Advancing Disease Research Through Spatial Proteomics

Spatial proteomics is a broad term that encompasses many techniques and technologies that use advanced imaging and molecular profiling methods to map dozens of proteins simultaneously within their native cellular and tissue architecture, enabling researchers to decode immune landscapes, tumor microenvironments, and other complex biological systems.

“Spatial proteomics is fundamentally changing how we study protein biology within intact tissues and specimens,” said Erika Leonard, Director of R&D at Vector Laboratories. She noted that these technologies allow researchers to map protein localization with high resolution, surpassing traditional bulk approaches by revealing how protein expression and post-translational modifications vary across specific cellular compartments and tissue microenvironments.

Why spatial context matters in proteomics

Although some of these methods have existed for years, spatial proteomics is now achieving broad recognition.¹ Nikhil Rao, Chief Commercial Officer at Syncell, explained that it is gaining significant momentum because it connects the “where” to the “what,” revealing what proteins are present and where they are located within complex tissues. This added layer of information is especially valuable in heterogeneous environments where visualizing changes across tissue regions helps connect pathology with downstream analytical methods. Rao also noted that spatial proteomics is gaining ground over transcriptomics because it focuses on proteins, the primary targets of most drugs, and therefore provides more clinically actionable insights.

The value of this spatial context is especially clear in cancer research. Rebecca Critchley-Thorne, Ph.D., Vice President of Research & Development at Castle Biosciences, explained that it enables detailed characterization of tumors and the interactions between tumor cells, stromal cells, and diverse immune populations. This level of analysis is essential for detecting early signs of disease progression, even when those signals are subtle, localized, and driven by multiple factors. Critchley-Thorne added that pre-cancerous tissues often show high levels of heterogeneity and background noise from inflammation or mutations, which can obscure important changes in bulk analyses. Spatial proteomics preserves tissue architecture and helps identify meaningful signals within this complexity, making it a valuable tool for improving risk assessment and supporting clinical decision making.

Spatial proteomics tools

Recently, the spatial proteomics toolbox has been rapidly expanding, offering researchers a range of technologies to study proteins or their modifications in tissue context. One widely used method is Imaging Mass Cytometry™ (IMC™), which enables highplex, spatially resolved protein analysis by imaging over 40 markers in a single scan using metal-labeled antibodies, explained Jennifer Ellis, MS, Director of Technical and Scientific Content at Standard BioTools. This approach avoids common fluorescence limitations such as spectral overlap and autofluorescence, while providing a more quantitative approach with a wider dynamic range and flexible imaging modes to enable either high-throughput or highly detailed studies. “Each marker is a quantitative assay in its own right,” noted Ellis, allowing researchers to explore tissue organization and cell interactions without repeated staining cycles. She added that IMC reagents and stained slides are stable over many years, which supports long-term studies and efficient workflows.

Other platforms are pushing spatial proteomics to the subcellular level, like Syncell’s Microscoop Mint. Rao explained that this system uses a two-photon laser, epifluorescence microscope, and photochemical reagents to tag and isolate proteins from regions as small as 350 nanometers. The isolated proteins are analyzed by mass spectrometry, allowing researchers to profile the entire proteome within precise areas of interest. “You don’t need to know what you’re looking for,” Rao stated, highlighting the technology’s potential for discovery-driven research and novel target identification. Additionally, Microscoop is compatible with diverse tissue types and can be applied to both fresh and preserved samples, which allows flexible experimental design across a wide range of research areas.

Spatial proteomics also includes tools for studying post-translational modifications, which are key to understanding cell signaling and disease mechanisms. Leonard highlighted that Vector Laboratories develops solutions to study protein-specific glycosylation and protein-glycan interactions in situ. Their workflows pair highly validated lectins with proximity ligation assay (PLA) technology to confirm glycan-protein proximity within intact tissues and deliver higher-confidence detection than spatial overlap alone. “This spatially resolved insight is critical for understanding biological processes such as tumor progression, immune evasion, and biomarker discovery, where both protein expression and glycosylation states are highly dynamic and tightly regulated within specific tissue microenvironments,” stated Leonard.

