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Integrative analysis of platelet-related genes for the prognosis of esophageal cancer

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BACKGROUND Every year, esophageal cancer is responsible for 509000 deaths and around 572000 new cases worldwide. Although esophageal cancer treatment options have advanced, patients still have a dismal 5-year survival… Click to show full abstract

BACKGROUND Every year, esophageal cancer is responsible for 509000 deaths and around 572000 new cases worldwide. Although esophageal cancer treatment options have advanced, patients still have a dismal 5-year survival rate. AIM To investigate the relationship between genes associated to platelets and the prognosis of esophageal cancer. METHODS We searched differentially expressed genes for changes between 151 tumor tissues and 653 normal, healthy tissues using the “limma” package. To develop a prediction model of platelet-related genes, a univariate Cox regression analysis and least absolute shrinkage and selection operator Cox regression analysis were carried out. Based on a median risk score, patients were divided into high-risk and low-risk categories. A nomogram was created to predict the 1-, 2-, and 3-year overall survival (OS) of esophageal cancer patients using four platelet-related gene signatures, TNM stages, and pathological type. Additionally, the concordance index, receiver operating characteristic curve, and calibration curve were used to validate the nomogram. RESULTS The prognosis of esophageal cancer was associated to APOOL, EP300, PLA2G6, and VAMP7 according to univariate Cox regression analysis and least absolute shrinkage and selection operator regression analysis. Patients with esophageal cancer at high risk had substantially shorter OS than those with cancer at low risk, according to a Kaplan-Meier analysis (P < 0.05). TNM stage (hazard ratio: 2.187, 95% confidence interval: 1.242-3.852, P = 0.007) in both univariate and multivariate Cox regression and risk score were independently correlated with OS (hazard ratio: 2.451, 95% confidence interval: 1.599-3.756, P < 0.001). CONCLUSION A survival risk score model and independent prognostic variables for esophageal cancer have been developed using APOOL, EP300, PLA2G6, and VAMP7. OS for esophageal cancer might be predicted using the nomogram based on TNM stage, pathological type, and risk score. The nomogram demonstrated strong predictive ability, as shown by the concordance index, receiver operating characteristic curve, and calibration curve.

Keywords: esophageal cancer; analysis; risk; prognosis esophageal; cancer

Journal Title: World Journal of Clinical Cases
Year Published: 2022

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