DNA methylation microarray analysis of adult gliomas: A pilot study at Groote Schuur Hospital
SA Journal of Oncology
| Field | Value | |
| Title | DNA methylation microarray analysis of adult gliomas: A pilot study at Groote Schuur Hospital | |
| Creator | Price, Brendon | |
| Description | Background: Accurate glioma diagnosis requires a combination of histology, radiology and identification of key genetic mutations. Currently, multiple tests are required to identify these mutations. Deoxyribonucleic acid (DNA) methylation microarray coupled with digital classification algorithms can subclassify gliomas and identify multiple mutations in a single experiment, thereby potentially replacing current modalities and reduce turnaround times.Aim: This study aims to compare results obtained by DNA methylation microarray on select adult glioma cases previously classified and graded on the basis of morphology and currently available ancillary tests.Setting: Cape Town, South Africa.Methods: Eight cases comprising astrocytic and oligodendroglial tumours (WHO grades 2–4) were analysed using the Illumina Infinium MethylationEPIC 850k microarray platform. Tumour classification and O6-methylguanine DNA-methyltransferase (MGMT) promoter methylation status were determined via online classification algorithms. Key genetic and chromosomal changes were identified by copy number variation plots.Results: Seven of the eight cases were successfully assigned a methylation class and showed concordance with previously determined histological tumour type, isocitrate dehydrogenase and 1p/19q co-deletion status. Of these, tumour grading remained unchanged in five cases, upgraded in one case and downgraded in the other. The remaining case could not be classified. The MGMT promoter methylation status and diagnostically relevant copy number variants were also identified.Conclusion: Tumour classification and grading can be accurately determined by methylation microarray analysis in adult gliomas.Contribution: Methylation microarray provides greater molecular information than current methods, thereby potentially improving diagnostic accuracy and patient prognostication. | |
| Publisher | AOSIS | |
| Date | 2024-03-13 | |
| Identifier | 10.4102/sajo.v8i0.269 | |
| Source | South African Journal of Oncology; Vol 8 (2024); 10 pages 2523-0646 2518-8704 | |
| Language | eng | |
| Relation |
The following web links (URLs) may trigger a file download or direct you to an alternative webpage to gain access to a publication file format of the published article:
https://sajo.org.za/index.php/sajo/article/view/269/818
https://sajo.org.za/index.php/sajo/article/view/269/819
https://sajo.org.za/index.php/sajo/article/view/269/820
https://sajo.org.za/index.php/sajo/article/view/269/821
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