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.
ABSTRACT
BACKGROUND: Currently, there are many therapeutic methods for lung adenocarcinoma (LUAD), but the 5-year survival rate is still only 15% at later stages. Epithelial- mesenchymal transition (EMT) has been shown to be closely associated with local dissemination and subsequent metastasis of solid tumors. However, the role of EMT in the occurrence and development of LUAD remains unclear. AIM: To further elucidate the value of EMT-related genes in LUAD prognosis. METHODS: Univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were applied to establish and validate a new EMT-related gene signature for predicting LUAD prognosis. The risk model was evaluated by Kaplan-Meier survival analysis, principal component analysis, and functional enrichment analysis and was used for nomogram construction. The potential structures of drugs to which LUAD is sensitive were discussed with respect to EMT-related genes in this model. RESULTS: Thirty-three differentially expressed genes related to EMT were found to be highly associated with overall survival (OS) by using univariate Cox regression analysis (log2FC ≥ 1, false discovery rate < 0.001). A prognostic signature of 7 EMT-associated genes was developed to divide patients into two risk groups by high or low risk scores. Kaplan-Meier survival analysis showed that the OS of patients in the high-risk group was significantly poorer than that of patients in the low-risk group (P < 0.05). Multivariate Cox regression analysis showed that the risk score was an independent risk factor for OS (HR > 1, P < 0.05). The results of receiver operator characteristic curve analysis suggested that the 7-gene signature had a perfect ability to predict prognosis (all area under the curves > 0.5). CONCLUSION: The EMT-associated gene signature classifier could be used as a feasible indicator for predicting OS.
