Evidence map›Paper›PMID 39924768›Full record

ArticleOncoimmunology2025

Metabolic heterogeneity in tumor cells impacts immunology in lung squamous cell carcinoma.

Qian Wang, Na Sun, Chaoyang Zhang, Thomas Kunzke, Philipp Zens, Annette Feuchtinger, Sabina Berezowska, Axel Walch

Abstract read
In one paragraph

Article in Oncoimmunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Uridine-Based PET/NIRF Dual-Modality imaging for precision tumor diagnosis and surgery.European journal of nuclear medicine and molecular imaging · 2026
    Article
  4. Review
  5. Review
  6. [Applications and Advances of Metabolomics in Lung Cancer Research].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025
    Review
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

8 authors.

Qian WangResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Na SunResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Chaoyang ZhangResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Thomas KunzkeResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Philipp ZensInstitute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
Annette FeuchtingerResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Sabina BerezowskaInstitute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
Axel WalchResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic processes are crucial in immune regulation, yet the impact of metabolic heterogeneity on immunological functions remains unclear. Integrating metabolomics into immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. To elucidate such insight in lung squamous cell carcinoma (LUSC), we analyzed 106 LUSC tumor tissues. We performed high-resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to obtain spatial metabolic profiles, and immunohistochemistry to detect tumor-infiltrating T lymphocytes (TILs). Unsupervised k-means clustering and Simpson's diversity index were employed to assess metabolic heterogeneity, identifying five distinct metabolic tumor subpopulations. Our findings revealed that TILs are specifically associated with metabolite distributions, not randomly distributed. Integrating a validation cohort, we found that heterogeneity-correlated metabolites interact with CD8+ TIL-associated genes, affecting survival. High metabolic heterogeneity was linked to worse survival and lower TIL levels. Pathway enrichment analyses highlighted distinct metabolic pathways in each subpopulation and their potential responses to chemotherapy. This study uncovers the significant impact of metabolic heterogeneity on immune functions in LUSC, providing a foundation for tailoring therapeutic strategies.

Indexed as

Carcinoma, Squamous CellLung NeoplasmsLymphocytes, Tumor-InfiltratingAgedCD8-Positive T-LymphocytesFemaleHumansMaleMetabolomeMetabolomicsMiddle AgedSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationImmunologylung cancermetabolic heterogeneitymetabolic tumor subpopulationSpatial metabolomics

Identifiers

PMID39924768
PMCPMC11812363

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.