High-throughput proteomics-guided biomarker discovery of hepatocellular carcinoma
Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%–90% of all primary liver malignancies. However, only 20–30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for ea...
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Veröffentlicht in: | Biomedical Journal 2025-02, Vol.48 (1), p.100752, Article 100752 |
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Zusammenfassung: | Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%–90% of all primary liver malignancies. However, only 20–30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for early detection and prognosis of HCC. This underscores the critical need for molecular biomarkers for HCC management. Since proteins reflect disease status directly, proteomics has been utilized in biomarker developments for HCC. In particular, proteomics coupled with liquid chromatography-mass spectrometer (LC-MS) methods facilitate the process of discovering biomarker candidates for diagnosis, prognosis, and therapeutic strategies.
In this work, we investigated LC-MS-based proteomics methods through recent reference reviews, with a particular focus on sample preparation and LC-MS methods appropriate for the discovery of HCC biomarkers and their clinical applications.
We classified proteomics studies of HCC according to sample types, and we examined the coverage of protein biomarker candidates based on LC-MS methods in relation to study scales and goals. Comprehensively, we proposed protein biomarker candidates categorized by sample types and biomarker types for appropriate clinical use.
In this review, we summarized recent LC-MS-based proteomics studies on HCC and proposed potential protein biomarkers. Our findings are expected to expand the understanding of HCC pathogenesis and enhance the efficiency of HCC diagnosis and prognosis, thereby contributing to improved patient outcomes. |
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ISSN: | 2319-4170 2320-2890 2320-2890 |
DOI: | 10.1016/j.bj.2024.100752 |