Contextual inhibition of fatty acid synthesis by metformin involves glucose-derived acetyl-CoA and cholesterol in pancreatic tumor cells

Metformin augments major cytoplasmic organization except for spindle organization in oocytes cultured under hyperglycemic and hyperlipidemic conditions: An in vitro study

The present study aimed to investigate the role of antidiabetic drug metformin on the cytoplasmic organization of oocytes. Germinal vesicle (GV) stage oocytes were collected from adult female Swiss albino mice and subjected to in vitro maturation (IVM) in various experimental groups- control, vehicle control (0.3% ethanol), metformin (50 μg/mL), high glucose and high lipid (HGHL, 10 mM glucose; 150 μM palmitic acid; 75 μM stearic acid and 200 μM oleic acid in ethanol), and HGHL supplemented with metformin. The metaphase II (MII) oocytes were analyzed for lipid accumulation, mitochondrial and endoplasmic reticulum (ER) distribution pattern, oxidative and ER stress, actin filament organization, cortical granule distribution pattern, spindle organization and chromosome alignment. An early polar body extrusion was observed in the HGHL group. However, the maturation rate at 24 h did not differ significantly among the experimental groups compared to the control. The HGHL conditions exhibited significantly higher levels of oxidative stress, ER stress, poor actin filament organization, increased lipid accumulation, altered mitochondrial distribution, spindle abnormalities, and chromosome misalignment compared to the control. Except for spindle organization, supplementation of metformin to the HGHL conditions improved all the parameters (non-significant for ER and actin distribution pattern). These results show that metformin exposure in the culture media helped to improve the hyperglycemia and hyperlipidemia-induced cytoplasmic anomalies except for spindle organization. Given the crucial role of spindle organization in proper chromosome segregation during oocyte maturation and meiotic resumption, the implications of metformin's limitations in this aspect warrant careful evaluation and further investigation.

Progress on diagnostic and prognostic markers of pancreatic cancer

Pancreatic cancer is a malignant disease characterized by low survival and high recurrence rate, whose patients are mostly at the stage of locally advanced or metastatic disease when first diagnosed. Early diagnosis is particularly important because prognostic/predictive markers help guide optimal individualized treatment regimens. So far, CA19-9 is the only biomarker for pancreatic cancer approved by the FDA, but its effectiveness is limited by low sensitivity and specificity. With recent advances in genomics, proteomics, metabolomics, and other analytical and sequencing technologies, the rapid acquisition and screening of biomarkers is now possible. Liquid biopsy also occupies a significant place due to its unique advantages. In this review, we systematically describe and evaluate the available biomarkers that have the greatest potential as vital tools in diagnosing and treating pancreatic cancer.

Single cell mass spectrometry analysis of drug-resistant cancer cells: Metabolomics studies of synergetic effect of combinational treatment

Irinotecan (IRI), a topoisomerase I inhibitor blocking DNA synthesis, is a widely used chemotherapy drug for metastatic colorectal cancer. Despite being an effective chemotherapy drug, its clinical effectiveness is limited by both intrinsic and acquired drug resistance. Previous studies indicate IRI induces cancer stemness in irinotecan-resistant (IRI-resistant) cells. Metformin, an oral antidiabetic drug, was recently reported for anticancer effects, likely due to its selective killing of cancer stem cells (CSCs). Given IRI-resistant cells exhibiting high cancer stemness, we hypothesize metformin can sensitize IRI-resistant cells and rescue the therapeutic effect. In this work, we utilized the Single-probe mass spectrometry technique to analyze live IRI-resistant cells under different treatment conditions. We discovered that metformin treatment was associated with the downregulation of lipids and fatty acids, potentially through the inhibition of fatty acid synthase (FASN). Importantly, certain species can be only detected from cells in their living status. The level of synergistic effect of metformin and IRI in their co-treatment of IRI-resistant cells was evaluated using Chou-Talalay combinational index. Using enzymatic activity assay, we determined that the co-treatment exhibit the highest FASN inhibition compared with the mono-treatment of IRI or metformin. To our knowledge, this is the first single-cell MS metabolomics study demonstrating metformin-IRI synergistic effect overcoming drug resistance in IRI-resistant cells.

