Autor: |
Miner Hu, Xiaojun Xia, Lichao Chen, Yunpeng Jin, Zhenhua Hu, Shudong Xia, Xudong Yao |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
|
Zdroj: |
Annals of Hepatology, Vol 28, Iss 6, Pp 101137- (2023) |
Druh dokumentu: |
article |
ISSN: |
1665-2681 |
DOI: |
10.1016/j.aohep.2023.101137 |
Popis: |
Most cases of hepatocellular carcinoma (HCC) are able to be diagnosed through regular surveillance in an identifiable patient population with chronic hepatitis B or cirrhosis. Nevertheless, 50% of global cases might present incidentally owing to symptomatic advanced-stage HCC after worsening of liver dysfunction. A systematic search based on PUBMED was performed to identify relevant outcomes, covering newer surveillance modalities including secretory proteins, DNA methylation, miRNAs, and genome sequencing analysis which proposed molecular expression signatures as ideal tools in the early-stage HCC detection. In the face of low accuracy without harmonization on the analytical approaches and data interpretation for liquid biopsy, a more accurate incidence of HCC will be unveiled by using deep machine learning system and multiplex immunohistochemistry analysis. A combination of molecular-secretory biomarkers, high-definition imaging and bedside clinical indexes in a surveillance setting offers a comprehensive range of HCC potential indicators. In addition, the sequential use of numerous lines of systemic anti-HCC therapies will simultaneously benefit more patients in survival. This review provides an overview on the most recent developments in HCC theranostic platform. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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