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Updated: Feb 8, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Potential candidate treatment agents for targeting of cholangiocarcinoma identified by gene expression profile
Suthipong Chujan1, Tawit Suriyo2,3, Teerapat Ungtrakul4
1Applied Biological Sciences Program, Chulabhorn Graduate Institute, Chulabhorn Royal Academy, Bangkok 10210, Thailand.
Abstract:
Cholangiocarcinoma (CCA) remains to be a major health problem in several Asian countries including Thailand. The molecular mechanism of CCA is poorly understood. Early diagnosis is difficult, and at present, no effective therapeutic drug is available. The present study aimed to identify the molecular mechanism of CCA by gene expression profile analysis and to search for current approved drugs which may interact with the upregulated genes in CCA. Gene Expression Omnibus (GEO) was used to analyze the gene expression profiles of CCA patients and normal subjects. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG), gene ontology enrichment analysis was also performed, with the KEGG pathway analysis indicating that pancreatic secretion, protein digestion and absorption, fat digestion and absorption, and glycerolipid metabolism may serve important roles in CCA oncogenesis. The drug signature database (DsigDB) was used to search for US Food and Drug Administration (FDA)-approved drugs potentially capable of reversing the effects of the upregulated gene expression in CCA. A total of 61 antineoplastic and 86 non-antineoplastic drugs were identified. Checkpoint kinase 1 was the most interacting with drug signatures. Many of the targeted protein inhibitors that were identified have been approved by the US-FDA as therapeutic agents for non-antineoplastic diseases, including cimetidine, valproic acid and lovastatin. The current study demonstrated an application for bioinformatics analysis in assessing the potential efficacy of currently approved drugs for novel use. The present results suggest novel indications regarding existing drugs useful for CCA treatment. However, further in vitro and in vivo studies are required to support the current predictions.
Insights
This study identifies key molecular pathways in cholangiocarcinoma (CCA) using bioinformatics. It also reveals potential new uses for existing FDA-approved drugs in treating this challenging cancer.
Area of Science:
- Oncology
- Bioinformatics
- Genomics
Background:
- Cholangiocarcinoma (CCA) poses a significant health challenge, particularly in Asia.
- The molecular underpinnings of CCA are not well understood, hindering early diagnosis and effective treatment.
- There is a critical need for novel therapeutic strategies for CCA.
Purpose of the Study:
- To elucidate the molecular mechanisms of CCA through gene expression profiling.
- To identify existing US Food and Drug Administration (FDA)-approved drugs that could potentially treat CCA.
- To explore novel therapeutic indications for repurposed drugs in CCA treatment.
Main Methods:
- Utilized Gene Expression Omnibus (GEO) for gene expression data analysis.
- Performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology enrichment analysis.
- Employed the Drug Signatures Database (DsigDB) to identify FDA-approved drugs targeting upregulated genes in CCA.
Main Results:
- KEGG pathway analysis highlighted roles for pancreatic secretion, protein/fat digestion and absorption, and glycerolipid metabolism in CCA.
- Identified 61 antineoplastic and 86 non-antineoplastic drugs with potential interactions.
- Checkpoint kinase 1 emerged as a key interacting target; drugs like cimetidine, valproic acid, and lovastatin showed promise.
Conclusions:
- Bioinformatics analysis offers a powerful approach to identify potential new uses for approved drugs.
- The study suggests novel therapeutic avenues for CCA using existing medications.
- Further in vitro and in vivo validation is necessary to confirm these findings for clinical application.
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