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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 (ORs) and 95% confidence intervals (CIs) for colon cancer risk. Tryptophan was inversely associated with colon cancer risk in ColoCare (OR per 1-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 vs nondetectable 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., (© 2021 UICC.)

Colorectal cancer is the second most common cause of cancer-related death globally, with marked differences in prognosis by disease stage at diagnosis. We studied circulating metabolites in relation to disease stage to improve the understanding of metabolic pathways related to colorectal cancer progression. We investigated plasma concentrations of 130 metabolites among 744 Stages I-IV colorectal cancer patients from ongoing cohort studies. Plasma samples, collected at diagnosis, were analyzed with liquid chromatography-mass spectrometry using the Biocrates AbsoluteIDQ™ p180 kit. We assessed associations between metabolite concentrations and stage using multinomial and multivariable logistic regression models. Analyses were adjusted for potential confounders as well as multiple testing using false discovery rate (FDR) correction. Patients presented with 23, 28, 39 and 10% of Stages I-IV disease, respectively. Concentrations of sphingomyelin C26:0 were lower in Stage III patients compared to Stage I patients (p FDR  < 0.05). Concentrations of sphingomyelin C18:0 and phosphatidylcholine (diacyl) C32:0 were statistically significantly higher, while citrulline, histidine, phosphatidylcholine (diacyl) C34:4, phosphatidylcholine (acyl-alkyl) C40:1 and lysophosphatidylcholines (acyl) C16:0 and C17:0 concentrations were lower in Stage IV compared to Stage I patients (p FDR  < 0.05). Our results suggest that metabolic pathways involving among others citrulline and histidine, implicated previously in colorectal cancer development, may also be linked to colorectal cancer progression., (© 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Colorectal cancer is known to arise from multiple tumorigenic pathways; however, the underlying mechanisms remain not completely understood. Metabolomics is becoming an increasingly popular tool in assessing biological processes. Previous metabolomics research focusing on colorectal cancer is limited by sample size and did not replicate findings in independent study populations to verify robustness of reported findings. Here, we performed a ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) screening on EDTA plasma from 268 colorectal cancer patients and 353 controls using independent discovery and replication sets from two European cohorts (ColoCare Study: n = 180 patients/n = 153 controls; the Colorectal Cancer Study of Austria (CORSA) n = 88 patients/n = 200 controls), aiming to identify circulating plasma metabolites associated with colorectal cancer and to improve knowledge regarding colorectal cancer etiology. Multiple logistic regression models were used to test the association between disease state and metabolic features. Statistically significant associated features in the discovery set were taken forward and tested in the replication set to assure robustness of our findings. All models were adjusted for sex, age, BMI and smoking status and corrected for multiple testing using False Discovery Rate. Demographic and clinical data were abstracted from questionnaires and medical records., (© 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)