Translational applications and disease discovery

Advances in spatial proteomics are creating new opportunities to identify biomarkers and pathways that drive disease progression. For instance, Castle Biosciences applies spatial proteomics and morphology assessments in its clinically validated TissueCypher test for patients with Barrett’s esophagus, a precursor to esophageal adenocarcinoma. In this condition, early cancer risk can be signaled by localized shifts in specific biomarkers, such as HER2/neu or HIF1α, that standard pathology may overlook. The TissueCypher test uses multiplexed fluorescence imaging and quantitative analysis to detect these subtle, spatially organized protein patterns and help identify patients at higher risk of progression.² By identifying these changes earlier, clinicians can have more precise risk stratification and guide decisions on surveillance and preventive treatment.

Along with clinical testing, spatial proteomics is advancing basic and translational research. Researchers at the University of Stuttgart used Syncell’s Microscoop technology to study triple-negative breast cancer (TNBC) by photolabeling and isolating PRC2 nuclear bodies for mass spectrometry analysis.³ This approach led to the discovery of peptide candidates involved in chromatin regulation, including PHF19. While previously unstudied in breast cancer, PHF19 was found to play a key role in nuclear body formation and promote metastasis. Knocking out PHF19 dissolved these nuclear structures and reduced cell motility, suggesting it contributes to the metastatic behavior of TNBC cells.

Spatial proteomics is also being applied to understand disease progression at the single-cell level. In another example, researchers applied multiplex IMC to analyze over 1,000 tumor regions from primary breast cancers and matched lymph node metastases in 205 patients.⁴ The study revealed extensive phenotypic variability between primary and metastatic sites, with disseminated tumor cells often differing from the clinical disease subtype. Certain single-cell phenotypes and spatial arrangements in lymph node metastases correlated strongly with patient survival, and elevated p53 and GATA3 expression provided prognostic value beyond standard clinical classifiers.

In addition to identifying spatial patterns of protein expression, researchers are also using spatial methods to study post-translational modifications. A recent study examined whether cancer-specific glycosylation patterns of prostate-specific antigen (PSA) could improve prostate cancer diagnosis.⁵ Using an in situ proximity ligation assay with a PSA-specific antibody and glycan-binding lectins from Vector Laboratories, researchers found that certain PSA glycoforms were significantly enriched in cancer tissue, while total PSA levels were higher in benign regions. These findings confirm that PSA glycosylation is frequently altered in prostate cancer and support the potential for serum-based tests to improve diagnostic accuracy.

Future directions in spatial proteomics

As these technologies advance, spatial proteomics is becoming increasingly multiomic. Rao sees the future of the field as being shaped by the convergence of traditionally separate disciplines, including pathology, imaging, mass spectrometry, and sequencing. This integration is broadening the definition of “spatial” and bringing established tools into new contexts. He noted that this merging of approaches, driven by multiple companies, is creating a unique and promising space for biological discovery.

Critchley-Thorne also highlighted the potential of integrated strategies, particularly in precision medicine. “I see significant promise in integrating spatial proteomics with other omics approaches, such as genomics, epigenomics, and transcriptomics,” she said. “Evaluating multiple omic layers could provide a more complete picture of a patient’s unique biology that could indicate risk of developing cancer, risk of cancer recurrence, or response to therapies.”

Together, these insights show how spatial proteomics can drive translational and clinical advances, while also deepening discovery through integration with other omics.

References

1. Method of the Year 2024: spatial proteomics. Nat Methods 21, 2195–2196 (2024).

2. Diehl DL, Khara HS, Akhtar N, Critchley-Thorne RJ. TissueCypher Barrett's esophagus assay impacts clinical decisions in the management of patients with Barrett's esophagus. Endosc Int Open. 2021;9(3):E348-E355. 

3. Pelzer N, Lukic T, Ge W, et al. PHF19 drives PRC2 sub-nuclear compartmentalization to promote motility in TNBC cells. bioRxiv. Published online March 14, 2025. 

4. Fischer JR, Jackson HW, de Souza N, et al. Multiplex imaging of breast cancer lymph node metastases identifies prognostic single-cell populations independent of clinical classifiers. Cell Rep Med. 2023;4(3):100977. 

5. Koistinen H, Merivirta RM, Lehto TP, et al. Altered Glycosylation of PSA in Prostate Cancer Tissue. Prostate. Published online July 9, 2025.