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Colorectal cancer (CRC) is increasingly recognized as a heterogeneous disease. No studies have prospectively examined associations of blood metabolite concentrations with all-cause mortality in patients with colon and rectal cancer separately. Targeted metabolomics (Biocrates AbsoluteIDQ p180) and pathway analyses (MetaboAnalyst 4.0) were performed on pre-surgery collected plasma from 674 patients with non-metastasized (stage I–III) colon (n = 394) or rectal cancer (n = 283). Metabolomics data and covariate information were received from the international cohort consortium MetaboCCC. Cox proportional hazards models were computed to investigate associations of 148 metabolite levels with all-cause mortality adjusted for age, sex, tumor stage, tumor site (whenever applicable), and cohort; the false discovery rate (FDR) was used to account for multiple testing. A total of 93 patients (14%) were deceased after an average follow-up time of 4.4 years (60 patients with colon cancer and 33 patients with rectal cancer). After FDR adjustment, higher plasma creatinine was associated with a 39% increase in all-cause mortality in patients with rectal cancer. HR: 1.39, 95% CI 1.23–1.72, pFDR = 0.03; but not colon cancer: pFDR = 0.96. Creatinine is a breakdown product of creatine phosphate in muscle and may reflect changes in skeletal muscle mass. The starch and sucrose metabolisms were associated with increased all-cause mortality in colon cancer but not in rectal cancer. Genes in the starch and sucrose metabolism pathways were previously linked to worse clinical outcomes in CRC. In summary, our findings support the hypothesis that colon and rectal cancer have different etiological and clinical outcomes that need to be considered for targeted treatments.

The underlying biological mechanisms causing persistent fatigue complaints after colorectal cancer treatment need further investigation. We investigated longitudinal associations of circulating concentrations of 138 metabolites with total fatigue and subdomains of fatigue between 6 weeks and 2 years after colorectal cancer treatment. Among stage I-III colorectal cancer survivors (n = 252), blood samples were obtained at 6 weeks, and 6, 12 and 24 months posttreatment. Total fatigue and fatigue subdomains were measured using a validated questionnaire. Tandem mass spectrometry was applied to measure metabolite concentrations (BIOCRATES AbsoluteIDQp180 kit). Confounder-adjusted longitudinal associations were analyzed using linear mixed models, with false discovery rate (FDR) correction. We assessed interindividual (between-participant differences) and intraindividual longitudinal associations (within-participant changes over time). In the overall longitudinal analysis, statistically significant associations were observed for 12, 32, 17 and three metabolites with total fatigue and the subscales "fatigue severity," "reduced motivation" and "reduced activity," respectively. Specifically, higher concentrations of several amino acids, lysophosphatidylcholines, diacylphosphatidylcholines, acyl-alkylphosphatidylcholines and sphingomyelins were associated with less fatigue, while higher concentrations of acylcarnitines were associated with more fatigue. For "fatigue severity," associations appeared mainly driven by intraindividual associations, while for "reduced motivation" stronger interindividual associations were found. We observed longitudinal associations of several metabolites with total fatigue and fatigue subscales, and that intraindividual changes in metabolites over time were associated with fatigue severity. These findings point toward inflammation and an impaired energy metabolism due to mitochondrial dysfunction as underlying mechanisms. Mechanistic studies are necessary to determine whether these metabolites could be targets for intervention.

Dysregulation of tryptophan metabolism has been linked to colorectal tumorigenesis, however, epidemiological studies investigating tryptophan metabolites in relation to colorectal cancer risk are limited. We studied associations of plasma tryptophan, serotonin, and kynurenine with colon cancer risk in two studies with cancer patients and controls, and in one prospective cohort: ColoCare Study (110 patients/153 controls), the Colorectal Cancer Study of Austria (CORSA; 46 patients/390 controls), and the European Prospective Investigation into Cancer and Nutrition (EPIC; 456 matched case-control pairs). Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for colon cancer risk. Tryptophan was inversely associated with colon cancer risk in ColoCare [OR per 1-standard deviation (SD) = 0.44; 95% CI, 0.31-0.64] and EPIC (OR per 1-SD = 0.86; 95% CI, 0.74-0.99). Comparing detectable versus non-detectable levels, serotonin was positively associated with colon cancer in CORSA (OR = 6.39; 95% CI, 3.61-11.3) and EPIC (OR = 2.03; 95% CI, 1.20-3.40). Kynurenine was inversely associated with colon cancer in ColoCare (OR per 1-SD = 0.74; 95% CI, 0.55-0.98), positively associated in CORSA (OR per 1-SD = 1.79; 95% CI, 1.27-2.52), while no association was observed in EPIC. The kynurenine-to-tryptophan ratio was positively associated with colon cancer in ColoCare (OR per 1-SD = 1.38; 95% CI, 1.03-1.84) and CORSA (OR per 1-SD = 1.44; 95% CI, 1.06-1.96), but not in EPIC. These results suggest that higher plasma tryptophan may be associated with lower colon cancer risk, while increased serotonin may be associated with a higher risk of colon cancer. The kynurenine-to-tryptophan ratio may also reflect altered tryptophan catabolism during colon cancer development. This article is protected by copyright. All rights reserved.

