Pharmaceutical targets of curcumin in liver cancer treatment and molecular mechanisms: a bioinformatics analysis and computer-aided study

The most common type of primary liver cancer, hepatocellular carcinoma (HCC, or LIHC), is one of the leading causes of cancer-associated death worldwide. Patients with HCC have a short 5-year survival rate. Identifying useful biomarkers and developing effective drugs can improve early diagnosis and treatment efficacy to increase the survival rate of LIHC patients. However, the process of screening effective biomarkers and drugs for treatment is time- and cost-consuming. Repurposing naturally derived bioactive products is a promising strategy to address this issue. Herein, we took advantage of the bioinformatics analysis and computational-aided processes to explore the therapeutic potential of bioactive compound curcumin against LIHC. The functional enrichment and signaling pathway enrichment of curcumin-targeted proteins were analyzed, and 10 key hub genes were identified as potential targets. By further analyzing the mRNA expression levels and their association with the clinical prognostic outcomes of LIHC patients, we identified that four key genes ( AKT1, GSK3B, MMP9 , and SERPINE1 ) were therapeutic targets of curcumin in LIHC treatment. The binding affinity and molecular mechanisms of curcumin and target proteins were examined using computational-based approaches. The results in this study shed light on how curcumin functions as a treatment or template drug against LIHC.

Authors

Institutions

Publication Details

Journal
In Silico Research in Biomedicine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.insi.2025.100045
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pharmaceutical targets of curcumin in liver cancer treatment and molecular mechanisms: a bioinformatics analysis and computer-aided study

Chunye Zhang, Ming Yang, Shuai Liu, Yuxiang Sui
In Silico Research in Biomedicine
Computational Drug Discovery Methods
article

Pharmaceutical targets of curcumin in liver cancer treatment and molecular mechanisms: a bioinformatics analysis and computer-aided study

Chunye Zhang, Ming Yang, Shuai Liu, Yuxiang Sui
article en

Abstract

The most common type of primary liver cancer, hepatocellular carcinoma (HCC, or LIHC), is one of the leading causes of cancer-associated death worldwide. Patients with HCC have a short 5-year survival rate. Identifying useful biomarkers and developing effective drugs can improve early diagnosis and treatment efficacy to increase the survival rate of LIHC patients. However, the process of screening effective biomarkers and drugs for treatment is time- and cost-consuming. Repurposing naturally derived bioactive products is a promising strategy to address this issue. Herein, we took advantage of the bioinformatics analysis and computational-aided processes to explore the therapeutic potential of bioactive compound curcumin against LIHC. The functional enrichment and signaling pathway enrichment of curcumin-targeted proteins were analyzed, and 10 key hub genes were identified as potential targets. By further analyzing the mRNA expression levels and their association with the clinical prognostic outcomes of LIHC patients, we identified that four key genes ( AKT1, GSK3B, MMP9 , and SERPINE1 ) were therapeutic targets of curcumin in LIHC treatment. The binding affinity and molecular mechanisms of curcumin and target proteins were examined using computational-based approaches. The results in this study shed light on how curcumin functions as a treatment or template drug against LIHC.

In Silico Research in BiomedicineVol. 1
Shanxi Normal University (CN), First Affiliated Hospital Zhejiang University (CN), UConn Health (US), University of Missouri (US)
Good health and well-being
Openalex Percentile: Top 78%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.