A review on the molecular mechanisms, the therapeutic treatment including the potential of herbs and natural products, and target prediction of obesity-associated colorectal cancer

Colorectal cancer (CRC) is the third leading cause of cancer death worldwide. Obesity has been proven to be closely related to colorectal carcinogenesis. This review summarized the potential underlying mechanisms linking obesity to CRC in different aspects, including energy metabolism, inflammation, activities of adipokines and hormones. Furthermore, the potential therapeutic targets of obesity-associated CRC were predicted using network-based target analysis, with total predicted pathways not only containing previously reported pathways, but also putative signaling pathways pending for investigation. In addition, the current conventional therapeutic treatment options, plus the potential use of herbs and natural products in the management of obesity-associated CRC were also discussed. Taken together, the aim of this review article is to provide strong theoretical basis for future drug development, particularly herbs and natural products, in obesity-associated CRC.

Deuterium Depletion Inhibits Cell Proliferation, RNA and Nuclear Membrane Turnover to Enhance Survival in Pancreatic Cancer

The effects of deuterium-depleted water (DDW) containing deuterium (D) at a concentration of 25 parts per million (ppm), 50 ppm, 105 ppm and the control at 150 ppm were monitored in MIA-PaCa-2 pancreatic cancer cells by the real-time cell impedance detection xCELLigence method. The data revealed that lower deuterium concentrations corresponded to lower MiA PaCa-2 growth rate. Nuclear membrane turnover and nucleic acid synthesis rate at different D-concentrations were determined by targeted [1,2-13C2]-D-glucose fate associations. The data showed severely decreased oxidative pentose cycling, RNA ribose 13C labeling from [1,2-13C2]-D-glucose and nuclear membrane lignoceric (C24:0) acid turnover. Here, we treated advanced pancreatic cancer patients with DDW as an extra-mitochondrial deuterium-depleting strategy and evaluated overall patient survival. Eighty-six (36 male and 50 female) pancreatic adenocarcinoma patients were treated with conventional chemotherapy and natural water (control, 30 patients) or 85 ppm DDW (56 patients), which was gradually decreased to preparations with 65 ppm and 45 ppm deuterium content for each 1 to 3 months treatment period. Patient survival curves were calculated by the Kaplan-Meier method and Pearson correlation was taken between medial survival time (MST) and DDW treatment in pancreatic cancer patients. The MST for patients consuming DDW treatment (n = 56) was 19.6 months in comparison with the 6.36 months' MST achieved with chemotherapy alone (n = 30). There was a strong, statistically significant Pearson correlation (r = 0.504, p < 0.001) between survival time and length and frequency of DDW treatment.

Metformin in colorectal cancer: molecular mechanism, preclinical and clinical aspects

Growing evidence showed the increased prevalence of cancer incidents, particularly colorectal cancer, among type 2 diabetic mellitus patients. Antidiabetic medications such as, insulin, sulfonylureas, dipeptyl peptidase (DPP) 4 inhibitors and glucose-dependent insulinotropic peptide (GLP-1) analogues increased the additional risk of different cancers to diabetic patients. Conversely, metformin has drawn attention among physicians and researchers since its use as antidiabetic drug exhibited beneficial effect in the prevention and treatment of cancer in diabetic patients as well as an independent anticancer drug. This review aims to provide the comprehensive information on the use of metformin at preclinical and clinical stages among colorectal cancer patients. We highlight the efficacy of metformin as an anti-proliferative, chemopreventive, apoptosis inducing agent, adjuvant, and radio-chemosensitizer in various colorectal cancer models. This multifarious effects of metformin is largely attributed to its capability in modulating upstream and downstream molecular targets involved in apoptosis, autophagy, cell cycle, oxidative stress, inflammation, metabolic homeostasis, and epigenetic regulation. Moreover, the review highlights metformin intake and colorectal cancer risk based on different clinical and epidemiologic results from different gender and specific population background among diabetic and non-diabetic patients. The improved understanding of metformin as a potential chemotherapeutic drug or as neo-adjuvant will provide better information for it to be used globally as an affordable, well-tolerated, and effective anticancer agent for colorectal cancer.