Background: Obesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known. Methods: The association of metabolically defined body size phenotypes with endometrial cancer risk was investigated in a nested case–control study (817 cases/ 817 controls) within the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of C-peptide were used to define metabolically healthy (MH, World Health Organization, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Danish Cancer Society, Ligue nationale contre le cancer, Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, Institut National de la Sante et de la Recherche Medicale (Inserm), Deutsche Krebshilfe, Helmholtz Association, German Institute of Human Nutrition PotsdamRehbruecke (DIfE), Federal Ministry of Education & Research (BMBF), Fondazione AIRC per la ricerca sul cancro, Compagnia di San Paolo, Consiglio Nazionale delle Ricerche (CNR), Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds Netherlands Organization for Scientific Research (NWO), World Cancer Research Fund (WCRF-ERC) 232997, Netherlands Government, Health Research Fund (FIS)-Instituto de Salud Carlos III (ISCIII), Junta de Andalucia, Principality of Asturias, Basque Government, Regional Government of Murcia, Regional Government of Navarra, Catalan Institute of OncologyICO (Spain), Swedish Cancer Society Swedish Research Council, European Commission, County Council of Skane, County Council of Vasterbotten (Sweden), Cancer Research UK 14136 C8221/A29017 C19335/A21351, UK Research & Innovation (UKRI), Medical Research Council UK (MRC), European Commission 1000143 MR/M012190/1

Purpose Emerging evidence suggests that diet is linked to survival in colorectal cancer patients, although underlying mechanisms are not fully understood. The aim of this study was to evaluate whether dietary exposures are associated with metabolite concentrations in colorectal cancer patients. Methods Concentrations of 134 metabolites of the Biocrates AbsoluteIDQ p180 kit were quantified in plasma samples collected at diagnosis from 195 stage I-IV colorectal cancer patients. Food frequency questionnaires were used to calculate adherence to the World Cancer Research Fund (WCRF) dietary recommendations and the Dutch Healthy Diet (DHD15) index as well as to construct dietary patterns using Principal Component Analysis. Multivariable linear regression models were used to determine associations between dietary exposures and metabolite concentrations. All models were adjusted for age, sex, body mass index, smoking status, analytical batch, cancer stage, and multiple testing using false discovery rate. Results Participants had a mean (SD) age of 66 (9) years, were mostly men (60%), and mostly diagnosed with stage II and III cancer. For the dietary pattern analyses, Western, Carnivore, and Prudent patterns were identified. Better adherence to the WCRF dietary recommendations was associated with lower concentrations of ten phosphatidylcholines. Higher intake of the Carnivore pattern was associated with higher concentrations of two phosphatidylcholines. The DHD15-index, Western pattern, or Prudent pattern were not associated with metabolite concentrations. Conclusion In the current study, the WCRF dietary score and the Carnivore pattern are associated with phosphatidylcholines. Future research should elucidate the potential relevance of phosphatidylcholine metabolism in the colorectal cancer continuum. Clinical trial registry ClinicalTrials.gov Identifier: NCT03191110.

Obesity and obesity-driven cancer rates are continuing to rise worldwide. We hypothesize that adipocyte–colonocyte interactions are a key driver of obesity-associated cancers. To understand the clinical relevance of visceral adipose tissue in advancing tumor growth, we analyzed paired tumor-adjacent visceral adipose, normal mucosa, and colorectal tumor tissues as well as presurgery blood samples from patients with sporadic colorectal cancer. We report that high peroxisome proliferator-activated receptor gamma (PPARG) visceral adipose tissue expression is associated with glycoprotein VI (GPVI) signaling—the major signaling receptor for collagen—as well as fibrosis and adipogenesis pathway signaling in colorectal tumors. These associations were supported by correlations between PPARG visceral adipose tissue expression and circulating levels of plasma 4-hydroxyproline and serum intercellular adhesion molecule 1 (ICAM1), as well as gene set enrichment analysis and joint gene-metabolite pathway results integration that yielded significant enrichment of genes defining epithelial-to-mesenchymal transition—as in fibrosis and metastasis—and genes involved in glycolytic metabolism, confirmed this association. We also reveal that elevated prostaglandin-endoperoxide synthase 2 (PTGS2) colorectal tumor expression is associated with a fibrotic signature in adipose–tumor crosstalk via GPVI signaling and dendritic cell maturation in visceral adipose tissue. Systemic metabolite and biomarker profiling confirmed that high PTGS2 expression in colorectal tumors is significantly associated with higher concentrations of serum amyloid A and glycine, and lower concentrations of sphingomyelin, in patients with colorectal cancer. This multi-omics study suggests that adipose–tumor crosstalk in patients with colorectal cancer is a critical microenvironment interaction that could be therapeutically targeted. See related spotlight by Colacino et al., p. 803

