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PDF - 217KB, Additional information regarding the search strategy used in the main paper. Supplementary Table: List of reported metabolites to be altered in human cancers. Supplementary Figure: General overview over the metabolomics workflow.

Metabolomics, the systematic investigation of all metabolites present within a biologic system, is used in biomarker development for many human diseases, including cancer. In this review, we investigate the current role of mass spectrometry–based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase, and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case–control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification, or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including less than 100 patients. Standardization is required especially concerning sample preparation and data analysis. In the second part of this review, we reconstructed a metabolic network of patients with cancer by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane, and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed. Cancer Epidemiol Biomarkers Prev; 22(12); 2182–201. ©2013 AACR.

Background: Aspirin use is an effective strategy for the chemoprevention of colorectal cancer, even at low doses. However, in order to implement aspirin interventions, risk–benefit balances and biologic mechanisms need to be better defined; to further this aim, we used a metabolomics approach.Methods: We metabolically profiled 40 healthy, nonsmoking men and women ages 20 to 45 years enrolled in a randomized, double-blind, crossover trial of 325 mg aspirin/day over a period of 60 days. Gas and liquid chromatography–mass spectrometry were used to comprehensively profile participants' plasma samples after aspirin and placebo interventions.Results: A total of 363 metabolites, covering most human biochemical pathways, were measured. Compared with placebo-treated participants, plasma concentrations of the oncometabolite 2-hydroxyglutarate (R+S) decreased after aspirin treatment in both men and women (P = 0.005). This signal proved robust during 20-fold random splitting of the data using 80% of the samples in each split. We subsequently performed functional follow-up studies using targeted, enantiospecific detection in human colorectal cancer cell lines and observed an aspirin-induced reduction of (R)-2-hydroxyglutarate. We further showed that salicylate, the primary aspirin metabolite, inhibits the hydroxyacid–oxoacid transhydrogenase mediated production of (R)-2-hydroxyglutarate, thereby providing mechanistic evidence for the clinically observed effects of aspirin on total-2-hydroxyglutarate.Conclusions: Using a metabolomics approach with functional follow-up, we propose that a decrease in the oncometabolite (R)-2-hydroxyglutarate may identify an additional mechanism for aspirin or its metabolites in cancer prevention.Impact: Reduction of the oncometabolite (R)-2-hydroxyglutarate identifies a novel, non–COX-inhibition-mediated mechanism of aspirin. Cancer Epidemiol Biomarkers Prev; 25(1); 180–7. ©2015 AACR.

Objective: High-throughput metabolomics assays can generate thousands of biomarker measurements and provide novel opportunities for prognostic modeling in colorectal cancer (CRC) research. The high dimensionality of metabolic data brings unforeseen statistical challenges and traditional variable selection methods may not perform well due to simultaneous challenges of computational expediency, statistical accuracy, and algorithmic stability. The Iterative Sure Independence Screening (ISIS) has demonstrated superior theoretical properties in handling such situations, and may be a viable alternative. Methods: In a prospective study of 77 newly diagnosed CRC patients (stage I-IV), pre-surgical urinary samples were analyzed on a gas chromatography-mass spectrometry platform. After exclusion of metabolites with >30% coefficient of variation, 168 metabolites remained for statistical analysis. Raw measures were processed following a standard normalization pipeline. The primary outcome was overall survival (OS) as measured from date of cancer diagnosis. In addition to metabolomics data, the predictor set included baseline clinical characteristics, such as age, sex, body mass index, tumor site, tumor stage, and receipt of neo-adjuvant and/or adjuvant treatment. We applied the ISIS method with Lasso penalty on a Cox regression model (ISIS-Lasso) to identify features associated with OS. Cox models with either Lasso regularization or backward selection were also considered as competing methods. The performance of the models was assessed through two standard performance matrices: Uno's time-dependent Area Under the Curve (tAUC) and Brier's score, both with resample-based validation. Results: Based on bootstrapped tAUC curves, we demonstrated that the screening step in ISIS can significantly improve model performance, since its predicted mean (and median) AUC are larger across clinically relevant follow-up time points (2 and 5 years after diagnosis) relative to the corresponding measures from the other two models. The prediction error based on Brier's score with 0.632+ bootstrap from ISIS-Lasso was also noticeably lower compared to the model from backward selections. Based on the ISIS-Lasso model, we identified two features, that were predictive of OS in CRC patients: tumor stage and cystine. When fixing all other clinical measures, patients with early stage (I-III) had 52% lower risk of death, compared to late stage (IV); 1 standard deviation of increase of cystine level was associated with 62% increased risk of death. Conclusion: We have demonstrated the feasibility and effectiveness of an ISIS-based method to improve selection of prognostic models derived from metabolomics data. This may be especially useful for studies with moderate sample sizes. We have identified cystine as a potentially important prognostic biomarker. Citation Format: Tengda Lin, Biljana Gigic, Kenneth Boucher, Ben Haaland, David Liesenfeld, Robert Owen, Petra Schrotz-King, Jourgen Boehm, Anita Peoples, Augustin Scalbert, Martin Schneider, Jane Figueiredo, William Grady, Christopher Li, David Shibata, Erin Siegel, Adetunji Toriola, Alexis Ulrich, Neli Ulrich, Jincheng Shen, Jennifer Ose. Application of iterative sureindependence screening to improve urinary metabolomics-based prediction of survival in colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 892.

