Evidence map›Paper›PMID 42747540›Full record

ReviewAnalytical and bioanalytical chemistry2026

Emerging technologies in the spatial proteomics landscape.

Matthew Heck, Jia Guo

Abstract readReview
PubMed Publisher
In one paragraph

Review in Analytical and bioanalytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Matthew HeckBiodesign Institute & School of Molecular Sciences, Arizona State University, Tempe, AZ, 85287, USA.
Jia GuoBiodesign Institute & School of Molecular Sciences, Arizona State University, Tempe, AZ, 85287, USA. jguo57@asu.edu.ORCID http://orcid.org/0000-0001-8036-5349

Funding

NIGMS NIH HHS 1R01GM127633
6 · The paper itself

Abstract

Spatial proteomics has rapidly advanced the ability to measure protein expression, localization, and tissue organization directly within intact biological specimens. Unlike bulk proteomics or transcript-centered approaches, spatial protein imaging can capture cell-to-cell heterogeneity, local signaling states, and multicellular tissue structure while preserving histologic context. This review examines the major technology classes shaping the field, with primary emphasis on multiplexed in situ protein imaging. We discuss region-of-interest digital spatial profiling, mass spectrometry-based spatial proteomics, iterative immunofluorescence, and signal amplification strategies, and compare their major strengths and limitations in the context of sensitivity, multiplexing capacity, spatial resolution, sample throughput, and tissue compatibility. Particular attention is given to how different signal-reset and amplification designs have expanded fluorescence-based imaging beyond the limits of conventional low-plex immunostaining. We also summarize major biological applications in cancer, immunology, and neurology, where spatial proteomics has enabled the identification of tissue architecture, cellular neighborhoods, and disease-associated protein states that are difficult to resolve by nonspatial methods. Finally, we outline the principal limitations and future directions shaping the field, including incomplete proteome coverage, multimodal spatial integration, image-analysis challenges, assay reproducibility, and translation into standardized biological and clinical workflows. Overall, multiplexed in situ protein imaging is becoming an increasingly important framework for linking molecular state to tissue organization in both biological research and translational pathology.

Indexed as

Cleavable fluorescent antibodiesCleavable fluorescent tyramideFormalin-fixed paraffin-embedded tissuesIterative immunofluorescenceSignal amplificationSingle-cell spatial proteomics

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.