; fumarate hydratase
10.  Cancer metabolism: current perspectives and future directions 
Cell Death & Disease  2012;3(1):e248-.
Cellular metabolism influences life and death decisions. An emerging theme in cancer biology is that metabolic regulation is intricately linked to cancer progression. In part, this is due to the fact that proliferation is tightly regulated by availability of nutrients. Mitogenic signals promote nutrient uptake and synthesis of DNA, RNA, proteins and lipids. Therefore, it seems straight-forward that oncogenes, that often promote proliferation, also promote metabolic changes. In this review we summarize our current understanding of how ‘metabolic transformation' is linked to oncogenic transformation, and why inhibition of metabolism may prove a cancer′s ‘Achilles' heel'. On one hand, mutation of metabolic enzymes and metabolic stress sensors confers synthetic lethality with inhibitors of metabolism. On the other hand, hyperactivation of oncogenic pathways makes tumors more susceptible to metabolic inhibition. Conversely, an adequate nutrient supply and active metabolism regulates Bcl-2 family proteins and inhibits susceptibility to apoptosis. Here, we provide an overview of the metabolic pathways that represent anti-cancer targets and the cell death pathways engaged by metabolic inhibitors. Additionally, we will detail the similarities between metabolism of cancer cells and metabolism of proliferating cells.
PMCID: PMC3270265  PMID: 22237205
cancer; cell metabolism; glucose; oncogenes
11.  Targeting Tumor Suppressor Networks for Cancer Therapeutics 
Current drug targets  2014;15(1):2-16.
Cancer is a consequence of mutations in genes that control cell proliferation, differentiation and cellular homeostasis. These genes are classified into two categories: oncogenes and tumor suppressor genes. Together, overexpression of oncogenes and loss of tumor suppressors are the dominant driving forces for tumorigenesis. Hence, targeting oncogenes and tumor suppressors hold tremendous therapeutic potential for cancer treatment. In the last decade, the predominant cancer drug discovery strategy has relied on a traditional reductionist approach of dissecting molecular signaling pathways and designing inhibitors for the selected oncogenic targets. Remarkable therapies have been developed using this approach; however, targeting oncogenes is only part of the picture. Our understanding of the importance of tumor suppressors in preventing tumorigenesis has also advanced significantly and provides a new therapeutic window of opportunity. Given that tumor suppressors are frequently mutated, deleted, or silenced with loss-of-function, restoring their normal functions to treat cancer holds tremendous therapeutic potential. With the rapid expansion in our knowledge on cancer over the last several decades, developing effective anticancer regimens against tumor suppressor pathways has never been more promising. In this article, we will review the concept of tumor suppression, and outline the major therapeutic strategies and challenges of targeting tumor suppressor networks for cancer therapeutics.
PMCID: PMC4032821  PMID: 24387338
tumor suppressors; RB; p53; BRCA1; BRCA2; gene therapy; small molecule inhibitors
12.  Redox-Directed Cancer Therapeutics: Molecular Mechanisms and Opportunities 
Antioxidants & Redox Signaling  2009;11(12):3013-3069.
Redox dysregulation originating from metabolic alterations and dependence on mitogenic and survival signaling through reactive oxygen species represents a specific vulnerability of malignant cells that can be selectively targeted by redox chemotherapeutics. This review will present an update on drug discovery, target identification, and mechanisms of action of experimental redox chemotherapeutics with a focus on pro- and antioxidant redox modulators now in advanced phases of preclinal and clinical development. Recent research indicates that numerous oncogenes and tumor suppressor genes exert their functions in part through redox mechanisms amenable to pharmacological intervention by redox chemotherapeutics. The pleiotropic action of many redox chemotherapeutics that involves simultaneous modulation of multiple redox sensitive targets can overcome cancer cell drug resistance originating from redundancy of oncogenic signaling and rapid mutation. Moreover, some redox chemotherapeutics may function according to the concept of synthetic lethality (i.e., drug cytotoxicity is confined to cancer cells that display loss of function mutations in tumor suppressor genes or upregulation of oncogene expression). The impressive number of ongoing clinical trials that examine therapeutic performance of novel redox drugs in cancer patients demonstrates that redox chemotherapy has made the crucial transition from bench to bedside. Antioxid. Redox Signal. 11, 3013–3069.
The (redox) war on cancer
Developing anticancer redox chemotherapeutics
Redox chemotherapeutics: More than neocytotoxics?
Redox chemotherapeutics: Pleiotropic ‘dirty’ drugs?
Redox chemotherapeutics: Combinatorial or stand-alone drugs?
