Courtney Dennis

MTAP deletion confers enhanced dependency on the PRMT5 arginine methyltransferase in cancer cells

Tumors put in a vulnerable position Cancer cells often display alterations in metabolism that help fuel their growth. Such metabolic “rewiring” may also work against the cancer cells, however, by creating new vulnerabilities that can be exploited therapeutically. A variety of human tumors show changes in methionine metabolism caused by loss of the gene coding for 5-methylthioadenosine phosphorylase (MTAP). Mavrakis et al. and Kryukov et al. found that the loss of MTAP renders cancer cell lines sensitive to growth inhibition by compounds that suppress the activity of a specific arginine methyltransferase called PRMT5. Conceivably, drugs that inhibit PRMT5 activity could be developed into a tailored therapy for MTAP-deficient tumors. Science, this issue pp. 1208 and 1214 Tumors cope with a genomic change by rewiring their metabolism, but this makes them more susceptible to certain drugs. The discovery of cancer dependencies has the potential to inform therapeutic strategies and to identify putative drug targets. Integrating data from comprehensive genomic profiling of cancer cell lines and from functional characterization of cancer cell dependencies, we discovered that loss of the enzyme methylthioadenosine phosphorylase (MTAP) confers a selective dependence on protein arginine methyltransferase 5 (PRMT5) and its binding partner WDR77. MTAP is frequently lost due to its proximity to the commonly deleted tumor suppressor gene, CDKN2A. We observed increased intracellular concentrations of methylthioadenosine (MTA, the metabolite cleaved by MTAP) in cells harboring MTAP deletions. Furthermore, MTA specifically inhibited PRMT5 enzymatic activity. Administration of either MTA or a small-molecule PRMT5 inhibitor showed a modest preferential impairment of cell viability for MTAP-null cancer cell lines compared with isogenic MTAP-expressing counterparts. Together, our findings reveal PRMT5 as a potential vulnerability across multiple cancer lineages augmented by a common “passenger” genomic alteration.

Metabolites of Glutamate Metabolism Are Associated With Incident Cardiovascular Events in the PREDIMED PREvención con DIeta MEDiterránea (PREDIMED) Trial

Background Glutamate metabolism may play a role in the pathophysiology of cardiometabolic disorders. However, there is limited evidence of an association between glutamate‐related metabolites and, moreover, changes in these metabolites, and risk of cardiovascular disease (CVD). Methods and Results Plasma levels of glutamate and glutamine were measured at baseline and 1‐year follow‐up in a case‐cohort study including 980 participants (mean age 68 years; 46% male) from the PREvención con DIeta MEDiterránea (PREDIMED) randomized trial, which assessed a Mediterranean diet intervention in the primary prevention of CVD. During median 4.8 years of follow‐up, there were 229 incident CVD events (nonfatal stroke, nonfatal myocardial infarction, or CVD death). In fully adjusted models, per 1‐SD, baseline glutamate was associated with 43% (95% CI: 16% to 76%) and 81% (39% to 137%) increased risk of composite CVD and stroke alone, respectively, and baseline glutamine‐to‐glutamate ratio with 25% (6% to 40%) and 44% (25% to 58%) decreased risk of composite CVD and stroke alone, respectively. Associations appeared linear for stroke (both P linear trend≤0.005). Among participants with high baseline glutamate, the interventions lowered CVD risk by 37% compared to the control diet; the intervention effects were not significant when baseline glutamate was low (P interaction=0.02). No significant effect of the intervention on year‐1 changes in metabolites was observed, and no effect of changes themselves on CVD risk was apparent. Conclusions Baseline glutamate was associated with increased CVD risk, particularly stroke, and glutamine‐to‐glutamate ratio was associated with decreased risk. Participants with high glutamate levels may obtain greater benefits from the Mediterranean diet than those with low levels. Clinical Trial Registration URL: www.controlled-trials.com. Unique identifier: ISRCTN 35739639.

Altered exocrine function can drive adipose wasting in early pancreatic cancer

Malignancy is accompanied by changes in the metabolism of both cells and the organism1,2. Pancreatic ductal adenocarcinoma (PDAC) is associated with wasting of peripheral tissues, a metabolic syndrome that lowers quality of life and has been proposed to decrease survival of patients with cancer3,4. Tissue wasting is a multifactorial disease and targeting specific circulating factors to reverse this syndrome has been mostly ineffective in the clinic5,6. Here we show that loss of both adipose and muscle tissue occurs early in the development of pancreatic cancer. Using mouse models of PDAC, we show that tumour growth in the pancreas but not in other sites leads to adipose tissue wasting, suggesting that tumour growth within the pancreatic environment contributes to this wasting phenotype. We find that decreased exocrine pancreatic function is a driver of adipose tissue loss and that replacement of pancreatic enzymes attenuates PDAC-associated wasting of peripheral tissues. Paradoxically, reversal of adipose tissue loss impairs survival in mice with PDAC. When analysing patients with PDAC, we find that depletion of adipose and skeletal muscle tissues at the time of diagnosis is common, but is not associated with worse survival. Taken together, these results provide an explanation for wasting of adipose tissue in early PDAC and suggest that early loss of peripheral tissue associated with pancreatic cancer may not impair survival.Pancreatic ductal adenocarcinoma in mice induces loss of adipose tissue through altered function of the exocrine pancreas, and supplementing pancreatic enzymes attenuates the wasting of peripheral tissues induced by pancreatic cancer.

