ArticleFEBS open bio2023
Immune-related matrisomes are potential biomarkers to predict the prognosis and immune microenvironment of glioma patients.
Article in FEBS open bio, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The entanglement of extracellular matrix molecules and immune checkpoint inhibitors in cancer: a systematic review of the literature.Frontiers in immunology · 2023Pooled it
- TMBIM6 promotes glioma progression according to integrated bioinformatics and experimental evidence.Scientific reports · 2025Article
- SMOC1 colocalizes with Alzheimer's disease neuropathology and delays Aβ aggregation.Acta neuropathologica · 2024Article
- SMOC1 colocalizes with Alzheimer's disease neuropathology and delays Aβ aggregation.Research square · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The extracellular matrix (ECM) plays a vital role in the progression and metastasis of glioma and is an important part of the tumor microenvironment. The matrisome is composed of ECM components and related proteins. There have been several studies on the effects of matrisomes on the glioma immune microenvironment, but most of these studies were performed on individual glioma immune-related matrisomes rather than integral analysis. Hence, an overall analysis of all potential immune-related matrisomes in gliomas is needed. Here, we divided 667 glioma patients in The Cancer Genome Atlas (TCGA) database into low, moderate, and high immune infiltration groups. Immune-related matrisomes differentially expressed among the three groups were analyzed, and a risk signature was established. Eight immune-related matrisomes were screened, namely, LIF, LOX, MMP9, S100A4, SRPX2, SLIT1, SMOC1, and TIMP1. Kaplan-Meier analysis, operating characteristic curve analysis, and nomogram were constructed to analyze the relationships between risk signatures and the prognosis of glioma patients. The risk signature was significantly correlated with the overall survival of glioma patients. Both high- and low-risk signatures were also associated with some immune checkpoints. In addition, analysis of somatic mutations and anti-PD1/L1 immunotherapy responses in the high- and low-risk groups showed that the high-risk group had worse prognosis and a higher response to anti-PD1/L1 immunotherapy. Our analysis of immune-related matrisomes may improve understanding of the characteristics of the glioma immune microenvironment and provide direction for glioma immunotherapy development in the future.
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