Related Experiment Video
Updated: Dec 9, 2025
Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Integrating Differential Gene Expression Analysis with Perturbagen-Response Signatures May Identify Novel Therapies
John Y Lee1, Ryan A Gallo1, Paul J Ledon1
1Dr. Nasser Al-Rashid Orbital Vision Research Center, Bascom Palmer Eye Institute, Department of Ophthalmology, University of Miami Miller School of Medicine, Miami, Florida, USA.
Purpose:
To evaluate the efficacy of Library of Integrated Network-based Cellular Signatures (LINCS) perturbagen prediction software to identify small molecules that revert pathologic gene signature and alter disease phenotype in orbital adipose stem cells (OASCs) derived from patients with thyroid-associated orbitopathy (TAO).
Methods:
Differentially expressed genes identified via RNA sequencing were inputted into LINCS L1000 Characteristic Direction Signature Search Engine (L1000CDS2) to predict candidate small molecules to reverse pathologic gene expression. TAO OASC cell lines were treated in vitro with six identified small molecules (Torin-2, PX12, withaferin A, isoliquiritigenin, mitoxantrone, and MLN8054), and expression of key adipogenic and differentially expressed genes was measured with quantitative polymerase chain reaction after 7 days of treatment. OASCs were differentiated into adipocytes, treated for 15 days, and stained with Oil Red O (OD 490 nm) to evaluate adipogenic changes.
Results:
The expression of key differentially expressed genes (IRX1, HOXB2, S100B, and KCNA4) and adipogenic genes (peroxisome proliferator activated receptor-γ, FABP4) was significantly decreased in TAO OASCs after treatment (P < .05). In treated TAO adipocytes (n = 3), all six tested small molecules yielded significant decrease (P < .05) in Oil Red O staining. In treated non-TAO adipocytes (n = 3), only three of the drugs yielded a significant decrease in Oil Red O staining.
Conclusions:
Combining disease expression signatures with LINCS small molecule prediction software can identify promising preclinical drug candidates for TAO.
Translational Relevance:
These findings may offer insight into future potential therapeutic options for TAO and demonstrate a streamlined model to predict drug candidates for other diseases.
Insights
This study used the LINCS software to identify small molecules that could reverse disease gene signatures in thyroid-associated orbitopathy (TAO) stem cells. Six tested molecules effectively reduced disease markers and altered cell characteristics, suggesting potential new treatments for TAO.
Area of Science:
- Biomedical research
- Genomics
- Drug discovery
Background:
- Thyroid-associated orbitopathy (TAO) involves complex cellular changes in orbital adipose stem cells (OASCs).
- Identifying targeted therapies for TAO requires understanding and modulating disease-specific gene expression patterns.
Purpose of the Study:
- To assess the effectiveness of the Library of Integrated Network-based Cellular Signatures (LINCS) software in predicting small molecules.
- To identify compounds capable of reversing pathologic gene signatures and disease phenotypes in TAO-derived OASCs.
Main Methods:
- RNA sequencing was used to identify differentially expressed genes in TAO OASCs.
- The LINCS L1000 Characteristic Direction Signature Search Engine (L1000CDS²) predicted small molecules targeting these genes.
- TAO OASCs and derived adipocytes were treated with six predicted small molecules, and gene expression and adipogenesis were analyzed.
Main Results:
- Treatment with six small molecules significantly decreased key differentially expressed and adipogenic genes in TAO OASCs.
- All six molecules significantly reduced Oil Red O staining in TAO adipocytes, indicating reduced adipogenesis.
- Three of the six molecules also significantly reduced adipogenesis in non-TAO adipocytes.
Conclusions:
- The LINCS platform, combined with disease expression signatures, successfully identified potential drug candidates for TAO.
- This approach offers a streamlined model for predicting therapeutic small molecules for TAO and other diseases.