Plasma Metabolites From Choline Pathway and Risk of Cardiovascular Disease in the PREDIMED (Prevention With Mediterranean Diet) Study

Background The relationship between plasma concentrations of betaine and choline metabolism and major cardiovascular disease (CVD) end points remains unclear. We have evaluated the association between metabolites from the choline pathway and risk of incident CVD and the potential modifying effect of Mediterranean diet interventions. Methods and Results We designed a case‐cohort study nested within the PREDIMED (Prevention With Mediterranean Diet) trial, including 229 incident CVD cases and 751 randomly selected participants at baseline, followed up for 4.8 years. We used liquid chromatography–tandem mass spectrometry to measure, at baseline and at 1 year of follow‐up, plasma concentrations of 5 metabolites in the choline pathway: trimethylamine N‐oxide, betaine, choline, phosphocholine, and α‐glycerophosphocholine. We have calculated a choline metabolite score using a weighted sum of these 5 metabolites. We used weighted Cox regression models to estimate CVD risk. The multivariable hazard ratios (95% confidence intervals) per 1‐SD increase in choline and α‐glycerophosphocholine metabolites were 1.24 (1.05–1.46) and 1.24 (1.03–1.50), respectively. The baseline betaine/choline ratio was inversely associated with CVD. The baseline choline metabolite score was associated with a 2.21‐fold higher risk of CVD across extreme quartiles (95% confidence interval, 1.36–3.59; P<0.001 for trend) and a 2.27‐fold higher risk of stroke (95% confidence interval, 1.24–4.16; P<0.001 for trend). Participants in the higher quartiles of the score who were randomly assigned to the control group had a higher risk of CVD compared with participants in the lower quartile and assigned to the Mediterranean diet groups (P=0.05 for interaction). No significant associations were observed for 1‐year changes in individual plasma metabolites and CVD. Conclusions A metabolite score combining plasma metabolites from the choline pathway was associated with an increased risk of CVD in a Mediterranean population at high cardiovascular risk. Clinical Trial Registration URL: http://www.controlled-trials.com. Unique identifier: ISRCTN35739639.

Association of Tryptophan Metabolites with Incident Type 2 Diabetes in the PREDIMED Trial: A Case–Cohort Study

BACKGROUND Metabolites of the tryptophan-kynurenine pathway (i.e., tryptophan, kynurenine, kynurenic acid, quinolinic acid, 3-hydroxyanthranilic) may be associated with diabetes development. Using a case-cohort design nested in the Prevención con Dieta Mediterránea (PREDIMED) study, we studied the associations of baseline and 1-year changes of these metabolites with incident type 2 diabetes (T2D). METHODS Plasma metabolite concentrations were quantified via LC-MS for n = 641 in a randomly selected subcohort and 251 incident cases diagnosed during 3.8 years of median follow-up. Weighted Cox models adjusted for age, sex, body mass index, and other T2D risk factors were used. RESULTS Baseline tryptophan was associated with higher risk of incident T2D (hazard ratio = 1.29; 95% CI, 1.04-1.61 per SD). Positive changes in quinolinic acid from baseline to 1 year were associated with a higher risk of T2D (hazard ratio = 1.39; 95% CI, 1.09-1.77 per SD). Baseline tryptophan and kynurenic acid were directly associated with changes in homeostatic model assessment for insulin resistance (HOMA-IR) from baseline to 1 year. Concurrent changes in kynurenine, quinolinic acid, 3-hydroxyanthranilic acid, and kynurenine/tryptophan ratio were associated with baseline-to-1-year changes in HOMA-IR. CONCLUSIONS Baseline tryptophan and 1-year increases in quinolinic acid were positively associated with incident T2D. Baseline and 1-year changes in tryptophan metabolites predicted changes in HOMA-IR. Tryptophan levels may initially increase and then deplete as diabetes progresses in severity.

netome: a computational framework for metabolite profiling and omics network analysis

