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A novel molecular and clinical staging model to predict survival for patients with esophageal squamous cell carcinoma.

ABSTRACT: Current prognostic factors fail to accurately determine prognosis for patients with esophageal squamous cell carcinoma (ESCC) after surgery. Here, we constructed a survival prediction model for prognostication in patients with ESCC. Candidate molecular biomarkers were extracted from the Gene Expression Omnibus (GEO), and Cox regression analysis was performed to determine significant prognostic factors. The survival prediction model was constructed based on cluster and discriminant analyses in a training cohort (N=205), and validated in a test cohort (N=207). The survival prediction model consisting of two genes (UBE2C and MGP) and two clinicopathological factors (tumor stage and grade) was developed. This model could be used to accurately categorize patients into three groups in the test cohort. Both disease-free survival and overall survival differed among the diverse groups (P<0.05). In summary, we have developed and validated a predictive model that is based on two gene markers in conjunction with two clinicopathological variables, and which can accurately predict outcomes for ESCC patients after surgery.

SUBMITTER: Wang W

PROVIDER: S-EPMC5325382 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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A novel molecular and clinical staging model to predict survival for patients with esophageal squamous cell carcinoma.

Wang Wei W Wang Zhiwei Z Zhao Jun J Wei Min M Zhu Xinghua X He Qi Q Ling Tianlong T Chen Xiaoyan X Cao Ziang Z Zhang Yixin Y Liu Lei L Shi Minxin M

Oncotarget 20160901 39

Current prognostic factors fail to accurately determine prognosis for patients with esophageal squamous cell carcinoma (ESCC) after surgery. Here, we constructed a survival prediction model for prognostication in patients with ESCC. Candidate molecular biomarkers were extracted from the Gene Expression Omnibus (GEO), and Cox regression analysis was performed to determine significant prognostic factors. The survival prediction model was constructed based on cluster and discriminant analyses in a ...[more]

PMID: 27556859

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Project description:BackgroundOesophageal squamous cell carcinoma (ESCC) is the predominant subtype of oesophageal carcinoma in China, with the overall 5-year survival rate of <10%. The current tumour-node-metastasis (TNM) staging system has become so complex that it is not easy to use in the life expectancy assessment. We aim to combine clinical variables and biomarkers to develop and validate a relative simple and reliable model, named the FENSAM, for ESCC prognosis.MethodsTo build the FENSAM, we analysed 22 potential prognostic factors from 461 patients, including 9 biomarkers (Ezrin, Fascin, desmocollin 2 (DSC2), pFascin, activating transcription factor 3 (ATF3), connective-tissue growth factor (CTGF), neutrophil gelatinase-associated lipocalin (NGAL), NGAL receptor (NGALR), and cysteine-rich angiogenic protein 61 (CYR61)) and other 13 clinical variables. We selected significant factors associated with survival of ESCC patients, and used them to build our FENSAM model. We then obtained the hazard risk score of the model to classify ESCC patients. In addition, we validated the model in an independent cohort of 290 patients from the same hospital. The predictive performance of the model was assessed by the Area under the Receiver Operating Characteristic Curve (AUC) and Kaplan-Meier survival analysis.ResultsWe found six markers significantly associated with survival of ESCC patients (Ezrin, Fascin, ATF3, surgery extent, N-stage, and M-stage). They were combined to create a novel four-stage FENSAM model for patients' classification. FENSAM possessed a high classification precision similar to the TNM staging system, but with a much simpler model. The efficiency of FENSAM was evaluated by different quantiles of AUC and the results of survival analysis. The validation result demonstrated the potential of the FENSAM model to improve classification accuracy for ESCC patients.ConclusionsFENSAM provides an alternative classifier for ESCC patients with a high classification precision using a simple model.

Project description:BackgroundThe site of lymph node metastasis (LNM) may affect the prognosis of patients with esophageal squamous cell carcinoma (ESCC). To investigate the prognoses of pararespiratory and paradigestive LNM and to propose a novel N (nN) staging system that integrates both the LNM site and count.MethodsThis study was a multicenter, large-sample, retrospective cohort study that included ESCC patients with LNM between January 2014 and December 2019 from three Chinese institutes. Patients were set into training (two institutes) and external validation (one institute) cohorts. The primary outcomes were survival differences in LNM site and the development of novel nodal staging system. The overall survival (OS) of patients with pararespiratory LNM only (Group A), paradigestive LNM only (Group B), and both sites (Group C) was evaluated by Kaplan-Meier. Cox proportional hazards models were used to identify the independent prognostic factors. An nN staging system considering both the LNM site and count was developed and evaluated by the area under the receiver operating characteristic curve (AUC).ResultsIn total, 1313 patients were included and split into training (n = 1033) and external validation (n = 280) cohorts. There were 342 (26.0%), 568 (43.3%) and 403 (30.7%) patients in groups A, B and C, respectively. The OS of patients with pararespiratory and patients with paradigestive LNM presented significant differences in the training and validation cohorts (P < 0.050). In the training cohort, LNM site was an independent prognostic factor (hazard ratio: 1.58, 95% confidence intervals: 1.41-1.77, P < 0.001). The nN staging definition: nN1 (1-2 positive pararespiratory/paradigestive LNs), nN2 (3-6 pararespiratory LNs or 1 pararespiratory with 1paradigestive LN), nN3 (3-6 LNs with ≥ 1 paradigestive LN), nN4 (≥ 7 LNs). Subsets of patients with different nN stages showed significant differences in OS (P < 0.050). The prognostic model of the nN staging system presented higher performance in the training and validation cohorts at 3-year OS (AUC, 0.725 and 0.751, respectively) and 5-year OS (AUC, 0.740 and 0.793, respectively) than the current N staging systems.ConclusionsCompared to pararespiratory LNM, the presence of paradigestive LNM is associated with worse OS. The nN staging system revealed superior prognostic ability than current N staging systems.

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A novel molecular and clinical staging model to predict survival for patients with esophageal squamous cell carcinoma.

Publications

A novel molecular and clinical staging model to predict survival for patients with esophageal squamous cell carcinoma.

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