Proteomic Characterization of Liver Cancer Cells Treated with Clinical Targeted Drugs for Hepatocellular Carcinoma

<b>Background/Objectives</b>: Hepatocellular carcinoma (HCC) remains a significant global health concern, primarily due to the limited efficacy of targeted therapies, which are often compromised by drug resistance and adverse side effects. <b>Methods</b>: In this study, we utilized a Tandem Mass Tag (TMT)-based quantitative proteomic approach to analyze global protein expression and serine/threonine/tyrosine (S/T/Y) phosphorylation modifications in HepG2 cells following treatment with three clinically relevant hepatocellular carcinoma-targeted agents: apatinib, regorafenib, and lenvatinib. <b>Results</b>: Utilizing KEGG pathway enrichment analysis, biological process enrichment analysis, and protein interaction network analysis, we elucidated the common and specific metabolic pathways, biological processes, and protein interaction regulatory networks influenced by three liver cancer therapeutics. The study additionally proposed potential combinational treatment strategies, highlighting a possible synergistic interaction between HCC-targeted drugs and the DNA methyltransferase inhibitor. Furthermore, through the integration of clinical phosphorylation site data, we identified several phosphorylation sites that exhibited higher abundance in tumor tissues compared to adjacent non-tumor tissues. These sites were associated with poor prognosis and elevated functional scores. <b>Conclusions</b>: In summary, this study conducted an in-depth analysis of the molecular alterations in proteins and phosphorylation modifications induced by clinical HCC-targeted drugs, predicting drug combination strategies and therapeutic targets.

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Publication Details

Journal
Biomedicines
Published
2025-01-09
DOI
https://doi.org/10.3390/biomedicines13010152
Citations
4
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
3.22

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article

Proteomic Characterization of Liver Cancer Cells Treated with Clinical Targeted Drugs for Hepatocellular Carcinoma

Caicun Zhou, Jun‐Yu Xu, Shuyu Xie, Hui Long et al.
4 citations
Biomedicines
Bioinformatics and Genomic Networks
3.22
article

Proteomic Characterization of Liver Cancer Cells Treated with Clinical Targeted Drugs for Hepatocellular Carcinoma

Caicun Zhou, Jun‐Yu Xu, Shuyu Xie, Hui Long, Minjia Tan, Jingling Wang, Jiafu Zhou
article en
4 citations

Abstract

<b>Background/Objectives</b>: Hepatocellular carcinoma (HCC) remains a significant global health concern, primarily due to the limited efficacy of targeted therapies, which are often compromised by drug resistance and adverse side effects. <b>Methods</b>: In this study, we utilized a Tandem Mass Tag (TMT)-based quantitative proteomic approach to analyze global protein expression and serine/threonine/tyrosine (S/T/Y) phosphorylation modifications in HepG2 cells following treatment with three clinically relevant hepatocellular carcinoma-targeted agents: apatinib, regorafenib, and lenvatinib. <b>Results</b>: Utilizing KEGG pathway enrichment analysis, biological process enrichment analysis, and protein interaction network analysis, we elucidated the common and specific metabolic pathways, biological processes, and protein interaction regulatory networks influenced by three liver cancer therapeutics. The study additionally proposed potential combinational treatment strategies, highlighting a possible synergistic interaction between HCC-targeted drugs and the DNA methyltransferase inhibitor. Furthermore, through the integration of clinical phosphorylation site data, we identified several phosphorylation sites that exhibited higher abundance in tumor tissues compared to adjacent non-tumor tissues. These sites were associated with poor prognosis and elevated functional scores. <b>Conclusions</b>: In summary, this study conducted an in-depth analysis of the molecular alterations in proteins and phosphorylation modifications induced by clinical HCC-targeted drugs, predicting drug combination strategies and therapeutic targets.

BiomedicinesVol. 13(1)
Nanjing University of Chinese Medicine (CN), Chinese Academy of Sciences (CN), Shanghai Institute of Materia Medica (CN), Southern Medical University (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 10%
Bioinformatics and Genomic Networks
3.22
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