Identifying novel biomarkers for Saudi glioblastoma multiform using multi-omics approach

Background: Glioblastoma Multiform (GBM) is a high grade aggressive glioma of the brain and it accounts for almost half of malignant tumours of the central nervous system. As per the latest Saudi Cancer Incidence Report, GBM is the most common central nervous system tumour nationally with about 15 months survival following diagnosis. Aims: There is a need to identify new molecular biomarkers that can improve diagnostic accuracy and provide a more reliable prognostic prediction, especially for Saudi GBM patients. Methods: The study recruited 30 consented GBM patients from King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA) hospitals, Riyadh, under protocol No. RC13/258/R. Resected brain tumour tissues were collected on surgery day and immediately were snap-frozen. DNA and RNA extraction were conducted as per standard protocols. Libraries for Illumina Whole Genome Sequencing, Illumina RNA Sequencing and MGI Whole Genome Bisulfite Sequencing were prepared as per manufacturer's protocols. Analysis pipeline included: 1) quality check of sequence reads, 2) trimming, 3) mapping to reference genome (annotation), 4) generating hit counts, 5) pairwise comparison/enrichment analysis, and 6) pathway analysis. Results: Preliminary RNA sequencing data of two trial GBM samples has generated 19k and 21k paired end 2 x 150 sequence reads. Majority of the sequence reads (87%) had good quality (Phred Score > 30) and majority had a unique genome mapping (70% of sequence reads). The analysis revealed 19,007 normalised counts and the two samples had high correlation (Spearman's correlation r = 0.787, P < 0.001). Additionally, the analysis identified 904 Differentially Expressed Genes (DEG), of which 434 and 470 upregulated and downregulated genes, respectively. Additional sequencing data are expected to be generated with full multi-omics integration analysis to be done. Conclusion: This study marks the first to investigate the GBM multi-omics profile of the untapped Saudi GBM and to further identify and validate novel biomarkers that are population-specific to guide clinical diagnosis and prognosis for GBM.