Redox chemotherapeutics and personalized medicine
Redox dysregulation as anticancer drug target
ROS in cancer chemotherapy: From toxicological liability to therapeutic asset
Reactive Pharmacophores for Anticancer Redox Chemotherapy
Organic endoperoxides: Artemisinins
Arsenicals: As2O3 and darinaparsin
Redox cyclers: Motexafin gadolinium
Motexafin gadolinium
Acetaminophen and O-acetylsalicylic acid
3,7-Diaminophenothiazinium redox dyes
Metal chelators: Disulfiram and triapine
Triapine and others
Di- and polysulfides: Varacin and diallyltrisulfide
Calicheamicin γ1I
Varacin and other polysulfides
Diallyldisulfide and diallyltrisulfide
Isothiocyanate organosulfur agents: β-Phenylethylisothiocyanate
Electrophilic Michael acceptors: Parthenolide and neratinib
Sacrificial antioxidants: L-Ascorbate
Molecular Targets for Anticancer Redox Chemotherapy
Targeting the SOD system
SOD inhibitors: ATN-224
SOD mimetics: Mangafodipir
MnTBAP and others
TEMPO and others
Targeting the glutathione redox system: Imexon and NOV002
Targeting the thioredoxin system: PX-12 and PMX464
Chaetocin and gliotoxin
Targeting the Nrf2/Keap1-ARE pathway
Targeting HO-1: Zinc protoporphyrin IX
Targeting NQO1: Dicoumarol and ES936
Targeting APE/Ref1: E3330 and PNRI-299
PNRI-299 and resveratrol
Lucanthone and CRT0044876
Targeting Cdc25 phosphatases: NSC 67121 and F-NSC 67121
NSC 67121 and F-NSC 67121
Targeting zinc finger transcription factors: DIBA
In search of a molecular target: elesclomol
Functional Targets for Anticancer Redox Chemotherapy
Prooxidant intervention targeting glucose metabolism: 2-DG and DCA
Prooxidant intervention targeting mitochondria
Targeting mitochondrial respiration: α-TOS, DIM, and Bz-423
Targeting VDACs: Erastin
Targeting tumor hypoxia
Hypoxia-activated redox chemotherapeutics: TPZ, AQ4N, and PR-104
AQ4N and PR-104
Targeting HIF-1α: PX-478
PMCID: PMC2824519  PMID: 19496700
13.  Global Metabolic Profiling of Infection by an Oncogenic Virus: KSHV Induces and Requires Lipogenesis for Survival of Latent Infection 
PLoS Pathogens  2012;8(8):e1002866.
Like cancer cells, virally infected cells have dramatically altered metabolic requirements. We analyzed global metabolic changes induced by latent infection with an oncogenic virus, Kaposi's Sarcoma-associated herpesvirus (KSHV). KSHV is the etiologic agent of Kaposi's Sarcoma (KS), the most common tumor of AIDS patients. Approximately one-third of the nearly 200 measured metabolites were altered following latent infection of endothelial cells by KSHV, including many metabolites of anabolic pathways common to most cancer cells. KSHV induced pathways that are commonly altered in cancer cells including glycolysis, the pentose phosphate pathway, amino acid production and fatty acid synthesis. Interestingly, over half of the detectable long chain fatty acids detected in our screen were significantly increased by latent KSHV infection. KSHV infection leads to the elevation of metabolites involved in the synthesis of fatty acids, not degradation from phospholipids, and leads to increased lipid droplet organelle formation in the infected cells. Fatty acid synthesis is required for the survival of latently infected endothelial cells, as inhibition of key enzymes in this pathway led to apoptosis of infected cells. Addition of palmitic acid to latently infected cells treated with a fatty acid synthesis inhibitor protected the cells from death indicating that the products of this pathway are essential. Our metabolomic analysis of KSHV-infected cells provides insight as to how oncogenic viruses can induce metabolic alterations common to cancer cells. Furthermore, this analysis raises the possibility that metabolic pathways may provide novel therapeutic targets for the inhibition of latent KSHV infection and ultimately KS tumors.
Author Summary
In recent years there has been a resurgence in the study of metabolic changes in tumor cells. To determine if an oncogenic virus alters similar metabolic pathways as cancer cells, we measured the levels of a large number of metabolites in endothelial cells infected with Kaposi?s Sarcoma-associated herpesvirus (KSHV). KSHV is the etiologic agent of Kaposi's Sarcoma (KS), the most common tumor of AIDS patients world wide. Latent KSHV infection of endothelial cells altered a significant proportion of the host cell metabolites. Many metabolic pathways that are altered in most tumor cells were also altered by KSHV. In particular, KSHV upregulated fatty acid synthesis, a pathway that provides membrane material and metabolites critical for cell proliferation. Inhibitors of fatty acid synthesis kill many types of tumor cells and we found that these inhibitors led to death of cells latently infected with KSHV. In summary, we found that a directly oncogenic virus alters the same host metabolic pathways that are dysregulated in many cancer cells and that inhibition of these pathways can be used to kill off infected cells, thereby providing novel therapeutic targets for KSHV and ultimately KS tumors.
