Grant Duncan Stewart

TERRA is a foundation model for spatial transcriptomics that predicts tissue behavior under perturbation and identifies multi-scale biological insights across tissues.

This paper presents a network medicine framework integrating multi-modal data to identify therapeutic targets in clear cell renal cell carcinoma, recovering established targets and predicting five candidates, with ENO2 inhibition showing the strongest anti-tumour effect.

This study shows SET1B maintains HIF activity in ccRCC, correlates with disease progression, and is a target for HIF-2 inhibitors.

This study identifies HIF1A as a key inhibitor of VHL null cell fitness and shows that combined VHL/HIF1A inactivation can confer resistance to PROTAC-based therapies.

The paper assesses neoadjuvant axitinib response in RCC with VTT using multiparametric analysis and identifies angiogenic and immune predictors of treatment response.

A multi-regional single-cell study of kidney tumours reveals clonotypic heterogeneity, immune cell exhaustion, and potential therapeutic targets through transcriptomic and exomic analysis.