Abstract
BackgroundOesophageal squamous cell carcinoma (ESCC) is one of the most malignant cancers worldwide. Treatment of ESCC is in progress through accurate staging and risk assessment of patients. The emergence of potential molecular markers inspired us to construct novel staging systems with better accuracy by incorporating molecular markers.MethodsWe measured H scores of 23 protein markers and analysed eight clinical factors of 77 ESCC patients in a training set, from which we identified an optimal MASAN (MYC, ANO1, SLC52A3, Age and N-stage) signature. We constructed MASAN models using Cox PH models, and created MASAN-staging systems based on k-means clustering and minimum-distance classifier. MASAN was validated in a test set (n = 77) and an independent validation set (n = 150).ResultsMASAN possessed high predictive accuracies and stratified ESCC patients into three prognostic groups that were more accurate than the current pTNM-staging system for both overall survival and disease-free survival. To facilitate clinical utilisation, we also constructed MASAN-SI staging systems based on staining indices (SI) of protein markers, which possessed similar prognostic performance as MASAN.ConclusionMASAN provides a good alternative staging system for ESCC prognosis with a high precision using a simple model.
Highlights
Oesophageal squamous cell carcinoma (ESCC) is the fourth leading cause of cancer-related mortality, and approximately half of the world’s 500,000 new ESCC cases occur annually in China.[1, 2] The survival for ESCC is poor, with a 5-year overall survival (OS) of 20.9%.3 Treatment of ESCC remains a challenging problem.treatment outcomes are being improved through accurate staging and risk assessment of patients.[4, 5] Accurate staging techniques, including molecular staging, allow us to understand prognosis and to tailor therapy to individuals to achieve the best outcomes.Currently, the most commonly used staging systems for ESCC is the pTNM staging system proposed by the American Joint Committee on Cancer (AJCC).[6]
In this study, we examined the expressions of 23 potential protein markers and eight clinical characteristics of ESCC patients, from which we identified an optimal feature combination (MASAN) for precise prediction of ESCC survival outcome
The prognostic value of the MASAN models was verified in a test set and an independent validation set
Summary
Oesophageal squamous cell carcinoma (ESCC) is the fourth leading cause of cancer-related mortality, and approximately half of the world’s 500,000 new ESCC cases occur annually in China.[1, 2] The survival for ESCC is poor, with a 5-year overall survival (OS) of 20.9%.3 Treatment of ESCC remains a challenging problem.treatment outcomes are being improved through accurate staging and risk assessment of patients.[4, 5] Accurate staging techniques, including molecular staging, allow us to understand prognosis and to tailor therapy to individuals to achieve the best outcomes.Currently, the most commonly used staging systems for ESCC is the pTNM (pathological tumour-node metastasis) staging system (the 7th edition) proposed by the American Joint Committee on Cancer (AJCC).[6]. Treatment of ESCC is in progress through accurate staging and risk assessment of patients. METHODS: We measured H scores of 23 protein markers and analysed eight clinical factors of 77 ESCC patients in a training set, from which we identified an optimal MASAN (MYC, ANO1, SLC52A3, Age and N-stage) signature. RESULTS: MASAN possessed high predictive accuracies and stratified ESCC patients into three prognostic groups that were more accurate than the current pTNM-staging system for both overall survival and disease-free survival. We constructed MASAN-SI staging systems based on staining indices (SI) of protein markers, which possessed similar prognostic performance as MASAN. CONCLUSION: MASAN provides a good alternative staging system for ESCC prognosis with a high precision using a simple model
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