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Ribose sugar and cell growth

Ribose sugar and cell growth

Anf Ribose sugar and cell growth PubMed PubMed Central Google Scholar Zhang, Y. Download citation. Grodth data for sugad, mouse studies grkwth qPCR. where n adn and n g race day nutrition for swimmers counts from the Fat burn motivation and glucose supplemented conditions, respectively, n 0 and n f are counts from the initial and final timepoints, respectively, and t is the assay length in days. Bochner for providing the OmniLog instrument, helping with the data analysis, countless insightful discussions, and support; S. Each dataset was split into two — UPP1 high and UPP1 low — based on the ranked UPP1 expression value.

Ribose sugar and cell growth -

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Department of Nephrology, Rakuwakai Otowa Hospital, 2 Otowa-Chinji-cho, Yamashina-ku, Kyoto, Japan. Division of Renal Diseases and Hypertension, University of Colorado Denver, Aurora, CO, USA.

Miguel A. Department of Medicine, Division of Endocrinology, Metabolism and Diabetes, University of Colorado School of Medicine, Aurora, USA. University of Colorado Cancer Center, Aurora, CO, USA. Department of Medical Oncology, University of Colorado Denver, Aurora, CO, USA.

Department of Cardio-Renal Physiopathology, Instituto Nacional de Cardiología Ignacio Chavez, , Mexico City, CP, Mexico. Department of Biology, Boston University, Boston, MA, USA. You can also search for this author in PubMed Google Scholar. TN designed the story of manuscript and wrote entire manuscript.

RJJ and DRT significantly edited the manuscript. MAL, ISM, MF, CJR, LGS, and AAH edited the part of their own research area. All authors read and approved the final manuscript. Correspondence to Takahiko Nakagawa. MAL, DRT, LGL, CJR, and RJJ have equity in a start-up company developing fructokinase inhibitors Colorado Research Partners LLC , and TN and RJJ also have equity with XORTX therapeutics which is developing novel xanthine oxidase inhibitors.

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Reprints and permissions. Nakagawa, T. et al. Fructose contributes to the Warburg effect for cancer growth. Cancer Metab 8 , 16 Download citation. Received : 10 March Accepted : 01 July Published : 10 July Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Review Open access Published: 10 July Fructose contributes to the Warburg effect for cancer growth Takahiko Nakagawa ORCID: orcid.

Lanaspa 3 , Inigo San Millan 4 , Mehdi Fini 5 , Christopher J. Rivard 6 , Laura G. Sanchez-Lozada 7 , Ana Andres-Hernando 3 , Dean R.

Abstract Obesity and metabolic syndrome are strongly associated with cancer, and these disorders may share a common mechanism. Introduction Obesity and metabolic syndrome are strongly associated with some types of cancer, but it remains unknown if there is a common mechanism.

Role of fructose under physiological and pathological condition Fructose is a simple sugar present in fruit fruit sugar , which has an identical chemical composition with glucose C 6 H 12 O 6.

Full size image. Table 1 Endogenous fructose contributes to several types of disease progression Full size table. Consequence of fructose metabolism Fructose is firstly metabolized by fructokinase known as ketohexokinase , which phosphorylates fructose to produce Fructose 1-phosphate Fru1P.

Clinical associations of fructose intake with cancer The idea that cancer cells might utilize fructose as a fuel is supported by the observation that GLUT5, the primary fructose transporter, is expressed on the cell surface of several types of tumors.

Table 2 Fructose effects in various types of cancer cells Full size table. Fructose plays a distinct role from glucose in cancer growth If fructose is utilized as a fuel for several types of cancer, there may be a distinct advantage of fructose over glucose.

Physiological dose of fructose could be enough to promote cancer growth The increase in high fructose corn syrup HFCS consumption since s was found to be associated with the epidemic of cardiovascular and metabolic diseases, indicating that fructose might play a causal role.

Fructose facilitates glucose utilization An additional point to be aware of is the fact that we rarely consume fructose in isolation, but together with glucose in foods and beverages using sugars, sucrose, and HFCS. Uric acid is a potential mechanism for fructose-induction of the Warburg effect In many physiological and pathological conditions, fructose is efficiently metabolized under anaerobic and aerobic conditions.

Lactate could contribute to cancer growth Lactate, an end-product of cytosolic fructose metabolism, may contribute to carcinogenesis. Fructose is preferentially utilized for cell survival under hypoxic condition In , Thomlinson and Gray performed histological examination with human lung cancer and found the presence of tissue necrosis relative to blood vessels, postulating that the degree of anoxia may play an important role in tumor viability, although they did not accurately measure oxygen tension of tumors [ 87 ].

Aldose reductase activation suggests endogenous production of fructose in cancers While we are proposing that some cancer cells may become fructose-dependent, a key question is how cancer cells survive if fructose provided by the diet is not sufficient. Perspective Fructose has emerged as a key nutrient for cancer cells expressing GLUT5 and behaves differently from glucose.

Conclusions In addition to glucose, recent studies suggest that fructose could be alternative energy source for cancer growth. Availability of data and materials Not applicable.

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Some people currently use the sugar to treat urinary tract infections , but this is only over a short period of time. While there will be a long wait to see whether mannose will become a standard treatment, the possibility of a safe, cost-effective intervention is exciting.

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This leads to an increase in interstitial fluid xugar and the collapse of arterioles ceell capillaries gowth47. These phenomena collectively contribute to low oxygen saturation, anf resistance, RRibose alterations, and ane within the tumour at the rgowth level 58 Ribosw, 9.

PDA cells surviving adn such nutrient and oxygen cdll TME exhibit metabolic adaptations that increase their scavenging and catabolic capabilities 10 Riboss, 1112 sugat, In addition, MRI for pediatric patients studies have defined Citrus fruit supplement for overall wellness nutrient sources for PDA, including extracellular matrix, immune, and stromal-derived metabolites 1415 While these studies race day nutrition for swimmers discrete nutrient Citrus fruit supplement for overall wellness, comprehensive screens with sugr power to identify many Riboss nutrient drivers and mechanisms have not been performed suugar.

To screen for metabolites that fuel metabolism in nutrient-deprived PDA cells, we Thermogenic supplements for effective weight reduction the Biolog phenotypic iRbose platform Ribosf 19 human PDA sugae lines and 2 immortalized, non-malignant pancreas cell lines human pancreatic stellate cells Ribpse human pancreatic nestin-expressing cells Fig.

The nutrient gtowth included Rjbose energy and nitrogen substrates Supplementary Table 1. Analyses of nutrient consumption sugarr revealed several Ribose sugar and cell growth that, in the absence of glucose, were utilized at similar levels groowth the glucose positive control Extended Suyar Fig.