Adipose tissue is one of the main organs regulating energy homeostasis via energy storage as well as endocrine function. The adipocyte cell number is largely determined by adipogenesis. While the molecular mechanism of adipogenesis has been extensively studied, its role in dynamic DNA methylation plasticity remains unclear. Recently, it has been shown that Tet methylcytosine dioxygenase (TET) is catalytically capable of oxidizing DNA 5-methylcytosine (5-mC) to 5-hydroxymethylcytosine (5-hmC) toward a complete removal of the methylated cytosine. We investigate whether expression of the Tet genes and production of hydroxymethylcytosine are required for preadipocyte differentiation.Murine 3T3-L1 preadipocytes were used to evaluate the role of Tet1 and Tet2 genes during adipogenesis. Changes in adipogenic ability and in epigenetic status were analyzed, with and without interfering Tet1 and Tet2 expression using small interfering RNA (siRNA). The adipogenesis was evaluated by Oil-Red-O staining and induced expression of adipogenic genes using quantitative polymerase chain reaction (qPCR). Levels of 5-hmC and 5-mC were measured by MassARRAY, immunoprecipitation and GC mass spectrometry at specific loci as well as globally.Both Tet1 and Tet2 genes were upregulated in a time-dependent manner, accompanied by increased expression of hallmark adipogenic genes such as Pparγ and Fabp4 (P0.05). The TET upregulation led to reduced DNA methylation and elevated hydroxymethylcytosine, both globally and specifically at the Pparγ locus (P0.05 and P0.01, respectively). Knockdown of Tet1 and Tet2 blocked adipogenesis (P0.01) by repression of Pparγ expression (P0.05). In particular, Tet2 knockdown repressed conversion of 5-mC to 5-hmC at the Pparγ locus (P0.01). Moreover, vitamin C treatment enhanced adipogenesis (P0.05), while fumarate treatment inhibited it (P0.01) by modulating TET activities.TET proteins, particularly TET2, were required for adipogenesis by modulating DNA methylation at the Pparγ locus, subsequently by inducing Pparγ gene expression.

Cachexia is a multifactorial syndrome that is characterized by loss of skeletal muscle mass in cancer patients. The biological pathways involved remain poorly characterized. Here, we compare urinary metabolic profiles in newly diagnosed colorectal cancer patients (stage I&ndash, IV) from the ColoCare Study in Heidelberg, Germany. Patients were classified as cachectic (n = 16), pre-cachectic (n = 13), or non-cachectic (n = 23) based on standard criteria on weight loss over time at two time points. Urine samples were collected pre-surgery, and 6 and 12 months thereafter. Fat and muscle mass area were assessed utilizing computed tomography scans at the time of surgery. N = 152 compounds were detected using untargeted metabolomics with gas chromatography&ndash, mass spectrometry and n = 154 features with proton nuclear magnetic resonance spectroscopy. Thirty-four metabolites were overlapping across platforms. We calculated differences across groups and performed discriminant and overrepresentation enrichment analysis. We observed a trend for 32 compounds that were nominally significantly different across groups, although not statistically significant after adjustment for multiple testing. Nineteen compounds could be identified, including acetone, hydroquinone, and glycine. Comparing cachectic to non-cachectic patients, higher levels of metabolites such as acetone (Fold change (FC) = 3.17, p = 0.02) and arginine (FC = 0.33, p = 0.04) were observed. The two top pathways identified were glycerol phosphate shuttle metabolism and glycine and serine metabolism pathways. Larger subsequent studies are needed to replicate and validate these results.

