T cell receptor signaling pathway subgroups and construction of a novel prognostic model in osteosarcoma.

Background: T cell receptor (TCR) signaling pathway is closely related to tumor progress and immunotherapy. This study aimed to explore the clinical significance, prognosis, immune infiltration and chemotherapy sensitivity of TCR in osteosarcoma (OS). Material and methods: OS data were obtained from TARGET and GEO database. TCR signaling pathway-related genes (TCRGs) were extracted from Molecular Signatures Database. Unsupervised non-negative matrix factorization clustering analysis was used to identify OS molecular subtypes. Differential expressed TCRGs between molecular subtypes were screened with univariate Cox regression, LASSO regression and multivariate Cox regression. Subsequently, an OS-associated prognostic model was constructed and validated. Nomogram was established and verified. Immune landscape analysis including immune infiltration analysis, ESTIMATE algorithm and immune checkpoints expression levels of molecular subtypes and different risk groups were analyzed. Finally, chemotherapy sensitivity and potential therapeutic agents between different risk groups was identified. Results: Two TCRGs related subclusters were identified. Two hundred and seventy-two Differential expressed TCRGs were screened between two subclusters. A robust prognostic model were constructed. High and low risk groups were stratified. Low risk group showed higher ESTIMATE, immune and stromal scores, while high risk group exhibited higher tumor purity and the lower expression levels of immune checkpoints. A nomogram comprising metastasis and risk score was successfully built. The sensitivity to chemotherapy agents were different across high and low risk groups. Conclusions: Our study proposed TCR related molecular subtypes and provided a prognostic model for OS. Our findings may bring a new insight into the immunotherapy for OS patients.