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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.

Apparent heterogeneity in diagnostic performance of quantitative FITs can be overcome to a large extent by adjusting thresholds to yield defined levels of specificity or positivity rates. Rather than simply using thresholds recommended by the manufacturer, screening programs should choose thresholds based on intended levels of specificity and manageable positivity rates.

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.

Purpose While obesity is considered a prognostic factor in colorectal cancer (CRC), there is increasing evidence that not only body-mass-index (BMI) matters, but specifically abdominal fat distribution. As part of the ColoCare study, this study measured the distribution of adipose tissue compartments in CRC patients and aimed to identify the body metric that best correlates with these measurements as a useful proxy for adipose tissue distribution. Materials and methods In 120 newly-diagnosed CRC patients who underwent multi-detector-CT, densitometric quantification of total(TFA), visceral(VFA), intraperitoneal(IFA), retroperitoneal(RFA) and subcutaneous fat area(SFA), M.erector spinae and psoas was performed to test the association with gender, age, tumor stage, metabolic equivalents, BMI, Waist-to-Height (WHtR) and Waist to-Hip ratio (WHR). Results VFA was 28.8% higher in men (pVFA<0.0001) and 30.5% higher in patients older than 61 years (pVFA<0.0001). WHtR correlated best with all adipose tissue compartments (rVFA=0.69, rTFA=0.84, p<0.0001) and visceral-to-subcutaneous-fat-ratio(VFR, rVFR=0.22, p=<0.05). Patients with tumor stages III/IV showed significantly lower overall adipose tissue than I/II. Increased M. erector spinae mass was inversely correlated with all compartments. Conclusion Densitometric quantification on CT is a highly reproducible and reliable method to show fat distribution across adipose tissue compartments. This distribution might be best reflected by WHtR, rather than BMI or WHR.

Introduction 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 describe changes in the metabolome in the longer clinical follow-up and describe initial predictors as candidate markers with possibly prognostic significance Methods In total, 199 urine samples from CRC patients pre-surgery (n=97), 1–8 days post-surgery (n=12) and then after 6 and 12 months (n=52 and 38, respectively) 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. Results 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 CRC patients prior to surgery from those at any post-surgery timepoint using a multivariate model containing 20 marker metabolites (AUCROC=0.89; 95% CI:0.84–0.95). Conclusion To the best of our knowledge, 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 pin point metabolites which may serve as candidates for prognostic biomarkers of CRC.

Fecal immunochemical tests (FITs) for hemoglobin (Hb) are increasingly used for colorectal cancer (CRC) screening. We aimed to review, summarize and compare reported diagnostic performance of various FITs. PubMed and Web of Science were searched from inception to July 24, 2017. Data on diagnostic performance of quantitative FITs, conducted in colonoscopy-controlled average-risk screening populations, were extracted. Summary receiver operating characteristic (ROC) curves were plotted and correlations between thresholds, positivity rates (PRs), sensitivities and specificities were assessed. Seven test brands were investigated across 22 studies. Although reported sensitivities for CRC, advanced adenoma (AA) and any advanced neoplasm (AN) varied widely (ranges: 25-100%, 6-44% and 9-60%, respectively), with specificities for AN ranging from 82% to 99%, the estimates were very close to the respective summary ROC curves whose areas under the curve (95% CI) were 0.905 (0.88-0.94), 0.683 (0.67-0.70) and 0.710 (0.70-0.72) for CRC, AA and AN, respectively. The seemingly large heterogeneity essentially reflected variations in test thresholds (range: 2-82 µg Hb/g feces) and showed moderate correlations with sensitivity (r = -0.49) and specificity (r = 0.60) for AN. By contrast, observed PRs (range: 1-21%) almost perfectly correlated with sensitivity (r = 0.84) and specificity (r = -0.94) for AN. The apparent large heterogeneity in diagnostic performance between various FITs can be almost completely overcome by appropriate threshold adjustments. Instead of simply applying the threshold recommended by the manufacturer, screening programs should adjust the threshold to yield a desired PR which is a very good proxy indicator for the specificity and the subsequent colonoscopy workload.