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Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
Published on: October 4, 2019
Predicting glioma survival and extracellular matrix remodeling through MRI radiogenomics
Yifan Bie1, Xiuyu Chi1, Yufan Chen2
1Department of Radiology, The Second Hospital of Shandong University, Jinan, Shandong, P.R. China.
Abstract:
Extracellular matrix (ECM) remodeling is essential for glioma invasion, yet lacks non-invasive assessment methods. This study employs radiogenomics to enable non-invasive survival prediction and ECM remodeling assessment in glioma. Utilizing a multi-dataset data (n = 891), an 11-feature radiomics signature is developed stratifying patients into low- and high-Rad-score groups (area under the receiver operator characteristic curve [AUC] = 0.886, 95% confidence interval [CI]: 0.807-0.964 in the training set from two local centers; AUC = 0.828, 95% CI: 0.796-0.893 in the validation set from five public datasets). Radiogenomic analysis (n = 572) reveals differentially expressed genes significantly associated with Rad-scores, particularly enriched in pathways associated with ECM remodeling, and identifies seven related hub genes (MMP2, MMP9, CXCL8, TIMP1, IL-6, COL1A2, and CCL2). These findings are validated using an external radiogenomic dataset and orthotopic (both syngeneic and xenograft) mouse models, where silencing MMP2 reduced Rad-scores and tumor infiltration. This study highlights the potential of MRI-based radiomics signatures in assessing ECM remodeling for survival prediction and improved glioma clinical management.
