Identification and Verification of a Prognostic Risk Signature in Oral Squamous Cell Carcinoma.

INTRODUCTION

Oral squamous cell carcinoma (OSCC) is a prevalent malignant condition. This study aimed to investigate the role of mTORC1 signaling and develop a prognostic model for OSCC.

MATERIALS AND METHODS

The single-sample gene set enrichment analysis (ssGSEA) algorithm was utilized to calculate the Z-Score of Hallmarks in OSCC, followed by univariate Cox regression analysis to identify processes associated with prognosis. Weighted gene co-expression network analysis (WGCNA) was performed using transcriptomic data from the cancer genome atlas (TCGA) cohort to identify genes correlated with mTORC1 signaling. A six-gene prognostic model was constructed using multifactorial Cox regression analysis and validated using an external dataset.

RESULTS

The study uncovered a strong linkage between mTORC1, glycolysis, hypoxia, and the prognosis of OSCC. mTORC1 signaling emerged as the most significant risk factor, negatively impacting patient survival. Additionally, a six-gene prognostic risk score model was developed which provided a quantitative measure of patients' survival probabilities. Interestingly, within the context of these findings, TP53 gene mutations were predominantly observed in the high-risk group, potentially underlining the genetic complexity of this patient subgroup. Additionally, differential immune cell infiltration and an integrated nomogram were also reported.

CONCLUSION

This study highlights the importance of mTORC1 signaling in OSCC prognosis and presents a robust prognostic model for predicting patient outcomes.