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Extracting Potential New Targets for Treatment of Adenoid Cystic Carcinoma using Bioinformatic Methods
Tayebeh Forooghi Pordanjani1, Bahareh Dabirmanesh1, Peyman Choopanian2
1Department of Biochemistry, Faculty of Biological Science, Tarbiat Modares University, Tehran, Iran.
Background:
Adenoid cystic carcinoma is a slow-growing malignancy that most often occurs in the salivary glands. Currently, no FDA-approved therapeutic target or diagnostic biomarker has been identified for this cancer. The aim of this study was to find new therapeutic and diagnostic targets using bioinformatics methods.
Methods:
We extracted the gene expression information from two GEO datasets (including GSE59701 and GSE88804). Different expression genes between adenoid cystic carcinoma (ACC) and normal samples were extracted using R software. The biochemical pathways involved in ACC were obtained by using the Enrichr database. PPI network was drawn by STRING, and important genes were extracted by Cytoscape. Real-time PCR and immunohistochemistry were used for biomarker verification.
Results:
After analyzing the PPI network, 20 hub genes were introduced to have potential as diagnostic and therapeutic targets. Among these genes, PLCG1 was presented as new biomarker in ACC. Furthermore, by studying the function of the hub genes in the enriched biochemical pathways, we found that insulin-like growth factor type 1 receptor and PPARG pathways most likely play a critical role in tumorigenesis and drug resistance in ACC and have a high potential for selection as therapeutic targets in future studies.
Conclusion:
In this study, we achieved the recognition of the pathways involving in ACC pathogenesis and also found potential targets for treatment and diagnosis of ACC. Further experimental studies are required to confirm the results of this study.
Insights
Researchers identified 20 potential diagnostic and therapeutic targets for adenoid cystic carcinoma (ACC), a rare cancer. PLCG1 emerged as a promising new biomarker, while specific pathways show potential for future drug development.
Area of Science:
- Oncology
- Bioinformatics
- Genomics
Background:
- Adenoid cystic carcinoma (ACC) is a slow-growing malignancy primarily affecting salivary glands.
- Currently, there are no FDA-approved therapeutic targets or diagnostic biomarkers for ACC.
- This study aimed to identify novel therapeutic and diagnostic targets for ACC using bioinformatics approaches.
Purpose of the Study:
- To identify potential diagnostic and therapeutic targets for adenoid cystic carcinoma (ACC).
- To explore key biochemical pathways involved in ACC pathogenesis.
- To validate potential biomarkers for ACC.
Main Methods:
- Gene expression data from two GEO datasets (GSE59701, GSE88804) were analyzed.
- Differentially expressed genes were identified using R software.
- Pathway enrichment analysis was performed using Enrichr, and protein-protein interaction (PPI) networks were constructed with STRING and visualized with Cytoscape. Biomarker verification used real-time PCR and immunohistochemistry.
Main Results:
- Twenty hub genes with potential as diagnostic and therapeutic targets were identified from the PPI network analysis.
- PLCG1 was highlighted as a novel potential biomarker for ACC.
- The insulin-like growth factor type 1 receptor and PPARG pathways were identified as critically involved in ACC tumorigenesis and drug resistance, suggesting their therapeutic potential.
Conclusions:
- This study successfully identified key pathways and potential targets for ACC diagnosis and treatment.
- Further experimental validation is necessary to confirm the identified targets and pathways for clinical application.
