Genomic Analysis Revealed Mutational Traits Associated with Clinical Outcomes in Osteosarcoma

Cancer Manag Res. 2021 Jun 28:13:5101-5111. doi: 10.2147/CMAR.S317809. eCollection 2021.

Abstract

Objective: The limited understanding of correlation between genomic features and biological behaviors has impeded the therapeutic breakthrough in osteosarcoma (OS). This study aimed to reveal the correlation of mutational and evolutionary traits with clinical outcomes.

Methods: We applied a case-based targeted and whole exome sequencing of eleven matched primary, recurrent and metastatic samples from three OS patients characterized by different clinical behaviors in local recurrence or systematic progression pattern.

Results: Extensive OS-associated driver genes were detected including TP53, RB1, NF1, PTEN, SPEN, CDKN2A. Oncogenic signaling pathways including cell cycle, TP53, MYC, Notch, WNT, RTK-RAS and PI3K were determined. MYC amplification was observed in the patient with shortest disease-free interval. Linear, branched or mixed evolutionary models were constructed in the three OS cases. A branched evolution with limited root mutation was detected in patient with shorter survival interval. ADAM17 mutation and HEY1 amplification were identified in OS happening dedifferentiation. Signatures 21 associated with microsatellite instability (MSI) was identified in OS patient with extra-pulmonary metastases.

Conclusion: OS was characterized by complex genomic alterations. MYC aberration, limited root mutations, and a branched evolutionary model were observed in OS patient with relatively aggressive course. Extra-pulmonary metastases of OS might attribute to distinct mutational process pertaining to MSI. Further research in a larger number of people is needed to confirm these findings.

Keywords: clinical behavior; evolution; extra-pulmonary metastase; microsatellite instability; osteosarcoma; root mutation.

Grants and funding

This work was supported by National Natural Science Foundation of China [grant code 81872180] and National Natural Science Foundation of China [grant code 81972509].