Characterizing two subtypes of osteosarcoma using G2M checkpoint-related genes and revealing its immune landscape

Background: Although the G2M checkpoint has been implicated in Cancer metastasis in numerous studies, the genetic characteristics associated with the G2M checkpoint in Osteosarcoma (OS) remain unexplored.

Methods: Through univariate COX regression analysis, we screened for G2M checkpoint-related genes associated with OS survival. The ConsensusClusterPlus R package was employed for clustering analysis of the TARGET-OS dataset. Finally, the immune infiltration, biological function, mutation and drug sensitivity of different clusters were analyzed. Furthermore, the functional mechanism of KIF20B was elucidated through in vitro experiments.

Results: The TARGET-OS cohort was clustered into two distinct clusters (Cluster 1 and Cluster 2). Compared to Cluster 2, Cluster 1 showed a trend towards higher overall survival rates, with higher immune scores, stromal scores, and ESTIMATE scores, alongside lower tumor purity. Additionally, the infiltration levels of immune cells were substantially higher in Cluster 1. In vitro experiments confirmed that overexpression of KIF20B promoted the proliferation and invasion of SOSP-9607 cells and induced G2/M phase arrest, upregulating the expression of core proteins in the G2/M pathway. Overexpression of KIF20B enhanced the sensitivity of cells to zoledronic acid, while the G2/M pathway inhibitor AZD-1775 reversed this effect.

Conclusion: This study elucidates the prognostic and immune microenvironmental characteristics of G2M checkpoint-related genes in OS, and validates the critical oncogenic function of KIF20B and its regulatory role in drug sensitivity. This study provides novel potential targets and strategies for molecular subtyping and targeted therapy of OS.

Drugs; G2M checkpoint; Immune profiling; Osteosarcoma; Subtypes.