FABP5 enhances malignancies of lower‐grade gliomas via canonical activation of NF‐κB signaling

Yichang Wang,Dongze Xu,Ning Wang,Wei Wu,Wanfu Xie,Maode Wang,Jia Wang,Xudong Ma,Alafate Wahafu,Longwei Huo,Xiaobin Bai,Jianyang Xiang,Hao Liu

doi:10.1111/jcmm.16536

Abstract

Low‐grade gliomas (LGGs) are grade III gliomas based on the WHO classification with significant genetic heterogeneity and clinical properties. Traditional histological classification of gliomas has been challenged by the improvement of molecular stratification; however, the reproducibility and diagnostic accuracy of LGGs classification still remain poor. Herein, we identified fatty acid binding protein 5 (FABP5) as one of the most enriched genes in malignant LGGs and elevated FABP5 revealed severe outcomes in LGGs. Functionally, lentiviral suppression of FABP5 reduced malignant characters including proliferation, cloning formation, immigration, invasion and TMZ resistance, contrarily, the malignancies of LGGs were enhanced by exogenous overexpression of FABP5. Mechanistically, epithelial‐mesenchymal transition (EMT) was correlated to FABP5 expression in LGGs and tumour necrosis factor α (TNFα)‐dependent NF‐κB signalling was involved in this process. Furthermore, FABP5 induced phosphorylation of inhibitor of nuclear factor kappa‐B kinase α (IKKα) thus activated nuclear factor kappa‐B (NF‐κB) signalling. Taken together, our study indicated that FABP5 enhances malignancies of LGGs through canonical activation of NF‐κB signalling, which could be used as individualized prognostic biomarker and potential therapeutic target of LGGs.

Highlights

Lower-grade gliomas (LGGs) are grade II/III gliomas based on the World Health Organization (WHO) classification with significant genetic heterogeneity and clinical properties
Epithelial-mesenchymal transition (EMT) was correlated to fatty acid binding protein 5 (FABP5) expression in LGGs and tumor necrosis factor α (TNFα)-dependent NF-κB signaling was involved in this process
Our study indicated that FABP5 enhances malignancies of LGGs through canonical activation of NF-κB signaling, which could be used as individualized prognostic biomarker and potential therapeutic target of LGGs

Summary

Methods

We derived all relevant data of LGGs including TCGA and CGGA databases from official websites. Gene expression datasets and relevant clinical data of LGG were respectively extracted from Chinese Glioma Genome Atlas (CGGA, mRNASeq_693, http://cgga.org.cn/) and GDC Data Portal (https://portal.gdc.cancer.gov/). These gene expression profile data were preprocessed by background correction, gene symbol transformation and normalization using R programming (version 4.0.0). Time-dependent ROC analysis was performed according to previous reference for further measurement of the predictive performance among the candidate genes[16]. False positive rate and true positive rate were used as x axis and y axis, respectively, the performance of a gene candidate was evaluated by the area under the ROC curve (AUC) in which a higher AUC value indicates a better performance

Results

Discussion

Conclusion