Evidence map›Paper›PMID 42015540›Full record

ReviewImmunoHorizons2026

Spatial instruction of tissue immunity.

Miguel Reina-Campos

Abstract readReview
In one paragraph

Review in ImmunoHorizons, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. ASPIRE to new horizons.ImmunoHorizons · 2026
    Article
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

1 author.

Miguel Reina-CamposLa Jolla Institute for Immunology, La Jolla, CA 92037, United States.ORCID 0000-0002-0704-4271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tissue immunity must meet the architectural and physiological demands of each organ, from viral entry in the respiratory tract to immune surveillance in the gastrointestinal mucosa. Recent advances in spatial technologies and computational biology now allow us to map entire immune communities in situ, capturing not only their composition but their positional logic, connectivity patterns, and local transcriptional landscapes. These tools are revealing that immune function is not evenly distributed but is patterned along regionalized cytokine gradients, anatomical landmarks, and physical niches that confer specialized capabilities. Understanding the principles driving this spatiotemporal logic is essential to decipher how immune networks are built, maintained, and subverted in disease. To this end, network topology analyses, immune allocation plots, and spatial reference frameworks are beginning to define the "wiring diagrams" of immunity, while emerging perturbation-coupled spatial approaches enable causal dissection of the signals that program location-specific phenotypes. These insights have broad implications, from explaining why certain organs resist tumor initiation or metastasis, to revealing metabolic constraints on immune cells in solid tumors, to understanding clonal lymphocyte dynamics in health and disease. Here, we synthesize recent conceptual and technological advances that are transforming how we study tissue immunity; highlight exemplar findings from infection, cancer, and autoimmunity; and outline the experimental and computational innovations needed to bridge key knowledge gaps. We propose that the next phase of immunology will require integrating multiomic, high-resolution spatial data with predictive models of immune behavior to forecast disease risk, design personalized therapies, and ultimately deploy immune protection at the right place and time.

Indexed as

ImmunityNeoplasmsAnimalsComputational BiologyHumansImmunoinformaticsSpatial Transcriptomicscancerinfectionspatial transcriptomicsT cellstissue immunity

Identifiers

PMID42015540
PMCPMC13168768

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.