Expression patterns and clinical significance of vasculogenic mimicry-related genes in patients with head and neck squamous cell carcinoma - Lai, Rui; Gu, Xuanyu; Cai, Yueyue; Li, Qiang (Frontiers in Immunology, 2025)
BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most prevalent malignant neoplasms worldwide. Despite advances in conventional therapies such as surgery, radiotherapy, and chemotherapy, many patients still have a poor prognosis due to drug resistance, recurrence, and distant metastasis. In recent years, vasculogenic mimicry has become one of the most studied mechanisms that promote cancer incidence and progression. However, research on the association between vasculogenic mimicry-related genes (VMRGs) and HNSCC is currently limited, and the impact of vasculogenic mimicry on HNSCC requires further investigation.MethodsTranscriptome and clinical data for HNSCC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. We found that VMRG expression differed between tumor and normal tissues. Cox and LASSO regression analyses were employed to construct a prognostic risk model for VMRG expression. The predictive ability of the prognostic model was assessed using Kaplan–Meier and receiver operating characteristic (ROC) curves. Additionally, we conducted a systematic assessment of the clinical association between high- and low-risk cohorts, including gene set enrichment analysis (GSEA), immunological landscape profiling, tumor mutational burden, immunotherapy response, and drug sensitivity. Finally, we verified the expression of all genes implicated in the construction of the prediction model at both cellular and tissue levels using quantitative reverse transcription polymerase chain reaction (RT-qPCR).ResultsA total of 39 VMRGs related to prognosis were screened, and five were selected to build the predictive model. The results of the Kaplan–Meier analysis indicated reduced overall survival in patients in the high-risk category. Cox regression and ROC analyses showed that the risk model provided independent and robust predictive value for the prospects of individuals with HNSCC. Mechanistically, clinical correlation, GSEA, immunological landscape, tumor mutational burden, immunotherapy response, and drug sensitivity analyses demonstrated notable variations. RT-qPCR results revealed aberrant expression of model-related genes, and the expression trends were consistent with the bioinformatic findings.ConclusionThis study elucidated the impact of VMRGs on immunological mechanisms in HNSCC. Our prognostic model of VMRGs highlighted their predictive relevance in patients with HNSCC and revealed potential new prospective treatment options.