The gut-brain-axis: A positive relationship between gut microbial dysbiosis and glioblastoma brain tumour

Abstract

The glioblastoma brain tumour (GBM) stands out as the most aggressive and resistant-to-treatment malignancy. Nevertheless, the gut-brain connection plays a pivotal role in influencing the growth and activation of the central nervous system. In this particular investigation, we aimed to assess and characterize the gut microbial ecosystem in GBM patients, both quantitatively and qualitatively. We collected faecal samples from 15 healthy volunteers and 25 GBM patients. To delve into the microbial content, we employed PCR-DGGE, targeting the V3 region of the 16S rRNA gene, and conducted qPCR to measure the levels of crucial intestinal bacteria. For a more in-depth analysis, high-throughput sequencing was performed on a selection of 20 random faecal samples (10 from healthy individuals and 10 from GBM patients), targeting the V3+V4 region of the 16S rRNA gene. Our findings from examining the richness and diversity of the gut microbiota unveiled that GBM patients exhibited significantly higher microbial diversity compared to healthy individuals. At the phylum level, Proteobacteria saw a significant increase, while Firmicutes experienced a noteworthy decrease in the GBM group. Moving down to the family level, we observed significantly elevated levels of Enterobacteriaceae, Bacteroidaceae, and Lachnospiraceae in GBM patients, while levels of Veillonellaceae, Rikenellaceae, and Prevotellaceae were notably lower. Delving into genera statistics, we noted a substantial increase in the abundance of Parasutterella, Escherichia-Shigella, and Bacteroides, alongside significantly lower levels of Ruminococcus 2, Faecalibacterium, and Prevotella_9 in the GBM group compared to the control group. Furthermore, when examining specific species, we found a significant increase in Bacteroides vulgatus and Escherichia coli in the GBM group. These observations collectively indicate a marked dysbiosis in the gut microbial composition of GBM patients. Additionally, the GBM group exhibited notably higher levels of alpha diversity when compared to the control group. This increase in diversity suggests a significant bacterial overgrowth in the gut of GBM patients in contrast to the controls. As a result, this research opens up potential avenues to gain a better understanding of the underlying mechanisms, pathways, and potential treatments for GBM, stemming from the significant implications of gut microbial dysbiosis in these patients.

Keywords: Characterization; DGGE; GBM; Gut bacteria; Highthrough-put sequencing.

Graphical abstract

Scheme 1

The whole study findings clearly show that GBM patients have gut bacterial dysbiosis.

Fig. 1

(A) Constructing the DGGE profiling of GBM patients (D1-D8) and healthy controls (C1–C5). (B) Cluster analysis using UPGMA compared diseased (D1-D25) and control (C1–C15) groups. The letters D and C signify the GBM and control, respectively.

Fig. 2

Depicts the OTUs numbers of GBM and control groups sample-wise, average and total numbers.

Fig. 3

Highthrough-put sequencing reveals the glioblastoma cancer sample diversity. The UPGMA algorithm is established on weighted UniFrac distances. The letters D and C represent GBM and control groups, respectively. PCA (principal component analysis) and NMDS (Non-metric dimensional scaling) based on OTU numbers were carried out, showing how the gut bacterial composition differed between the two groups, as depicted in Fig. 4A and B.

Fig. 4

Beta diversity between healthy and diseased subjects. (A) PCA plots generated by Highthrough-put sequencing of faecal bacterial DNA samples. (B) NMDS plot of bacterial DNA samples from experimental and control groups. Each faecal bacterial DNA sample from the study and control groups is represented by dots in the plot.

Fig. 5

(A) Highthrough-put sequencing findings show the phyla-level gut microbiome. The prevalence of the most common phyla in GBM patients is higher than in controls. (B). Findings from Highthrough-put sequencing of intestinal microbial ecology at the family level. The relative abundance of the most prevalent families in GBM patients and healthy controls. (C). Highthrough-put sequencing data revealed the genus levels of gut microbial assemblages. The comparative occurrence of the most common genera in patients with GBM versus healthy controls. (D) applying the linear discriminant analysis (LDA) scores distribution histogram, the most altered intestinal microbial taxon abundance was identified between GBM and control groups. The letters D and C represent the GBM and the control groups, respectively.