1. Academic Validation
  2. LTBP1 plays a potential bridge between depressive disorder and glioblastoma

LTBP1 plays a potential bridge between depressive disorder and glioblastoma

  • J Transl Med. 2020 Oct 15;18(1):391. doi: 10.1186/s12967-020-02509-3.
Xiaojun Fu 1 2 Pei Zhang 3 Hongwang Song 4 Chenxing Wu 1 Shengzhen Li 3 Shouwei Li 5 Changxiang Yan 6
Affiliations

Affiliations

  • 1 Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Xiangshanyikesong 50#, HaiDian District, Beijing, 100093, China.
  • 2 Capital Medical University, Beijing, People's Republic of China.
  • 3 Beijing Institute of Technology, Beijing, China.
  • 4 Department of Emergency Medicine, Shengjing Hospital of China Medical University, Shenyang, People's Republic of China.
  • 5 Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Xiangshanyikesong 50#, HaiDian District, Beijing, 100093, China. lishouweisbh@sina.com.
  • 6 Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Xiangshanyikesong 50#, HaiDian District, Beijing, 100093, China. ycxsbh@sina.com.
Abstract

Background: Glioblastoma multiforme (GBM) is the most malignant tumor in human brain. Diagnosis and treatment of GBM may lead to psychological disorders such as depressive and anxiety disorders. There was no research focusing on the correlation between depressive/anxiety disorder and the outcome of GBM. Thus, the aim of this study was to investigate the possibility of depressive/anxiety disorder correlated with the outcome of GBM patients, as well as the overlapped mechanism bridge which could link depressive/anxiety disorders and GBM.

Methods: Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) were used to investigate the psychological condition of GBM patients in our department. To further explore the potential mechanism, bioinformatic methods were used to screen out genes that could be indicators of outcome in GBM, followed by gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-protein interaction (PPI) analysis. Further, cellular experiments were conducted to evaluate the proliferation, migration capacity of primary GBM cells from the patients.

Results: It was revealed that patients with higher PHQ-9 and GAD-7 scores had significantly worse prognosis than their lower-scored counterparts. Bioinformatic mining revealed that LTBP1 could be a potential genetic mechanism in both depressive/anxiety disorder and GBM. Primary GBM cells with different expression level of LTBP1 should significantly different proliferation and migration capacity. GO, KEGG analysis confirmed that extracellular matrix (ECM) was the most enriched function of LTBP1. PPI network showed the interaction of proteins altered by LTBP1. Hub genes COL1A2, COL5A1 and COL10A1, as well as mesenchymal marker CD44 and Vimentin were statistically higher expressed in LTBP1 high group; while proneural marker E-cadherin was significantly higher expressed in low LTBP1 group.

Conclusion: There is closely correlation between depressive/anxiety disorders and GBM. LTBP1 could be a potential bridge linking the two diseases through the regulation of ECM.

Keywords

Anxiety disorder; Bioinformatic; Depressive disorder; Glioblastoma; Patient outcome.

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