Linlin Ji1,2, Jianping Wang2, Bo Yang1,2, Jianping Zhu3, Yini Wang2, Jiaqi Jiao2, Kai Zhu1, Min Zhang4, Liqiang Zhai4, Tongqing Gong5, Changqing Sun6, Jun Qin7, Guangshun Wang8. 1. Department of Thoracic Surgery, Baodi Clinical College, Tianjin Medical University, Tianjin, 301800, China. 2. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China. 3. Department of Thoracic Surgery, Henan Cancer Hospital, Zhengzhou, 450000, China. 4. Department of Oncology, Baodi Clinical College, Tianjin Medical University, Tianjin, 301800, China. 5. Beijing Pineal Health Management Co., Ltd, Beijing, 102206, China. 6. Joint Center for Translational Medicine, Baodi Clinical College, Tianjin Medical University, Tianjin, 301800, China. 7. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China. jqin1965@126.com. 8. Department of Thoracic Surgery, Baodi Clinical College, Tianjin Medical University, Tianjin, 301800, China. WGS@bddhospital.com.
Abstract
PURPOSE: Discovery of noninvasive urinary biomarkers for the early diagnosis of esophageal squamous carcinoma (ESCC). METHODS: We conducted proteomic analyses of 499 human urine samples obtained from healthy individuals (n = 321) and ESCC (n = 83), bladder cancer (n = 17), breast cancer (n = 12), colorectal cancer (n = 16), lung cancer (n = 33) and thyroid cancer (n = 17) patients from multiple medical centers. Those samples were divided into a discovery set (n = 247) and an independent validation set (n = 157). RESULTS: Among urinary proteins identified in the comprehensive quantitative proteomics analysis, we selected a panel of three urinary biomarkers (ANXA1, S100A8, TMEM256), and established a logistic regression model in the discovery set that can correctly classify the majority of ESCC cases in the validation sets with the area under the curve (AUC) values of 0.825. This urinary biomarker panel not only discriminates ESCC patients from healthy individuals but also differentiates ESCC from other common tumors. Notably, the panel distinguishes stage I ESCC patients from healthy individuals with AUC values of 0.886. On the analysis of stage-specific biomarkers, another combination panel of protein (ANXA1, S100A8, SOD3, TMEM256) demonstrated a good AUC value of 0.792 for stage I ESCC. CONCLUSIONS: Urinary biomarker panel represents a promising auxiliary diagnostic tool for ESCC, including early-stage ESCC.
PURPOSE: Discovery of noninvasive urinary biomarkers for the early diagnosis of esophageal squamous carcinoma (ESCC). METHODS: We conducted proteomic analyses of 499 human urine samples obtained from healthy individuals (n = 321) and ESCC (n = 83), bladder cancer (n = 17), breast cancer (n = 12), colorectal cancer (n = 16), lung cancer (n = 33) and thyroid cancer (n = 17) patients from multiple medical centers. Those samples were divided into a discovery set (n = 247) and an independent validation set (n = 157). RESULTS: Among urinary proteins identified in the comprehensive quantitative proteomics analysis, we selected a panel of three urinary biomarkers (ANXA1, S100A8, TMEM256), and established a logistic regression model in the discovery set that can correctly classify the majority of ESCC cases in the validation sets with the area under the curve (AUC) values of 0.825. This urinary biomarker panel not only discriminates ESCC patients from healthy individuals but also differentiates ESCC from other common tumors. Notably, the panel distinguishes stage I ESCC patients from healthy individuals with AUC values of 0.886. On the analysis of stage-specific biomarkers, another combination panel of protein (ANXA1, S100A8, SOD3, TMEM256) demonstrated a good AUC value of 0.792 for stage I ESCC. CONCLUSIONS: Urinary biomarker panel represents a promising auxiliary diagnostic tool for ESCC, including early-stage ESCC.
Authors: Freddie Bray; Jacques Ferlay; Isabelle Soerjomataram; Rebecca L Siegel; Lindsey A Torre; Ahmedin Jemal Journal: CA Cancer J Clin Date: 2018-09-12 Impact factor: 508.702