PMCID: PMC3420960  PMID: 22916018
14.  Induction of BIM Is Essential for Apoptosis Triggered by EGFR Kinase Inhibitors in Mutant EGFR-Dependent Lung Adenocarcinomas 
PLoS Medicine  2007;4(10):e294.
Mutations in the epidermal growth factor receptor (EGFR) gene are associated with increased sensitivity of lung cancers to kinase inhibitors like erlotinib. Mechanisms of cell death that occur after kinase inhibition in these oncogene-dependent tumors have not been well delineated. We sought to improve understanding of this process in order to provide insight into mechanisms of sensitivity and/or resistance to tyrosine kinase inhibitors and to uncover new targets for therapy.
Methods and Findings
Using a panel of human lung cancer cell lines that harbor EGFR mutations and a variety of biochemical, molecular, and cellular techniques, we show that EGFR kinase inhibition in drug-sensitive cells provokes apoptosis via the intrinsic pathway of caspase activation. The process requires induction of the proapoptotic BH3-only BCL2 family member BIM (i.e., BCL2-like 11, or BCL2L11); erlotinib dramatically induces BIM levels in sensitive but not in resistant cell lines, and knockdown of BIM expression by RNA interference virtually eliminates drug-induced cell killing in vitro. BIM status is regulated at both transcriptional and posttranscriptional levels and is influenced by the extracellular signal-regulated kinase (ERK) signaling cascade downstream of EGFR. Consistent with these findings, lung tumors and xenografts from mice bearing mutant EGFR-dependent lung adenocarcinomas display increased concentrations of Bim after erlotinib treatment. Moreover, an inhibitor of antiapoptotic proteins, ABT-737, enhances erlotinib-induced cell death in vitro.
In drug-sensitive EGFR mutant lung cancer cells, induction of BIM is essential for apoptosis triggered by EGFR kinase inhibitors. This finding implies that the intrinsic pathway of caspase activation may influence sensitivity and/or resistance of EGFR mutant lung tumor cells to EGFR kinase inhibition. Manipulation of the intrinsic pathway could be a therapeutic strategy to enhance further the clinical outcomes of patients with EGFR mutant lung tumors.
Using a panel of human drug-sensitive EGFR mutant lung cancer cells, William Pao and colleagues show that induction of BIM, a member of the BCL2 family, is essential for apoptosis triggered by EGFR kinase inhibitors.
Editors' Summary
Lung cancer, a common type of cancer, has a very low cure rate. Like all cancers, it occurs when cells begin to divide uncontrollably because of changes (mutations) in their genes. Chemotherapy drugs kill these rapidly dividing cells but, because some normal tissues are sensitive to these agents, it is hard to destroy the cancer without causing serious side effects. Recently, “targeted” therapies have brought new hope to some patients with cancer. These therapies attack the changes in cancer cells that allow them to divide uncontrollably but leave normal cells unscathed. One of the first molecules for which a targeted therapy was developed was the epidermal growth factor receptor (EGFR). In normal cells, messenger proteins bind to EGFR and activate its “tyrosine kinase,” an enzyme that sticks phosphate groups on tyrosine (an amino acid) in other proteins. These proteins then tell the cell to divide. Alterations to this signaling system drive uncontrolled cell division in some cancers so blocking the EGFR signaling pathway should stop these cancers growing. Indeed, some lung cancers with mutations in the tyrosine kinase of EGFR shrink dramatically when treated with gefitinib or erlotinib, two tyrosine kinase inhibitors (TKIs).
Why Was This Study Done?
TKI-sensitive lung cancers shrink when treated with TKIs because of drug-induced cell death, but what are the molecular mechanisms underlying this death? A better understanding of how TKIs kill cancer cells might provide new insights into why not all cancer cells with mutations in EGFR (the gene from which EGFR is made) are sensitive to TKIs. It might also uncover new targets for therapy. TKIs do not completely kill lung cancers, but if the mechanism of TKI-induced cell death were understood, it might be possible to enhance their effects. In this study, the researchers have investigated how cell death occurs after kinase inhibition in a panel of human lung cancer cell lines (cells isolated from human tumors that grow indefinitely in dishes) that carry EGFR mutations.
What Did the Researchers Do and Find?
The researchers show, first, that erlotinib induces a type of cell death called apoptosis in erlotinib-sensitive cell lines but not in resistant cell lines. Apoptosis can be activated by two major pathways. In this instance, the researchers report, the so-called “intrinsic” pathway activates apoptosis. This pathway is stimulated by proapoptotic members of the BCL2 family of proteins and is blocked by antiapoptotic members, so the researchers examined the effect of erlotinib treatment on the expression of BCL2 family members in the EGFR mutant cell lines. Erlotinib treatment increased the expression of the proapoptotic protein BIM in sensitive but not in resistant cell lines. It also removed phosphate groups from BIM—dephosphorylated BIM is a more potent proapoptotic protein. Conversely, blocking BIM expression using a technique called RNA interference virtually eliminated the ability of erlotinib to kill EGFR mutant cell lines. The researchers also report that erlotinib treatment increased BIM expression in erlotinib-sensitive lung tumors growing in mice and that an inhibitor of the anti-apoptotic protein BCL2 enhanced erlotinib-induced death in drug-sensitive cells growing in dishes.
