BackgroundEsophageal squamous cell carcinoma (ESCC) has a high incidence rate and poor prognosis. In this study, we aimed to develop a predictive model to estimate the individualized 5-year absolute risk for ESCC in Chinese populations living in the high-risk areas of China.MethodsWe developed a risk-predicting model based on the epidemiologic data from a population-based case-control study including 244 newly diagnosed ESCC patients and 1,220 healthy controls. Initially, we included easy-to-obtain risk factors to construct the model using the multivariable logistic regression analysis. The area under the ROC curves (AUC) with cross-validation methods was used to evaluate the performance of the model. Combined with local age- and sex-specific ESCC incidence and mortality rates, the model was then used to estimate the absolute risk of developing ESCC within 5 years.ResultsA relative risk model was established that included eight factors: age, sex, tobacco smoking, alcohol drinking, education, and dietary habits (intake of hot food, intake of pickled/salted food, and intake of fresh fruit). The relative risk model had good discrimination [AUC, 0.785; 95% confidence interval (CI), 0.749–0.821]. The estimated 5-year absolute risk of ESCC for individuals varied widely, from 0.0003% to 19.72% in the studied population, depending on the exposure to risk factors.ConclusionsOur model based on readily identifiable risk factors showed good discriminative accuracy and strong robustness. And it could be applied to identify individuals with a higher risk of developing ESCC in the Chinese population, who might benefit from further targeted screening to prevent esophageal cancer.

Background Despite research efforts, the causative factors that contribute to esophageal squamous cell carcinoma (ESCC) in high-risk areas have not yet been understood. In this study, we, therefore, aimed to describe the risk factors associated with ESCC and its precursor lesions. Methods We performed an endoscopic examination of 44,857 individuals aged 40–69 years from five high incidence regions of China in 2017–2018. Participants were classified as 4 groups of normal control, esophagitis, low-grade intraepithelial neoplasia (LGIN) and high-grade intraepithelial neoplasia/esophageal squamous cell carcinoma (HGIN/ESCC) using an unconditional logistic regression determine risk factors. Results We identified 4890 esophagitis, 1874 LGIN and 437 HGIN/ESCC cases. Crude odds ratios (ORs) and adjusted odds ratios were calculated using unconditional logistic regression. Drinking well and surface water, salty diet, and positive family history of cancer were the common risk factors for esophagitis, LGIN and HGIN/ESCC. History of chronic hepatitis/cirrhosis was the greatest risk factor of esophagitis (adjusted OR 2.96, 95%CI 2.52–3.47) and HGIN/ESCC (adjusted OR 1.91, 95%CI 1.03–3.22). Pesticide exposure (adjusted OR 1.20, 95%CI 1.05–1.37) was essential risk factor of LGIN. Conclusions Among individuals aged 40–69 years in high incidence regions of upper gastrointestinal cancer, the results provided important epidemiological evidence for the prevention of different precancerous lesions of ESCC.

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BackgroundCircular RNAs (circRNAs) are described as endogenous non-coding RNAs that have been reported to play important roles in the development and progression of cancers. This study aimed to reveal the circRNA-related regulatory mechanism in esophageal squamous cell carcinoma (ESCC).MethodsA genome-wide circRNA microarray assay was performed to profile the expression of circRNAs in the blood of preoperative ESCC patients and healthy controls. A systematic method of data mining was performed to identify the differentially expressed miRNAs (DEmiRs) and differentially expressed genes (DEGs) based on the metaMA and RankProd analysis. Bioinformatics analyses and multiple tools were employed to construct the potential circRNA–miRNA–mRNA regulatory network.ResultsThirty-three differentially expressed circRNAs were identified in the ESCC blood, including 31 downregulated and two upregulated circRNAs in the blood of ESCC patients compared with the healthy controls. Twenty-three DEmiRs and 2,220 DEGs were obtained by the integration of microarray datasets. An ESCC-associated circRNA–miRNA–mRNA network was constructed based on 31 circRNAs, 3 DEmiRs, and 190 DEGs. Enrichment analyses indicated that the DEGs were associated with a series of biological processes and cancer-related pathways. The protein–protein interaction (PPI) network was generated by the 190 DEGs, with 10 hub genes verified in the network. Subsequently, a sub-network was established for ESCC, which included 29 circRNAs, 2 miRNAs, and 10 hub genes.ConclusionOur study provided a novel clue to help understand the circRNA–miRNA–mRNA regulatory mechanism, highlighting the potential roles of circRNAs in the pathogenesis and development of ESCC.

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