Evidence map›Paper›PMID 42387647›Full record

ArticleActa neuropathologica communications2026

MET-associated immune prognostic signature predicts survival and guides personalized therapy in glioma.

Ying Zhang, Chengjun Zheng, Qiaodong Chen, Wenlu Tan, Fei Liu, Zheng Fang, Hanxiao Zhou, Changyuan Ren, Jinhao Zhang, Changlin Yang and 5 more

Abstract read
In one paragraph

Article in Acta neuropathologica communications, 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

15 authors.

Ying Zhang *Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.ORCID http://orcid.org/0000-0002-7613-6188
Chengjun Zheng *Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.ORCID http://orcid.org/0000-0001-8027-6557
Qiaodong ChenBeijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Wenlu TanBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Fei LiuBeijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Zheng FangBeijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Hanxiao ZhouBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Changyuan RenBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Jinhao ZhangBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Changlin YangBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Menghui XuBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Lingxiang WuBeijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Ji ShiBeijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Zheng ZhaoBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Zhaoshi BaoBeijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China. baozhaoshittyy@163.com.ORCID http://orcid.org/0000-0003-4922-4470

Funding

Beijing Research Ward Excellence Program BRWEP2024W032040204National Natural Science Foundation of China 82573705National Science and Technology Major Project for Innovative Drug Development No. 2026ZD1804600, No. 2026ZD1804601Natural Science Foundation of Beijing Municipality 7262011
6 · The paper itself

Abstract

Glioma is an aggressive malignancy characterized by an immunosuppressive tumor microenvironment (TME) that drives therapeutic resistance. MET alterations promote tumor progression and immune evasion, yet their clinical implications in glioma immunotherapy remain unclear. Here, we integrated multi-omics data from four independent cohorts to establish a MET-associated immune prognostic signature (MIPS) comprising 18 immune-related genes. MIPS effectively stratified glioma patients into low- and high-MIPS subgroups. High-MIPS patients exhibited significantly poorer overall survival than low-MIPS patients across all cohorts and was an independent prognostic factor independent of clinicopathological and molecular features. High-MIPS scores correlated with increased M2 macrophage infiltration, elevated B7-H3 expression, and higher TIDE scores, indicating immunotherapy resistance. Bioinformatic prediction and patient-derived organoid assays verified that low-MIPS tumors were sensitive to multiple targeted drugs (e.g., Axitinib, AZD-8055, Gefitinib, and Lenalidomide), while high-MIPS tumors were relatively resistant. MIPS derived from MET alteration serves as a robust biomarker for prognosis and predictive tool for immunotherapy and chemotherapy, facilitating patient stratification and precision therapy.

Indexed as

Brain NeoplasmsGliomaPrecision MedicineProto-Oncogene Proteins c-metBiomarkers, TumorFemaleHumansImmunotherapyMalePrognosisTumor MicroenvironmentBiomarkers, TumorProto-Oncogene Proteins c-met

Identifiers

PMID42387647
PMCPMC13591705

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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.