What Do These Findings Mean?
These findings indicate that BIM activity is essential for the apoptosis triggered by TKIs in drug-sensitive lung cancer cells that carry EGFR mutations, and that treatment of these cells with TKIs induces both the expression and dephosphorylation of BIM. The finding that the intrinsic pathway of apoptosis activation is involved in TKI-induced cell death suggests that changes in this pathway (possibly mutations in some of its components) might influence the sensitivity of EGFR mutant lung cancers to TKIs. Finally, these findings suggest that giving drugs that affect the intrinsic pathway of apoptosis activation at the same time as TKIs might further improve the clinical outcome for patients with EGFR mutant tumors. Such combinations will have to be tested in clinical trials before being used routinely.
Additional Information.
Please access these Web sites via the online version of this summary at
US National Cancer Institute information for patients and professionals on lung cancer (in English and Spanish)
Information for patients from Cancer Research UK on lung cancer including information on treatment with TKIs
Wikipedia pages on apoptosis, epidermal growth factor receptor, and BCL-2 proteins (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Information for patients from Cancerbackup on erlotinib and gefitinib
PMCID: PMC2001209  PMID: 17927446
15.  Sirtuin-3 (SIRT3), a therapeutic target with oncogenic and tumor-suppressive function in cancer 
Cell Death & Disease  2014;5(2):e1047-.
Sirtuin-3 (SIRT3), a major mitochondria NAD+-dependent deacetylase, may target mitochondrial proteins for lysine deacetylation and also regulate cellular functions. And, SIRT3 is an emerging instrumental regulator of the mitochondrial adaptive response to stress, such as metabolic reprogramming and antioxidant defense mechanisms. Accumulating evidence has recently demonstrated that SIRT3 may function as either oncogene or tumor suppressor on influencing cell death by targeting a series of key modulators and their relevant pathways in cancer. Thus, in this review, we present the structure, transcriptional regulation, and posttranslational modifications of SIRT3. Subsequently, we focus on highlighting the Janus role of SIRT3 with oncogenic or tumor-suppressive function in cancer, which may provide more new clues for exploring SIRT3 as a therapeutic target for drug discovery.
PMCID: PMC3944233  PMID: 24503539
sirtuin-3 (SIRT3); mitochondria; oncogene; tumor suppressor; therapeutic target
16.  Mapping cancer cell metabolism with13C flux analysis: Recent progress and future challenges 
The reprogramming of energy metabolism is emerging as an important molecular hallmark of cancer cells. Recent discoveries linking specific metabolic alterations to cancer development have strengthened the idea that altered metabolism is more than a side effect of malignant transformation, but may in fact be a functional driver of tumor growth and progression in some cancers. As a result, dysregulated metabolic pathways have become attractive targets for cancer therapeutics. This review highlights the application of13C metabolic flux analysis (MFA) to map the flow of carbon through intracellular biochemical pathways of cancer cells. We summarize several recent applications of MFA that have identified novel biosynthetic pathways involved in cancer cell proliferation and shed light on the role of specific oncogenes in regulating these pathways. Through such studies, it has become apparent that the metabolic phenotypes of cancer cells are not as homogeneous as once thought, but instead depend strongly on the molecular alterations and environmental factors at play in each case.
PMCID: PMC3746411  PMID: 23961260
Aerobic glycolysis; isotopomer analysis; metabolomics; reductive carboxylation; warburg effect
17.  AMPK as a Potential Anticancer Target – Friend or Foe? 
Current pharmaceutical design  2014;20(15):2607-2618.
Adenosine monophosphate-activated protein kinase (AMPK) is a key player in maintaining energy homeostasis in response to metabolic stress. Beyond diabetes and metabolic syndrome, there is a growing interest in the therapeutic exploitation of the AMPK pathway in cancer treatment in light of its unique ability to regulate cancer cell proliferation through the reprogramming of cell metabolism. Although many studies support the tumor-suppressive role of AMPK, emerging evidence suggests that the metabolic checkpoint function of AMPK might be overridden by stress or oncogenic signals so that tumor cells use AMPK activation as a survival strategy to gain growth advantage. These findings underscore the complexity in the cellular function of AMPK in maintaining energy homeostasis under physiological versus pathological conditions. Thus, this review aims to provide an overview of recent findings on the functional interplay of AMPK with different cell metabolic and signaling effectors, particularly histone deacetylases, in mediating downstream tumor suppressive or promoting mechanisms in different cell systems. Although AMPK activation inhibits tumor growth by targeting multiple signaling pathways relevant to tumorigenesis, under certain cellular contexts or certain stages of tumor development, AMPK might act as a protective response to metabolic stresses, such as nutrient deprivation, low oxygen, and low pH, or as a downstream effectors of oncogenic proteins, including androgen receptor, hypoxia-inducible factor-1α, c-Src, and MYC. Thus, investigations to define at which stage(s) of tumorigenesis and cancer progression or for which genetic aberrations AMPK inhibition might represent a more relevant strategy than AMPK activation for cancer treatment are clearly warranted.
