Unveiling novel potential drug targets for lung cancer through Mendelian randomization analysis
Yawei Huang, Mengya Geng, Mukun Zhang · 2025
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Description
Yawei Huang, Mengya Geng, and Mukun Zhang mine genetic data for fresh drug targets against lung cancer, in a study from twenty twenty-five. Their method, Mendelian randomization, uses inherited variants as natural experiments to test whether gene activity or protein levels actually drive the disease.
Hundreds of gene-expression signals and dozens of protein signals showed causal links at first pass. Robustness checks kept most of them, and colocalization narrowed the field to twenty strong expression targets. A network exercise matched targets to hundreds of candidate drugs and flagged diseases sharing the same pathways. One drug, valproic acid, bound strongly to eight genes. Seven targets survived validation across two analyses. The authors offer them as leads for drug development.
Catalog record
| CREATOR | Yawei Huang, Mengya Geng, Mukun Zhang |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |