ArticleJournal of translational medicine2019
Multicellular gene network analysis identifies a macrophage-related gene signature predictive of therapeutic response and prognosis of gliomas.
Article in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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42 citing papers in PubMed, 60 citations in OpenAlex.
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- Identification of novel characteristic biomarkers and immune infiltration profile for the anaplastic thyroid cancer via machine learning algorithms.Journal of endocrinological investigation · 2023Article
- Integrated partially linear model for multi-center studies with heterogeneity and batch effect in covariates.Statistics · 2023Article
- Multiscale modeling of drug resistance in glioblastoma with gene mutations and angiogenesis.Computational and structural biotechnology journal · 2023Article
- The core role of macrophages in hepatocellular carcinoma: the definition of molecular subtypes and the prognostic risk system.Frontiers in pharmacology · 2023Article
- Glioblastoma survival is associated with distinct proteomic alteration signatures post chemoirradiation in a large-scale proteomic panel.Frontiers in oncology · 2023Article
- Network-based approaches for modeling disease regulation and progression.Computational and structural biotechnology journal · 2023Review
- Interrogating glioma-M2 macrophage interactions identifies Gal-9/Tim-3 as a viable target againstScience advances · 2022Article
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5 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundThe tumor-associated microenvironment plays important roles in tumor progression and drug resistance. However, systematic investigations of macrophage-tumor cell interactions to identify novel macrophage-related gene signatures in gliomas for predicting patient prognoses and responses to targeted therapies are lacking.
methodsWe developed a multicellular gene network approach to investigating the prognostic role of macrophage-tumor cell interactions in tumor progression and drug resistance in gliomas. Multicellular gene networks connecting macrophages and tumor cells were constructed from re-grouped drug-sensitive and drug-resistant samples of RNA-seq data in mice gliomas treated with BLZ945 (a CSF1R inhibitor). Subsequently, a differential network-based COX regression model was built to identify the risk signature using a cohort of 310 glioma samples from the Chinese Glioma Genome Atlas database. A large independent validation set of 690 glioma samples from The Cancer Genome Atlas database was used to test the prognostic significance and accuracy of the gene signature in predicting prognosis and targeted therapeutic response of glioma patients.
resultsA macrophage-related gene signature was developed consisting of twelve genes (ANPEP, DPP4, PRRG1, GPNMB, TMEM26, PXDN, CDH6, SCN3A, SEMA6B, CCDC37, FANCA, NETO2), which was tested in the independent validation set to examine its prognostic significance and accuracy. The generation of 1000 random gene signatures by a bootstrapping scheme justified the non-random nature of the macrophage-related gene signature. Moreover, the discovered gene signature was verified to be predictive of the sensitivity or resistance of glioma patients to molecularly targeted therapeutics and outperformed other existing gene signatures. Additionally, the macrophage-related gene signature was an independent and the strongest prognostic factor when adjusted for clinicopathologic risk factors and other existing gene signatures.
conclusionThe multicellular gene network approach developed herein indicates profound roles of the macrophage-mediated tumor microenvironment in the progression and drug resistance of gliomas. The identified macrophage-related gene signature has good prognostic value for predicting resistance to targeted therapeutics and survival of glioma patients, implying that combining current targeted therapies with new macrophage-targeted therapy may be beneficial for the long-term treatment outcomes of glioma patients.
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