PMCID: PMC4264967  PMID: 23859619
AMPK; metabolic homeostasis; cancer therapy; LKB1; mTORC1; HDAC; Foxo3a; HIF-1α
18.  Human Gene Control by Vital Oncogenes: Revisiting a Theoretical Model and Its Implications for Targeted Cancer Therapy 
An important assumption of our current understanding of the mechanisms of carcinogenesis has been the belief that clarification of the cancer process would inevitably reveal some of the crucial mechanisms of normal human gene regulation. Since the momentous work of Bishop and Varmus, both the molecular and the biochemical processes underlying the events in the development of cancer have become increasingly clear. The identification of cellular signaling pathways and the role of protein kinases in the events leading to gene activation have been critical to our understanding not only of normal cellular gene control mechanisms, but also have clarified some of the important molecular and biochemical events occurring within a cancer cell. We now know that oncogenes are dysfunctional proto-oncogenes and that dysfunctional tumor suppressor genes contribute to the cancer process. Furthermore, Weinstein and others have hypothesized the phenomenon of oncogene addiction as a distinct characteristic of the malignant cell. It can be assumed that cancer cells, indeed, become dependent on such vital oncogenes. The products of these vital oncogenes, such as c-myc, may well be the Achilles heel by which targeted molecular therapy may lead to truly personalized cancer therapy. The remaining problem is the need to introduce relevant molecular diagnostic tests such as genome microarray analysis and proteomic methods, especially protein kinase identification arrays, for each individual patient. Genome wide association studies on cancers with gene analysis of single nucleotide and other mutations in functional proto-oncogenes will, hopefully, identify dysfunctional proto-oncogenes and allow the development of more specific targeted drugs directed against the protein products of these vital oncogenes. In 1984 Willis proposed a molecular and biochemical model for eukaryotic gene regulation suggesting how proto-oncogenes might function within the normal cell. That model predicted the existence of vital oncogenes and can now be used to hypothesize the biochemical and molecular mechanisms that drive the processes leading to disruption of the gene regulatory machinery, resulting in the transformation of normal cells into cancer.
PMCID: PMC3269688  PMID: 22312254
oncogenes; gene regulation; gene transcription; transcription activator; targeted cancer therapy; signal transduction; carcinogenesis; protein kinase; cell cycle control; steroid hormone action
19.  Targeting SREBP-1-driven lipid metabolism to treat cancer 
Current pharmaceutical design  2014;20(15):2619-2626.
Metabolic reprogramming is a hallmark of cancer. Oncogenic growth signaling regulates glucose, glutamine and lipid metabolism to meet the bioenergetics and biosynthetic demands of rapidly proliferating tumor cells. Emerging evidence indicates that sterol regulatory element-binding protein 1 (SREBP-1), a master transcription factor that controls lipid metabolism, is a critical link between oncogenic signaling and tumor metabolism. We recently demonstrated that SREBP-1 is required for the survival of mutant EGFR-containing glioblastoma, and that this pro-survival metabolic pathway is mediated, in part, by SREBP-1-dependent upregulation of the fatty acid synthesis and low density lipoprotein (LDL) receptor (LDLR). These results have identified EGFR/PI3K/Akt/SREBP-1 signaling pathway that promotes growth and survival in glioblastoma, and potentially other cancer types. Here, we summarize recent insights in the understanding of cancer lipid metabolism, and discuss the evidence linking SREBP-1 with PI3K/Akt signaling-controlled glycolysis and with Myc-regulated glutaminolysis to lipid metabolism. We also discuss the development of potential drugs targeting the SREBP-1-driven lipid metabolism as anti-cancer agents.