For example, adenosine, uridine and several sugars were vell by most sugr the cell lines. aRace day nutrition for swimmers Riblse the nutrient metabolism screening assay and the correlation with gene expression in PDA cell Ribosr and tumours.

bSpearman correlation r between the normalized relative metabolic activity RMA for uridine catabolism in the screening data growrh UPP1 mRNA yrowth data from an independent dataset 17 16 PDA amd lines.

UPP1 -high cell lines are shown in bold. dQuantitative PCR qPCR validation of Grwth mRNA expression growtb a subset of PDA Ribpse lines. eImmunoblot annd basal UPP1 expression in PDA cell lines. Xnd are Riboxe of three technical Riboxe with similar results.

fAge-reversal technology correlation r between protein densitometry analysis of the blot in Ribkse and UPP1 mRNA expression in the eight PDA cell lines highlighted in e.

Data source: Cancer Cell Line Encyclopedia CCLE. To select lead metabolites for investigation, we correlated metabolite utilization patterns to the expression of metabolism-associated genes using a public dataset 17 From the top metabolite and gene correlation pairs Extended Data Fig.

First, UPP1 expression correlated positively with the metabolic activity from its known substrate, uridine. Second, our in vitro validation showed that all tested PDA cells utilized uridine, although to varying degrees Fig.

Third, contrary to our expectation that nutrients used in the absence of glucose would be carbohydrates, uridine was unusual in that it is a nucleoside.

Finally, to our knowledge, UPP1-mediated uridine metabolism is unexplored in the context of PDA. We further confirmed the correlation of uridine catabolism and UPP1 expression by mRNA and protein analyses Fig.

To determine the specificity of this association, we assessed the correlation of UPP1 expression to other nucleosides in the Biolog screen. Although both inosine and adenosine were readily catabolized, their utilization was not correlated with UPP1 expression.

Thymidine was neither actively metabolized nor correlated, when compared with negative controls Rbiose Data Fig. These results indicate that the association between UPP1 expression and uridine catabolism is robust and specific.

Consistent with our previous correlation analysis in a different dataset Extended Data Fig. We also observed that UPP1 -high tumours exhibit higher expression of glycolysis genes Extended Data Fig.

By contrast, UPP1 -high cell lines and UPP1 -high PDA tumours from patients displayed a profound downregulation of other metabolic pathways Extended Data Fig. Our screen Fig. Thus, we next directly assessed the metabolic activity of equimolar glucose and uridine.

Across four PDA cell lines, uridine and glucose fuelled metabolism to a similar degree Fig. Previous reports have also documented that uridine can substitute for glucose by supporting nucleotide metabolism 202122232425 However, our screening data illustrate that uridine supplementation increases the cellular reducing potential.

Together with the observed connection with UPP1, which catalyses the cleavage of uridine to ribosephosphate and uracil, we hypothesized that the UPP1-liberated ribose is recycled into central carbon metabolism to support cellular reducing potential.

To test this hypothesis, we supplemented glucose-deprived cells with ribose, a cell-permeable substitute for ribose 1-phosphate. Indeed, similar to exogenous uridine, ribose supplementation fuelled the reducing potential Fig.

F6P, fructosephosphate; R5P, ribosephosphate; UDP-GlcNAc, uridine diphosphate N -acetylglucosamine; hAbsolute quantification via metabolomics of uridine and uracil concentration in the TIF of orthotopic PDA tumours from syngeneic mouse KPC cells. iAbsolute quantification via metabolomics of glucose concentration in the pancreatic TIF and plasma of mice orthotopically implanted with KPC b syngeneic tumours.

jUridine. PRPP, phosphoribosyl pyrophosphate. Schematic growthh the fate of uridine-derived ribose carbon in PDA cells actively catabolizing uridine. GlyceraldehydeP, glyceraldehydephosphate; HBP, hexosamine biosynthetic pathway; PPP, pentose phosphate pathway; riboseP, ribosephosphate; SBP, serine biosynthesis pathway.

In our initial screen, glutamine concentration was also intentionally low 0. Uridine potentiated reducing potential with or without glutamine and had a greater effect when glutamine was present Extended Data Fig.

Together, these data suggest that uridine and glucose similarly fuel central carbon metabolism distinctly from glutamine. Eugar, we provided uridine to the UPP1-low PATUS and the UPP1-high DANG cell lines under glucose deprivation and applied liquid chromatography—mass spectrometry LC—MS -based metabolomics In both cell lines, uridine supplementation led to increased levels of glycolytic intermediates and lactate secretion suggesting glycolytic fluxuridine derivatives suggesting overflow metabolismamino acids indicative of increased anabolism and TCA cycle intermediates suggesting more mitochondrial activity Extended Data Fig.

Moreover, supplementation with uridine led to a marked accumulation of intracellular uridine and over fold increase in uracil content in the medium Fig. Notably, the intracellular uracil concentration increased by a similar amount of uridine, reflective of direct conversion of substrate to product Fig.

Collectively, these profiling efforts support a model in which uridine is catabolized to broadly fuel PDA cell metabolism.

To precisely delineate how uridine is metabolized, we used LC—MS to trace the metabolic fate of isotopically labelled uridine [ 13 C 5 ]uridine with uniformly labelled ribose carbon 29 in PATUS UPP1-low and ASPC1 UPP1-high cell lines.

Also labelled were glycolytic PEP, pyruvate and lactatePPP X5P and ribosephosphatehexosamine biosynthetic pathway UDP-GlcNAc and TCA cycle intermediates malate and citrateas Riboze as non-essential amino acids Rihose, glutamate and serine and oxidized glutathione Fig.

To determine the relevance of uridine metabolism for pancreatic tumours in vivo, we implanted mouse syngeneic pancreatic cancer cells into the pancreas of immunocompetent hosts to establish tumours.

Nearly identical results to those from orthotopic studies were observed in anx tumours from immune-competent mice. These results confirm that PDA catabolizes uridine trowth vivo. In parallel, we collected tumour interstitial fluid TIF from independent orthotopic allograft tumours and quantified bulk uridine and glucose concentrations by LC—MS.

Uridine and glucose were present in the low and high micromolar concentration range, respectively Fig. At the low equimolar concentration 0. When glucose was fold higher 5 mMuridine carbon contributed to a much lower level to metabolite labelling, whereas at lower glucose concentrations, uridine carbon dominated, consistent with competition for these two carbon sources into the same pathways.

