Key Takeaways & Executive Findings
- •• Integrated transcriptomic and proteomic analysis identified a five-biomarker panel with 92% sensitivity and 88% specificity for early HCC detection. • A prognostic signature based on the biomarkers effectively stratifies HCC patients into distinct risk groups with significant survival differences. • Novel candidate biomarkers were validated in independent cohorts, demonstrating reproducibility and clinical utility. • The multi-omics approach offers a comprehensive framework for personalized HCC diagnosis and treatment.
Abstract
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with late diagnosis contributing to poor prognosis. This study integrates transcriptomic and proteomic analyses to identify novel biomarkers for early detection and prognostic assessment of HCC. Using RNA sequencing and mass spectrometry on tumor and adjacent non-tumor tissues from 120 HCC patients, we identified 45 differentially expressed genes and 23 proteins consistently altered in HCC. Among these, a panel of five biomarkers (including AFP, GPC3, and three novel candidates) demonstrated high sensitivity (92%) and specificity (88%) for early-stage HCC detection. Furthermore, a prognostic signature based on these biomarkers stratified patients into high- and low-risk groups with significantly different overall survival (p < 0.001). Our findings provide a robust multi-omics framework for HCC management, potentially improving clinical outcomes through earlier intervention and personalized treatment strategies.
1. Introduction
Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and the fourth leading cause of cancer-related death globally. Despite advances in diagnostic imaging and therapeutic modalities, the prognosis of HCC patients remains poor, largely due to late-stage diagnosis and high recurrence rates. Early detection is critical for improving survival, yet current biomarkers such as alpha-fetoprotein (AFP) have limited sensitivity and specificity. Therefore, there is an urgent need for novel biomarkers that can facilitate early diagnosis and accurate prognosis.
Recent technological advancements in high-throughput omics, including transcriptomics and proteomics, have enabled comprehensive molecular profiling of tumors. Integration of these data can reveal dysregulated genes and proteins that may serve as reliable biomarkers. In this study, we performed RNA sequencing and mass spectrometry on HCC tissues to identify candidate biomarkers, followed by validation in independent cohorts. Our aim is to develop a multi-omics-based biomarker panel that can improve early detection and prognostic stratification of HCC, ultimately guiding personalized therapeutic decisions.
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ZHANG Wei, LI Ming, WANG Fang, CHEN Jie, LIU Yang, ZHAO Lei, SUN Hong, ZHOU Qiang (2025). A Comprehensive Analysis of Hepatocellular Carcinoma Biomarkers: Integrating Transcriptomic and Proteomic Approaches for Early Diagnosis and Prognosis. Chinese Journal of New Drugs. https://doi.org/pub_80__articleID_190
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Frequently Asked Questions
What is the significance of the five-biomarker panel for HCC detection?
The five-biomarker panel, comprising AFP, GPC3, and three novel candidates, achieved 92% sensitivity and 88% specificity for early-stage HCC, significantly outperforming AFP alone. This panel could enable earlier diagnosis and improve patient outcomes.
How was the prognostic signature developed and validated?
The prognostic signature was developed using Cox regression analysis on the biomarker expression levels in the discovery cohort and validated in two independent cohorts. It effectively stratified patients into high- and low-risk groups with significant differences in overall survival.
What are the novel biomarkers identified in this study?
Three novel biomarkers were identified: a long non-coding RNA (lncRNA) and two proteins involved in cell proliferation and immune evasion. These were validated by qRT-PCR and Western blot, showing consistent upregulation in HCC tissues.
How does this multi-omics approach benefit clinical practice?
By integrating transcriptomic and proteomic data, this approach provides a more comprehensive molecular view of HCC, enabling the identification of robust biomarkers that reflect both genetic and protein-level alterations. This can lead to more accurate diagnosis, prognosis, and personalized treatment strategies.
What are the limitations of this study?
The study is retrospective and based on a relatively small sample size. Prospective validation in larger, diverse cohorts is needed to confirm clinical utility. Additionally, the functional roles of the novel biomarkers require further investigation.
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