p13CMFA: Parsimonious 13C metabolic flux analysis

Deciphering the mechanisms of regulation of metabolic networks subjected to perturbations, including disease states and drug-induced stress, relies on tracing metabolic fluxes. One of the most informative data to predict metabolic fluxes are ¹³C based metabolomics, which provide information about how carbons are redistributed along central carbon metabolism. Such data can be integrated using ¹³C Metabolic Flux Analysis (¹³C MFA) to provide quantitative metabolic maps of flux distributions. However, ¹³C MFA might be unable to reduce the solution space towards a unique solution either in large metabolic networks or when small sets of measurements are integrated. Here we present parsimonious ¹³C MFA (p¹³CMFA), an approach that runs a secondary optimization in the ¹³C MFA solution space to identify the solution that minimizes the total reaction flux. Furthermore, flux minimization can be weighted by gene expression measurements allowing seamless integration of gene expression data with ¹³C data. As proof of concept, we demonstrate how p¹³CMFA can be used to estimate intracellular flux distributions from ¹³C measurements and transcriptomics data. We have implemented p¹³CMFA in Iso2Flux, our in-house developed isotopic steady-state ¹³C MFA software. The source code is freely available on GitHub (https://github.com/cfoguet/iso2flux/releases/tag/0.7.2).

¹³C Metabolic Flux Analysis (¹³C MFA) is a well-established technique that has proven to be a valuable tool in quantifying the metabolic flux profile of central carbon metabolism. When a biological system is incubated with a ¹³C-labeled substrate, ¹³C propagates to metabolites throughout the metabolic network in a flux and pathway-dependent manner. ¹³C MFA integrates measurements of ¹³C enrichment in metabolites to identify the flux distributions consistent with the measured ¹³C propagation. However, there is often a range of flux values that can lead to the observed ¹³C distribution. Indeed, either when the metabolic network is large or a small set of measurements are integrated, the range of valid solutions can be too wide to accurately estimate part of the underlying flux distribution. Here we propose to use flux minimization to select the best flux solution in the¹³C MFA solution space. Furthermore, this approach can integrate gene expression data to give greater weight to the minimization of fluxes through enzymes with low gene expression evidence in order to ensure that the selected solution is biologically relevant. The concept of using flux minimization to select the best solution is widely used in flux balance analysis, but it had never been applied in the framework of ¹³C MFA. We have termed this new approach parsimonious ¹³C MFA (p¹³CMFA).

Potential application of cell reprogramming techniques for cancer research

The ability to control the transition from an undifferentiated stem cell to a specific cell fate is one of the key techniques that are required for the application of interventional technologies to regenerative medicine and the treatment of tumors and metastases and of neurodegenerative diseases. Reprogramming technologies, which include somatic cell nuclear transfer, induced pluripotent stem cells, and the direct reprogramming of specific cell lineages, have the potential to alter cell plasticity in translational medicine for cancer treatment. The characterization of cancer stem cells (CSCs), the identification of oncogene and tumor suppressor genes for CSCs, and the epigenetic study of CSCs and their microenvironments are important topics. This review summarizes the application of cell reprogramming technologies to cancer modeling and treatment and discusses possible obstacles, such as genetic and epigenetic alterations in cancer cells, as well as the strategies that can be used to overcome these obstacles to cancer research.

The role of metabolic adaptation to nutrient stress in pancreatic cancer

Pancreatic cancer is the fourth most common cause of cancer-related mortality, with a dismal prognosis that has changed little over the past few decades. Despite extensive efforts in understanding the oncogenetics of this pathology, pancreatic cancer remained largely elusive. One of the main characteristics of pancreatic cancer is the reduced level of oxygen and nutrient perfusion, caused by the new matrix formation, through the activation of stromal cells (desmoplasia). This stromal reaction leads to metabolic adaptations in surviving tumor cells in order to cope with these challenging conditions. The oncogenic signaling driven by KRAS mutation is necessary to fuel pancreatic tumors by activating key metabolic processes, including enhanced glycolysis and glutamine consumption. Here we review our current understanding of the pancreatic cancer metabolism as well as discuss recent work pointing to the importance of various metabolic strategies as well as autophagy and macropinocytosis as critical nutrient supply pathways. The elucidation of these metabolic networks may highlight new opportunities to further develop novel therapeutic strategies.