This work was supported by the French National Cancer Institute (INCa SHSESP17, grant No. 2017-127 to N. Murphy). The coordination of EPIC is financially supported by International Agency for Research on Cancer (IARC) and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, which has additional infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, Institut National de la Sante et de la Recherche Medicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), German Institute of Human Nutrition PotsdamRehbruecke (DIfE), Federal Ministry of Education and Research (BMBF) (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (the Netherlands); Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII), Regional Governments of Andalucia, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology-ICO (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Ska degrees ne and V_asterbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A29017 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford) (United Kingdom)., Background: Observational studies have consistently reported that postmenopausal hormone therapy use is associated with lower colon cancer risk, but epidemiologic studies examining the associations between circulating concentrations of endogenous estrogens and colorectal cancer have reported inconsistent results. Methods: We investigated the associations between circulating concentrations of estrone, estradiol, free estradiol, testosterone, free testosterone, androstenedione, dehydroepiandrosterone (DHEA), progesterone, and sex hormone–binding globulin (SHBG) with colon cancer risk in a nested case-control study of 1028 postmenopausal European women (512 colon cancer cases, 516 matched controls) who were noncurrent users of exogenous hormones at blood collection. Multivariable conditional logistic regression models were used to compute odds ratios and 95% confidence intervals to evaluate the association between circulating sex hormones and colon cancer risk. We also conducted a dose-response meta-analysis of prospective studies of circulating estrone and estradiol with colorectal, colon, and rectal cancer risk in postmenopausal women. All statistical tests were 2-sided. Results: In the multivariable model, a nonstatistically significantly positive relationship was found between circulating estrone and colon cancer risk (odds ratio per log2 1-unit increment¼1.17 [95% confidence interval¼1.00 to 1.38]; odds ratioquartile4-quartile1¼1.33 [95% confidence interval¼0.89 to 1.97], Ptrend¼.20). Circulating concentrations of estradiol, free estradiol, testosterone, free testosterone, androstenedione, DHEA, progesterone, and SHBG were not associated with colon cancer risk. In the doseresponse meta-analysis, no clear evidence of associations were found between circulating estradiol and estrone concentrations with colorectal, colon, and rectal cancer risk. Conclusion: Our observational and meta-analysis results do not support an association between circulating concentrations of endogenous sex hormones and colon or rectal cancer in postmenopausal women., French National Cancer Institute (INCa SHSESP17) 2017-127, World Health Organization, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Danish Cancer Society, Ligue Contre le Cancer (France), Institut Gustave Roussy (France), Mutuelle Generale de l'Education Nationale (France), Institut National de la Sante et de la Recherche Medicale (Inserm), Deutsche Krebshilfe German Cancer Research Center (DKFZ) (Germany) German Institute of Human Nutrition Potsdam Rehbruecke (DIfE) (Germany), Federal Ministry of Education & Research (BMBF), Fondazione AIRC per la ricerca sul cancro, Compagnia di San Paolo Consiglio Nazionale delle Ricerche (CNR), Netherlands Government, World Cancer Research Fund International (WCRF), Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII) (Spain) Junta de Andalucia Regional Government of Asturias (Spain) Regional Government of Basque Country (Spain) Regional Government of Murcia (Spain) Regional Government of Navarra (Spain) Catalan Institute of Oncology-ICO (Spain), Swedish Cancer Society Swedish Research Council County Council of Skane (Sweden) County Council of Vasterbotten (Sweden), Cancer Research UK 14136 C8221/A29017 UK Research & Innovation (UKRI) Medical Research Council UK (MRC) 1000143 MR/M012190/1

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers, imputation of missing data, (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis, (iii) application of linear mixed models to remove unwanted variability, including samples’ originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through PC-PR2 analysis; (iii) application of linear mixed models to remove unwanted variability, including samples’ originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

