MedCMU Grant 0992563 Supplementary Data

<b>Whole Genome Sequencing to RNA-seq analysis for the discovery of genetic predisposition, causal driver gene mutation, and prognosis in 3 patients with osteosarcoma at Maharaj Nakorn Chiang Mai Hospital.</b>Osteosarcoma (OS) is the most common primary bone malignancy in adolescents and young adults, marked by a high mortality rate despite its rarity. Treatment protocols remain complex, and poor clinical outcomes are common among high-risk patients. In this study, we performed a comparative genomic variation analysis to identify chemotherapy metabolism-related genes affected by genomic alterations in three OS patients who exhibited poor responses to chemotherapy, developed lung metastases, and eventually succumbed to the disease. Genes of interest were curated through a systematic review of apoptosis, autophagy, necroptosis, and chemotherapy-related databases. Whole-genome sequencing (WGS) was used to detect deleterious single nucleotide polymorphisms (SNPs), copy number variations (CNVs), and structural variations (SVs) in both germline and tumor DNA, while transcriptomic analyses and protein association network modeling were used to identify dysregulated candidate genes and disrupted biological pathways. Pathogenic SNPs were identified exclusively in patients P1 and P3. Patient P1 carried a missense mutation in <i>PIK3CD</i> and a splice donor site mutation in <i>TP53</i>, while patient P3 harbored a nonsense mutation in <i>MLH1</i>. CNV analysis revealed extensive genomic alterations in patient P1, with fewer CNVs in patients P2 and P3. <i>TBX4</i> and <i>PPM1D</i> were among the genes commonly affected in both patients P1 and P2. Structural variants were detected in all three tumor genomes, impacting critical genes involved in platinum drug resistance and DNA repair, with SVs in <i>TDG</i> and <i>SPECC1</i> found across all patients. Importantly, transcriptome analysis confirmed dysregulated expression in many genes of interest, supporting their involvement in tumor progression and treatment resistance. These genomic and transcriptomic findings were also consistent with the clinical features of the patients, reinforcing their biological relevance. This study highlights the potential of integrating genomic and transcriptomic data to unravel mechanisms underlying chemotherapy resistance, tumor progression, and metastasis in OS. The identification of key genetic alterations and disrupted pathways provides insights for developing targeted therapies and predictive biomarkers. These findings support the advancement of precision oncology and pave the way for more personalized and effective treatment strategies to improve outcomes in osteosarcoma patients.