Abstract

The tumor microenvironment (TME) is of great clinical significance for predicting the therapeutic effect of tumors. Nonetheless, there was no systematic analysis of cellular interactions in the TME of head and neck cancer (HNSC). This study used gene expression data from 816 patients with HNSC to analyze the scores of 22 immune cells. On this basis, we have established a novel TMEscore-based prognostic risk model. The relationship between TMEscore and clinical and genomic characteristics was analyzed. The sample was divided into risk-H and risk-L groups based on the prognosis risk model of TMEscore, with significant differences in overall survival between the two groups (log rank p < 0.001). In terms of clinical features, the TMEscore is closely related to the T staging, Grade, and HPV. As for genomic characteristics, the genomic features of the Risk-H samples are a low expression of immune-related genes and high-frequency mutations of TP53 and CEP152. This model was validated in an external test set, in which the prognosis for Risk-H group and Risk-L group was also significantly different (log rank p = 0.017). A quantitative method of TME infiltration pattern is established, which may be a potential predictor of HNSC prognosis.

Highlights

  • The tumor microenvironment (TME) is of great clinical significance for predicting the therapeutic effect of tumors

  • We used a univariate cox model to analyze the relationship between these 22 immune cell scores and prognosis

  • The score of Macrophage M0, Mast cell activated, and Neutrophils were significantly associated with poor prognosis

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Summary

Introduction

The tumor microenvironment (TME) is of great clinical significance for predicting the therapeutic effect of tumors. This study used gene expression data from 816 patients with HNSC to analyze the scores of 22 immune cells. On this basis, we have established a novel TMEscore-based prognostic risk model. As for genomic characteristics, the genomic features of the Risk-H samples are a low expression of immune-related genes and high-frequency mutations of TP53 and CEP152 This model was validated in an external test set, in which the prognosis for Risk-H group and Risk-L group was significantly different (log rank p = 0.017). Some immune related parameters have been reported to predict the prognosis of HNSC patients These studies further show that different immune states have a significant effect on the prognosis of HNSC p­ atients[8,9]. It is urgent to integrate a large number of HNSC transcription data to construct a new immune-related prognostic factor

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