Abstract
Background: The aim of this study was to identify prognostic markers for esophageal squamous cell carcinoma (ESCC) and build an effective prognostic nomogram for ESCC. Methods: A total of 365 patients with ESCC from three medical centers were divided into four cohorts. In the discovery phase of the study, we analyzed transcriptional data from 179 cancer tissue samples and identified nine marker genes using edgeR and rbsurv packages. In the training phase, penalized Cox regression was used to select the best marker genes and clinical characteristics in the 179 samples. In the verification phase, these marker genes and clinical characteristics were verified by internal validation cohort (n = 58) and two external cohorts (n = 81, n = 105). Results: We constructed and verified a nomogram model based on multiple clinicopathologic characteristics and gene expression of a patient cohort undergoing esophagectomy and adjuvant radiochemotherapy. The predictive accuracy for 4-year overall survival (OS) indicated by the C-index was 0.75 (95% CI, 0.72–0.78), which was statistically significantly higher than that of the American Joint Committee on Cancer (AJCC) seventh edition (0.65). Furthermore, we found two marker genes (TM9SF1, PDZK1IP) directly related to the OS of esophageal cancer. Conclusion: The nomogram presented in this study can accurately and impersonally predict the prognosis of ESCC patients after partial resection of the esophagus. More research is required to determine whether it can be applied to other patient populations. Moreover, we found two marker genes directly related to the prognosis of ESCC, which will provide a basis for future research.
Highlights
Esophageal cancer (EC) is a very common digestive tract tumor with the sixth highest mortality rate in the world, and there are about 150,000 deaths from EC in China every year. (Rubenstein and Shaheen, 2015; Liang et al, 2017) The histological types of EC mainly include esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC)
The tumor-node-metastasis (TNM) staging system ignores the important clinical factors of tumor prognosis, and the great difference in clinical course leads to the inaccuracy of TNM staging, so it is necessary to establish a new ESCC prognosis grading system. (Cao et al, 2016; Duan et al, 2016) A nomogram can successfully quantify risk prediction by incorporating and illustrating important factors for tumor prognosis. (Wierda et al, 2007; Zhang et al, 2018; Sun et al, 2019) Compared with the TNM staging system, a nomogram can predict the survival of all types of cancer patients more accurately and quantify the outcome of survival prediction by using clinical factors and other factors affecting the prognosis of cancer
To the best of the authors’ knowledge, this paper presents the first ESCC nomogram model based on multiple clinicopathologic characteristics and gene expression of a patient cohort undergoing esophagectomy and adjuvant radiochemotherapy
Summary
Esophageal cancer (EC) is a very common digestive tract tumor with the sixth highest mortality rate in the world, and there are about 150,000 deaths from EC in China every year. (Rubenstein and Shaheen, 2015; Liang et al, 2017) The histological types of EC mainly include esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). A Prognostic Model for ESCC worldwide were diagnosed with EC, and more than 500,000 people died of EC in the same year. (Cao et al, 2016; Duan et al, 2016) A nomogram can successfully quantify risk prediction by incorporating and illustrating important factors for tumor prognosis. (Wierda et al, 2007; Zhang et al, 2018; Sun et al, 2019) Compared with the TNM staging system, a nomogram can predict the survival of all types of cancer patients more accurately and quantify the outcome of survival prediction by using clinical factors and other factors affecting the prognosis of cancer. The nomogram is a new prognostic criterion that produces a quantified risk probability of clinical survival by creating a linear graph of the prediction model instead of the traditional method. HER-2 is not an efficient prognostic biomarker and potential therapeutic target for Iranian ESCC patients. The aim of this study was to identify prognostic markers for esophageal squamous cell carcinoma (ESCC) and build an effective prognostic nomogram for ESCC
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