Colorectal polyps are precancerous diseases of colorectal cancer. Early detection and resection of colorectal polyps can effectively reduce the mortality of colorectal cancer. Endoscopic mucosal resection (EMR) is a common polypectomy procedure in clinical practice, but it has a high postoperative recurrence rate. Currently, there is no predictive model for the recurrence of colorectal polyps after EMR.

To construct and validate a machine learning (ML) model for predicting the risk of colorectal polyp recurrence one year after EMR.

This study retrospectively collected data from 1694 patients at three medical centers in Xuzhou. Additionally, a total of 166 patients were collected to form a prospective validation set. Feature variable screening was conducted using univariate and multivariate logistic regression analyses, and five ML algorithms were used to construct the predictive models. The optimal models were evaluated based on different performance metrics. Decision curve analysis (DCA) and SHapley Additive exPlanation (SHAP) analysis were performed to assess clinical applicability and predictor importance.

Multivariate logistic regression analysis identified 8 independent risk factors for colorectal polyp recurrence one year after EMR (P < 0.05). Among the models, eXtreme Gradient Boosting (XGBoost) demonstrated the highest area under the curve (AUC) in the training set, internal validation set, and prospective validation set, with AUCs of 0.909 (95%CI: 0.89-0.92), 0.921 (95%CI: 0.90-0.94), and 0.963 (95%CI: 0.94-0.99), respectively. DCA indicated favorable clinical utility for the XGBoost model. SHAP analysis identified smoking history, family history, and age as the top three most important predictors in the model.

The XGBoost model has the best predictive performance and can assist clinicians in providing individualized colonoscopy follow-up recommendations.

Colorectal cancer (CRC) originates from pre-existing polyps in the colon. The development of different subtypes of CRC is influenced by various genetic and epigenetic characteristics. CpG island methylator phenotype (CIMP) is found in about 15-20% of sporadic CRCs and is associated with hypermethylation of certain gene promoters. This study aims to find prognostic genes and compare their expression and methylation status as potential biomarkers in patients with serrated sessile adenomas/polyps (SSAP) and CRC, in order to evaluate which, one is a better predictor of disease.

This study employed a multi-phase approach to investigate genes associated with CRC and SSAP. Initially, two gene expression datasets were analyzed using R and Limma package to identify differentially expressed genes (DEGs). Venn diagram analysis further refined the selection, revealing four genes from the Weissenberg panel with significant changes. These genes, underwent thorough in silico evaluations. Once confirmed, they proceeded to wet lab experimentation, focusing on expression and methylation status. This comprehensive methodology ensured a robust examination of the genes involved in CRC and SSAP.

This study identified cancer-specific genes, with 8,351 and 1,769 genes specifically down-regulated in SSAP and CRC tissues, respectively. The down-regulated genes were associated with cell adhesion, negative regulation of cell proliferation, and drug response. Four highly downregulated genes in the Weissenberg panel, including CACNA1G, IGF2, MLH1, and SOCS1. In vitro analysis showed that they are hypermethylated in both SSAP and CRC samples while their expressions decreased only in CRC samples.

This suggests that the decrease in gene expression could help determine whether a polyp will become cancerous. Using both methylation status and gene expression status of genes in the Weissenberg panel in prognostic tests may lead to better prognoses for patients.

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

Colorectal cancer syndrome has been one of the greatest concerns in the world. Although several epidemiological studies have shown that hepatic low lipoprotein lipase (LPL) mRNA expression may be associated with dyslipidemia and tumor progression, it is still not known whether the liver plays an essential role in hyperlipidemia of Apc^Min/+ mice.

We measured the expression of metabolic enzymes that involved fatty acid uptake, de novo lipogenesis (DNL), β-oxidation and investigated hepatic triglyceride production in the liver of wild-type and Apc^Min/+ mice.

We found that hepatic fatty acid uptake and DNL decreased, but there was no significant difference in fatty acid β-oxidation. Interestingly, the production of hepatic very low-density lipoprotein-triglyceride (VLDL-TG) decreased at 20 weeks of age, but marked steatosis was observed in the livers of the Apc^Min/+ mouse. To further explore hypertriglyceridemia, we assessed the function of hepatic glycosylphosphatidylinositol-anchored high-density lipoprotein binding protein 1 (GPIHBP1) for the first time. GPIHBP1 is governed by the transcription factor octamer-binding transcription factor-1 (Oct-1) which are involved in the nuclear factor-κB (NF-κB) signaling pathway in the liver of Apc^Min/+ mice. Importantly, it was also confirmed that sn50 (100 μg/mL, an inhibitor of the NF-κB) reversed the tumor necrosis factor α (TNFα)-induced Oct-1 and GPIHBP1 reduction in HepG2 cells.

Altogether, these findings highlighted a novel role of GPIHBP1 that might be responsible for hypertriglyceridemia in Apc^Min/+ mice. Hypertriglyceridemia in these mice may be associated with their hepatic lipid metabolism development.