Molecular genetics of osteosarcoma

Abstract

Osteosarcoma is the predominant form of bone cancer, affecting mostly adolescents. Recent progress made in molecular genetic studies of osteosarcoma has changed our view on the cause of the disease and ongoing therapeutic approaches for patients. As we draw closer to gaining more complete catalogs of candidate cancer driver genes in common forms of cancer, the landscape of somatic mutations in osteosarcoma is emerging from its first phase. In this review, we summarize recent whole genome and/or whole exome genomic studies, and then put these findings in the context of genetic hallmarks of somatic mutations and mutational processes in human osteosarcoma. One of the lessons learned here is that the extent of somatic mutations and complexity of the osteosarcoma genome are similar to that of common forms of adult cancer. Thus, a much higher number of samples than those currently obtained are needed to complete the catalog of driver mutations in human osteosarcoma. In parallel, genetic studies in other species have revealed candidate driver genes and their roles in the genesis of osteosarcoma. This review also summarizes newly identified drivers in genetically engineered mouse models (GEMMs) and discusses our understanding of the impact of nature and number of drivers on tumor latency, subtypes, and metastatic potentials of osteosarcoma. It is becoming apparent that a synergistic team composed of three drivers (one ‘first driver’ and two ‘synergistic drivers’) may be required to generate an animal model that recapitulates aggressive osteosarcoma with a short latency. Finally, new cancer therapies are urgently needed to improve survival rate and quality of life for osteosarcoma patients. Several vulnerabilities in osteosarcoma are illustrated in this review to exemplify the opportunities for next generation molecularly targeted therapies. However, much work remains in order to complete our understanding of the somatic mutation basis of osteosarcoma, to develop reliable animal models of human disease, and to apply this information to guide new therapeutic approaches for reducing morbidity and mortality of this rare disease.