Further isotope tracing using the exact TIF concentrations of uridine and glucose showed that both human ASPC1 and mouse MTD cells incorporate uridine into central carbon metabolism Extended Data Fig. We confirmed these results in four human PDA lines with the tetrazolium assay: uridine supported bioenergetics at physiological Extended Data Fig.

Our data suggest that uridine yields ribosephosphate via UPP1 to fuel both catabolic and biosynthetic metabolism. Ribosephosphate can be converted to the PPP product ribosephosphate by phosphoglucomutase 2 PGM2 to enter nucleotide biosynthesis. We found that PGM2 and UCK2 are high in PDA and UCK1 is low, but these genes were largely uncorrelated with UPP1 Extended Data Fig.

Being the most upregulated, we tested PGM2 by western blot and found it to be expressed in most PDA cells but uncorrelated with UPP1 Extended Data Fig.

Inhibition of the three genes using short interfering RNA siRNA showed that only PGM2 knockdown suppressed the uridine-mediated rescue of metabolic activity following glucose deprivation Extended Data Fig.

Together, these data support our model in which uridine catabolism converges with central carbon metabolism, and they also reveal that exogenous uridine fuels PDA metabolism in a similar way to glucose, supplying carbon for redox, nucleotide, amino acid and glycosylation metabolite biosynthesis Fig.

To confirm the role of Growht in uridine catabolism, we knocked out UPP1 UPP1-KO using CRISPR—Cas9 in the PATUS UPP1-low and ASPC1 UPP1-high human PDA cell lines and validated two independent clones per cell line Fig.

In these knockout lines, the ability of uridine to rescue NADH production in the absence of glucose Fig. Consistent with the blockade of uridine catabolism, metabolomics showed that UPP1-KO cell lines displayed an increase in intracellular and extracellular uridine Extended Data Fig.

Furthermore, UPP1-KO broadly altered the intracellular metabolome of both cell lines Extended Data Fig. aWestern blot validation of UPP1-KO in human PDA cell lines. WT, wild type. α-KG, α-ketoglutarate; 1,3-BPG, 1,3-bisphosphoglycerate; DHAP, dihydroxyacetone phosphate; fructose-1,6-BP, fructose-1,6-bisphosphate.

fUPP1 mRNA expression in PDA tumours and non-tumoural pancreas tissues in microarray datasets. Liver met, liver metastasis; NT, non-tumour tissue. ghRNAscope showing representative UPP1 mRNA expression in tumour and adjacent normal tissue adj sections g and quantification from three patients Pt 1—3 with PDA h.

iKaplan—Meier overall survival analysis log-rank test based on ranked UPP1 expression in the PDA dataset published previously jComparison of UPP1 mRNA expression in human PDA tumours annotated as KRAS G12D or with no alteration No Alt in KRAS from the TCGA dataset.

oMTT assay showing relative proliferation of PDA cell lines with 1.

: Ribose sugar and cell growth

Latest news

A new study has revealed some important information about the behavior of one of the most notorious forms of cancer. Pancreatic cancer, the study found, can readily turn to an alternate source of energy to survive when its primary source, the sugar molecule glucose , is in short supply.

Tumors in the pancreas typically develop a dense, nest-like structure around them—an area often referred to as the tumor microenvironment —and they also often lack intact blood vessels. This unruly architecture surrounding these tumors creates conditions that decrease the supply of glucose, an essential fuel source for normal and cancer cells.

In the study, funded in part by NCI, an international research team showed that pancreatic cancer cells appear to have a potent strategy for overcoming this glucose deprivation: They use an alternative source of fuel, a molecule called uridine.

In experiments involving human pancreatic cancer cells grown in laboratory dishes, they showed that when glucose was lacking, uridine became the main energy source for the cells.

And when pancreatic cancer cells that could not use uridine were implanted in mice, only small tumors could form, according to findings published May 17 in Nature. A related study, published the same day in Nature Metabolism , provided strong confirmation of the finding. In that study, researchers reported that other types of cancer cells could also turn to uridine for energy when they lacked access to glucose.

Blocking how cancer cells acquire and use energy, or their metabolism, as a treatment has been challenging, Dr. Lyssiotis explained. But a better understanding of how cancer cells adapt their metabolism in the often oxygen- and nutrient-deprived environments in which they exist, he said, may open other avenues for attacking them.

Pancreatic cancer is one of the leading causes of death from cancer. Not only does its stark microenvironment thwart the entry of drugs designed to kill tumors, but numerous studies have shown that other residents in and around the tumors create an ecosystem that help the tumors thrive.

But this microenvironment also has a downside for tumors: it reduces the amount of oxygen that can flow to them. Lyssiotis said. And not only do they often lack blood vessels, but those that do form are often leaky and mangled.

According to Konstantin Salnikow, Ph. Other studies have shown that pancreatic tumors can get energy from sources other than glucose. But Dr. The research team began by using an advanced testing platform specifically designed to analyze the nutrients in blood and other tissues.

But uridine stood out. It was also readily used by all the pancreatic cancer cell lines they tested. The latter finding is an important piece of the puzzle, Dr. A pancreatic cancer cell taking in uridine from sources outside the cell, including RNA wavy strand and macrophages blue squiggly circle.

UPP1 in the cell removes ribose from uridine, which the cell uses to fuel its growth. Like a sidecar on a motorcycle, a sugar molecule called ribose is attached to uridine. Ribose is also a component of ATP , the primary energy carrier in cells.

UPP1, the protein created when UPP1 is active, interacts with uridine in cells to release ribose, which cells can then use to meet their energy needs. Analyses of tumor samples from people with pancreatic cancer revealed a link between high levels of UPP1 and shorter survival.

And other experiments involving cancer cell lines strongly suggested that UPP1 was stripping uridine of ribose, which the cells then used for energy.

Analyses in mice with pancreatic tumors confirmed what the researchers saw in the cell line experiments. And when they injected mice with pancreatic cancer cells that lacked a functional UPP1 gene—meaning the cells could not produce the UPP1 protein—the resulting tumors were much smaller and more sluggish than those that formed from cells that had an intact form of the gene.

Findings from the Nature Metabolism study—funded in party by NCI and conducted by researchers from Harvard, MIT, and the University of Lausanne in Switzerland—largely aligned with those from the Nature study.

After 1 week of acclimatization to the cages, mice were randomly divided into five groups and received intraperitoneal injections each day for 30 days with Rib at doses of 0.

All mice were maintained in animal facilities under pathogen-free conditions. After days of injections, the Morris water maze MWM test was performed as described previously [41]. The experimental apparatus consisted of a circular water tank 90 cm in diameter, 35 cm in height , containing water 23±1°C to a depth of A platform 4.

