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Institute
Early-onset colorectal cancer has been on the rise in Western populations. Here, we compare patient characteristics between those with early- (<50 years) vs. late-onset (≥50 years) disease in a large multinational cohort of colorectal cancer patients (n = 2193). We calculated descriptive statistics and assessed associations of clinicodemographic factors with age of onset using mutually-adjusted logistic regression models. Patients were on average 60 years old, with BMI of 29 kg/m2, 52% colon cancers, 21% early-onset, and presented with stage II or III (60%) disease. Early-onset patients presented with more advanced disease (stages III–IV: 63% vs. 51%, respectively), and received more neo and adjuvant treatment compared to late-onset patients, after controlling for stage (odds ratio (OR) (95% confidence interval (CI)) = 2.30 (1.82–3.83) and 2.00 (1.43–2.81), respectively). Early-onset rectal cancer patients across all stages more commonly received neoadjuvant treatment, even when not indicated as the standard of care, e.g., during stage I disease. The odds of early-onset disease were higher among never smokers and lower among overweight patients (1.55 (1.21–1.98) and 0.56 (0.41–0.76), respectively). Patients with early-onset colorectal cancer were more likely to be diagnosed with advanced stage disease, to have received systemic treatments regardless of stage at diagnosis, and were less likely to be ever smokers or overweight.
Alterations within the tryptophan–kynurenine metabolic pathway have been linked to the etiology of colorectal cancer (CRC), but the relevance of this pathway for prognostic outcomes in CRC patients needs further elucidation. Therefore, we investigated associations between circulating concentrations of tryptophan–kynurenine pathway metabolites and all‐cause mortality among CRC patients. This study utilizes data from 2102 stage I–III CRC patients participating in six prospective cohorts involved in the international FOCUS Consortium. Preoperative circulating concentrations of tryptophan, kynurenine, kynurenic acid (KA), 3‐hydroxykynurenine (HK), xanthurenic acid (XA), 3‐hydroxyanthranilic acid (HAA), anthranilic acid (AA), picolinic acid (PA), and quinolinic acid (QA) were measured by liquid chromatography–tandem mass spectrometry. Using Cox proportional hazards regression, we examined associations of above‐mentioned metabolites with all‐cause mortality, adjusted for potential confounders. During a median follow‐up of 3.2 years (interquartile range: 2.2–4.9), 290 patients (13.8%) deceased. Higher blood concentrations of tryptophan, XA, and PA were associated with a lower risk of all‐cause mortality (per doubling in concentrations: tryptophan: HR = 0.56; 95%CI:0.41,0.76, XA: HR = 0.74; 95%CI:0.64,0.85, PA: HR = 0.76; 95%CI:0.64,0.92), while higher concentrations of HK and QA were associated with an increased risk of death (per doubling in concentrations: HK: HR = 1.80; 95%CI:1.47,2.21, QA: HR = 1.31; 95%CI:1.05,1.63). A higher kynurenine‐to‐tryptophan ratio, a marker of cell‐mediated immune activation, was associated with an increased risk of death (per doubling: HR = 2.07; 95%CI:1.52,2.83). In conclusion, tryptophan–kynurenine pathway metabolites may be prognostic markers of survival in CRC patients.
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.
Background: Physical activity and BMI have been individually associated with cancer survivorship but have not yet been studied in combinations in colorectal cancer patients. Here, we investigate individual and combined associations of physical activity and BMI groups with colorectal cancer survival outcomes.
Methods: Self-reported physical activity levels (MET hrs/wk) were assessed using an adapted version of the International Physical Activity Questionnaire (IPAQ) at baseline in 931 patients with stage I-III colorectal cancer and classified into ‘highly active’ and ’not-highly active’ (≥/ < 18 MET hrs/wk). BMI (kg/m2) was categorized into ‘normal weight’, ‘overweight’, and ‘obese’. Patients were further classified into combined physical activity and BMI groups. Cox-proportional hazard models with Firth correction were computed to assess associations [hazard ratio (HR), 95% profile HR likelihood confidence interval (95% CI) between individual and combined physical activity and BMI groups with overall and disease-free survival in colorectal cancer patients.
Results: ‘Not-highly active’ compared to ‘highly active’ and ‘overweight’/‘obese’ compared to ‘normal weight’ patients had a 40–50% increased risk of death or recurrence (HR: 1.41 (95% CI: 0.99–2.06), p=0.03; HR: 1.49 (95% CI: 1.02–2.21) and HR: 1.51 (95% CI: 1.02–2.26), p= 0.04, respectively). ‘Not-highly active’ patients had worse disease-free survival outcomes, regardless of their BMI, compared to ‘highly active/normal weight’ patients. ‘Not-highly active/obese’ patients had a 3.66 times increased risk of death or recurrence compared to ‘highly active/normal weight’ patients (HR: 4.66 (95% CI: 1.75–9.10), p=0.002). Lower activity thresholds yielded smaller effect sizes.
Conclusion: Physical activity and BMI were individually associated with disease-free survival among colorectal cancer patients. Physical activity seems to improve survival outcomes in patients regardless of their BMI.
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: Cachexia accounts for about 20% of all cancer‐related deaths and indicates poor prognosis. The impact of Fusobacterium nucleatum (Fn), a microbial risk factor for colorectal cancer (CRC), on the development of cachexia in CRC has not been established.
Methods: We evaluated the association between Fn abundance in pre‐surgical stool samples and onset of cachexia at 6 months post‐surgery in n = 87 patients with stages I–III CRC in the ColoCare Study.
Results: High fecal Fn abundance compared to negative/low fecal Fn abundance was associated with 4‐fold increased risk of cachexia onset at 6 months post‐surgery (OR = 4.82, 95% CI = 1.15, 20.10, p = 0.03).
Conclusion: Our findings suggest that high fecal Fn abundance was associated with an increased risk of cachexia at 6 months post‐surgery in CRC patients. This is the first study to link Fn abundance with cachexia in CRC patients, offering novel insights into biological mechanisms and potential management of cancer cachexia. Due to the small sample size, our results should be interpreted with caution. Future studies with larger sample sizes are needed to validate these findings.
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.