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Updated: Mar 15, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
Phospho-Network Analysis Identifies and Quantifies Hepatitis C Virus (HCV)-induced Hepatocellular Carcinoma (HCC)
Nu T Lu1, Natalie M Liu2, James Q Vu2
1Department of Pathology and Laboratory Medicine, University of California Los Angeles, Los Angeles, CA, U.S.A Department of Hematology and Oncology, University of California Los Angeles, Los Angeles, CA, U.S.A.
Background:
Patients with chronic hepatitis C virus (HCV) infection are at risk of serious complications of cirrhosis and hepatocellular carcinoma (HCC). Mass spectrometry (MS) is a versatile methodology that produces a global proteomic landscape for analysis of cancer mechanisms.
Materials And Methods:
Using multiplex peptide stable isotopic labeling and immobilized metal affinity chromatography (IMAC), we enriched and quantified the phosphoproteome of HCC, with and without HCV. While raw data identified protein targets based on expression alone, we also used abundance groups for comprehensive functional analysis.
Results:
Analysis of functional differences highlighted deregulated phosphoprotein networks. This uncovered additional candidates that could be directly derived from the MS data. Cellular processes and pathways that may differ with HCV infection include: cytoskeletal dynamics, insulin response, gene expression, and PI3K/AKT oncogenesis.
Conclusion:
This function-focused workflow provides a simple framework to analyze MS data. Phosphoproteome quantitation with inclusive functional analysis can generate hypotheses for liver cancer research to improve early screening and identification of molecular targets for therapy.
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