PMCID: PMC4148912  PMID: 23859617
20.  Balancing glycolytic flux: the role of 6-phosphofructo-2-kinase/fructose 2,6-bisphosphatases in cancer metabolism 
The increased glucose metabolism in cancer cells is required to fulfill their high energetic and biosynthetic demands. Changes in the metabolic activity of cancer cells are caused by the activation of oncogenes or loss of tumor suppressors. They can also be part of the metabolic adaptations to the conditions imposed by the tumor microenvironment, such as the hypoxia response. Among the metabolic enzymes that are modulated by these factors are the 6-phosphofructo-2-kinase/fructose 2,6-bisphosphatases (PFKFBs), a family of bifunctional enzymes that control the levels of fructose 2,6-bisphosphate (Fru-2,6-P2). This metabolite is important for the dynamic regulation of glycolytic flux by allosterically activating the rate-limiting enzyme of glycolysis phosphofructokinase-1 (PFK-1). Therapeutic strategies designed to alter the levels of this metabolite are likely to interfere with the metabolic balance of cancer cells, and could lead to a reduction in cancer cell proliferation, invasiveness and survival. This article will review our current understanding of the role of PFKFB proteins in the control of cancer metabolism and discuss the emerging interest in these enzymes as potential targets for the development of antineoplastic agents.
PMCID: PMC4178209  PMID: 24280138
Cancer metabolism; Fructose 2,6-bisphosphate; PFK-2/FBPase-2
The majority of lung cancers are caused by long term exposure to the several classes of carcinogens present in tobacco smoke. While a significant fraction of lung cancers in never smokers may also be attributable to tobacco, many such cancers arise in the absence of detectable tobacco exposure, and may follow a very different cellular and molecular pathway of malignant transformation. Recent studies summarized here suggest that lung cancers arising in never smokers have a distinct natural history, profile of oncogenic mutations, and response to targeted therapy. The majority of molecular analyses of lung cancer have focused on genetic profiling of pathways responsible for metabolism of primary tobacco carcinogens. Limited research has been conducted evaluating familial aggregation and genetic linkage of lung cancer, particularly among never smokers in whom such associations might be expected to be strongest. Data emerging over the past several years demonstrates that lung cancers in never smokers are much more likely to carry activating mutations of the Epidermal Growth Factor Receptor (EGFR), a key oncogenic factor and direct therapeutic target of several newer anti-cancer drugs. EGFR mutant lung cancers may represent a distinct class of lung cancers, enriched in the never smoking population, and less clearly linked to direct tobacco carcinogenesis. These insights followed initial testing and demonstration of efficacy of EGFR-targeted drugs. Focused analysis of molecular carcinogenesis in lung cancers in never smokers is needed, and may provide additional biologic insight with therapeutic implications for lung cancers in both ever smokers and never smokers.
PMCID: PMC2950319  PMID: 19755392
22.  The Human Adenovirus E4-ORF1 Protein Subverts Discs Large 1 to Mediate Membrane Recruitment and Dysregulation of Phosphatidylinositol 3-Kinase 
PLoS Pathogens  2014;10(5):e1004102.
Adenoviruses infect epithelial cells lining mucous membranes to cause acute diseases in people. They are also utilized as vectors for vaccination and for gene and cancer therapy, as well as tools to discover mechanisms of cancer due to their tumorigenic potential in experimental animals. The adenovirus E4-ORF1 gene encodes an oncoprotein that promotes viral replication, cell survival, and transformation by activating phosphatidylinositol 3-kinase (PI3K). While the mechanism of activation is not understood, this function depends on a complex formed between E4-ORF1 and the membrane-associated cellular PDZ protein Discs Large 1 (Dlg1), a common viral target having both tumor suppressor and oncogenic functions. Here, we report that in human epithelial cells, E4-ORF1 interacts with the regulatory and catalytic subunits of PI3K and elevates their levels. Like PI3K activation, PI3K protein elevation by E4-ORF1 requires Dlg1. We further show that Dlg1, E4-ORF1, and PI3K form a ternary complex at the plasma membrane. At this site, Dlg1 also co-localizes with the activated PI3K effector protein Akt, indicating that the ternary complex mediates PI3K signaling. Signifying the functional importance of the ternary complex, the capacity of E4-ORF1 to induce soft agar growth and focus formation in cells is ablated either by a mutation that prevents E4-ORF1 binding to Dlg1 or by a PI3K inhibitor drug. These results demonstrate that E4-ORF1 interacts with Dlg1 and PI3K to assemble a ternary complex where E4-ORF1 hijacks the Dlg1 oncogenic function to relocate cytoplasmic PI3K to the membrane for constitutive activation. This novel mechanism of Dlg1 subversion by adenovirus to dysregulate PI3K could be used by other pathogenic viruses, such as human papillomavirus, human T-cell leukemia virus type 1, and influenza A virus, which also target Dlg1 and activate PI3K in cells.
Author Summary
Adenoviruses cause acute illnesses in people, and are additionally utilized both as vehicles to cure genetic diseases, fight cancer, and deliver vaccines, and as tools to discover how cancers develop due to a capacity to generate tumors in experimental animals. The adenovirus E4-ORF1 protein reprograms cell metabolism to enhance virus production in infected cells and promotes cell survival and tumors by activating the important cellular protein phosphatidylinositol 3-kinase (PI3K). How E4-ORF1 activates PI3K is not known, though this function depends on E4-ORF1 binding to the membrane-associated cellular protein Discs Large 1 (Dlg1), which many different viruses evolved to target. In this study, we identify PI3K as a new direct target of E4-ORF1. Results further show that E4-ORF1 binds to PI3K in the cytoplasm and delivers it to Dlg1 at the membrane where the three proteins form a complex that activates PI3K and induces oncogenic growth in cells. This novel molecular mechanism in which adenovirus subverts Dlg1 to dysregulate PI3K may serve as a paradigm to understand PI3K activation mediated by other important pathogenic viruses, such as human papillomavirus, human T-cell leukemia virus type 1, and influenza A virus, which also target Dlg1 in infected cells.
PMCID: PMC4006922  PMID: 24788832
23.  STAT3 in Cancer—Friend or Foe? 
Cancers  2014;6(3):1408-1440.
The roles and significance of STAT3 in cancer biology have been extensively studied for more than a decade. Mounting evidence has shown that constitutive activation of STAT3 is a frequent biochemical aberrancy in cancer cells, and this abnormality directly contributes to tumorigenesis and shapes many malignant phenotypes in cancer cells. Nevertheless, results from more recent experimental and clinicopathologic studies have suggested that STAT3 also can exert tumor suppressor effects under specific conditions. Importantly, some of these studies have demonstrated that STAT3 can function either as an oncoprotein or a tumor suppressor in the same cell type, depending on the specific genetic background or presence/absence of specific coexisting biochemical defects. Thus, in the context of cancer biology, STAT3 can be a friend or foe. In the first half of this review, we will highlight the “evil” features of STAT3 by summarizing its oncogenic functions and mechanisms. The differences between the canonical and non-canonical pathway will be highlighted. In the second half, we will summarize the evidence supporting that STAT3 can function as a tumor suppressor. To explain how STAT3 may mediate its tumor suppressor effects, we will discuss several possible mechanisms, one of which is linked to the role of STAT3β, one of the two STAT3 splicing isoforms. Taken together, it is clear that the roles of STAT3 in cancer are multi-faceted and far more complicated than one appreciated previously. The new knowledge has provided us with new approaches and strategies when we evaluate STAT3 as a prognostic biomarker or therapeutic target.
PMCID: PMC4190548  PMID: 24995504
STAT3; oncoprotein; tumor suppressor; STAT3β; prognostic marker; therapeutic target
24.  Tumor Metabolism of Malignant Gliomas 
Cancers  2013;5(4):1469-1484.
Constitutively activated oncogenic signaling via genetic mutations such as in the EGFR/PI3K/Akt and Ras/RAF/MEK pathways has been recognized as a major driver for tumorigenesis in most cancers. Recent insights into tumor metabolism have further revealed that oncogenic signaling pathways directly promote metabolic reprogramming to upregulate biosynthesis of lipids, carbohydrates, protein, DNA and RNA, leading to enhanced growth of human tumors. Therefore, targeting cell metabolism has become a novel direction for drug development in oncology. In malignant gliomas, metabolism pathways of glucose, glutamine and lipid are significantly reprogrammed. Moreover, molecular mechanisms causing these metabolic changes are just starting to be unraveled. In this review, we will summarize recent studies revealing critical gene alterations that lead to metabolic changes in malignant gliomas, and also discuss promising therapeutic strategies via targeting the key players in metabolic regulation.
PMCID: PMC3875949  PMID: 24217114
glioblastoma; tumor metabolism; SREBP-1; LDLR; LXR; glucose; lipids; cholesterol
25.  A Genome-Wide Screen for Promoter Methylation in Lung Cancer Identifies Novel Methylation Markers for Multiple Malignancies  
PLoS Medicine  2006;3(12):e486.
Promoter hypermethylation coupled with loss of heterozygosity at the same locus results in loss of gene function in many tumor cells. The “rules” governing which genes are methylated during the pathogenesis of individual cancers, how specific methylation profiles are initially established, or what determines tumor type-specific methylation are unknown. However, DNA methylation markers that are highly specific and sensitive for common tumors would be useful for the early detection of cancer, and those required for the malignant phenotype would identify pathways important as therapeutic targets.
Methods and Findings
In an effort to identify new cancer-specific methylation markers, we employed a high-throughput global expression profiling approach in lung cancer cells. We identified 132 genes that have 5′ CpG islands, are induced from undetectable levels by 5-aza-2′-deoxycytidine in multiple non-small cell lung cancer cell lines, and are expressed in immortalized human bronchial epithelial cells. As expected, these genes were also expressed in normal lung, but often not in companion primary lung cancers. Methylation analysis of a subset (45/132) of these promoter regions in primary lung cancer (n = 20) and adjacent nonmalignant tissue (n = 20) showed that 31 genes had acquired methylation in the tumors, but did not show methylation in normal lung or peripheral blood cells. We studied the eight most frequently and specifically methylated genes from our lung cancer dataset in breast cancer (n = 37), colon cancer (n = 24), and prostate cancer (n = 24) along with counterpart nonmalignant tissues. We found that seven loci were frequently methylated in both breast and lung cancers, with four showing extensive methylation in all four epithelial tumors.
