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Published on: May 4, 2012
Changes in the Glycosylation of Kininogen and the Development of a Kininogen-Based Algorithm for the Early Detection
Mengjun Wang1, Miloslav Sanda2, Mary Ann Comunale3
1Department of Cell and Molecular Pharmacology, Medical University of South Carolina, Medical University of South Carolina, Charleston, South Carolina.
Insights
A new biomarker algorithm combining fucosylated kininogen and alpha-fetoprotein (AFP) significantly improves early detection of hepatocellular carcinoma (HCC), especially in patients with low AFP levels. This advancement aids in earlier treatment for cirrhosis patients.
Area of Science:
- Oncology
- Biomarker Discovery
- Hepatology
Background:
- Hepatocellular carcinoma (HCC) presents a growing mortality challenge in the US, largely due to late detection.
- Developing noninvasive biomarkers is crucial for reducing HCC-related deaths through early diagnosis.
Purpose of the Study:
- To develop and validate a novel algorithm for early hepatocellular carcinoma (HCC) detection.
- To enhance HCC detection rates, particularly in patients with low alpha-fetoprotein (AFP) levels or early-stage disease.
Main Methods:
- A primary algorithm integrated routine clinical data, improving HCC detection compared to AFP alone in over 3,000 patients.
- A secondary algorithm incorporated fucosylated kininogen to specifically address limitations in detecting early-stage and AFP-negative HCC.
- Glycan analysis was performed to understand the role of kininogen modifications in HCC.
Main Results:
- The secondary algorithm demonstrated an improved detection rate of 89% for early-stage, AFP-negative HCC, a significant increase from 0% with AFP alone.
- The combined algorithm showed high accuracy for early HCC detection.
- Fucoylated kininogen exhibited glycan modifications associated with HCC, including increased fucosylation and branching.
Conclusions:
- A combined algorithm utilizing fucosylated kininogen, AFP, and clinical factors offers high accuracy for early HCC detection.
- This biomarker approach holds potential to improve eligibility for curative treatments in cirrhotic patients.
Abstract:
Background: Hepatocellular carcinoma (HCC) has the greatest increase in mortality among all solids tumors in the United States related to low rates of early tumor detection. Development of noninvasive biomarkers for the early detection of HCC may reduce HCC-related mortality.Methods: We have developed an algorithm that combines routinely observed clinical values into a single equation that in a study of >3,000 patients from 5 independent sites improved detection of HCC as compared with the currently used biomarker, alpha-fetoprotein (AFP), by 4% to 20%. However, this algorithm had limited benefit in those with AFP <20 ng/mL. To that end, we have developed a secondary algorithm that incorporates a marker, fucosylated kininogen, to improve the detection of HCC, especially in those with AFP <20 ng/mL and early-stage disease.Results: The ability to detect early-stage AFP-negative (AFP <20 ng/mL) HCC increased from 0% (AFP alone) to 89% (for the new algorithm). Glycan analysis revealed that kininogen has several glycan modifications that have been associated with HCC, but often not with specific proteins, including increased levels of core and outer-arm fucosylation and increased branching.Conclusions: An algorithm combining fucosylated kininogen, AFP, and clinical characteristics is highly accurate for early HCC detection.Impact: Our biomarker algorithm could significantly improve early HCC detection and curative treatment eligibility in patients with cirrhosis. Cancer Epidemiol Biomarkers Prev; 26(5); 795-803. ©2017 AACR.