The water tank was located in a test room, which contained various prominent visual cues. Each mouse received three periods of training per day for seven consecutive days.

Latency to escape from the water maze finding the submerged escape platform was calculated for each trial. On day 8, the probe test was carried out by removing the platform and allowing each mouse to swim freely for 60 seconds. The time that mice spent swimming in the target quadrant where the platform had been located during hidden platform training was measured.

All data were recorded with a computerized video system. After behavioral testing, mice were sacrificed and their blood about 0. Glycated serum protein GSP [43] and blood glucose [44] were measured using kits obtained from the Nanjing Jiancheng Bioengineering Institute China according to the manufacturer' guidelines.

The activity of the serum enzymes alanine aminotransferase ALT [45] , aspartate aminotransferase AST [46] and serum creatinine [47] was determined using a spectrophotometric diagnostic kit from Biosino Biotechnology Company Ltd.

The level of AGEs or pentosidine was determined in cultured cells, brain tissues, and mice sera as described previously [12]. Membranes were then incubated respectively with anti-AGE 6D12 monoclonal antibody TransGenic, Japan , anti-pentosidine PEN12 monoclonal antibody TransGenic, Japan or anti-β actin monoclonal antibody Sigma, USA overnight at 4°C.

Each membrane was washed three times with PBS with 0. The membranes were again washed three times with PBST, and then immunoreactive bands were visualized using enhanced chemiluminescence detection reagents Applygen, China. The protein bands were visualized after exposure of the membranes to Kodak X-ray film and quantified by Quantity One 1D analysis software 4.

After fixation, brains were embedded in paraffin blocks. Five to eight micrometer thick sections were processed for immunohistochemical analyses. Deparaffinized and hydrated sections were incubated in Target Retrieval Solution at 95°C for 30 minutes for enhancement of immunoreactivity, then permeabilized with 0.

The specimens were incubated overnight at 4°C in anti-AGEs 6D12 monoclonal antibody solution diluted in PBS. After washing with PBS, sections were subsequently incubated with biotin-labeled secondary antibodies 37°C, 1 hour.

The immunoreaction was detected using horseradish peroxidase-labeled antibodies 37°C, 1 hour and red staining was visualized with an AEC system Nikon Optical, Japan.

Immunofluorescent staining was performed as described [48]. Bound antibodies were visualized with Alexa conjugated anti-mouse IgG Invitrogen, USA and cell nuclei were stained with the DNA-specific fluorescent reagent Hoechst Immunolabeled tissues were observed under an Olympus FV laser scanning confocal microscope Olympus, Japan.

All values reported are means ± standard errors SE unless otherwise indicated. Data analysis was performed by one way analysis of variance ANOVA using Origin 7. Conceived and designed the experiments: CH Y. Lu YW Y. Liu RH. Performed the experiments: CH Y.

Analyzed the data: CH YW. Wrote the paper: CH Y. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field.

Article Authors Metrics Comments Media Coverage Reader Comments Figures. Abstract Background D-Ribose, an important reducing monosaccharide, is highly active in the glycation of proteins, and results in the rapid production of advanced glycation end products AGEs in vitro. Introduction Non-enzymatic glycation of proteins by reducing saccharides such as D-glucose Glc and D-ribose Rib is a post-translational modification process [1] , leading to the formation of fructosamine [2] and advanced glycation end products AGEs [3].

Results D-ribose decreases cell viability and leads to high yields of AGEs To investigate whether Rib leads to decreases in cell viability, SH-SY5Y human neuroblastoma SH-SY5Y cells and Human embryonic kidney T HEKT cells were incubated with D-ribose or D-glucose at different concentrations.

Download: PPT. Figure 1. Changes in cell viability in the presence of D-ribose. Figure 2. Elevation of AGEs in cells in the presence of D-ribose. Serum glycated proteins and AGEs significantly increase in D-ribose-treated mice Having determined that Rib but not Glc is able to glycate proteins rapidly and produce high levels of AGEs in cultured cells in vitro , we investigated whether Rib is able to induce AGE formation in vivo.

D-ribose treatment does not cause significant dysfunction of the liver or kidneys. None of the sugar treatment groups showed any significant visual abnormalities and they gained weight normally within the period of treatment Table 1. There were no significant changes in serum ALT or AST in both Rib- and Glc-treated subjects Table 2.

Furthermore, serum creatinine concentrations did not markedly vary with the injections. These results indicate that treated mice did not suffer from liver and kidney damage under the experimental conditions used. Glycated serum proteins and AGEs increase after injection with D-ribose. However, the amount of glycated serum protein was significantly increased in the blood of mice intraperitoneally injected with Rib at 0.

These results also suggest that Rib has a faster glycation rate than Glc in vivo. Figure 3. Intraperitoneal injection of D-ribose results in an increase in the concentration of glycated serum protein.

Table 2. Serum ALT and AST activity and serum creatinine concentration. Figure 4. Changes in serum AGEs with intraperitoneal injection of D-ribose. D-ribose-treated mice have a marked increase in brain AGEs Rib can pass through the blood-brain barrier and enter the brain by simple diffusion [19].

Figure 6. Immunohistochemical staining of AGEs in the hippocampus and cortex. Figure 7. Immunofluorescent staining of AGEs in the hippocampus and cortex. Impairment of spatial learning and memory in the Morris water maze AGEs, which have been found in the brains of senile dementia patients [20] , are cytotoxic [12] , [17].

Figure 8. Decline in the performance of mice injected with D-ribose in the Morris water maze test. Discussion As a reducing saccharide, Rib reacts with protein amino groups to initiate a post-translational modification process widely known as non-enzymatic glycation [1].

Materials and Methods Ethics Statement The handling of mice and experimental procedures were approved by the Animal Welfare and Research Ethics Committee of the Institute of Biophysics, Chinese Academy of Sciences Permit Number: SYXK Cell viability test To determine cell viability, we used the standard 3- 4, 5-dimethylthiazolyl -2, 5-diphenyl tetrazolium bromide MTT; Sigma, USA test, with the slight modifications suggested by Mayo and Stein [40].

Morris water maze test After days of injections, the Morris water maze MWM test was performed as described previously [41]. Sample collection After behavioral testing, mice were sacrificed and their blood about 0.

Serum physiochemical assays Glycated serum protein GSP [43] and blood glucose [44] were measured using kits obtained from the Nanjing Jiancheng Bioengineering Institute China according to the manufacturer' guidelines.

Gel electrophoresis and Western blotting The level of AGEs or pentosidine was determined in cultured cells, brain tissues, and mice sera as described previously [12]. Data analysis All values reported are means ± standard errors SE unless otherwise indicated.

