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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

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Incorporating Tissue-Specific Gene Expression Data to Improve Chemical-Disease Inference of in Silico Toxicogenomics

Shan-Shan Wang^1,2,3, Chia-Chi Wang⁴, Chien-Lun Wang³

¹Ph.D. Program in Environmental and Occupational Medicine, College of Medicine, Kaohsiung Medical University and National Health Research Institutes, Kaohsiung 80708, Taiwan.

Journal of Xenobiotics

|August 27, 2024

Summary

This study enhances in silico toxicogenomics by incorporating tissue-specific gene expression into the ChemDIS system. This improves chemical-disease inference accuracy, reducing false positives and identifying more specific toxicological effects.

Keywords:

chemical–disease inference enrichment analysis in silico toxicogenomics tissue-specific gene expression tissue-specific protein expression

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Area of Science:

Toxicogenomics
Computational Biology
Bioinformatics

Background:

In silico toxicogenomics aids in predicting chemical-protein-disease links.
Current methods lack tissue-specificity, leading to overpredicted diseases (false positives).

Purpose of the Study:

To improve the accuracy of in silico toxicogenomics by integrating tissue-specific gene expression data.
To reduce false positives in chemical-disease association predictions.

Main Methods:

Collected six tissue-specific gene and protein expression datasets from Expression Atlas.
Categorized genes into high, medium, and low expression levels per tissue.
Integrated tissue-specific expression data into the ChemDIS system by filtering low-expressed genes.

Main Results:

Achieved up to a 62.26% improvement in the enrichment rate for chemical-disease inference.
Demonstrated improved specificity in identifying disease terms through a melamine case study.
Implemented a user-friendly interface within the ChemDIS system.

Conclusions:

Incorporating tissue-specific gene expression significantly enhances chemical-disease inference accuracy.
The refined ChemDIS system provides more precise toxicological insights.
This methodology can be applied to other in silico toxicogenomics tools for broader applications.