Affiliation:
1. First Affiliated Hospital of Guangxi Medical University
Abstract
Abstract
Background Research has shown that reprogramming of fatty acid metabolism (FAM) is involved in tumorigenicity and cancer progression, as well as the impact of tumor immune microenvironments (TME) on tumorigenesis, metastasis, and the prognosis of head and neck squamous cell carcinoma (HNSCC). However, no reliable molecular markers based on fatty acid metabolism have been identified to predict prognosis, immune infiltration, and treatment in HNSCC.Methods In the HNSCC samples of TCGA, we performed a consensus clustering algorithm to separate molecular subtypes. And then we established a risk model for prognosis with Cox regression and the least absolute shrinkage and selection operator (LASSO) regression. The predictive efficacy of risk model was also verified by another HNSCC cohort from GEO.We also evaluated the risk score association with the clinicopathological features and explored differences of immune cell infiltration, immune status and chemotherapeutic drugs IC 50 value concentration between high and low risk subgroup.Results Three distinct fatty acid metabolism subtypes were identified among 494 HNSCC samples, which were also associated with different clinical outcomes, TME characteristics and clinical features. 9 prognosisrelated genes which were different expressed among three subgroups were screened out for prognostic signature. According to the risk score caculated by the signature genes, patients in TCGA cohort can be divided into high and low risk score subgroups. The low risk score subgroup patients displayed a better prognosis. Further analysis indicated that low risk score correlated with higher immune cells infiltration. In addition, patients with higher risk scores showed a better chemotherapy sensetivity of cisplatin and docetaxel.Conclusions We developed a signature capable of predicting prognosis, representing the TME, enhancing individualized therapy, and providing a novel immunotherapeutic marker in HNSCC.
Publisher
Research Square Platform LLC
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