Using Liquid Biopsy in the Treatment of Patient with OS.

Liquid biopsies encompass a number of new technologies designed to derive tumor data through the minimally invasive sampling of an accessible body fluid. These technologies remain early in their clinical development, and applications for patients with osteosarcoma are actively under investigation. In this chapter, we outline the current state of liquid biopsy technologies as they apply to cancer generally and osteosarcoma specifically, focusing on assays that detect and profile circulating tumor DNA (ctDNA), microRNAs (miRNA), and circulating tumor cells (CTCs). At present, ctDNA assays are the most mature, with multiple assays demonstrating the feasibility of detecting and quantifying ctDNA from blood samples of patients with osteosarcoma. Initial studies show that ctDNA can be detected in the majority of patients with osteosarcoma and that the detection and level of ctDNA correlates with a worse prognosis. Profiling of ctDNA can also identify specific somatic events that may have prognostic relevance, such as 8q gain in osteosarcoma. miRNAs are stable RNAs that regulate gene expression and are known to be dysregulated in cancer, and patterns of miRNA expression have been evaluated in multiple studies of patients with osteosarcoma. While studies have identified differential expression of many miRNAs in osteosarcomas compared to healthy controls, a consensus set of prognostic miRNAs has yet to be definitively validated. Recent studies have also demonstrated the feasibility of capturing CTCs in patients with osteosarcoma. The development of assays that quantify and profile CTCs for use as prognostic biomarkers or tools for biologic discovery is still in development. However, CTC technology holds incredible promise given the potential to perform multi-omic approaches in single cancer cells to understand osteosarcoma heterogeneity and tumor evolution. The next step required to move liquid biopsy technologies closer to helping patients will be wide-scale collection of patient samples from large prospective studies.