Radiotherapy is a fundamental part of cancer treatment but its use is limited by the onset of late adverse effects in the normal tissue, especially radiation-induced fibrosis. Since the molecular causes for fibrosis are largely unknown, we analyse if epigenetic regulation might explain inter-individual differences in fibrosis risk. DNA methylation profiling of dermal fibroblasts obtained from breast cancer patients prior to irradiation identifies differences associated with fibrosis. One region is characterized as a differentially methylated enhancer of diacylglycerol kinase alpha (DGKA). Decreased DNA methylation at this enhancer enables recruitment of the profibrotic transcription factor early growth response 1 (EGR1) and facilitates radiation-induced DGKA transcription in cells from patients later developing fibrosis. Conversely, inhibition of DGKA has pronounced effects on diacylglycerol-mediated lipid homeostasis and reduces profibrotic fibroblast activation. Collectively, DGKA is an epigenetically deregulated kinase involved in radiation response and may serve as a marker and therapeutic target for personalized radiotherapy., Radiotherapy can induce fibrosis in cancer patients, limiting its use in clinical settings. Here, the authors identify a differentially methylated enhancer of the lipid kinase DGKA in fibroblasts from breast cancer patients developing fibrosis after radiotherapy and they show that DGKA inhibition affects lipid homeostasis and reduces pro-fibrotic fibroblast activation.

Quality control of BRAF mutation testing methods used in routine practice is crucial for optimal treatment selection. In this prospective study, we assessed the impact of patient/sample characteristics on BRAF mutation testing results in patients with melanoma, during clinical practice. Data were collected on routine testing practices and documented mutation status in patients with melanoma stages IIIB, IIIC, or IV across 28 diagnostic pathology centers in Germany. Patient/sample data collected included: patient age, location of primary melanoma and metastases, origin of sample, melanoma subtype, and quality of tissue. Statistical influence of patient/sample characteristics on BRAF mutation rate was assessed using multiple logistic regression analyses and statistical models developed to predict the probability of BRAF mutations for individual patient cohorts. Data/samples from 642 patients with melanoma were analyzed. BRAF mutations were documented in 241/642 patients (37.5%). The primary statistical model to predict BRAF mutation rates included: age (continuous), origin of sample, method of mutation analysis, and quality of tissue. Analyses of post hoc collected data identified major deviations between documented mutation rates included in this study vs. routinely recorded mutation rates for three centers. When samples from these centers were excluded, the influence of testing method was no longer statistically significant. The final model included patient age, origin of sample (including metastasis location), and quality of tissue. Once validated in an independent population, this type of model could allow pathology centers to compare the performance of their testing methods with what would be expected based on patient, tumor, and sample characteristics.

Branched-chain amino acids (BCAA) have been previously linked to survival in colorectal cancer (CRC) patients. It is unclear whether BCAAs are prognostic biomarkers or surrogate markers for energy balance.We aimed to determine correlations of BCAAs with markers of energy balance over time and to investigate prognostic significance of BCAAs in CRC.We used urinary samples from newly diagnosed CRC patients [n=163; (stage I - IV)] from the ColoCare study in Heidelberg, Germany, collected at surgery (n=163), 6 (n=83) and 12 months follow-up (n=54). Isoleucine, leucine, valine, (2Z)-3-methylglutaconic acid (3HM), 2-ethylhydracrylic acid (2EA), 2-methyl-3-hydroxybutyrate (2M3H) were detected using gas-chromatography mass-spectrometry and proton-nuclear-magnetic-resonance spectroscopy. Partial correlation coefficients between BCAAs with body mass index (BMI), physical activity (metabolic equivalent [MET]) and muscle area were computed and adjusted for sex and age at diagnosis. We used Cox proportional hazard models to investigate overall survival (OS) after 24 months of follow-up.We did not observe significant correlations between BCAAs and parameters of energy balance at all time points (correlation ranges: BMI: r= -0.13 to -0.01; METs: r=-0.14 to 0.02; dorsal muscle: r=-0.03 to 0.10). BCAAs were not associated with risk of death in stage I-III (e.g., valine: HROur study suggests that BCAAs in colorectal cancer patients do not reflect parameters of energy balance and may be independently associated with overall survival.

