Diagnostic value of combined detection of ascites and serum extracellular vesicle contents for HBV-related primary hepatocellular carcinoma
10.11816/cn.ni.2025-250428
- VernacularTitle:腹水和血清细胞外囊泡内容物联合检测HBV相关原发性肝细胞癌的诊断价值
- Author:
Chenhongmei WANG
1
;
Jiaheng ZHU
;
Xiaohui LIU
;
Zhihui XU
;
Jia LIU
;
Hanqian XING
;
Kaili WANG
;
Yanming HU
;
Yinyin LI
;
Jinsong MU
;
Xudong GAO
;
Bo LI
;
Boan LI
Author Information
1. 山东第二医科大学医学检验学院,山东潍坊 261053;解放军总医院第五医学中心检验科,北京 100039
- Publication Type:Journal Article
- Keywords:
Hepatitis B virus;
Hepatocellular carcinoma;
Extracellular vesicle;
Micro RNA;
Alpha-fetoprotein;
Protein induced by vitamin K absence or antagonist-Ⅱ;
Machine learning
- From:
Chinese Journal of Nosocomiology
2025;35(19):2921-2926
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To explore the diagnostic value of combined detection of microRNA(miRNA)and alpha-fetoprotein(AFP),protein induced by vitamin K absence or antagonist-Ⅱ(PIVKA-Ⅱ)in ascites and serum ex-tracellular vesicles(EVs)for hepatitis B virus(HBV)-related primary hepatocellular carcinoma(HCC).METHODS From Nov.2023 to Nov.2024,41 patients with liver cancer and 26 patients with liver cirrhosis who underwent ascites placement or ascites concentration and reinfusion procedures at the Fifth Medical Center of Chi-nese PLA General Hospital were selected as study subjects.Ascites and serum samples were collected.Real-time quantitative reverse transcription polymerase chain reaction(qRT-PCR)was used to detect the expression levels of miR-21,miR-125a,miR-150 and miR-200a in EVs.Chemiluminescence was used to measure the levels of AFP and PIVKA-Ⅱ in ascites,serum and EVs from ascites and serum.An artificial neural network was utilized to con-struct a combined diagnostic model of serum and ascites markers.RESULTS The area under the curve(AUC)for distinguishing HCC from liver cirrhosis using a combination of serum and other indicators was 0.933.The AUC for distinguishing HCC from liver cirrhosis using a combination of ascites and other indicators was 0.912.By screening all detected indicators using an artificial neural network and incorporating indicators with a relative im-portance＞0.5 into the diagnostic model,the model included four indicators:ascites AFP,ascites EVs miR-21,ascites EVs miR-200a and serum EVs miR-200a.This model had a sensitivity of 80.77％,a specificity of 87.80％and an AUC of 0.960 for distinguishing HCC from liver cirrhosis patients.CONCLUSION The combined diagnos-tic markers of miRNA,AFP and PIVKA-Ⅱ in ascites and serum-derived EVs have good application value in the diagnosis of HCC.
