On September 9, 2026 InduPro, Inc., a biotechnology company harnessing protein proximity to create novel therapeutics for cancer and autoimmune diseases, reported the publication in Nature of research establishing the spatial organization of cell-surface proteins as a new and therapeutically actionable dimension of disease biology.
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The study, Proximity-Guided Graph Learning Reveals Tumor-Associated Proximity Antigens, describes an integrated approach developed by InduPro to systematically map the nanoscale neighborhoods surrounding proteins on the surface of tumor cells, identify unique disease-associated spatial relationships, and translate those relationships into novel therapeutic strategies. The work defines Tumor-Associated Proximity Antigens, or TAPAs, a new class of co-targets distinguished not simply by protein co-expression, but by their disease-associated spatial proximity to another therapeutically relevant cell-surface antigen.
"By industrializing high-resolution proximity mapping and combining it with computational approaches that allow us to understand protein neighborhoods at scale, we can uncover biology that is invisible to expression-based approaches alone. TAPAs give us a new class of targets and, importantly, a new framework for designing medicines around relationships that are enriched in disease context," said Scott Lesley, Ph.D., President and Chief Scientific Officer of InduPro. "IDP-001, our lead clinical program in squamous and non-squamous solid tumors, is a powerful example of that translation, taking a newly uncovered protein pair and translating it into a highly differentiated therapeutic."
Mapping a previously hidden layer of cell-surface biology
Proteins on the surface of cells exist within organized, dynamic neighborhoods that influence signaling, trafficking and therapeutic response. Yet conventional target-discovery approaches have largely focused on which proteins are present and how they are expressed, leaving this spatial dimension of biology relatively unexplored.
The work builds on protein proximity-based mapping technology invented by Rob Oslund, Ph.D., Vice President of Platform Technology, and Niyi Fadeyi, Ph.D., Vice President of Chemical Sciences, both members of InduPro’s founding team. The technology was subsequently industrialized and expanded at InduPro into a scalable discovery platform.
In the Nature study, researchers applied this approach at scale across diverse tumor systems, creating a rich dataset of cell-surface protein neighborhoods and demonstrating that proximity reveals biological information beyond expression alone.
InduPro subsequently developed MetaMap to move beyond individual proximity maps and extract recurring spatial relationships across large datasets. By integrating proximity signatures across targets and biological contexts, MetaMap reveals protein communities and predicts spatial relationships even when proteins have not been directly mapped against one another. Graph-based machine learning further enables these relationships to be prioritized for therapeutic discovery.
"What began as a technology for labeling proteins within defined nanoscale environments has become something much broader: a way to systematically interrogate the spatial organization of the cell surface," said Rob Oslund, Ph.D., Vice President of Platform Technology at InduPro. "The critical step was industrializing the technology so we could generate these datasets at scale. MetaMap takes that evolution further by allowing us to learn across the collective dataset, moving beyond individual experiments toward a predictive understanding of protein relationships and creating an increasingly powerful foundation for therapeutic discovery."
TAPAs create a new class of therapeutic targets
A central advance described in the publication is the definition of Tumor-Associated Proximity Antigens, or TAPAs.
Rather than defining targets solely by differential expression, TAPAs are identified through disease-associated spatial relationships between proteins on the cell surface. These relationships create opportunities to design multispecific medicines that recognize a disease-associated protein neighborhood rather than relying on either antigen independently.
This approach has the potential to expand the universe of therapeutically actionable targets, including proteins that may not be sufficiently tumor-selective on their own, while creating new opportunities to improve selectivity, internalization and therapeutic activity through proximity-driven drug design.
"TAPAs represent a fundamentally different way to think about therapeutic targets," said Niyi Fadeyi, Ph.D., Vice President of Chemical Sciences at InduPro. "Rather than only asking which proteins are expressed in disease, we can also ask which proteins come together in a disease-specific context and whether that relationship creates a therapeutic opportunity. We believe this opens an important new dimension of target space and provides a foundation for designing medicines with differentiated selectivity and activity. Seeing this concept progress from the original science to therapeutic programs in the clinic provides validation of the approach and what we believe proximity biology can unlock."
Translating Proximity Biology into Medicines
The study demonstrates that proximity-defined relationships can be translated directly into therapeutic design. Using spatial relationships identified through the platform together with biological and translational data, InduPro demonstrated that co-targeting proximity-defined antigen pairs can produce differentiated tumor cell internalization and killing across therapeutic modalities.
These discoveries established the scientific foundation for InduPro’s proximity-guided therapeutic pipeline, including IDP-001, the Company’s lead bispecific antibody-drug conjugate, which has advanced into Phase 1 clinical development.
The progression from proximity-labeling technology, to industrialized spatial datasets, to MetaMap and computational prediction, to TAPAs and ultimately therapeutic candidates represents the broader vision of InduPro’s platform: transforming spatial relationships between proteins into a systematic source of new targets and differentiated medicines.
The article is available in Nature at View Source
(Press release, InduPro, SEP 9, 2026, View Source [SID1234670701])