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04 December 2020 : Database Analysis  

Construction and Validation of a 7-Immune Gene Model for Prognostic Assessment of Esophageal Carcinoma

Haitao Chen1ABCEF, Jun Luo23BCD, Jianchun Guo23ADEF*

DOI: 10.12659/MSM.927392

Med Sci Monit 2020; 26:e927392

Abstract

BACKGROUND: We constructed a predictive risk model of esophageal carcinoma (EC) for prognostic prediction.

MATERIAL AND METHODS: Immune genes and the expression data were downloaded from the ImmPort database and The Cancer Genome Atlas database. Univariate analysis, Lasso regression, and multivariate analysis were applied to screen the ultimately included prognostic immune genes for the model based on the training cohort. Survival analysis and receiver operating characteristic (ROC) curve were applied to evaluate the model. The model was further validated in the testing and entire cohorts, and the clinical utility of the model and its ability to assess the subtypes of EC were evaluated in the entire cohort.

RESULTS: We detected 297 differentially expressed immune genes, including 241 upregulated genes and 56 downregulated genes in EC patients. Based on these genes, we developed a 7-immune gene model of EC, including HSPA6, S100A12, NOS2, DKK1, OSM, AR, and OXTR. The area under the curve (AUC) of the model at 1 year was 0.825. Similarly, the AUC values for the validating cohorts were 0.813 and 0.816, respectively. Pathological stage and risk score of the model were independent prognostic factors. This model was effective for both subtypes of EC.

CONCLUSIONS: We constructed a 7-gene model consisting of HSPA6, S100A12, NOS2, DKK1, OSM, AR, and OXTR. This risk model could be used for prognostic prediction of EC.

Keywords: Biological Markers, Prognosis

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Editorial

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Editorial: Current Status of Oral Antiviral Drug Treatments for SARS-CoV-2 Infection in Non-Hospitalized Patients

Dinah V. Parums
Science Editor, Medical Science Monitor, International Scientific Information, Inc., Melville, NY, USA

DOI: 10.12659/MSM.935952

Med Sci Monit 2022; 28:e935952

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750