Insights into Gene Expression and the Influence of Regulatory Mechanisms within Meningioma - A Bioinformatic Approach
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Meningioma is cancer of the meninges, the protective lining of the brain and spinal cord. Currently meningioma is classified using WHO Grades (I-III) which is based on histological characteristics of the tumours. This approach can give inaccurate indication of tumour aggression and therefore an inappropriate treatment course is chosen. The aim of this study was to identify differentially expressed genes that may act as biomarkers to indicate tumour aggressiveness. A further aim was to infer and investigate the role of specific gene expression regulatory mechanisms within meningioma. Bioinformatic approaches for transcriptomic analysis were used to study microarray data of 62 meningioma tumour patients. Comparison of gene expression was carried out between the 3 WHO grades and between groups with different clinical rates of recurrence. Differential gene expression analysis was completed using online tools GEO2R and Network Analyst, enrichment analysis was performed using WebGestalt and X2KWeb was used to investigate transcription factor influence. Identified potential biomarkers of aggression include an upregulation of PTTG1, SRSF6, and FOXM1 and downregulation of LEPR and SFRP1. Furthermore, through enrichment analysis cell cycle, metabolic pathways and spliceosomes were identified to be overrepresented in the upregulated genes of both grade III and aggressive comparison groups. In conclusion this study identified potential genetic characteristics and the associated biological pathways and processes that are dysregulated in disease state. It also provides potential biomarkers of meningioma aggression for further functional validation.
Carr, L. (2020) ‘Insights into Gene Expression and the Influence of Regulatory Mechanisms within Meningioma - A Bioinformatic Approach’, The Plymouth Student Scientist, 13(1), p. 1-27.