Comprehensively investigating the expression levels and the prognostic role of transforming growth factor beta-induced (TGFBI) in glioblastoma multiforme

Jun Yin; Jin-Song Liu; Mei Feng; Jiao-Ming Li; Shun Lu; Mu Yang; Bang-Rong Cao; Jin-Yi Lang; Xiao-Dong Zhu

doi:10.21037/tcr-20-2906

Comprehensively investigating the expression levels and the prognostic role of transforming growth factor beta-induced (TGFBI) in glioblastoma multiforme

Transl Cancer Res. 2020 Oct;9(10):6487-6504. doi: 10.21037/tcr-20-2906.

Authors

Jun Yin^#^{1

2}, Jin-Song Liu^#³, Mei Feng², Jiao-Ming Li³, Shun Lu^{2

4}, Mu Yang⁴, Bang-Rong Cao⁴, Jin-Yi Lang², Xiao-Dong Zhu¹

Affiliations

¹ Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, China.
² Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
³ Department of Neurosurgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
⁴ Radiation Oncology Key Laboratory and Sichuan Province, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China.

^# Contributed equally.

Abstract

Background: Transforming growth factor beta-induced (TGFBI) protein has been found expressed in several cancer types, and expression levels of TGFBI can affect the cancer patients' outcomes, but the role of TGFBI in glioblastoma multiforme (GBM) remains obscure.

Methods: The TGFBI expression levels in GBM were performed via Gene Expression Profiling Interactive Analysis (GEPIA) and UALCAN databases. Further, the mutations types of TGFBI were analyzed by using the cBioportal dataset. LinkedOmics selected correlated genes, kinases, and microRNA (miRNA) targets of TGFBI. GEPIA conducted the prognostic value of TGFBI and correlated genes. Then, the relationship between TGFBI and immune infiltrates was performed by Tumor Immune Estimation Resource (Timer). We compared the TGFBI protein expression levels in GBM and control samples through the Human Protein Atlas (HPA). Finally, the GSCAlite was used to achieve the drugs, and molecules target the TGFBI and significantly correlated genes.

Results: TGFBI is significantly overexpressed in GBM, but the clinical features do not have considerable influence on TGFBI expression levels. Overexpression of TGFBI acts as an adverse biomarker of GBM. The enrichment function of TGFBI showed that the main biological functions, including extracellular matrix (ECM) organization, angiogenesis, leukocyte migration, T cell activation, cell cycle G2/M phase transition, and growth factor binding. About the significant correlated genes, overexpression of mitogen-activated protein kinase 13 (MAPK13) [Log-rank P=0.08 HR (high) =1.4], myosin IG (MYO1G) [Log-rank P=0.06 HR (high) =1.4], plasminogen activator urokinase receptor (PLAUR) [Log-rank P=0.03 HR (high) =1.5], thrombomodulin (THBD) [Log-rank P=0.028 HR (high) =1.5] indicated the poor prognosis of GBM. Further, TGFBI had a significant association with dendritic cell (DC) infiltrates (cor =0.516, P=9.00e-30). The higher the DC infiltration, the shorter survival of GBM. TGFBI protein expression levels were not significantly different in GBM and normal tissue. Finally, TGFBI is associated with resistance to belinostat, LAQ824, CAY10603, CUDC-101, methotrexate, 5-fluorouracil, and navitoclax.

Conclusions: In the present study, we showed TGFBI was overexpressed in GBM, and TGFBI is associated with DC cell infiltrates. Overexpression of TGFBI and high DC infiltration might be an adverse biomarker of GBM. Finally, TGFBI is associated with tumor multi-drug resistance.

Keywords: Transforming growth factor beta-induced (TGFBI); glioblastoma multiforme; prognostics values.