Graph attention networks for predicting drug-gene association of glucocorticoid in oral squamous cell carcinoma: A comparison with GraphSAGE
Monal Yuwanati, Santhanamari Thiyagarajan, Kranti Kiran Reddy Ealla, Yash Jain, Pradeep Kumar Yadalam, Senthil Murugan Mullainathan, Anima Nanda, Samir Sahoo, Daniel Ejim Uti
Abstract
Background
The present study evaluates the effectiveness of Graph Attention Networks (GAT) and GraphSAGE in predicting drug-gene interactions for glucocorticoids in oral squamous cell carcinoma, thereby aiding in developing better treatment strategies.
Introduction
Oral squamous cell carcinoma (OSCC) is a prevalent malignancy worldwide, with a significant prevalence in regions with high tobacco and alcohol consumption [1]. OSCC is responsible for nearly 3% of all cancers, with rates that are considerably higher in regions such as Southeast Asia, according to global cancer statistics [2].
Materials and method
Dataset preparation
Using the probe drugs tool [19], we retrieved drugs and genes associated with glucocorticoid receptors, and this data consists of id, gene name, target name, and biochemical activity. Using Cytoscape, an interactome was created, and with the cytohubba plugin, top hub drugs and genes were identified using the maximum clique centrality method (Fig 1).
Results
The network statistics include 174 nodes, 409 edges, an average number of neighbours, a diameter of 6 steps, a radius of 3, and a characteristic path length of 3.14 steps. The clustering coefficient indicates no clustering, and the density indicates a sparse network. The network heterogeneity indicates greater diversity in node connections, while the network centralization indicates moderate centrality. The network has only one connected component, confirming its full connectivity without isolated subgroups.
Discussion
OSCC remains a significant global health issue because of its increasing incidence and associated morbidity and mortality [20]. OSCC is significantly affected by various genetic and molecular determinants, particularly those linked to glucocorticoids and sex hormones, highlighting the intricate interplay between hormonal regulation and oncogenesis [12,13]. The role of glucocorticoids in OSCC is notable as these steroids, produced by the adrenal glands, can modulate the immune response and inflammation, potentially affecting tumor growth and progression.
Conclusion
The complex interrelationship among genetic constituents, hormonal signaling, and pharmacological interventions reveals a convoluted network governing OSCC development and progression through glucocorticoid receptors. By advancing our understanding of these interactions, we can refine therapeutic approaches, paving the way for personalized and more effective treatment regimens for patients confronting this challenging malignancy. Appreciating this complexity may improve survival outcomes and quality of life for individuals impacted by OSCC.
Citation: Yuwanati M, Thiyagarajan S, Ealla KKR, Jain Y, Yadalam PK, Mullainathan SM, et al. (2025) Graph attention networks for predicting drug-gene association of glucocorticoid in oral squamous cell carcinoma: A comparison with GraphSAGE. PLoS One 20(7): e0327619. https://doi.org/10.1371/journal.pone.0327619
Editor: Suyan Tian, The First Hospital of Jilin University, CHINA
Received: February 18, 2025; Accepted: June 10, 2025; Published: July 3, 2025
Copyright: © 2025 Yuwanati et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Available as supplementary material attached to this submission.
Funding: The author(s) received no specific funding for this work.
Competing interests: No competing interest.