By using a systematic biological screen we identified multiple genes that are methylated with high penetrance in primary lung, breast, colon, and prostate cancers. The cross-tumor methylation pattern we observed for these novel markers suggests that we have identified a partial promoter hypermethylation signature for these common malignancies. These data suggest that while tumors in different tissues vary substantially with respect to gene expression, there may be commonalities in their promoter methylation profiles that represent targets for early detection screening or therapeutic intervention.
John Minna and colleagues report that a group of genes are commonly methylated in primary lung, breast, colon, and prostate cancer.
Editors' Summary
Tumors or cancers contain cells that have lost many of the control mechanisms that normally regulate their behavior. Unlike normal cells, which only divide to repair damaged tissues, cancer cells divide uncontrollably. They also gain the ability to move round the body and start metastases in secondary locations. These changes in behavior result from alterations in their genetic material. For example, mutations (permanent changes in the sequence of nucleotides in the cell's DNA) in genes known as oncogenes stimulate cells to divide constantly. Mutations in another group of genes—tumor suppressor genes—disable their ability to restrain cell growth. Key tumor suppressor genes are often completely lost in cancer cells. But not all the genetic changes in cancer cells are mutations. Some are “epigenetic” changes—chemical modifications of genes that affect the amount of protein made from them. In cancer cells, methyl groups are often added to CG-rich regions—this is called hypermethylation. These “CpG islands” lie near gene promoters—sequences that control the transcription of DNA into RNA, the template for protein production—and their methylation switches off the promoter. Methylation of the promoter of one copy of a tumor suppressor gene, which often coincides with the loss of the other copy of the gene, is thought to be involved in cancer development.
Why Was This Study Done?
The rules that govern which genes are hypermethylated during the development of different cancer types are not known, but it would be useful to identify any DNA methylation events that occur regularly in common cancers for two reasons. First, specific DNA methylation markers might be useful for the early detection of cancer. Second, identifying these epigenetic changes might reveal cellular pathways that are changed during cancer development and so identify new therapeutic targets. In this study, the researchers have used a systematic biological screen to identify genes that are methylated in many lung, breast, colon, and prostate cancers—all cancers that form in “epithelial” tissues.
What Did the Researchers Do and Find?
The researchers used microarray expression profiling to examine gene expression patterns in several lung cancer and normal lung cell lines. In this technique, labeled RNA molecules isolated from cells are applied to a “chip” carrying an array of gene fragments. Here, they stick to the fragment that represents the gene from which they were made, which allows the genes that the cells express to be catalogued. By comparing the expression profiles of lung cancer cells and normal lung cells before and after treatment with a chemical that inhibits DNA methylation, the researchers identified genes that were methylated in the cancer cells—that is, genes that were expressed in normal cells but not in cancer cells unless methylation was inhibited. 132 of these genes contained CpG islands. The researchers examined the promoters of 45 of these genes in lung cancer cells taken straight from patients and found that 31 of the promoters were methylated in tumor tissues but not in adjacent normal tissues. Finally, the researchers looked at promoter methylation of the eight genes most frequently and specifically methylated in the lung cancer samples in breast, colon, and prostate cancers. Seven of the genes were frequently methylated in both lung and breast cancers; four were extensively methylated in all the tumor types.
What Do These Findings Mean?
These results identify several new genes that are often methylated in four types of epithelial tumor. The observation that these genes are methylated in multiple independent tumors strongly suggests, but does not prove, that loss of expression of the proteins that they encode helps to convert normal cells into cancer cells. The frequency and diverse patterning of promoter methylation in different tumor types also indicates that methylation is not a random event, although what controls the patterns of methylation is not yet known. The identification of these genes is a step toward building a promoter hypermethylation profile for the early detection of human cancer. Furthermore, although tumors in different tissues vary greatly with respect to gene expression patterns, the similarities seen in this study in promoter methylation profiles might help to identify new therapeutic targets common to several cancer types.
Additional Information.
Please access these Web sites via the online version of this summary at
US National Cancer Institute, information for patients on understanding cancer
CancerQuest, information provided by Emory University about how cancer develops
Cancer Research UK, information for patients on cancer biology
Wikipedia pages on epigenetics (note that Wikipedia is a free online encyclopedia that anyone can edit)
The Epigenome Network of Excellence, background information and latest news about epigenetics
PMCID: PMC1716188  PMID: 17194187

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