Fatty acid synthase (FASN) as a therapeutic target in breast cancer

INTRODUCTION

Ten years ago, we put forward the metabolo-oncogenic nature of fatty acid synthase (FASN) in breast cancer. Since the conception of this hypothesis, which provided a model to explain how FASN is intertwined with various signaling networks to cell-autonomously regulate breast cancer initiation and progression, FASN has received considerable attention as a therapeutic target. However, despite the ever-growing evidence demonstrating the involvement of FASN as part of the cancer-associated metabolic reprogramming, translation of the basic science-discovery aspects of FASN blockade to the clinical arena remains a challenge. Areas covered: Ten years later, we herein review the preclinical lessons learned from the pharmaceutical liabilities of the first generation of FASN inhibitors. We provide an updated view of the current development and clinical testing of next generation FASN-targeted drugs. We also discuss new clinico-molecular approaches that should help us to convert roadblocks into roadways that will propel forward our therapeutic understanding of FASN. Expert opinion: With the recent demonstration of target engagement and early signs of clinical activity with the first orally available, selective, potent and reversible FASN inhibitor, we can expect Big pharma to revitalize their interest in lipogenic enzymes as well-credentialed targets for oncology drug development in breast cancer.

Structural homologies between phenformin, lipitor and gleevec aim the same metabolic oncotarget in leukemia and melanoma

Phenformin's recently demonstrated efficacy in melanoma and Gleevec's demonstrated anti-proliferative action in chronic myeloid leukemia may lie within these drugs' significant pharmacokinetics, pharmacodynamics and structural homologies, which are reviewed herein. Gleevec's success in turning a fatal leukemia into a manageable chronic disease has been trumpeted in medical, economic, political and social circles because it is considered the first successful targeted therapy. Investments have been immense in omics analyses and while in some cases they greatly helped the management of patients, in others targeted therapies failed to achieve clinically stable recurrence-free disease course or to substantially extend survival. Nevertheless protein kinase controlling approaches have persisted despite early warnings that the targeted genomics narrative is overblown. Experimental and clinical observations with Phenformin suggest an alternative explanation for Gleevec's mode of action. Using 13C-guided precise flux measurements, a comparative multiple cell line study demonstrated the drug's downstream impact on submolecular fatty acid processing metabolic events that occurred independent of Gleevec's molecular target. Clinical observations that hyperlipidemia and diabetes are both reversed in mice and in patients taking Gleevec support the drugs' primary metabolic targets by biguanides and statins. This is evident by structural data demonstrating that Gleevec shows pyridine- and phenyl-guanidine homology with Phenformin and identical phenylcarbamoyl structural and ligand binding homology with Lipitor. The misunderstood mechanism of action of Gleevec is emblematic of the pervasive flawed reasoning that genomic analysis will lead to targeted, personalized diagnosis and therapy. The alternative perspective for Gleevec's mode of action may turn oncotargets towards metabolic channel reaction architectures in leukemia and melanoma, as well as in other cancers.

Metabolomics in pancreatic cancer biomarkers research

Pancreatic cancer is one of the worst prognoses of all malignancies. More than 40,000 deaths a year from this disease are observed in European Union alone. The only possibly curative treatment of pancreatic cancer is surgery, yet only 15-20% of patients have operable disease and even patients, which go through surgery and adjuvant chemotherapy, survival is less than 30%. The sensitive and specific biomarkers which could be used for the advance of early diagnostics are needed and constantly researched. Metabolomics is a technology which analyzes the concentrations of low-molecular-weight metabolites (the metabolome) has lately effectively developed due to the improvements in analytical technology. Metabolome analysis can be a one of the useful approaches for the biomarker discovery and disease diagnosis. Here we discuss recent discoveries in the field of pancreatic cancer metabolomics as well as the most promising biomarkers for diagnostics, prognosis and prediction.

Diabetes mellitus and metformin in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related death worldwide. Diabetes mellitus, a risk factor for cancer, is also globally endemic. The clinical link between these two diseases has been the subject of investigation for a century, and diabetes mellitus has been established as a risk factor for HCC. Accordingly, metformin, a first-line oral anti-diabetic, was first proposed as a candidate anti-cancer agent in 2005 in a cohort study in Scotland. Several subsequent large cohort studies and randomized controlled trials have not demonstrated significant efficacy for metformin in suppressing HCC incidence and mortality in diabetic patients; however, two recent randomized controlled trials have reported positive data for the tumor-preventive potential of metformin in non-diabetic subjects. The search for biological links between cancer and diabetes has revealed intracellular pathways that are shared by cancer and diabetes. The signal transduction mechanisms by which metformin suppresses carcinogenesis in cell lines or xenograft tissues and improves chemoresistance in cancer stem cells have also been elucidated. This review addresses the clinical and biological links between HCC and diabetes mellitus and the anti-cancer activity of metformin in clinical studies and basic experiments.