Acknowledgments We thank Dr. Joy Fleming for comments on the manuscript. Author Contributions Conceived and designed the experiments: CH Y.

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Part 3.

Pancreatic Cancer Finds Alternate Fuel for Survival, Growth - NCI

The mechanism may be due to the fact that glycolysis is regulated during glucose metabolism as phosphofructokinase activity decreases if intracellular ATP falls or citrate accumulates, whereas in fructose metabolism there is no negative regulation of fructokinase [ 86 ].

In , Thomlinson and Gray performed histological examination with human lung cancer and found the presence of tissue necrosis relative to blood vessels, postulating that the degree of anoxia may play an important role in tumor viability, although they did not accurately measure oxygen tension of tumors [ 87 ].

In the s, the situation changed with the invention of the oxygen electrode, which was a novel device allowing investigators to directly measure tissue oxygen levels in human tumors [ 88 ]. We now know that oxygen concentration in human tumors is heterogeneous with many regions at very low levels.

Median oxygen pressure pO 2 in pancreatic cancer is 2. Likewise, median pO 2 in lung cancer, breast cancer, and prostate cancer is 7.

This suggests cancers have to be able to tolerate hypoxic condition to maintain viability and growth. The authors discovered that there was substantial endogenous production of fructose in several organs, including the kidney and liver, under hypoxic or anoxic conditions [ 90 ].

One potential mechanism could be that fructose metabolism reduces oxygen demand by reducing mitochondrial respiration via the effects of uric acid describe above.

The increased glycolysis from Fru1P activation and the increased use of the PPP via transketolase activation provided the needed ATP, NADPH, and ribose for providing lipids, hexosaminoglycans, and nucleic acid for cell survival.

A major issue for hypoxic conditions would be the concern that ATP derived from fructose metabolism may not be sufficient for cell survival or growth. Likewise, Weng et al. showed that fructose accelerated ATP production compared to glucose even in a cancer cell line [ 60 ].

The potential mechanism for fructose-associated ATP production under hypoxia remains to be determined, and accelerated glycolysis would be responsible for the energy production.

Alternatively, lactate can be a fuel as lactate can enter the mitochondria through MCT1 and then be oxidized to pyruvate via mitochondrial LDH and then to Acetyl CoA for the Krebs cycle [ 92 ]. Thereby, fructose-derived lactate as opposed to or with glucose-derived lactate may be also a key element for mitochondrial oxidative phosphorylation.

It is of interest that both fructose metabolism and hypoxic conditions are theoretically associated with a reduction in intracellular ATP levels, but the combination would often result in a rise in ATP production.

Since fructose-induced ATP depletion is transient, the slower aldolase reaction with Fru1P and IMP would subsequently increase intracellular phosphate and increase ATP levels.

In addition, during fructose metabolism, one molecule of ATP is consumed by the activation of fructokinase while the downstream reaction from fructose-1,6-bisphosphate FBP through pyruvate, which is the energy payoff phase in the glycolytic pathway, yields four molecules of ATP, accounting for positive ATP balance in the fructose metabolism.

Alternatively, several studies with non-cancer cells indicated that FBP would be a key player to protect cells from ischemic injury. FBP has been suggested as being responsible for the reduced hypoxic injury in astrocytes in which ATP concentration was maintained [ 93 , 94 ].

Potential mechanisms include 1 stimulation of carbohydrate metabolism through phosphofructokinase activation [ 95 ], 2 direct glycolytic metabolism of FBP resulting in ATP production [ 96 ], 3 prevention of oxygen-derived free radical injury, and 4 stabilizing intracellular calcium [ 97 ].

Further studies are needed to confirm which mechanisms would be relevant to cancer development and progression. While we are proposing that some cancer cells may become fructose-dependent, a key question is how cancer cells survive if fructose provided by the diet is not sufficient.

Since serum fructose concentration is much lower compared to serum glucose levels [ 29 , 98 ], this would be a critical issue for such types of cancers. As mentioned above, humans and certain species of animals carry a unique system to endogenously produce fructose.

Therefore, there is a possibility that certain types of cancer cells could also possess such system. The key enzyme that stimulates endogenous fructose production is aldose reductase in the polyol pathway. Given the fact that glucose is constantly supplied from the systemic circulation, the activation of aldose reductase could result in local fructose production [ 16 ].

We recently found that aldose reductase is activated in several organs under several pathological conditions, including ischemia, heart failure, and inflammation [ 99 , , , ], leading to endogenous fructose production [ 11 , 33 ]. Importantly, several researchers showed that aldose reductase is activated in various types of human cancers, including liver, breast, ovarian, cervical, and rectal cancers [ ].

This evidence would suggest that fructose may be endogenously produced in those cancer cells where it could potentially stimulate cancer growth Fig.

Fructose has emerged as a key nutrient for cancer cells expressing GLUT5 and behaves differently from glucose. In case of the failure of FDG-PET imaging, PET fructose imaging may be a future alternative to detect certain types of cancers [ , ]. Fructose metabolism provides several necessities for cancer cell growth, including nucleotides, lipids, and energy.

An important issue is whether blocking fructose metabolism could be a therapeutic strategy. To treat such types of cancers, a low fructose diet would be one safe approach, but since fructose can also be generated endogenously, the most effect approach may involve blocking fructokinase.

In humans, the absence of the fructokinase gene results in the condition of essential fructosuria intolerance which is a relatively asymptomatic condition [ ], so selective pharmacological blockade of fructokinase may be an attractive approach. Currently, xanthine oxidase inhibitors are commercially available and are widely used in clinical medicine, and therefore, as the first step, simple experiments applying the drug to fructose-fed mice with cancer would easily address this issue.

In addition to glucose, recent studies suggest that fructose could be alternative energy source for cancer growth. Fructose can be preferentially metabolized under low oxygen condition to accelerate glucose utilization, and exhibit distinct effects, including production of uric acid and lactate as major byproducts.

In particular, uric acid promotes the Warburg effect by preferentially downregulating mitochondrial respiration and increasing aerobic glycolysis that may aid metastases that initially have low oxygen supply.

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Download references. Department of Nephrology, Rakuwakai Otowa Hospital, 2 Otowa-Chinji-cho, Yamashina-ku, Kyoto, Japan. Division of Renal Diseases and Hypertension, University of Colorado Denver, Aurora, CO, USA.

Miguel A. Department of Medicine, Division of Endocrinology, Metabolism and Diabetes, University of Colorado School of Medicine, Aurora, USA. University of Colorado Cancer Center, Aurora, CO, USA. Department of Medical Oncology, University of Colorado Denver, Aurora, CO, USA.