We investigated longitudinal associations of moderate-to-vigorous physical activity (MVPA) and light-intensity physical activity (LPA) with plasma concentrations of 138 metabolites after colorectal cancer (CRC) treatment. Self-reported physical activity data and blood samples were obtained at 6 weeks, and 6, 12 and 24 months post-treatment in stage I-III CRC survivors (n = 252). Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQp180 kit). Linear mixed models were used to evaluate confounder-adjusted longitudinal associations. Inter-individual (between-participant differences) and intra-individual associations (within-participant changes over time) were assessed as percentage difference in metabolite concentration per 5 h/week of MVPA or LPA. At 6 weeks post-treatment, participants reported a median of 6.5 h/week of MVPA (interquartile range:2.3,13.5) and 7.5 h/week of LPA (2.0,15.8). Inter-individual associations were observed with more MVPA being related (FDR-adjusted q-value

Background While mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density. Methods A total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers’ Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors. Results Sphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components. Conclusions We identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.

Background The mechanisms underlying the obesity-cancer relationship are incompletely understood. This study aimed to characterise metabolic signatures of greater body size and to investigate their association with two obesity-related malignancies, endometrial and colorectal cancers, and with weight loss within the context of an intervention study. Methods Targeted mass spectrometry metabolomics data from 4326 participants enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort and 17 individuals from a single-arm pilot weight loss intervention (Intercept) were used in this analysis. Metabolic signatures of body size were first determined in discovery (N = 3029) and replication (N = 1297) sets among EPIC participants by testing the associations between 129 metabolites and body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) using linear regression models followed by partial least squares analyses. Conditional logistic regression models assessed the associations between the metabolic signatures with endometrial (N = 635 cases and 648 controls) and colorectal (N = 423 cases and 423 controls) cancer risk using nested case-control studies in EPIC. Pearson correlation between changes in the metabolic signatures and weight loss was tested among Intercept participants. Results After adjustment for multiple comparisons, greater BMI, WC, and WHR were associated with higher levels of valine, isoleucine, glutamate, PC aa C38:3, and PC aa C38:4 and with lower levels of asparagine, glutamine, glycine, serine, lysoPC C17:0, lysoPC C18:1, lysoPC C18:2, PC aa C42:0, PC ae C34:3, PC ae C40:5, and PC ae C42:5. The metabolic signature of BMI (OR1-sd 1.50, 95% CI 1.30–1.74), WC (OR1-sd 1.46, 95% CI 1.27–1.69), and WHR (OR1-sd 1.54, 95% CI 1.33–1.79) were each associated with endometrial cancer risk. Risk of colorectal cancer was positively associated with the metabolic signature of WHR (OR1-sd: 1.26, 95% CI 1.07–1.49). In the Intercept study, a positive correlation was observed between weight loss and changes in the metabolic signatures of BMI (r = 0.5, 95% CI 0.06–0.94, p = 0.03), WC (r = 0.5, 95% CI 0.05–0.94, p = 0.03), and WHR (r = 0.6, 95% CI 0.32–0.87, p = 0.01). Conclusions Obesity is associated with a distinct metabolic signature comprising changes in levels of specific amino acids and lipids which is positively associated with both colorectal and endometrial cancer and is potentially reversible following weight loss.

The identification of patients at high-risk for colorectal cancer (CRC) recurrence remains an unmet clinical need. The aim of this study was to investigate associations of metabolites with risk of recurrence in stage II/III CRC patients. A targeted metabolomics assay (128 metabolites measured) was performed on pre-surgery collected EDTA plasma samples from n = 440 newly diagnosed stage II/III CRC patients. Patients have been recruited from four prospective cohort studies as part of an international consortium: Metabolomic profiles throughout the continuum of CRC (MetaboCCC). Cox proportional hazard models were computed to investigate associations of metabolites with recurrence, adjusted for age, sex, tumor stage, tumor site, body mass index, and cohort, false discovery rate (FDR) was used to account for multiple testing. Sixty-nine patients (15%) had a recurrence after a median follow-up time of 20 months. We identified 13 metabolites that were nominally associated with a reduced risk of recurrence. None of the associations were statistically significant after controlling for multiple testing. Pathway topology analyses did not reveal statistically significant associations between recurrence and alterations in metabolic pathways (e.g., sphingolipid metabolism p = 0.04, pFDR = 1.00). To conclude, we did not observe statistically significant associations between metabolites and CRC recurrence using a well-established metabolomics assay. The observed results require follow-up in larger studies.