Advances in Computational Drug Repurposing, Driver Genes, and Therapeutics in Lung Adenocarcinoma

Area of Science:

• Oncology
• Genomics
• Pharmacology

Background:

• Lung adenocarcinoma (LUAD) is a major cause of cancer mortality.
• Identifying driver genes and therapeutic targets is crucial for LUAD treatment.
• Drug repurposing offers a promising strategy to accelerate LUAD therapy development.

Purpose of the Study:

• To catalog LUAD driver genes and their roles in the disease.
• To review experimental and computational drug repurposing methods.
• To synthesize recent LUAD computational repurposing studies for translational research.

Main Methods:

• Cataloging candidate LUAD driver genes and their functions.
• Reviewing six experimental and eight computational drug repurposing method families.
• Appraising LUAD repurposing studies using a computational lens.

Main Results:

• A curated panel of LUAD driver genes mapped to pathways, alterations, functions, and therapeutic implications.
• An overview of drug repurposing methodologies, including experimental and computational approaches.
• Synthesis of recent LUAD computational repurposing studies, detailing methods, candidate drugs, and datasets.

Conclusions:

• Computational methods significantly complement experimental approaches in LUAD drug discovery.
• Integrating computational drug repurposing into translational research can accelerate LUAD therapeutic development.
• This review provides a framework for leveraging computational tools to identify novel LUAD treatment strategies.