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Background & Aims: Human studies examining associations between circulating levels of insulin-like growth factor 1 (IGF1) and insulin-like growth factor binding protein 3 (IGFBP3) and colorectal cancer risk have reported inconsistent results. We conducted complementary serologic and Mendelian randomization (MR) analyses to determine whether alterations in circulating levels of IGF1 or IGFBP3 are associated with colorectal cancer development.
Methods: Serum levels of IGF1 were measured in blood samples collected from 397,380 participants from the UK Biobank, from 2006 through 2010. Incident cancer cases and cancer cases recorded first in death certificates were identified through linkage to national cancer and death registries. Complete follow-up was available through March 31, 2016. For the MR analyses, we identified genetic variants associated with circulating levels of IGF1 and IGFBP3. The association of these genetic variants with colorectal cancer was examined with 2-sample MR methods using genome-wide association study consortia data (52,865 cases with colorectal cancer and 46,287 individuals without [controls])
Results: After a median follow-up period of 7.1 years, 2665 cases of colorectal cancer were recorded. In a multivariable-adjusted model, circulating level of IGF1 associated with colorectal cancer risk (hazard ratio per 1 standard deviation increment of IGF1, 1.11; 95% confidence interval [CI] 1.05–1.17). Similar associations were found by sex, follow-up time, and tumor subsite. In the MR analyses, a 1 standard deviation increment in IGF1 level, predicted based on genetic factors, was associated with a higher risk of colorectal cancer risk (odds ratio 1.08; 95% CI 1.03–1.12; P = 3.3 × 10–4). Level of IGFBP3, predicted based on genetic factors, was associated with colorectal cancer risk (odds ratio per 1 standard deviation increment, 1.12; 95% CI 1.06–1.18; P = 4.2 × 10–5). Colorectal cancer risk was associated with only 1 variant in the IGFBP3 gene region (rs11977526), which also associated with anthropometric traits and circulating level of IGF2.
Conclusions: In an analysis of blood samples from almost 400,000 participants in the UK Biobank, we found an association between circulating level of IGF1 and colorectal cancer. Using genetic data from 52,865 cases with colorectal cancer and 46,287 controls, a higher level of IGF1, determined by genetic factors, was associated with colorectal cancer. Further studies are needed to determine how this signaling pathway might contribute to colorectal carcinogenesis.
A major gap impeding development of new treatments for cancer-related fatigue is an inadequate understanding of the complex biological, clinical, demographic, and lifestyle mechanisms underlying fatigue. In this paper, we describe a new application of a comprehensive model for cancer-related fatigue: the predisposing, precipitating, and perpetuating (3P) factors model. This model framework outlined herein, which incorporates the emerging field of metabolomics, may help to frame a more in-depth analysis of the etiology of cancer-related fatigue as well as a broader and more personalized set of approaches to the clinical treatment of fatigue in oncology care. Included within this review paper is an in-depth description of the proposed biological mechanisms of cancer-related fatigue, as well as a presentation of the 3P model’s application to this phenomenon. We conclude that a clinical focus on organization risk stratification and treatment around the 3P model may be warranted, and future research may benefit from expanding the 3P model to understand fatigue not only in oncology, but also across a variety of chronic conditions.
Cancer-related fatigue (CRF) is considered one of the most frequent and distressing symptoms for cancer survivors. Despite its high prevalence, factors that predispose, precipitate, and perpetuate CRF are poorly understood. Emerging research focuses on cancer and treatment-related nutritional complications, changes in body composition, and nutritional deficiencies that can compound CRF. Nutritional metabolomics, the novel study of diet-related metabolites in cells, tissues, and biofluids, offers a promising tool to further address these research gaps. In this position paper, we examine CRF risk factors, summarize metabolomics studies of CRF, outline dietary recommendations for the prevention and management of CRF in cancer survivorship, and identify knowledge gaps and challenges in applying nutritional metabolomics to understand dietary contributions to CRF over the cancer survivorship trajectory.
Background: Folates, including folic acid, may play a dual role in colorectal cancer development. Folate is suggested to be protective in early carcinogenesis but could accelerate growth of premalignant lesions or micrometastases. Whether circulating concentrations of folate and folic acid, measured around time of diagnosis, are associated with recurrence and survival in colorectal cancer patients is largely unknown.
Methods: Circulating concentrations of folate, folic acid, and folate catabolites p-aminobenzoylglutamate and p-acetamidobenzoylglutamate were measured by liquid chromatography-tandem mass spectrometry at diagnosis in 2024 stage I-III colorectal cancer patients from European and US patient cohort studies. Multivariable-adjusted Cox proportional hazard models were used to assess associations between folate, folic acid, and folate catabolites concentrations with recurrence, overall survival, and disease-free survival.
Results: No statistically significant associations were observed between folate, p-aminobenzoylglutamate, and p-acetamidobenzoylglutamate concentrations and recurrence, overall survival, and disease-free survival, with hazard ratios ranging from 0.92 to 1.16. The detection of folic acid in the circulation (yes or no) was not associated with any outcome. However, among patients with detectable folic acid concentrations (n = 296), a higher risk of recurrence was observed for each twofold increase in folic acid (hazard ratio = 1.31, 95% confidence interval = 1.02 to 1.58). No statistically significant associations were found between folic acid concentrations and overall and disease-free survival.
Conclusions: Circulating folate and folate catabolite concentrations at colorectal cancer diagnosis were not associated with recurrence and survival. However, caution is warranted for high blood concentrations of folic acid because they may increase the risk of colorectal cancer recurrence.
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.
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 (pFDR < 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 (pFDR < 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.
Demographic, lifestyle and biospecimen-related factors at the time of blood collection can influence metabolite levels in epidemiological studies. Identifying the major influences on metabolite concentrations is critical to designing appropriate sample collection protocols and considering covariate adjustment in metabolomics analyses. We examined the association of age, sex, and other short-term pre-blood collection factors (time of day, season, fasting duration, physical activity, NSAID use, smoking and alcohol consumption in the days prior to collection) with 133 targeted plasma metabolites (acylcarnitines, amino acids, biogenic amines, sphingolipids, glycerophospholipids, and hexoses) among 108 individuals that reported exposures within 48 h before collection. The differences in mean metabolite concentrations were assessed between groups based on pre-collection factors using two-sided t-tests and ANOVA with FDR correction. Percent differences in metabolite concentrations were negligible across season, time of day of collection, fasting status or lifestyle behaviors at the time of collection, including physical activity or the use of tobacco, alcohol or NSAIDs. The metabolites differed in concentration between the age and sex categories for 21.8% and 14.3% metabolites, respectively. In conclusion, extrinsic factors in the short period prior to collection were not meaningfully associated with concentrations of selected endogenous metabolites in a cross-sectional sample, though metabolite concentrations differed by age and sex. Larger studies with more coverage of the human metabolome are warranted.
Background: The aim of this study is to review accelerometer wear methods and correlations between accelerometry and physical activity questionnaire data, depending on participant characteristics.
Methods: We included 57 articles about physical activity measurement by accelerometry and questionnaires. Criteria were to have at least 100 participants of at least 18 years of age with manuscripts available in English. Accelerometer wear methods were compared. Spearman and Pearson correlation coefficients between questionnaires and accelerometers and differences between genders, age categories, and body mass index (BMI) categories were assessed.
Results: In most investigations, requested wear time was seven days during waking hours and devices were mostly attached on hips with waist belts. A minimum of four valid days with wear time of at least ten hours per day was required in most studies. Correlations (r = Pearson, ρ = Spearman) of total questionnaire scores against accelerometer measures across individual studies ranged from r = 0.08 to ρ = 0.58 (P < 0.001) for men and from r = −0.02 to r = 0.49 (P < 0.01) for women. Correlations for total physical activity among participants with ages ≤65 ranged from r = 0.04 to ρ = 0.47 (P < 0.001) and from r = 0.16 (P = 0.02) to r = 0.53 (P < 0.01) among the elderly (≥65 years). Few studies investigated stratification by BMI, with varying cut points and inconsistent results.
Conclusion: Accelerometers appear to provide slightly more consistent results in relation to self-reported physical activity among men. Nevertheless, due to overall limited consistency, different aspects measured by each method, and differences in the dimensions studied, it is advised that studies use both questionnaires and accelerometers to gain the most complete physical activity information.
Background: To assess the predictive value of early metabolic response (ΔSUV) after short-term treatment with first-line cetuximab in patients (pts) with RAS-wt metastatic colorectal cancer (mCRC).
Methods: In this prospective phase II study, RAS-wt mCRC pts received a single-agent cetuximab run-in therapy of 2 weeks. ΔSUV was assessed with FDG-PET/CT on days 0 and 14. Early clinical response (ECR) was evaluated with CT on day 56 after treatment with FOLFIRI-cetuximab. Primary endpoint was the predictive significance of ΔSUV for ECR. Secondary endpoints were PFS (progression free survival), OS and the influence of ΔSUV on survival.
Results: Forty pts were enroled and 33 pts were evaluable for the primary endpoint. The CT response rate was 57.6%. For responders, ΔSUV was significantly higher (p = 0.0092). A significant association of ΔSUV with ECR was found (p = 0.02). Median PFS was 11.7 months and median OS was 33.5 months with a 1-year survival rate of 87.9%. ΔSUV was found to significantly impact the hazard for OS (p = 0.045).
Conclusions: We demonstrate that cetuximab induces metabolic responses in mCRC pts. The study endpoint was met with the ΔSUV discriminating between responders and non-responders. However, these data should be validated in larger patient cohorts.
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–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–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.