Discovery and validation of combined biomarkers for the diagnosis of esophageal intraepithelial neoplasia and esophageal squamous cell carcinoma

食管癌 食管 医学 食管肿瘤 食管鳞状细胞癌 上皮内瘤变 肿瘤科 癌症 病理 内科学 癌症研究 前列腺
作者
Ya-Qi Zheng,Haihua Huang,Shuxian Chen,Xiu‐E Xu,Zhi-Mao Li,Yuehong Li,Su-Zuan Chen,Wen-Xiong Luo,Yi Guo,Wei Liu,En‐Min Li,Li‐Yan Xu
出处
期刊:Journal of Proteomics [Elsevier BV]
卷期号:304: 105233-105233 被引量:2
标识
DOI:10.1016/j.jprot.2024.105233
摘要

Early diagnosis and intervention of esophageal squamous cell carcinoma (ESCC) can improve the prognosis. The purpose of this study was to identify biomarkers for ESCC and esophageal precancerous lesions (intraepithelial neoplasia, IEN). Based on the proteomic and genomic data of esophageal tissue including previously reported data, up-regulated proteins with copy number amplification in esophageal cancer were screened as candidate biomarkers. Five proteins, including KDM2A, RAD9A, ECT2, CYHR1 and TONSL, were confirmed by immunohistochemistry on ESCC and normal esophagus (NE). Then, we investigated the expression of 5 proteins in 236 participants (60 NEs, 93 IENs and 83 ESCCs) which were randomly divided into training set and test set. When distinguishing ESCC from NE, the area under curve (AUC) of the multiprotein model was 0.940 in the training set, while the lowest AUC of a protein was 0.735. In the test set, the results were similar. When distinguishing ESCC from IEN or distinguishing IEN from NE, the diagnostic efficiency of the multi-protein models were also improved compared with that of single protein. Our findings suggest that combined detection of KDM2A, RAD9A, ECT2, CYHR1 and TONSL can be used as potential biomarkers for the early diagnosis of ESCC and precancerous lesion development prediction. Candidate biomarkers including KDM2A, RAD9A, ECT2, CYHR1 and TONSL screened by integrating genomic and proteomic data from the esophagus can be used as potential biomarkers for the early diagnosis of esophageal squamous cell carcinoma and precancerous lesion development prediction.
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