Identification of Genomic Alterations in Chemotherapy-Related Genes: A Preliminary Study in Three Thai Adolescents with Fatal Osteosarcoma at Maharaj Nakorn Chiang Mai Hospital

OBJECTIVE Osteosarcoma (OS) is the most common primary bone malignancy among adolescents and young adults. It is characterized by a high mortality rate, though it remains a relatively rare disease overall. The treatment protocols can be complex and challenging. We conducted a comparative genomic variation study to identify genes involved in the metabolism of chemotherapy drugs that are affected by various genomic alterations. METHODS This study analyzed the germline and tumor genomes of three OS patients who responded poorly to chemotherapy, developed lung metastases, and ultimately succumbed to the disease. Genes of interest were identified through a systematic review of apoptosis, autophagy, necroptosis, and chemotherapy-related databases. Whole-genome sequencing (WGS) revealed deleterious single nucleotide polymorphisms (SNPs), copy number variations (CNVs), and structural variations (SVs) in genes linked to cancer and chemotherapy. Protein association network analyses were used to highlight both shared and unique biological processes associated with OS in these patients. RESULTS Pathogenic SNPs were identified exclusively in patients P1 and P3. Patient P1 exhibited a missense mutation in the PIK3CD gene and a splice donor site mutation in the TP53 gene, while patient P3 carried a nonsense mutation in the MLH1 gene. The tumor genome of patient P1 showed extensive CNVs, whereas those of patients P2 and P3 displayed fewer CNV regions. TBX4 and PPM1D were common genes affected in both patients P1 and P2. SVs were detected in all three tumor genomes, impacting different key genes involved in platinum drug resistance and DNA repair. Notably, all three patients shared SVs in the TDG and SPECC1 genes. All identified mutated genes were correlated with clinical features of the patients. CONCLUSIONS This study highlights the potential of genomic analysis to improve the diagnosis, treatment, and management of OS. Insights into therapy resistance mechanisms and key genomic alterations offer opportunities for developing targeted therapies and predictive biomarkers. These findings support the advancement of precision oncology in OS, as a means of paving the way for personalized treatment approaches to improve patient outcomes.