[Combination of proteome and transcriptome analysis to predict survival and immunotherapy response in patients with...

Objective:Proteins are closely associated with the development, progression, and immunotherapy of head and neck squamous cell carcinoma（HNSCC）. However, few clinical models utilize proteomics to predict prognosis and immunotherapy efficacy. In this study, we developed a protein prognostic model（PPM） to stratify survival outcomes and differential immunotherapy responses in HNSCC patients. Methods:Based on proteomic profiling, we constructed a PPM comprising 11 protein markers. Patients were classified into high-and low-risk groups according to PPM scores. The prognostic value of risk scores was evaluated using Cox regression analysis, and predictive accuracy was assessed via time-dependent receiver operating characteristic（ROC） curves. Additionally, we analyzed treatment responses to PD1/CTLA4 immunotherapy in PD1-or CTLA4-positive patients across risk groups. Results:Cox regression confirmed the risk score as an independent prognostic factor（HR=1.161, 95%CI 1.112-1.213, P<0.001）, with high-risk patients exhibiting significantly poorer survival than low-risk counterparts. The model demonstrated robust predictive accuracy, with 1-year and 3-year time-dependent ROC areas under the curve（AUC） of 0.713 and 0.707, respectively. In PD1/CTLA4-positive subgroups, low-risk patients showed superior immunotherapy responses compared to high-risk patients. Conclusion:The PPM can provide reliable prognostic stratification and preliminary guidance for immunotherapy in HNSCC. However, further clinical studies and basic experiments are needed for further verification.