Clinical and prognostic significance analysis of glycolysis-related genes in HNSCC

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Qiuyun Yuan, Mengqian Mao, Xiaoqiang Xia, Wanchun Yang
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Abstract

Background

Head and neck squamous cell carcinoma (HNSCC) represents one of the most malignant cancers worldwide, with poor survival. Experimental evidence implies that glycolysis/hypoxia is associated with HNSCC. In this study, we aimed to construct a novel glycolysis-/hypoxia-related gene (GHRG) signature for survival prediction of HNSCC.

Methods

A multistage screening strategy was used to establish the GHRG prognostic model by univariate/least absolute shrinkage and selection operator (LASSO)/step multivariate Cox regressions from The Cancer Genome Atlas cohort. A nomogram was constructed to quantify the survival probability. Correlations between risk score and immune infiltration and chemotherapy sensitivity were explored.

Results

We established a 12-GHRG mRNA signature to predict the prognosis in HNSCC patients. Patients in the high-risk score group had a much worse prognosis. The predictive power of the model was validated by external HNSCC cohorts, and the model was identified as an independent factor for survival prediction. Immune infiltration analysis showed that the high-risk score group had an immunosuppressive microenvironment. Finally, the model was effective in predicting chemotherapeutic sensitivity.

Conclusions

Our study demonstrated that the GHRG model is a robust prognostic tool for survival prediction of HNSCC. Findings of this work provide novel insights for immune infiltration and chemotherapy of HNSCC, and may be applied clinically to guide therapeutic strategies.

Abstract Image

糖酵解相关基因在 HNSCC 中的临床和预后意义分析。
背景:头颈部鳞状细胞癌(HNSCC头颈部鳞状细胞癌(HNSCC)是全球恶性程度最高的癌症之一,存活率很低。实验证据表明,糖酵解/缺氧与 HNSCC 有关。在这项研究中,我们旨在构建一个新的糖酵解/缺氧相关基因(GHRG)特征,用于预测HNSCC的生存率:方法:采用多级筛选策略,通过单变量/最小绝对缩小和选择算子(LASSO)/阶跃多变量 Cox 回归,从癌症基因组图谱队列中建立 GHRG 预后模型。构建了一个提名图来量化生存概率。探讨了风险评分与免疫浸润和化疗敏感性之间的相关性:我们建立了一个12-GHRG mRNA特征来预测HNSCC患者的预后。高风险评分组患者的预后更差。该模型的预测能力得到了外部 HNSCC 队列的验证,并且该模型被确定为生存预测的一个独立因素。免疫浸润分析表明,高风险评分组具有免疫抑制微环境。最后,该模型还能有效预测化疗敏感性:我们的研究表明,GHRG 模型是预测 HNSCC 生存率的可靠预后工具。这项工作的发现为 HNSCC 的免疫浸润和化疗提供了新的见解,并可应用于临床,指导治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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