Osteosarcoma (OS) is a primary malignant bone tumour affecting mainly children and young adults, with unknown disease pathogenesis, an increased likelihood of early metastasis and significant challenges in treatment. Novel and innovative therapeutics are urgently needed. Thus, this study aims to revolutionise the understanding of paediatric OS (pOS) by evaluating the status of DNAm and whether these epigenetic changes can serve as novel biomarkers for therapeutics.
Quantitative-MS polymerase chain reaction (qMS-PCR) coupled with high-resolution-melt (HRM) curve analysis was optimised using 3 cancerous and 2 non-cancerous cell lines and 10 genes. OS cell lines: MG-63, 143-B and NRH-OS-2 were cultured alongside human adipose-tissue-derived mesenchymal stem cells (AT-MSCs), which were isolated, expanded, and differentiated into osteoblasts. For locus-specific DNA methylation (DNAm) analysis, qMS-PCR and HRM were performed using bisulfite-converted genomic DNA (gDNA) from all cell lines, undifferentiated and differentiated AT-MSCs at various time points. Osteogenic differentiation was assessed by Alkaline Phosphatase (ALP) assay and Alizarin red staining. Fluorescent microscopy was conducted to observe changes in cellular structure.
Osteogenic diffentiation from AT-MSCs was confirmed by measuring ALP activity at days 4 and 10 and Alizarin Red staining of calcified extracellular matrix at day 21. Undifferentiated, spindle-shaped AT-MSCs become assumed polygonal/cuboidal morphology as they underwent commitment to an osteoblast lineage, as observed by fluorescent microscopy. The status of DNAm between the undifferentiated, differentiated AT-MSCs and OS cell lines varied among the genes tested, highlighting the importance of DNAm in pOS.
Clinically and non-clinically, both qMS-PCR and HRM analyses allow for precise quantification of locus-specific DNAm levels associated with diseases. Compared to other methods, it is relatively efficient and cost-effective, especially for large-scale studies where sequencing is non-essential and is a valuable validation tool for findings from other methylation analysis techniques. Data generated from qMS-PCR can potentially be used for diagnostics, prognostics or predictive purposes.