Evidence map›Paper›PMID 42094160›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Immune Subtypes and Survival in Patients with Primary Glioma.

Yu Fang, Jiwoong Kim, Zachary J Thompson, Youngchul Kim, Harshan Ravi, Asim Mazin, Carlos M Moran Segura, Jonathan V Nguyen, Robert J Macaulay, Filippo Veglia and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

14 authors.

Yu FangDept. of Mathematics & Statistics, University of South Florida, Tampa, FL, USA.
Jiwoong KimDept. of Mathematics & Statistics, University of South Florida, Tampa, FL, USA.
Zachary J ThompsonDept. of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL 33612, USA.
Youngchul KimDept. of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL 33612, USA.
Harshan RaviDept. of Metabolism & Physiology, Moffitt Cancer Center, Tampa, FL 33612, USA.
Asim MazinDept. of Metabolism & Physiology, Moffitt Cancer Center, Tampa, FL 33612, USA.
Carlos M Moran SeguraAdvanced Analytical and Digital Laboratory, Moffitt Cancer Center, Tampa, FL, USA.
Jonathan V NguyenAdvanced Analytical and Digital Laboratory, Moffitt Cancer Center, Tampa, FL, USA.
Robert J MacaulayDept. of Anatomic Pathology, Moffitt Cancer Center, Tampa, FL 33612, USA.
Filippo VegliaGenome Regulation and Cell Signaling Program, The Wistar Institute, Philadelphia, PA, USA.
Reid C ThompsonDept. of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA.
Sajeel A ChowdharyTampa General Hospital Cancer Center, Tampa General Hospital, Tampa, FL 33606, USA.
Kathleen M EganDept. of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL 33612, USA.
Natarajan RaghunandDept. of Metabolism & Physiology, Moffitt Cancer Center, Tampa, FL 33612, USA.ORCID 0000-0002-8893-7687

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI John L. Cleveland · 1998 to 2026
$93.5M
Metabolic and molecular regulation of myeloid cell functions in brain cancerR01NS131912 · NINDS · WISTAR INSTITUTE · PI Filippo Veglia · 2023 to 2026
$1.6M
NCI NIH HHS P30 CA076292NINDS NIH HHS R01 NS131912
6 · The paper itself

Abstract

Background: Gliomas are heterogeneous tumors with poor outcomes following current therapies, including immunotherapy. The tumor microenvironment (TME) is a critical determinant of therapeutic response in gliomas. We have classified the immune TME of gliomas by multiplex immunofluorescence (mIF). Methods: Tissue taken at initial resection from 354 patients with newly-diagnosed glioma grades 2-4 were analyzed using three mIF panels of markers for T, B, and myeloid cells. Tumor cores were characterized by the relative abundances of: (i) 15 primary immune phenotypes, (ii) 96 secondary immune phenotypes, and, (iii) 29 biologically meaningful multi-marker immune phenotypes. Results: Using unsupervised cluster analysis of WHO grade 4 gliomas we identified four subtypes α, β, γ, and δ that were internally reproducible. Immune subtype α was characterized by high abundance of antigen-presenting cells (APCs) and low levels of MHC II- monocytes. Subtype β was high in regulatory T cells and myeloid cells, but low in lymphocytes with effector functions. Subtype γ displayed high abundance of immune cell phenotypes, particularly lymphocytes with effector or helper functions. Subtype δ was low in lymphoid and myeloid immune phenotypes and APCs, with poorer outcomes. Grade 3 tumors could also be classified into α, β, γ, and δ subtypes, indicating generalizability of these immune TME subtypes across high grade gliomas. Conclusions: We have identified internally reproducible criteria for classifying gliomas according to the immune microenvironment, findings that could aid our understanding of the natural progression of low- and high-grade gliomas and inform the rational application of immune-oncologic therapeutic interventions.

Indexed as

gliomaimmune subtypeslymphoid cellsmyeloid cellssurvival analysis

Identifiers

PMID42094160
PMCPMC13142596

What OpenQuestion holds

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Registered trials

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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.