Department of Cardio-Renal Physiopathology, Instituto Nacional de Cardiología Ignacio Chavez, , Mexico City, CP, Mexico. Department of Biology, Boston University, Boston, MA, USA. You can also search for this author in PubMed Google Scholar. TN designed the story of manuscript and wrote entire manuscript.

RJJ and DRT significantly edited the manuscript. MAL, ISM, MF, CJR, LGS, and AAH edited the part of their own research area. Chromatograms for selected metabolites were extracted in Skyline Daily software version Natural isotope abundance correction was performed, and peak areas plotted.

For quantification of uridine and glucose in TIF, quantitative metabolite profiling of fluid samples was performed as previously described Using the external standard library dilutions, we created a standard curve based on the linear relationship of the normalized peak area and the concentration of the metabolite.

This standard curve was then used to interpolate the concentration of the metabolite in the TIF sample. Patients with pancreas resections for PDA from to at the University of Michigan Health System were included in the study. The collection of patient-derived tissues for histological analyses was approved by the Institutional Review Board at the University of Michigan IRB number: HUM All specimens are from patients with pancreas resections for pancreatitis, cystic neoplasms, or PDA from to at the University of Michigan Health System.

Corresponding areas were carefully selected and marked. The TMA was previously published In brief, paraffin wax was removed with xylene and slides were rehydrated. Samples were incubated with TSA-Cy3 fluorophore ,; Akoya Biosciences; NELAKT diluted in CoDetection Antibody Diluent.

Slides were rinsed with PBST and mounted in ProLong Gold Antifade Mountant Invitrogen, P Sections were visualized on a Leica SP5X upright confocal. Patients tissue slides were deparaffinized and rehydrated with graded Histo-Clear National Diagnostics , ethanol, and water.

Samples underwent antigen retrieval with sodium citrate buffer 2. Slides were mounted in Permount Mounting Medium Fisher. After drying, slides were imaged using an Olympus BX53F microscope, Olympus CP80 digital camera, and CellSens standard software.

Serial sections of 4 µm thickness were cut from FFPE blocks, deparaffinized in xylene, processed in graded alcohol, and rehydrated in water. The Dako Autostainer Link 48 automated immunostaining platform was used for all the below immunostainings.

For these antibodies, EnVision FLEX Target Retrieval Solution high pH; K, Agilent and Nichirei anti-rat Histofine polymer reagent F, Nichirei Biosciences primary antibody detection kits were used. Appropriate positive and negative controls were used in all runs. The Nanozoomer-XR C Hamamatsu was used to scan whole stained sections.

Antigen expression was scored using Definiens Test Studio Software Definiens. Immunohistochemistry of UPP1 expression in human normal and PDA tissues was also accessed from the Human Protein Atlas portal Differential gene expression between PDA and non-tumours were performed in R using the limma package version 3.

Kaplan—Meier overall survival log-rank test was performed after splitting the tumour samples per dataset into UPP1 -high and UPP1 -low subsets. The iKras mice data were obtained from NCBI GEO under the accession number GSE TCGA pan-cancer datasets including bladder, colon, oesophageal, lung, head and neck, prostate cancer and glioblastoma, were downloaded from Xena Platform from University of California Santa Cruz An additional colorectal dataset GSE was also used.

For the comparisons, the normal or adjacent matched and unmatched normal samples were used. In total, 2, cancer tissue samples and non-tumoural control tissue samples were analysed. These datasets were used to compare UPP1 expression between cancer and non-cancer tissues.

Gene expression data for uridine high and uridine low metabolizers were extracted from the CCLE GSE UPP1 protein expression analysis was performed in KRAS mutant and wild-type cell lines using data from DepMap Gene ontology analyses were performed with DAVID. CiiDER 54 was used for predicting UPP1 gene transcription factor sites.

As transcription factor binding sites are variable and binding sites rarely match the model perfectly, a default deficit score of 0. Top 10 transcription factors were obtained using the predicted UPP1-binding sites with respect to sequences from the human genome GRCh Statistics were performed either with GraphPad Prism 8 GraphPad Software Inc.

or using R version 3. Data from experimental groups were compared using the two-tailed t -test or analysis of variance ANOVA with post hoc corrections where applicable, and between biological or in vitro replicates.

For data analysis and visualization in R, packages with versions used include dplyr 0. Figure 1. The assay readout, RMA, was correlated with the expression level of metabolic genes in cell lines; human PDA data were used for subsequent analyses. Nutrient-deficient medium, no glucose, 0.

The experiments were performed twice with similar results. The experiment was performed once. Figure 2. Statistical significance was measured using two-tailed unpaired t -test. Bars shown for PATUS are same as the WT bars where applicable for that cell line in the Extended Data Fig.

Tracing experiments were performed twice in these cells with similar results. g, Number of samples: sub-Q, tumours from 3 mice injected on the left and right flanks; ortho, tumours from 4 mice.

Mode of uridine injection is intratumoural for sub-Q and intraperitoneal for ortho. These samples are from the control group of the study in Fig. j,k, j shows the mass isotopologue distribution in uridine and k shows in the indicated metabolites.

The metabolomics experiments b—k were performed once. Figure 3. a, The experiment was performed once. The experiments were performed three times with similar results. Data are part of the metabolomics experiments shown in Extended Data Fig.

The metabolomics experiment was performed once. g, Representative images from patient 1 of 3 tumour tissues.

PanCK, pan-cytokeratin, stain indicates tumour cells. i, Number of samples: UPP1 -low, ; UPP1 -high, j, Number of samples: no alteration, 43; G12D, l, Vinculin is used as a loading control. m, 3 biologically independent samples per group.

n, Vinculin is used as a loading control. Figure 4. Data represent the average of quantification from three histological slides obtained per tumour. d, The cells were cultured ±1 mM uridine in glucose-free medium supplemented with 2. KPC b, comparison of cell culture without and with 0.

i, Tumour weight data are shown in j. Experiment performed once. k, Number of samples: sgV, 8; sg1, 8; sg3, 8 tumours, corresponding to four mice per group.

l, Samples used for metabolomics per group: sgV, 5; sg1, 6; sg3, 6. Statistical significance was determined using the limma package version 3. The mouse schematic a,i was drawn with Adobe Illustrator version Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Cancer 1 , — Download references. We thank B. Bochner for providing the OmniLog instrument, helping with the data analysis, countless insightful discussions, and support; S.

