Detection of recurrent markers for hepatocellular carcinoma based on proteomic data

Abstract

Abstract: Objective Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. More than 500000 cases are diagnosed each year. The recurrence of HCC affects the prognosis of patients. Proteomics technology has great potential in searching related biomarkers, and also drives progress on new diagnostic Methods. The purpose of the study was to find new markers of HCC recurrence from the perspective of proteomics.Methods The proteomic data were from the clinical proteomic tumor analysis consortium (CPTAC) database. The data was grouped according to the recurrence of HCC, and differential proteins between the 2 groups were analyzed. Survival analysis, Cox regression and receiver operator characteristic (ROC) curve were used to screen clinically significant proteins. The key proteins were verified in the human protein map database.Results A total of 690 differential proteins were screened in 50 relapse cases and 77 non-relapse cases. Among them, 39 proteins were related to the survival analysis, 18 proteins were independent factors affecting the prognosis of HCC. The area under the ROC curve predicted of 7 proteins (BAHCC1、ESF1、RAP1GAP、RUFY1、SCAMP3、STK3、TMEM230) for the 5-year survival of HCC exceeded 0.7.Conclusion New proteins predicting the recurrence of HCC are screened in the study. The key proteins are not only independent factors, but also have good predictive value for the prognosis of HCC.

Key words: Hepatocellular carcinoma, Proteomics, Clinical proteomic tumor analysis consortium

YANG Yong-qin, FENG Gong, HAO Shuai, CHEN Min, LIANG Tian, YAN Hong-lin, HE Na. Detection of recurrent markers for hepatocellular carcinoma based on proteomic data[J]. Chinese Hepatolgy, 2022, 27(11): 1170-1174.

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