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. 2021 Dec;12(1):6643-6654.
doi: 10.1080/21655979.2021.1975980.

Four specific biomarkers associated with the progression of glioblastoma multiforme in older adults identified using weighted gene co-expression network analysis

Yushi Yang  1   2 , Liangzhao Chu  3 , Zhirui Zeng  1 , Shu Xu  2 , Hua Yang  3 , Xuelin Zhang  4 , Jun Jia  5 , Niya Long  3 , Yaxin Hu  6 , Jian Liu  1   7
Affiliations

Four specific biomarkers associated with the progression of glioblastoma multiforme in older adults identified using weighted gene co-expression network analysis

Yushi Yang et al. Bioengineered. 2021 Dec.

Abstract

Glioblastoma multiforme (GBM) is the most common primary intracranial malignancy in adults. Owing to individual tolerance and tumor heterogeneity, the therapy methods for young adults do not apply to older adults. The present study aimed to identify specific biomarkers for GBM in older adults using weighted gene co-expression network analysis (WGCNA). Gene expression profiles of older adults with GBM were downloaded from The Cancer Genome Atlas (TCGA) and set as a discovery cohort to construct WGCNA. Core genes of clinically significant modules were used to perform functional enrichment, protein-protein interaction, and Pearson correlation analyses. Gene expression profiles of young in TCGA and older GBM patients from our research group were set as verification cohorts for hub gene expression and diagnostic value. Four significant gene modules associated clinically with older adults with GBM were identified, whereas 251 genes were core genes with module membership>0.8 and gene significance>0.2. Ermin (ERMN), myelin-associated oligodendrocyte basic protein (MOBP), proteolipid protein 1 (PLP1), and oligodendrocytic myelin paranodal and inner loop protein (OPALIN) genes had significant relationships with the Karnofsky score (KPS) in older GBM patients. ERMN, MOBP, PLP1, and OPALIN had no relationship with KPS in young GBM patients. These genes were upregulated in GBM tissues from older patients with low but not high KPS and had high diagnostic value. In conclusion, ERMN, MOBP, PLP1, and OPALIN may serve as specific biomarkers for the progression of GBM in older adults.

Keywords: Glioblastoma; WGCNA; biomarkers; elder.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1.
Figure 1.
Structuring WGCNA. (a) Sample tree clustering and clinical traits (Survival days; vital: white = alive, red = dead, gray = missing value; KPS) heat map of 38 GBM tissues in older adults. (b) Scale independence of various soft-threshold values. (c) Mean connectivity of various soft-threshold values
Figure 2.
Figure 2.
Module clusters and relationships with clinical traits. (a) Clustering dendrograms of all genes with dissimilarity based on topological overlap, together with assigned module colors. (b) Identification of significant modules associated with clinical traits (survival days, vital, and KPS). Each cell in the heat map contains the corresponding correlation score and P-value. Red indicates a positive correlation, whereas green indicates a negative correlation
Figure 3.
Figure 3.
Relationship between gene significance (GS) and module membership (MM) in significant modules
Figure 4.
Figure 4.
GO analysis for the module core genes
Figure 5.
Figure 5.
Selecting hub genes in GBM. (a) Module core genes used to construct protein-protein interaction network. Nodes indicate genes, lines indicate interactions. (b) Genes with top 10 degree score are shown
Figure 6.
Figure 6.
Relationship between the expression of hub genes and KPS score in older patients with GBM
Figure 7.
Figure 7.
Relationship between the expression of hub genes and KPS score in young patients with GBM
Figure 8.
Figure 8.
ERMN, MOBP, PLP1 and OPALIN were highly expressed in the GBM tissues provided by the older patients with lower KPS scores. (a) IHC stain determined the expression of ERMN, MOBP, PLP1 and OPALIN in GBM tissues provided by the older patients with low and high KPS scores. (b) ROC analysis was performed to determine the diagnostic value of ERMN, MOBP, PLP1 and OPALIN to distinguish the GBM tissues provided by the older patients with low and high KPS scores
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This work was supported by the Major State Research Development Program of China (grant no. 2016YFC0106107), Program for Changjiang Scholars and Innovative Research Team in University (grant no. IRT13058), and Joint Fund Project of Guizhou Provincial Science and Technology Department [QianKeHe (2016) support 2905];the Major State Research Development Program of China [2016YFC0106107];Joint Fund Project of Guizhou Provincial Science and Technology Department [QianKeHe (2016) support 2905].