Serologic Assay of Liver Fibrosis

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Categories: “Diagnostics” & “Cancer Therapeutics

Reference #: 2017-009, 2019-048, 2021-033

OTC Contact: Zeinab Abouissa,  Phone: 202-687-2702, Email:


Treatment of cancer diseases improves with early detection. Dr. Goldman’s lab is investigating site-specific protein glycoforms as a molecular signature of hepatocellular carcinoma (HCC), the most common form of liver cancer. The incidence of HCC increases in the United States primarily due to hepatitis C viral infection and increased incidence of non-alcoholic steatohepatitis (NASH). HCV infection triggers changes in the glycosylation of liver-secreted proteins that can be followed along the progression of liver disease to HCC. Alpha-fetoprotein is an example of a liver-secreted glycoprotein used clinically to detect hepatocellular carcinoma. This protein detects approximately 60% of HCC patients and its glycosylated form has an improved specificity for the detection of HCC. Detailed characterization of the liver-secreted glycoproteins is challenging due to the heterogeneity of glycoforms at each glycosylation site.  Dr. Goldman has explored novel glycoforms of proteins that would improve the detection of liver diseases and HCC as well as optimizing analytical methods for glycoprotein characterization with a special interest in the quantification of the site-specific protein glycoforms.

Dr. Goldman’s technology combines liquid chromatography-mass spectrometry (LC-MS)-based glycoproteomic profiling of patient sera with informatics approaches for identifying liver-secreted glycoprotein biomarker candidates specific for liver diseases, in particular, HCC. Detailed characterization of liver-secreted glycoproteins is challenging due to glycan heterogeneity at each glycosylation site. The Goldman lab has designed glycosidase-assisted LC-MS methods for the selection of biomarker candidates. These methods allow the detection of disease-related changes at the glycopeptide level and are able to resolve linkage positions of relevant glycoforms. In addition, they are examining the connection of genomic variants affecting protein glycosylation with the development of hepatocellular carcinoma. They have established infrastructure for the identification of the variant glycoproteins as well as informatics analyses, including the development of software tools for the interpretation of glycopeptide LC-MS datasets, further refining the identification of biomarker candidates. It is expected that these methods will be compatible with the clinical testing of patient samples to allow the quantification of disease-specific glycoforms of glycoprotein biomarkers.  In addition, they have developed tools for the analysis of potential N-linked glycan attachment sites based on the NXS/T sequon. Integrated databases of genomic variants that affect protein sequences in a way that might alter the N-glycosylation state of proteins have also been developed. Such protein variants are associated with disease progression and will expand the identification of disease biomarkers. Site-specific glycoforms of the selected protein candidates are examined directly in patient samples in the appropriate disease context.

Identification of biomarker candidates and their accurate quantification by glycosidase-assisted LC-MS-MRM methods has profound implications in the field of glycobiology and public health. The glycosidase-assisted LC-MS methods have the ability to resolve linkage isoforms at site-specific locations. This allows an accurate quantitative assessment of glycosylation changes at specific proteins

and in specific sequons of a given protein. This also allows the desired resolution of the site-specific glycoforms, which is important for molecular disease classification.   The Goldman lab has tremendous capabilities to provide informatics analysis of select proteins of interest, which are highly specific and quantitatively accurate detection methods for this class of protein modifications that open new opportunities for molecular disease classification. These glycosidase-assisted LC-MS and LC-MS-MRM methods provide outstanding opportunities for collaboration with investigators and companies interested in targeted molecular classification of diseases.


Radoslav Goldman, Ph.D. Professor, Department of Oncology; Department of Biochemistry and Molecular & Cellular Biology Director, Proteomics Shared Resource