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Updated: Feb 7, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
GARD: Genomic Data based Drug Repurposing in Head and Neck Cancer with Large Language Model Validation
Pradham Tanikella1, Will Nenad2, Christophe Courtine3
1Department of Genetics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina.
Background/Objectives:
Head and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surgery, radiation, and immunotherapy, have shown limited improvement in outcomes. Drug repurposing offers a cost-effective strategy to identify new therapeutic options by leveraging existing medications with known safety profiles. Within this study we developed the GARD pipeline (Genomic Alteration-based Repurposing for Drugs), designed to uncover repurposing candidates for HNC using genomic and network-based approaches.
Methods:
GARD integrates multi-omics data from The Cancer Genome Atlas (TCGA), including copy number variation (CNV) and somatic mutations (SOM). The cohort was stratified by human papillomavirus (HPV) status. Risk-associated genes were identified and then expanded via high-confidence protein-protein interaction (PPI) networks. Top candidate genes were filtered through comprehensive analysis of publicly available literature data in PubMed using LLM to validate the relationship between the identified genes and HNC. The validated top risk genes and their network-expanded neighbors were mapped against DrugBank, and through statistical significance testing, established significant drug-gene associations.
Results:
Significant genes associated with HNC, inferred by genomics alteration, were identified across HPV-positive and HPV-negative subgroups, such as PIK3CA, SOX2, TP53, EIF4G1, TLR7, CLDN1, PRKCI, and EPHA2. Further expansion through the PPI network identified other targetable genes such as EGFR, ERBB2, and the FGFRs. Literature based validation efforts ensured provided confidence in the gene-disease association. Drug-gene mapping revealed candidates spanning already in clinical trials for HNC (e.g. Afatinib, Cabozantinib, Dasatinib, Brigatinib, Lenvatinib, Capivasertib, Erdafitinib) and emerging or repurposing candidates (Amuvatinib, XL765 (Voxtalisib), Golotimod, Artenimol, Quercetin, and Acetylsalicylic Acid), offering opportunities for precision repurposing.
Conclusions:
The GARD pipeline demonstrates a genomics-driven, network-informed framework for systematic drug repurposing in HNC. HPV stratification enhances precision, literature-based validation strengthens confidence, and integrated drug mapping enables refinement of existing therapies and discovery of novel candidates for personalized treatment strategies.
Code Availability:
The full implementation of the GARD pipeline, including preprocessing scripts, statistical analysis modules, and visualization tools, is publicly available on GitHub at: https://github.com/pvtanike/Genomic-Landscape-Based-Drug-Repurposing.git.
Insights
The GARD pipeline identifies new drug repurposing candidates for head and neck cancer (HNC) by integrating genomic data and network analysis. This approach accelerates the discovery of personalized treatments, offering cost-effective therapeutic options.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Head and neck cancer (HNC) is a globally prevalent malignancy with limited treatment outcome improvements.
- Drug repurposing offers a cost-effective strategy to identify novel therapeutic options using existing drugs with known safety profiles.
Purpose of the Study:
- To develop and implement the GARD (Genomic Alteration-based Repurposing for Drugs) pipeline for identifying drug repurposing candidates in HNC.
- To leverage genomic and network-based approaches for uncovering precision medicine strategies in HNC.
Main Methods:
- The GARD pipeline integrates multi-omics data (CNV, somatic mutations) from TCGA, stratified by HPV status.
- Risk-associated genes were identified, expanded via protein-protein interaction (PPI) networks, and literature-validated using LLM analysis of PubMed.
- Validated genes and network neighbors were mapped against DrugBank to identify significant drug-gene associations.
Main Results:
- Identified significant HNC-associated genes (e.g., PIK3CA, SOX2, TP53) across HPV+ and HPV- subgroups.
- Network expansion identified additional targetable genes (e.g., EGFR, ERBB2, FGFRs).
- Drug-gene mapping revealed candidates in clinical trials and novel repurposing agents (e.g., Afatinib, Cabozantinib, Amuvatinib, Quercetin, Aspirin).
Conclusions:
- The GARD pipeline provides a genomics-driven, network-informed framework for systematic drug repurposing in HNC.
- HPV stratification, literature validation, and integrated drug mapping enhance precision and accelerate the discovery of personalized HNC treatments.
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