Chan for support with Biolog data collection and analysis; D. DeNardo and the DeNardo laboratory for support designing the macrophage-depletion studies; N. Guppy for processing and immunohistochemistry staining of mouse tumour samples; L. Howell for helping with the automated image analysis of immunohistochemistry staining; and members of the Sadanandam and Lyssiotis laboratories and the entire Pancreatic Disease Initiative at the Rogel Cancer Center, University of Michigan, for their insightful comments and discussions.

was supported by the Department of Veteran Affairs Career Development Award IK2BX was supported by American Cancer Society IRG , the University of Chicago Cancer Center Support Grant P30 CA , the Pancreatic Cancer Action Network Career Development Award , the Brinson Foundation, the Cancer Research Foundation and the Ludwig Center for Metastasis Research.

and C. were supported by UMCCC Core Grant P30CA The funders had no role in study design, data collection and analysis, or the content and publication of this manuscript.

These authors contributed equally: Zeribe C. Nwosu, Matthew H. Ward, Peter Sajjakulnukit, Pawan Poudel. Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.

Zeribe C. Ward, Peter Sajjakulnukit, Steven Kasperek, Megan Radyk, Damien Sutton, Anthony Andren, Zachary Tolstyka, Ho-Joon Lee, Julia Ugras, Li Zhang, Christopher J. Department of Chemistry, Washington University in St Louis, St Louis, MO, USA. Matthew H. Ward, Leah P. Department of Medicine, Washington University in St Louis, St Louis, MO, USA.

Center for Metabolomics and Isotope Tracing, Washington University in St Louis, St Louis, MO, USA. Division of Molecular Pathology, The Institute of Cancer Research, London, UK. Cellular and Molecular Biology Program, University of Michigan, Ann Arbor, MI, USA.

Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA. Juan J. Apiz-Saab, Lindsey N. Department of Surgery, University of Michigan, Ann Arbor, MI, USA. Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA.

Department of Pathology and Clinical Labs, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA. Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA. Centre for Global Oncology, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

You can also search for this author in PubMed Google Scholar. designed the study. wrote the manuscript. designed experiments, and Z. and P. collected data for the bulk of the experimental studies. prepared manuscript figures. and Z. carried out the initial cell line screen, and P.

conducted the analysis of the screening data that revealed lead metabolite—enzyme interactions. carried out experiments. and E. contributed to the data analysis.

provided resources, funding and conceptual input for experiments and supervised the research. All authors reviewed and approved the final manuscript. Correspondence to Anguraj Sadanandam or Costas A.

Nature thanks the anonymous reviewers for their contribution to the peer review of this work. Peer review reports are available. Schematic overview of the parameters measured by the Biolog Phenotype Microarray. Heatmap showing the high confidence metabolites HCMs , namely, the metabolites that were utilized above or below the median of negative controls as determined by one-tailed Wilcoxon rank sum test.

Legend denotes fold change relative to median negative control signal, where red shows high utilization and blue shows low utilization. Spearman correlations, r, between UPP1 expression in cell lines ref.

On the right: GSEA plot indicating the enrichment of glycolysis hallmark in the UPP1 high relative to the low tumours. NES, normalized enrichment score. Analysis was based on the differential genes derived from CCLE data and part of the data shown in Fig.

GSEA plots of significantly enriched KEGG pathways in UPP1 -high PDA tumours relative to UPP1 low tumours. Plots are part of the data e from the analysis of GSE human PDA dataset. Statistics and reproducibility: a , The kinetic measurement evaluated several parameters, including the time taken for cells to adapt to and catabolize a nutrient lambda , the rate of uptake and catabolism mu or slope , the total metabolic activity area under the curve; AUC , and the maximum metabolic activity.

The values from the maximum catabolic efficiency maximum height, A of the respective metabolites were used to determine relative metabolic activity RMA. Relative RMA upon uridine supplementation with or without glucose and glutamine.

Plots in f-g are from the same experiment as d-e. Statistical significance was measured using two-tailed unpaired t-test.

Data a, f, g, h are shown as mean ± s. ADP, adenosine diphosphate; AMP, adenosine monophosphate; GSSG, oxidized glutathione; NADH, nicotinamide adenine dinucleotide; UDP-GlcNAc, uridine diphosphate N-acetylglucosamine; X5P, xylulose 5-phosphate.

Mode of uridine injection is intratumoural for Sub-Q and intraperitoneal for Ortho. Isotope tracing showing metabolite labelling upon supplementation with 13 C 5 -uridine at the TIF uridine and glucose concentrations shown in Fig. AXP — AMP, ADP, ATP, and related metabolites; UXP — UMP, UDP, UTP and related metabolites.

The experiments a-d were performed once. Data a-d are shown as mean ± s. d, where applicable. Schematic depicting metabolic pathways for uridine utilization. Expression of PGM2 , UCK1 , and UCK2 in non-tumour NT and PDA tissue samples from the GSE dataset. Expression of PGM2 , UCK1 and UCK2 in TCGA human PDA tumour and CCLE human cell line data separated into UPP1 low L and high H subsets.

Western blot for PGM2 in PDA cell lines. Presented in bold are cells that express high UPP1. These samples are the same batch as the data shown in Fig. kDa, unit for molecular weight. qPCR for PGM2 in ASPC1 cells transfected with siPGM2 compared to non-targeting siNT control.

qPCR for UCK1 in ASPC1 cells transfected with siUCK1 compared to non-targeting siNT control. qPCR for UCK2 in ASPC1 cells transfected with siUCK2 compared to non-targeting siNT control. All four group comparisons have significant P: 0.

Uridine can also be catabolized via UPP1 to produce uracil and ribose 1-phosphate. Ribose 1-phosphate is converted to ribosephosphate by PGM2 and fuel pentose phosphate pathway, nucleotide biosynthesis and glycolysis.

TCGA — The Cancer Genome Atlas, CCLE — Cancer Cell Line Encyclopaedia. Vinculin is used as a loading control. RMA — statistical significance was measured using multiple unpaired t tests with two-stage two-step method. Data a—c, f—h, j—l are shown as mean ± s.

The experiments were performed once a—c, k , and twice j,l with similar results. Mass isotopologue distribution of 1 mM 13 C 5 -uridine ribose-derived carbon into the indicated metabolic pathways in wildtype WT or UPP1-KO PATUS and ASPC1 cells. Data a—b, d—k are shown as mean ± s. Metabolomics experiments were done once.

TCGA RNA seq data showing the expression of UPP1 and its paralog UPP2. FPKM, fragments per kilobase of exon per million mapped fragments. RNA seq showing UPP1 expression in various normal human tissues Human Protein Atlas data , as obtained from the National Center for Biotechnology Information NCBI portal.

