Identification of telomere-related gene subtypes and prognostic signatures in osteosarcoma

Osteosarcoma (OS) is the prevalent primary bone cancer, with a high proclivity for local invasion and metastasis. Previous studies have indicated that telomeres are closely related to prognosis of cancer, but the significance of telomere-related features in OS remains uncertain. Thus, the goal of this work is to identified telomere-related subtypes based on the telomere-related genes (TRGs).

The data of OS was collected from TARGET and Gene Expression Omnibus databases. Firstly, we identified the subtypes mediated by TRGs in OS. Subsequently, we analyzed the immune characteristics of telomeres-related subtypes in OS. Moreover, we built a telomere-related signature via univariate and LASSO Cox regression analyses, and analyzed the correlation of telomere-related signature with TME. Finally, we analyzed the expression of hub TRGs in OS.

We discovered that TRGs could distinguish OS patients into two telomeres-related subtypes (C1 and C2). The survival rate of OS patients in C2 was inferior to that of patients in C1. The scores of stromal, immune and ESTIMATES were observably increased, and tumor purity was decreased in C1 subtypes compared to C2 subtypes. Differentially expressed genes between C1 and C2 were highly enriched in immune-related pathways. Moreover, C1 and C2 subtypes had different immune characteristic. Furthermore, a telomere prognostic model including six genes (PDK2, PPARG, MORC4, SP110, TERT and MAP3K5) was established to predict the prognosis of OS patients. High-risk group was correlated with inferior prognosis of OS patients, and risk score model was correlated with TME. Finally, we discovered that expression of PDK2, PPARG, MORC4, SP110, TERT and MAP3K5 was significantly decreased in OS cells.

In conclusion, our study has uncovered the importance of TRGs in defining distinct subtypes of OS with different survival outcomes and immune contexts. The telomere-related signature we developed may serve as a valuable tool for prognosis prediction and could inform future therapeutic strategies targeting the TME in OS.