Summary Advances in metabolomics technologies have enabled comprehensive analyses of associations between metabolites and human disease and have provided a means to study biochemical pathways and processes in detail using model systems. Liquid chromatography tandem mass spectrometry (LC-MS) is an analytical technique commonly used by metabolomics labs to measure hundreds of metabolites of known identity and thousands of “peaks” from yet to be identified compounds that are tracked by their measured masses and chromatographic retention times. netome is a computational framework that provides tools for analyzing processed LC-MS data. In this framework, we develop and provide various computational resources including individual software modules to inspect and adjust trends in raw data, align unknown peaks between separately acquired data sets, and to remove redundancies in nontargeted LC-MS data arising from multiple ionization products of a single metabolite. These tools are deployed through computing resources such as web servers and virtual machines with detailed documentation in order to support researchers. Availability and implementation netome is publicly available with extensive documentation and support via issue tracker at https://broadinstitute.github.io/netome under the MIT license. netome includes a set of computational methods that have been designed to execute quality control and post-raw data processing tasks for metabolomics data (e.g. scaling and clustering metabolite abundances), as well as statistical association testing in a network manner (e.g., testing relationship between metabolites and microbes). Each individual tool is available with source code, workshop-oriented documentation which includes instructions for installation and using tools with demonstration examples, and a web server with all services. We also provide a complete image of the netome package with all pre-installed dependencies and support for Google Compute Engine and Amazon EC2. All tools and related services are maintained, and upon new developments, new modules will be added to the environment. Contact rah@broadinstitute.org, clary@broadinstitute.org Supplementary information Supplementary data are available at Bioinformatics online.

Changes in Arginine are Inversely Associated with Type 2 Diabetes: A Case‐Cohort Study in the PREDIMED Trial

The associations between arginine‐based metabolites and incident type 2 diabetes (T2D) are unknown. We employed a case‐cohort design, nested within the PREDIMED trial, to examine six plasma metabolites (arginine, citrulline, ornithine, asymmetric dimethylarginine [ADMA], symmetric dimethylarginine [SDMA] and N‐monomethyl‐l‐arginine [NMMA]) among 892 individuals (251 cases) for associations with incident T2D and insulin resistance. Weighted Cox models with robust variance were used. The 1‐year changes in arginine (adjusted hazard ratio [HR] per SD 0.68, 95% confidence interval [CI] 0.49, 0.95; Q4 vs. Q1 0.46, 95% CI 0.21, 1.04; P trend = 0.02) and arginine/ADMA ratio (adjusted HR per SD 0.73, 95% CI 0.51, 1.04; Q4 vs. Q1 0.52, 95% CI 0.22, 1.25; P trend = 0.04) were associated with a lower risk of T2D. Positive changes of citrulline and ornithine, and negative changes in SDMA and arginine/(ornithine + citrulline) were associated with concurrent 1‐year changes in homeostatic model assessment of insulin resistance. Individuals in the low‐fat‐diet group had a higher risk of T2D for 1‐year changes in NMMA than individuals in Mediterranean‐diet groups (P interaction = 0.02). We conclude that arginine bioavailability is important in T2D pathophysiology.

Plasma Lipidomic Profiling and Risk of Type 2 Diabetes in the PREDIMED Trial

OBJECTIVE Specific lipid molecular changes leading to type 2 diabetes (T2D) are largely unknown. We assessed lipidome factors associated with future occurrence of T2D in a population at high cardiovascular risk. RESEARCH DESIGN AND METHODS We conducted a case-cohort study nested within the PREDIMED trial, with 250 incident T2D cases diagnosed during 3.8 years of median follow-up, and a random sample of 692 participants (639 noncases and 53 overlapping cases) without T2D at baseline. We repeatedly measured 207 plasma known lipid metabolites at baseline and after 1 year of follow-up. We built combined factors of lipid species using principal component analysis and assessed the association between these lipid factors (or their 1-year changes) and T2D incidence. RESULTS Baseline lysophosphatidylcholines and lysophosphatidylethanolamines (lysophospholipids [LPs]), phosphatidylcholine-plasmalogens (PC-PLs), sphingomyelins (SMs), and cholesterol esters (CEs) were inversely associated with risk of T2D (multivariable-adjusted P for linear trend ≤0.001 for all). Baseline triacylglycerols (TAGs), diacylglycerols (DAGs), and phosphatidylethanolamines (PEs) were positively associated with T2D risk (multivariable-adjusted P for linear trend <0.001 for all). One-year changes in these lipids showed associations in similar directions but were not significant after adjustment for baseline levels. TAGs with odd-chain fatty acids showed inverse associations with T2D after adjusting for total TAGs. CONCLUSIONS Two plasma lipid profiles made up of different lipid classes were found to be associated with T2D in participants at high cardiovascular risk. A profile including LPs, PC-PLs, SMs, and CEs was associated with lower T2D risk. Another profile composed of TAGs, DAGs, and PEs was associated with higher T2D risk.