Work

Sensitive Detection of Plasma Fibrinogen Chain A mRNA in Hepatocellular Carcinoma Using Semi-Nested RT-PCR

Year: 2025

Type: article

Abstract: Background/Objectives: Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality, with diagnostic limitations of existing biomarkers such as alpha-fetoprotein (AFP). This study evaluates plasma Fibrinogen chain A mRNA (FGA mRNA), alone and combined with AFP, for improving HCC diagnosis. Methods: A semi-nested RT-PCR assay was developed to quantify plasma FGA mRNA in 80 HCC patients and 74 controls (57 chronic liver disease [CLD] and 17 healthy donors [HDs]). Receiver operating characteristic (ROC) analysis was used to assess diagnostic performance, and logistic regression evaluated the combined biomarker model. Results: Plasma FGA mRNA levels were significantly higher in HCC patients than in CLD and HD controls (p < 0.0001). The area under the curve (AUC) for HCC vs. the combined control group (CLD + HD) was 0.721 (95% CI: 0.643–0.790), improving to 0.866 (95% CI: 0.782–0.927) when comparing HCC to HDs alone but declining for HCC vs. CLD (AUC = 0.678, 95% CI: 0.592–0.755). Combining FGA mRNA with AFP significantly enhanced diagnostic accuracy for HCC vs. CLD (AUC = 0.859, 95% CI: 0.790–0.913), with a sensitivity of 87.50% and specificity of 71.93%. In patients with low AFP levels (<20 ng/mL), the combined model identified 68.75% of HCC cases, outperforming AFP alone. Conclusions: FGA mRNA alone provides moderate diagnostic utility but substantially improves accuracy when combined with AFP, especially in low-AFP cases. This multi-biomarker approach holds promise for improving HCC detection and warrants further validation in larger cohorts.

Source: Diagnostics

DOI: 10.3390/diagnostics15111364

Authors: Huy Duong, Minh Ngo, Trang Dao, Trang Hoang, Ung Nguyen, Tho Ho

Institution: Vietnam Military Medical University

Language: English

Topic: Hepatocellular Carcinoma Treatment and Prognosis

Subfield: Hepatology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,137