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Proximity-guided graph learning reveals tumour-associated proximity antigens.

Created on 10 Sep 2026

Authors

Cody Scandore, Clare F Malone, Christopher K May, Anna K de Regt, Jeff Guernsey, Hayley Ma, Noah Dephoure, Ben Setter, Rebecca A Howell, Kendall R Johnson, Carol L Farr, Sophia Romero, Lydia Vignale, Tali Vittum, Emma Dawson, Tsadik Habtetsion, Francesca Nardi, Brian Woodruff, Martin Mathay, Julia Swanson, Mikaela Rusnak, Quynh Ton, Payam E Farahani, Robert W Gene, Jason Misurelli, Zach Caldwell, Hengyu Xu, Michael Hornsby, Marc A Gavin, Heath E Klock, Ertan Eryilmaz, Pamela M Holland, Scott A Lesley, Rob C Oslund, Olugbeminiyi O Fadeyi

Published in

Nature. Sep 09, 2026. Epub Sep 09, 2026.

Abstract

The spatial organization of membrane proteins is an underexplored dimension of cell surface biology1,2. Spatial proximity shapes cellular function and therapeutic targetability2,3, yet efforts to identify tumour-associated antigens (TAAs) have largely focused on expression alone4. Here, we developed an industrialized surface protein proximity-mapping workflow to interrogate TAAs within their membrane microenvironments. Using this workflow, we generated 248 proximity maps across 12 receptor tyrosine kinases and 28 tumour cell systems. The resulting atlas enabled the development of MetaMap, a correlation-based analytical framework that defines spatial protein communities and infers conserved proximity relationships among non-targeted proteins, and establishes the concept of tumour-associated proximity antigens (TAPAs), a class of co-targets defined by disease-specific spatial proximity to TAAs rather than expression alone. Integrating these proximity-derived relationships within a multimodal prioritization framework, we identified and validated EGFR-CDCP1 as a TAA-TAPA pair that enhances tumour cell killing across therapeutic modalities. Together, this work advances disease-associated membrane proximity as a guiding principle for the design of precision multispecific therapeutics.

PMID:
42717092
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.

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