Evidence map›Paper›PMID 41235771›Full record

ReviewEuropean journal of immunology2025

Spatial Immunometabolism: Integrating Technologies to Decode Cellular Metabolism in Tissues.

Felix J Hartmann

Abstract readReview
In one paragraph

Review in European journal of immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Resetting immunometabolic set points in autoimmune disease.Journal of translational autoimmunity · 2026
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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.

Felix J HartmannGerman Cancer Research Center (DKFZ), Systems Immunology & Single-Cell Biology, Heidelberg, Germany.ORCID https://orcid.org/0000-0002-4174-2276

Funding

European Research Council (ERC), European Union's Horizon 2020 research and innovation program 101116823Hector FoundationHelmholtz Initiative and Networking Fund VH-NG-1605Schwiete FoundationState Parliament of Baden-Württemberg for the Innovation Campus Health and Life Science Alliance Heidelberg-Mannheim
6 · The paper itself

Abstract

The metabolic programs of immune cells influence their activation, differentiation, and effector functions. While much of immunometabolism has focused on cell-intrinsic regulation, it is now clear that metabolic activity is profoundly influenced by the surrounding tissue environment. In tumors and other inflammatory settings, immune cells are shaped by nutrient gradients, hypoxia, and immunoregulatory metabolites, factors that are spatially heterogeneous and often poorly captured by traditional methods. This review highlights recent technological advances that enable spatially resolved analysis of immune metabolism, with an emphasis on multimodal integration and cancer as a model system. Mass spectrometry imaging (MALDI, DESI), high-resolution platforms like SIMS, and vibrational imaging approaches such as Raman microscopy enable direct visualization of metabolites in tissue. Transcriptomic and proteomic data can be used to infer metabolic states, and computational models are being developed to integrate these diverse data layers. Together, these technologies are transforming the study of immunometabolism from dissociated cells to the intact tissue context. Key challenges remain in resolution, annotation, and data integration, but spatial immunometabolism holds particular promise for illuminating mechanisms of immune regulation in health and disease.

Indexed as

Mass SpectrometryMultiomicsAnimalsHumansMetabolomicsMicroscopySpectrometry, Mass, Matrix-Assisted Laser Desorption-Ionizationantitumor immunitycellular metabolismimmunometabolismmultiplexed imagingspatial biologysystems immunologytumor microenvironment

Identifiers

PMID41235771
PMCPMC12617045

What OpenQuestion holds

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LicenceCC BY
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.