Background: Metabolic and transcriptomic differences between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) compartments, particularly in the context of obesity, may play a role in colorectal carcinogenesis. We investigated the differential functions of their metabolic compositions. Objectives: Biochemical differences between adipose tissues (VAT compared with SAT) in patients with colorectal carcinoma (CRC) were investigated by using mass spectrometry metabolomics and gene expression profiling. Metabolite compositions were compared between VAT, SAT, and serum metabolites. The relation between patients’ tumor stage and metabolic profiles was assessed. Design: Presurgery blood and paired VAT and SAT samples during tumor surgery were obtained from 59 CRC patients (tumor stages I–IV) of the ColoCare cohort. Gas chromatography time-of-flight mass spectrometry and liquid chromatography quadrupole time-of-flight mass spectrometry were used to measure 1065 metabolites in adipose tissue (333 identified compounds) and 1810 metabolites in serum (467 identified compounds). Adipose tissue gene expression was measured by using Illumina’s HumanHT-12 Expression BeadChips. Results: Compared with SAT, VAT displayed elevated markers of inflammatory lipid metabolism, free arachidonic acid, phospholipases (PLA2G10), and prostaglandin synthesis–related enzymes (PTGD/PTGS2S). Plasmalogen concentrations were lower in VAT than in SAT, which was supported by lower gene expression of FAR1, the rate-limiting enzyme for ether-lipid synthesis in VAT. Serum sphingomyelin concentrations were inversely correlated (P = 0.0001) with SAT adipose triglycerides. Logistic regression identified lipids in patients’ adipose tissues, which were associated with CRC tumor stage. Conclusions: As one of the first studies, we comprehensively assessed differences in metabolic, lipidomic, and transcriptomic profiles between paired human VAT and SAT and their association with CRC tumor stage. We identified markers of inflammation in VAT, which supports prior evidence regarding the role of visceral adiposity and cancer. This trial was registered at clinicaltrials.gov as {"type":"clinical-trial","attrs":{"text":"NCT02328677","term_id":"NCT02328677"}}NCT02328677.

Metabolomics is a valuable tool for biomarker screening of colorectal cancer (CRC). In this study, we profiled the urinary metabolomes of patients enrolled in a prospective patient cohort (ColoCare). We aimed to determine changes in the metabolome of the longer clinical follow-up and ascertain candidate markers with possibly prognostic significance. In total, 199 urine samples from CRC patients prior to surgery (n = 97) or 1–8 days post-surgery (n = 12), and then after 6 (n = 52) and 12 months (n = 38) were analyzed using both GC–MS and 1H-NMR. Both datasets were analyzed separately with built in uni- and multivariate analyses of Metaboanalyst 2.0. Furthermore, adjusted linear mixed effects regression models were constructed. Many concentrations of the metabolites derived from the gut microbiome were affected by CRC surgery, presumably indicating a tumor-induced shift in bacterial species. Associations of the microbial metabolites with disease stage indicate an important role of the gut microbiome in CRC. We were able to differentiate the metabolite profiles of pre-surgery CRC patients from those at any post-surgery timepoint using a multivariate model containing 20 marker metabolites (AUCROC = 0.89; 95 % CI 0.84–0.95). This is one of the first metabolomic studies to follow CRC patients in a prospective setting with repeated urine sampling over time. We were able to confirm markers initially identified in case–control studies and metabolites which may represent prognostic biomarker candidates of CRC.

Established by the Metabolomics Society, 2014 saw the Early Members Network (EMN) celebrate its first birthday. Initially run by nine early career researchers, forming the EMN-committee, the official EMN mission was to recognize the value and importance of early career members, to ensure that their views are heard and acted upon, ultimately improving their experience of metabolomics science and the community as a whole (Putri 2014). Dedicated to all Metabolomics Society members who are within 5 years of completing their higher degrees, the EMN has started to make significant strides to achieve its vision to establish a real sense of community and engagement between early career researchers globally through leading initiative and enthusiastic appearance. Past activities of 2014

Metabolomics, the systematic investigation of all metabolites present within a biologic system, is used in biomarker development for many human diseases, including cancer. In this review, we investigate the current role of mass spectrometry–based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase, and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case–control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification, or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including less than 100 patients. Standardization is required especially concerning sample preparation and data analysis. In the second part of this review, we reconstructed a metabolic network of patients with cancer by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane, and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed. Cancer Epidemiol Biomarkers Prev; 22(12); 2182–201. ©2013 AACR.