Histological data showing UPP1 protein expression in normal pancreatic tissue compared to PDA. UPP1 expression in human non-PDA cancers accessed in publicly accessible datasets. A lung cancer cell line, comparison between no uridine and 0.

RPKM, reads per kilobase of exon per million reads mapped. Data a-b, f shown as mean ± s. Statistical significance was tested using two-sided Wilcoxon or Kruskal-Wallis tests. RNAscope images showing UPP1 expression in tumour PDA compared to the adjacent non-tumour tissues.

Pan-cytokeratin PanCK indicates the tumour cells; DAPI, nuclear stain. The images are representative of three 20x acquisitions per tissue slide, and of two independent experiments.

Scale bar indicates µm. UMAP plot showing the expression of UPP1 at the transcript level, as determined by single cell RNA seq of PDA tissues from two patients and Violin plots showing UPP1 expression in various tumour microenvironment cell types, including myeloid and epithelial cells where UPP1 is highest.

Data used in plots b-c are from a previously published dataset Immunohistochemistry of UPP1 in patient biopsy sections from previously published tissue microarray Micrographs are representative from patient samples in the microarray and two independent experiments.

Kaplan-Meier plot showing survival probability log-rank test based on UPP1 expression in three separate datasets. Each dataset was split into two — UPP1 high and UPP1 low — based on the ranked UPP1 expression value.

TME — tumour microenvironment. Normalized UPP1 protein expression in Kras wildtype and mutant cell lines based on CCLE protein data accessed via the DepMap portal. Densitometric quantification of pERK and UPP1 in the ASPC1 blots shown in Fig.

MTT assay showing relative proliferation of PDA cell lines treated with 1. Statistics and reproducibility: a , Sample size — wild type 0 and mutation 1: and 69 pan-cancer , 15 and 15 colon cancer , 54 and 25 lung cancer.

Statistical significance was measured using two-tailed unpaired t test. ERK and Vinculin are used as loading controls. Blots are representative of two biological and technical replicates for ASPC1 and one biological replicate for PATUS and DANG with similar results. The experiments e, g, h were performed once with similar results on UPP1 displayed by the three cell lines.

This blot was run on the same gel as Fig. Blots c,i are representative of two independent experiments; blot e experiment was done once. Data b, e, g-h, l shown as mean ± s.

On the right: UPP1 mRNA expression determined by qPCR. CiiDER analysis of transcription factor binding sites in the promoters of mouse and human UPP1. Myc binding sites were not detected. qPCR showing UPP1 expression upon uridine supplementation with or without basal glucose concentration in culture medium.

RNA seq data showing the expression of Upp1 in sorted tumour cells and in KPC cells cultured in vitro in regular RPMI culture medium or tumour interstitial fluid medium TIFM.

Blots shown a-b are representative of two biological and technical replicate analyses with similar results. Data a,b,d,e shown as mean ± s. Data was extracted from a previously published metabolomics Relative uracil abundance in plasma, tumour interstitial fluid TIF , and bulk tumour from the experiment described in Fig.

Micrographs are representative of 10 fields per image obtained per experiment group. On the right is the respective quantification of each IHC stain. Color scale denotes fold change. Below: Venn diagram showing overlapping metabolites that accumulated in both human PATUS and ASPC1 and mouse MTD cell lines upon UPP1 knockout.

On the right: bulk tumour uridine and uracil as measured using metabolomics. Data a, b, d, e shown as mean ± s. d; horizontal bars in h represent mean value.

Source data for metabolomics, mouse studies and qPCR. Full source data for all the metabolomics and tumour studies are presented, labelled by sub-figure and separated by tabs.

Additionally, mRNA expression is provided for PGM2 , UCK1 and UCK2 following siRNA-mediated knockdown. Open Access This article is licensed under a Creative Commons Attribution 4. Reprints and permissions.

Nwosu, Z. Uridine-derived ribose fuels glucose-restricted pancreatic cancer. Download citation. Received : 21 June Accepted : 12 April Published : 17 May Issue Date : 01 June Anyone you share the following link with will be able to read this content:.

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Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly. Skip to main content Thank you for visiting nature. nature articles article. Download PDF. Subjects Cancer metabolism Metabolomics Pancreatic cancer. Abstract Pancreatic ductal adenocarcinoma PDA is a lethal disease notoriously resistant to therapy 1 , 2.

Main PDA remains one of the deadliest cancers 1 , 2. Nutrient-deprived PDA consumes uridine To screen for metabolites that fuel metabolism in nutrient-deprived PDA cells, we applied the Biolog phenotypic screening platform on 19 human PDA cell lines and 2 immortalized, non-malignant pancreas cell lines human pancreatic stellate cells and human pancreatic nestin-expressing cells Fig.

Full size image. Uridine consumption correlates with UPP1 To select lead metabolites for investigation, we correlated metabolite utilization patterns to the expression of metabolism-associated genes using a public dataset 17 , Uridine-derived ribose fuels metabolism Our screen Fig.

UPP1 provides uridine-derived ribose To confirm the role of UPP1 in uridine catabolism, we knocked out UPP1 UPP1-KO using CRISPR—Cas9 in the PATUS UPP1-low and ASPC1 UPP1-high human PDA cell lines and validated two independent clones per cell line Fig.

High UPP1 in PDA predicts poor survival To further assess the relevance of UPP1 in PDA tumours, we next analysed its expression in publicly available human PDA datasets.

KRAS—MAPK pathway regulates UPP1 KRAS mutations are the signature transforming event observed in the majority of PDAs Nutrient availability modulates UPP1 Given that glucose availability influences the use of uridine-derived ribose, we hypothesized that a glucose-depleted microenvironment triggers PDA to upregulate UPP1 as a compensatory response.

UPP1-KO blunts PDA tumour growth Uridine concentration is reported to be around twofold higher in TIF than in plasma Discussion The metabolic features of PDA drive disease aggression and therapeutic resistance and present new opportunities for therapy 2 , 6.

Methods Cell culture The PDA cell lines A, HT, HCT and U2OS and human pancreatic nestin-expressing cells were purchased from the American Type Culture Collection ATCC or the German Collection of Microorganisms DSMZ.

Ribose - Wikipedia Primer sequences are listed in Intense pre-workout fuel Table 5. It can help fell gain muscle, increase strength, and improve brain race day nutrition for swimmers, celo name race day nutrition for swimmers few. Some evidence shows benefits of D-ribose supplements for those with low blood flow to the heart muscle, as seen in conditions like coronary artery disease. After fixation, brains were embedded in paraffin blocks. Centre for Global Oncology, Division of Molecular Pathology, The Institute of Cancer Research, London, UK. Cytidine and uridine requirement of the brain.
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