Targeting Molecular Mechanisms Underlying Treatment Efficacy and Resistance in Osteosarcoma: A Review of Current and Future Strategies

Abstract

Osteosarcoma is the most common primary malignant bone tumour in children and adolescents. Due to micrometastatic spread, radical surgery alone rarely results in cure. Introduction of combination chemotherapy in the 1970s, however, dramatically increased overall survival rates from 20% to approximately 70%. Unfortunately, large clinical trials aiming to intensify treatment in the past decades have failed to achieve higher cure rates. In this review, we revisit how the heterogenous nature of osteosarcoma as well as acquired and intrinsic resistance to chemotherapy can account for stagnation in therapy improvement. We summarise current osteosarcoma treatment strategies focusing on molecular determinants of treatment susceptibility and resistance. Understanding therapy susceptibility and resistance provides a basis for rational therapy betterment for both identifying patients that might be cured with less toxic interventions and targeting resistance mechanisms to sensitise resistant osteosarcoma to conventional therapies.

Keywords: chemoresistance; cisplatin; combination chemotherapy; doxorubicin; drug synergy; ifosfamide; immunotherapy; methotrexate; osteosarcoma; tumour microenvironment.

Figure 1

Model for chemotherapy resistance in osteosarcoma. The untreated population of tumour cells contains cells that are either sensitive (brown) to therapy or intrinsically resistant (purple). Therapy eradicates the sensitive population, while the cells with intrinsic resistance are able to survive along with cells that acquire resistance due to therapeutic pressure. The resistant populations can become sensitive to chemotherapy by targeting mechanisms underlying their resistance.

Figure 2

Major mechanisms contributing to therapy resistance in an osteosarcoma tumour cell. (A) Inefficient drug delivery and/or penetration. (B) Reduced drug influx due to alterations to drug carriers such as the reduced folate carrier. (C) Increased drug efflux due to upregulated ATP-binding cassette (ABC)-family transporters. (D) Reduced affinity of drug to its target due to target overexpression, repression, or mutations at the interaction site. (E) Reduced accumulation due to intracellular drug modifications such as changes in the polyglutamylation (PG) of methotrexate (MTX) or conjugation with glutathione (GSH). (F) Perturbations in apoptosis and cell cycle regulation. (G) Alterations in DNA repair pathways. (H) Altered signal transduction. (I) Cancer stem cells (CSCs) and tumour microenvironment.

Figure 3

Schematic overview of somatic (red) and host (green) factors, which interact the efficacy of combination chemotherapy in osteosarcoma. Host factors: properties of microenvironment: vascularization, osteolytic activity, and inflammation are examples that modulate efficacy of chemotherapy. Immunological composition: the degree of immune cell infiltration, the type (e.g., tumour-associated macrophages and T-cells), and subtype (e.g., M2-polarization and CD8-positivity) as well as degree of immune cell exhaustion (e.g., expression of programmed death ligand-1 (PD-1)) correlate with treatment outcomes. Germ-line polymorphisms: pharmacokinetics of drugs like methotrexate modulate the effective drug exposure of tumour cells. Somatic factors: resistance mechanisms—upregulation and somatic mutations in, e.g., efflux pumps or catabolizing enzymes can detoxify osteosarcoma cells from cytotoxic drugs. Genetic vulnerabilities: activating mutations in signalling pathways can render osteosarcoma susceptible for small molecule inhibitors. Furthermore, while somatic defects in, e.g., the DNA damage response (“BRCAness”) might confer resistance to conventional cytotoxic agents, this also renders tumour cells vulnerable to synthetic lethality through poly (ADP-ribose) polymerase 1 (PARP) inhibitors. Determinants of synergy: currently unknown somatic factors that determine the extent of synergy, e.g., of cisplatin and doxorubicin, might help to predict responses to chemotherapy combinations. A rational choice of individualized combination chemotherapy would need to take these factors into account.