Background Branched-chain amino acids (BCAA; e.g., valine, leucine and isoleucine) have been previously linked with survival in colorectal cancer patients. It is unclear whether BCAAs are prognostic biomarkers or a surrogate endpoint for factors related to muscle mass. Thus, we investigated the correlation between BCAAs and muscle mass, physical activity and body mass index (BMI) at multiple time points during the course of disease in a prospective cohort of patients. Methods Patients with newly diagnosed colorectal cancer [n = 197; (stage I - IV)] from the ColoCare study in Heidelberg, Germany with baseline and follow-up data, and measurements of urinary BCAAs were eligible. Skeletal muscle mass of the dorsal muscle was quantified based on abdominal computed tomography (CT)-scans (vertebral body L3/4 and L4/5). BMI (kg/m2) and physical activity [metabolic equivalent (MET) hours/week] were reported by questionnaire. In addition, minutes of moderate and vigorous physical activity/week were measured by accelerometry. We prospectively monitored the urinary metabolome of these patients at multiple time points after surgery [baseline (n = 197), 6-month follow-up (n = 107) and 12 month follow-up (n = 75)]. BCAAs (valine, leucine and isoleucine) were identified using gas chromatography mass spectrometry (GC/MS). Metabolites were normalized based on the sum intensity of all annotated metabolites for statistical analyses. Pearson and partial correlation coefficients with parameters of energy balance/muscle mass were computed for each time point, adjusted for gender and age at diagnosis. Results As expected, urinary valine, leucine and isoleucine were highly correlated, independent of time point (r>0.95, P Conclusion The present data suggests that urinary levels of BCAA in colorectal cancer patients do not reflect parameters of energy balance and muscle mass. Thus, they warrant further investigation as potential prognostic biomarkers. Citation Format: Jennifer Ose, David B. Liesenfeld, Juergen Boehm, Nina Habermann, Robert W. Owen, Biljana Gigic, Stefanie Skender, Johanna Nattenmueller, Hans-Ulrich Kauczor, Cornelia Ulrich. Branched-chain amino acids in the urinary metabolic profile of colorectal cancer patients and associations with muscle mass, BMI, and physical activity in the ColoCare Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4282.

Ionizing radiation is a common treatment option for cancer but its use is limited by the unpredictable and highly heterogeneous onset of late side effects, especially radiation-induced fibrosis. Clinically applicable biomarkers and effective treatments for radiation fibrosis are currently unavailable. In order to identify novel markers we ran a genome-wide DNA methylation screen in primary dermal fibroblasts obtained from breast cancer patients before intraoperative radiotherapy. Cells from patients developing fibrosis within a three-year follow up were compared to those without fibrosis (12 individuals per group). Illumina Infinium HumanMethylation450 BeadChip analysis revealed differentially methylated sites which are associated with fibrosis. Notably, we identified a differentially methylated region (DMR) at the diacylglycerol kinase alpha (DGKA) locus as a potential fibrosis marker. This DGKA DMR was confirmed using quantitative MassARRAY technology in 75 patient fibroblast samples. We first investigated whether high or low DNA methylation at this DGKA DMR affects cellular radiation response. Functional in vitro analysis showed that the methylation status of the DGKA DMR inversely correlated with its radiation-induced mRNA and protein expression as well as with its enzymatic activity. We next examined the DMR for its role as a regulatory site. The intragenically located DMR was identified as a potential enhancer sequence using chromatin immunoprecipitation (ChIP) for H3K4me1 and H3K27ac as well as luciferase reporter assays. Chromatin conformation capture (3C) analysis revealed interaction of this enhancer with the DGKA promoter in fibroblasts with low DNA methylation, and further ChIP experiments showed a DNA methylation-dependent recruitment of the profibrotic transcription factor Early Growth Response 1 (EGR1) to this site. We finally asked how epigenetically altered DGKA expression could impact on cellular processes relevant to fibrosis such as fibroblast transactivation or stress response. Results in primary fibroblasts showed that, in response to ionizing radiation and other stress factors, DGKA affects global levels of its substrate diacylglycerol, as well as expression of the fibroblast activation markers Alpha Smooth Muscle Actin (ACTA2) and collagen 1 (COL1A1). Upon overexpression of DGKA in HEK293T cells, a luciferase-based screening of 15 stress-responsive signaling reporters revealed functional consequences on several response pathways. In summary, DGKA has emerged as a novel, epigenetically regulated signaling protein that has a role in radiation fibrosis and may serve as a new biomarker and therapeutic target. Citation Format: Christoph Weigel, Marlon R. Veldwijk, Christopher C. Oakes, Petra Seibold, Alla Slynko, David B. Liesenfeld, Carsten Herskind, Elena Sperk, Axel Benner, Christoph Plass, Frederik Wenz, Jenny Chang-Claude, Peter Schmezer, Odilia Popanda. Diacylglycerol kinase alpha as a novel epigenetically regulated risk marker for radiotherapy-induced fibrosis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3445. doi:10.1158/1538-7445.AM2015-3445