Evidence map›Paper›PMID 37543576›Full record

ArticleBMC cancer2023

Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma.

Jinna Li, Qing Guo, Rui Xing

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 8% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Rewriting the RNA code: an mFrontiers in immunology · 2026
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. EMP3: A promising biomarker for tumor prognosis and targeted cancer therapy.Cancer biomarkers : section A of Disease markers · 2024
    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

3 authors at 1 institution in 1 country.

Jinna LiDepartment of Oncology, Shengjing Hospital of China Medical University, Shenyang, 110000, China.
Qing GuoDepartment of Neurosurgery, The First Hospital of China Medical University, Shenyang, 110000, China. cmuguoqing@qq.com.
Rui XingDepartment of Oncology, Shengjing Hospital of China Medical University, Shenyang, 110000, China. xingr@sj-hospital.org.
China Medical University · CN

Funding

Natural Science Foundation of Liaoning Province 2020-BS-117Natural Science Foundation of Liaoning Province 2022-MS-11
6 · The paper itself

Abstract

backgroundLow grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be explored.

methodsFour independent glioma cohorts comprising 1,853 patients were enrolled for bioinformatics analysis. We used ConsensusClusterPlus to cluster patients into four different immune subtypes based on immune infiltration. The immune-infiltration signature (IIS) was constructed by LASSO regression analysis. Somatic mutation and copy number variation (CNV) analyses were performed to explore genomic and transcriptomic traits in the high- and low- risk groups. The correlation between response to programmed cell death 1 (PD-1) blockade and the IIS risk score was confirmed in an in vivo glioma model.

resultsPatients were clustered into four different immune subtypes based on immune infiltration, and the high immune infiltration subtype was associated with worse survival in LGG. The high immune infiltration subtype had stronger inflammatory response, immune response and immune cell chemotaxis. The IIS, consisting of EMP3, IQGAP2, METTL7B, SLC1A6 and TNFRSF11B, could predict LGG malignant progression, which was validated with internal clinical samples. M2 macrophage infiltration positively correlated with the IIS risk score. The high-risk group had significantly more somatic mutations and CNVs. The IIS risk score was related to immunomodulatory molecules and could predict immunotherapy clinical benefit. In vivo, immunotherapy-sensitive glioma model exhibited higher IIS risk score and more infiltration of immune cells, especially M2 macrophages. The IIS risk score was decreased in an immunotherapy-sensitive glioma model after anti-PD1 immunotherapy.

conclusionDifferent immune subtypes of LGG had unique immune cell infiltration characteristics, and the high immune infiltration subtype was associated with immunosuppressive signaling pathways. A novel IIS prognostic model based on immune infiltration status was constructed for immunophenotypic classification, risk stratification, prognostication and immunotherapy response prediction in LGG.

Indexed as

DNA Copy Number VariationsGliomaHumansImmunomodulationImmunotherapyMembrane GlycoproteinsPrognosisras GTPase-Activating ProteinsTumor MicroenvironmentEMP3 protein, humanIQGAP2 protein, humanMembrane Glycoproteinsras GTPase-Activating ProteinsGliomaImmune cell infiltrationImmune checkpoint inhibitorPrognosis

Identifiers

PMID37543576
PMCPMC10403952
OpenAlexW4385616388

What Socratic 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 Socratic graph.