Background: Despite its crucial role in immune surveillance and cell survival of tumors, the significance of MHC antigen processing and presentation machinery (APM) is still not fully understood in head and neck squamous cell carcinoma (HNSCC). We sought to develop an APM gene score (APMGS) to predict prognosis and reveal the molecular and immune traits of the APMGS-defined subgroups in HNSCC.
Methods: Based on the APM-related genes acquired from 6 databases, 117 combined machine learning algorithms were applied to develop APMGS with The Cancer Genome Atlas (TCGA)-HNSCC database and validated with the Gene Expression Omnibus (GEO) dataset. Comprehensive analysis was performed to investigate the molecular and immune features of APMGS subgroups.
Results: The APMGS constructed by StepCox [both] + Ridge method achieved the highest C-index and area under curve (AUC) at 3 years and were thus adopted as the final model. Low-APMGS patients exhibited superior overall survival compared with high-APMGS patients in both TCGA and GEO cohorts. Subsequent analysis confirmed that a low APMGS was associated with immune response-related pathways; low TP53 mutation rate and low tumor mutation burden (TMB); a less aggressive phenotype; high infiltration of activated CD4+ memory T cells, CD8+ T cells, follicular helper T cells, and Tregs; active immunity; and higher sensitivity to chemotherapeutic and targeted agents. In contrast, a high APMGS linked to proteasome and protein export pathways; high TP53 mutation rate and high TMB; a more aggressive phenotype; high infiltration of M0 macrophages and eosinophils; suppressed immunity; and lower sensitivity to chemotherapeutic and targeted agents.
Conclusions: Our findings suggest that APMGS has potential to predict the prognosis, and molecular and immune characteristics of HNSCC, and may also serve as an indicator for immunotherapy benefit.
Keywords: Antigen processing and presentation machinery; Head and neck squamous cell carcinoma; Prognostic biomarker.
© 2024. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).