Data supporting Multi-Disease Transcriptomic Integration and Network Toxicology Reveal Molecular Links Between 6PPD-Q and Respiratory Diseases
Description
This dataset contains research data and analysis outputs supporting a study of molecular associations between 6PPD-quinone and respiratory diseases. It includes SwissTargetPrediction and SEA outputs, a final curated list of 129 candidate targets integrating database-predicted and literature-supported targets, standardized respiratory disease-gene lists, differential-expression outputs and candidate-level expression matrices for GSE196399, GSE57148, and GSE67472, disease-context candidate genes, GO, KEGG, Reactome and Hallmark GSEA outputs, PPI and exploratory ROC analyses, molecular-docking structures and binding energies, and cell-viability data. Detailed folder organization, file descriptions, data provenance, and processing criteria are provided in the accompanying README and file manifest.
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Steps to reproduce
1. Public transcriptomic datasets were obtained from the Gene Expression Omnibus: GSE196399 for severe community-acquired pneumonia, GSE57148 for chronic obstructive pulmonary disease, and GSE67472 for asthma. 2. Candidate targets of 6PPD-quinone were collected from SwissTargetPrediction, SEA, and literature-supported records included in the curated target table. Gene identifiers were standardized and deduplicated, yielding 129 candidate targets. 3. Gene lists related to respiratory diseases, pneumonia, COPD, and asthma were standardized and deduplicated. Intersection analysis between the 129 compound-associated targets and the disease-related gene sets identified 65 common candidate genes. 4. The three GEO datasets were analyzed independently because they differed in tissue source and platform. GSE196399 was analyzed using DESeq2, whereas GSE57148 and GSE67472 were analyzed using limma. 5. Adjusted P < 0.05 was used to identify significant genes for candidate-gene intersection. The additional |log2FC| > 1 threshold was used to classify strongly altered genes in volcano plots. 6. Significant genes from each disease dataset were intersected with the 65 common candidate genes, yielding 45 pneumonia-, 30 COPD-, and 10 asthma-context candidate genes. 7. GO, KEGG, Reactome, and Hallmark GSEA analyses were performed using the candidate-gene lists and ranked transcriptomic results. PPI networks were constructed using STRING and analyzed in Cytoscape with cytoHubba. 8. Exploratory ROC analyses were conducted using expression values from the corresponding GEO datasets. Molecular docking of 6PPD-Q with MAPK14, ABL1, FYN, and GSK3B was performed using CB-Dock2 and AutoDock Vina. Cell-viability measurements were analyzed using GraphPad Prism. The folder structure, data provenance, file descriptions, and checksums are documented in the accompanying README and manifest files.
Institutions
- Jiamusi UniversityHeilongjiang, Jiamusi