A novel molecular subtyping based on multi-omics analysis for prognosis predicting in colorectal melanoma: A 16-year prospective multicentric study.

Colorectal melanoma (CRM) is a rare malignant tumor with severe complications, and there is currently a lack of systematic research. We conducted a study that combined proteomics and mutation data of CRM from a cohort of three centers over a 16-years period (2005-2021). The patients were divided into a training set consisting of two centers and a testing set comprising the other center. Unsupervised clustering was conducted on the training set to form two molecular subtypes for clinical characterization and functional analysis. The testing set was used to validate the survival differences between the two subtypes. The comprehensive analysis identified two subtypes of CRM: immune exhausted C1 cluster and DNA repair C2 cluster. The former subtype exhibited characteristics of metabolic disturbance, immune suppression, and poor prognosis, along with APC mutations. A machine learning algorithm named Support Vector Machine (SVM) was applied to predict the classification of CRM patients based on protein expression in the external testing cohort. Two subtypes of primary CRM with clinical and proteomic characteristics provides a reference for subsequent diagnosis and treatments.

Diet-Wide Association, Genetic Susceptibility and Colorectal Cancer Risk: A Prospective Cohort Study.

BACKGROUND: Both genetic and dietary factors play significant roles in the etiology of colorectal cancer (CRC). To evaluate the relationship between certain food exposures and the risk of CRC, we carried out a large-scale association analysis in the UK Biobank. METHODS: The associations of 139 foods and nutrients' intake with CRC risk were assessed among 118,210 participants. A polygenic risk score (PRS) of CRC was created to explore any interaction between dietary factors and genetic susceptibility in CRC risk. The hazard ratio (HR) and 95% confidence interval (CI) of CRC risk linked to dietary variables and PRS were estimated using Cox regression models. Multiple comparisons were corrected using the error discovery rate (FDR). RESULTS: During a mean follow-up of 12.8 years, 1466 incidents of CRC were identified. In the UK Biobank, alcohol and white bread were associated with increased CRC risk, and their HRs were 1.08 (95% CI: 1.03-1.14; FDRP = 0.028) and 1.10 (95% CI: 1.05-1.16; FDRP = 0.003), whereas dietary fiber, calcium, magnesium, phosphorus, and manganese intakes were inversely associated. We found no evidence of any PRS-nutrient interaction relationship in relation to CRC risk. CONCLUSIONS: Our results show that higher intakes of alcohol and white bread are associated with increased CRC risk, whilst dietary fiber, calcium, magnesium, phosphorus, and manganese are inversely associated.