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. 2022 Sep 24;17(1):73.
doi: 10.1186/s13000-022-01253-0.

An integrative bioinformatics investigation and experimental validation of critically involved genes in high-grade gliomas

Reza Ahmadi-Beni  1 , Shirin Shahbazi  2 , Alireza Khoshnevisan  3
Affiliations

An integrative bioinformatics investigation and experimental validation of critically involved genes in high-grade gliomas

Reza Ahmadi-Beni et al. Diagn Pathol. .

Abstract

Background: Lack of knowledge around underlying mechanisms of gliomas mandates intense research efforts to improve the disease outcomes. Identification of high-grade gliomas pathogenesis which is known for poor prognosis and low survival is of particular importance. Distinguishing the differentially expressed genes is one of the core approaches to clarify the causative factors.

Methods: Microarray datasets of the treatment-naïve gliomas were provided from the Gene Expression Omnibus considering the similar platform and batch effect removal. Interacting recovery of the top differentially expressed genes was performed on the STRING and Cytoscape platforms. Kaplan-Meier analysis was piloted using RNA sequencing data and the survival rate of glioma patients was checked considering selected genes. To validate the bioinformatics results, the gene expression was elucidated by real-time RT-qPCR in a series of low and high-grade fresh tumor samples.

Results: We identified 323 up-regulated and 253 down-regulated genes. The top 20 network analysis indicated that PTX3, TIMP1, CHI3L1, LTF and IGFBP3 comprise a crucial role in gliomas progression. The survival was inversely linked to the levels of all selected genes. Further analysis of RNA sequencing data indicated a significant increase in all five genes in high-grade tumors. Among them, PTX3, TIMP1 and LTF did not show any change in low-grade versus controls. Real-time RT-qPCR confirmed the in-silico results and revealed significantly higher expression of selected genes in high-grade samples compared to low-grade.

Conclusions: Our results highlighted the role of PTX3 and TIMP1 which were previously considered in glioma tumorigenesis as well as LTF as a new potential biomarker.

Keywords: Adult glioma; Differentially expressed genes; GEO data; Integrated bioinformatics.

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Conflict of interest statement

There are no competing interests declared by the authors.

Figures

Fig. 1
Fig. 1
PCA scatter plot based on gene expression profiles in 301 samples from 5 datasets. Left: Merged datasets before batch effect correction; datasets are specified with different colors. LGG and HGG samples are shown with circle and triangle symbols, respectively. Right: Merged datasets after batch effect correction; blue and red dots are shown HGG and LGG samples, respectively
Fig. 2
Fig. 2
Volcano plot visualizing the DEGs in a total of 22,189 genes; green points represent 323 upregulated and red represents 253 down-regulated genes
Fig. 3
Fig. 3
Top three pathways analysis of molecular function (MF), biological process (BP) and cellular components (CC) of GO, as well as KEGG analysis results. Left; up-regulated DEGs, Right; down-regulated DEGs
Fig. 4
Fig. 4
Protein–protein interaction network illustrated by Cytoscape software. The 25 genes of the top 20 DEGs interact with each other amongst them TIMP1, CHI3L1 and PTX3 have the most interactions. The green nodes represent upregulated genes, whereas nodes in red represent down-regulated genes. The Yellow circles contain upregulated hub DEGs with interactions to PTX3. Transcription factors are in triangular shape. The arrows represent the direction of interactions
Fig. 5
Fig. 5
Kaplan–Meier survival curves using The Cancer Genome Atlas database validate the prognostic value of genes expressed in gliomas (blue—low risk; red—high risk)
Fig. 6
Fig. 6
The GEPIA database results for the expression level of selected genes. The y axis represents log2(TPM + 1). TPM: transcripts per million
Fig. 7
Fig. 7
Mean relative expression of LTF, IGFBP3, CHI3L1, TIMP1 and PTX3 in HGG compared to LGG in patient samples
See this image and copyright information in PMC

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