Trans-Omics: How To Reconstruct Biochemical Networks Across Multiple 'Omic' Layers

We propose 'trans-omic' analysis for reconstructing global biochemical networks across multiple omic layers by use of both multi-omic measurements and computational data integration. We introduce technologies for connecting multi-omic data based on prior knowledge of biochemical interactions and characterize a biochemical trans-omic network by concepts of a static and dynamic nature. We introduce case studies of metabolism-centric trans-omic studies to show how to reconstruct a biochemical trans-omic network by connecting multi-omic data and how to analyze it in terms of the static and dynamic nature. We propose a trans-ome-wide association study (trans-OWAS) connecting phenotypes with trans-omic networks that reflect both genetic and environmental factors, which can characterize several complex lifestyle diseases as breakdowns in the trans-omic system.

Metformin: A Novel but Controversial Drug in Cancer Prevention and Treatment

Metformin, a biguanide derivative that is widely used for treating type 2 diabetes mellitus, has recently been shown to exert potential anticancer effects. Many retrospective data and laboratory studies suggest the idea that metformin has antineoplastic activity, but some other studies reach conflicting conclusions. Although the precise molecular mechanisms by which metformin affects various cancers have not been fully elucidated, activation of AMPK-dependent and AMPK-independent pathways along with energy metabolism aberration, cell cycle arrest and apoptosis or autophagy induction have emerged as crucial regulators in this process. In this Review, we describe the role of metformin in the prevention and treatment of a variety of cancers and summarize the molecular mechanisms that are currently well documented in the ability of metformin as an anticancer agent. In addition, the scientific and clinical hurdles regarding the potential role of metformin in cancer will be discussed.

Plasma membrane regulates Ras signaling networks

Ras GTPases activate more than 20 signaling pathways, regulating such essential cellular functions as proliferation, survival, and migration. How Ras proteins control their signaling diversity is still a mystery. Several pieces of evidence suggest that the plasma membrane plays a critical role. Among these are: (1) selective recruitment of Ras and its effectors to particular localities allowing access to Ras regulators and effectors; (2) specific membrane-induced conformational changes promoting Ras functional diversity; and (3) oligomerization of membrane-anchored Ras to recruit and activate Raf. Taken together, the membrane does not only attract and retain Ras but also is a key regulator of Ras signaling. This can already be gleaned from the large variability in the sequences of Ras membrane targeting domains, suggesting that localization, environment and orientation are important factors in optimizing the function of Ras isoforms.

Targeting cancer cell metabolism in pancreatic adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is expected to become the second leading cause of cancer death by 2030. Current therapeutic options are limited, warranting an urgent need to explore innovative treatment strategies. Due to specific microenvironment constraints including an extensive desmoplastic stroma reaction, PDAC faces major metabolic challenges, principally hypoxia and nutrient deprivation. Their connection with oncogenic alterations such as KRAS mutations has brought metabolic reprogramming to the forefront of PDAC therapeutic research. The Warburg effect, glutamine addiction, and autophagy stand as the most important adaptive metabolic mechanisms of cancer cells themselves, however metabolic reprogramming is also an important feature of the tumor microenvironment, having a major impact on epigenetic reprogramming and tumor cell interactions with its complex stroma. We present a comprehensive overview of the main metabolic adaptations contributing to PDAC development and progression. A review of current and future therapies targeting this range of metabolic pathways is provided.

Diabetes, pancreatic cancer, and metformin therapy

Pancreatic cancer carries a poor prognosis as most patients present with advanced disease and preferred chemotherapy regimens offer only modest effects on survival. Risk factors include smoking, obesity, heavy alcohol, and chronic pancreatitis. Pancreatic cancer has a complex relationship with diabetes, as diabetes can be both a risk factor for pancreatic cancer and a result of pancreatic cancer. Insulin, insulin-like growth factor-1 (IGF-1), and certain hormones play an important role in promoting neoplasia in diabetics. Metformin appears to reduce risk for pancreatic cancer and improve survival in diabetics with pancreatic cancer primarily by decreasing insulin/IGF signaling, disrupting mitochondrial respiration, and inhibiting the mammalian target of rapamycin (mTOR) pathway. Other potential anti-tumorigenic effects of metformin include the ability to downregulate specificity protein transcription factors and associated genes, alter microRNAs, decrease cancer stem cell proliferation, and reduce DNA damage and inflammation. Here, we review the most recent knowledge on risk factors and treatment of pancreatic cancer and the relationship between diabetes, pancreatic cancer, and metformin as a potential therapy.

Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks

The rapid emergence of metabolomics has enabled system-wide measurements of metabolites in various organisms. However, advances in the mechanistic understanding of metabolic networks remain limited, as most metabolomics studies cannot routinely provide accurate metabolite identification, absolute quantification and flux measurement. Stable isotope labeling offers opportunities to overcome these limitations. Here we describe some current approaches to stable isotope-labeled metabolomics and provide examples of the significant impact that these studies have had on our understanding of cellular metabolism. Furthermore, we discuss recently developed software solutions for the analysis of stable isotope-labeled metabolomics data and propose the bioinformatics solutions that will pave the way for the broader application and optimal interpretation of system-scale labeling studies in metabolomics.

N-methylnicotinamide and nicotinamide N-methyltransferase are associated with microRNA-1291-altered pancreatic carcinoma cell metabolome and suppressed tumorigenesis

The cell metabolome comprises abundant information that may be predictive of cell functions in response to epigenetic or genetic changes at different stages of cell proliferation and metastasis. An unbiased ultra-performance liquid chromatography-mass spectrometry-based metabolomics study revealed a significantly altered metabolome for human pancreatic carcinoma PANC-1 cells with gain-of-function non-coding microRNA-1291 (miR-1291), which led to a lower migration and invasion capacity as well as suppressed tumorigenesis in a xenograft tumor mouse model. A number of metabolites, including N-methylnicotinamide, involved in nicotinamide metabolism, and l-carnitine, isobutyryl-carnitine and isovaleryl-carnitine, involved in fatty acid metabolism, were elevated in miR-1291-expressing PANC-1. Notably, N-methylnicotinamide was elevated to the greatest extent, and this was associated with a sharp increase in nicotinamide N-methyltransferase (NNMT) mRNA level in miR-1291-expressing PANC-1 cells. In addition, expression of NNMT mRNA was inversely correlated with pancreatic tumor size in the xenograft mouse model. These results indicate that miR-1291-altered PANC-1 cell function is associated with the increase in N-methylnicotinamide level and NNMT expression, and in turn NNMT may be indicative of the extent of pancreatic carcinogenesis.

microRNAs and cancer metabolism reprogramming: the paradigm of metformin

Increasing evidence witnesses that cancer metabolism alterations represent a critical hallmark for many types of human tumors. There is a strong need to understand and dissect the molecular mechanisms underlying cancer metabolism to envisage specific biomarkers and underpin critical molecular components that might represent novel therapeutic targets. One challenge, that is the focus of this review, is the reprogramming of the altered metabolism of a cancer cell toward that of un-transformed cell. The anti-hyperglicemic agent, metformin has proven to be effective in reprogramming the metabolism of cancer cells even from those subpopulations endowed with cancer stem like features and very high chemoresistenace to conventional anticancer treatments. A functional interplay involving selective modulation of microRNAs (miRNAs) takes place along the anticancer metabolic effects exerted by metformin. The implications of this interplay will be also discussed in this review.

Contribution of serine, folate and glycine metabolism to the ATP, NADPH and purine requirements of cancer cells

Recent observations on cancer cell metabolism indicate increased serine synthesis from glucose as a marker of poor prognosis. We have predicted that a fraction of the synthesized serine is routed to a pathway for ATP production. The pathway is composed by reactions from serine synthesis, one-carbon (folate) metabolism and the glycine cleavage system (SOG pathway). Here we show that the SOG pathway is upregulated at the level of gene expression in a subset of human tumors and that its level of expression correlates with gene signatures of cell proliferation and Myc target activation. We have also estimated the SOG pathway metabolic flux in the NCI60 tumor-derived cell lines, using previously reported exchange fluxes and a personalized model of cell metabolism. We find that the estimated rates of reactions in the SOG pathway are highly correlated with the proliferation rates of these cell lines. We also observe that the SOG pathway contributes significantly to the energy requirements of biosynthesis, to the NADPH requirement for fatty acid synthesis and to the synthesis of purines. Finally, when the PC-3 prostate cancer cell line is treated with the antifolate methotrexate, we observe a decrease in the ATP levels, AMP kinase activation and a decrease in ribonucleotides and fatty acids synthesized from [1,2-¹³C₂]-D-glucose as the single tracer. Taken together our results indicate that the SOG pathway activity increases with the rate of cell proliferation and it contributes to the biosynthetic requirements of purines, ATP and NADPH of cancer cells.