Identification and validation of a novel cuproptosis-related lncRNA signature for prognosis and immunotherapy of head and neck squamous cell carcinoma

被引:4
|
作者
Xu, Qiu-Shuang [1 ,2 ]
Shen, Zheng-Zhong [3 ]
Yuan, Ling-Qing [1 ,2 ]
机构
[1] Cent South Univ, Xiangya Hosp 2, Natl Clin Res Ctr Metab Dis, Changsha, Peoples R China
[2] Cent South Univ, Xiangya Hosp 2, Dept Endocrinol & Metab, Changsha, Peoples R China
[3] Cent South Univ, Xiangya Hosp, Dept Oral & Maxillofacial Surg, Ctr Stomatol, Changsha, Peoples R China
基金
中国国家自然科学基金;
关键词
head and neck squamous cell carcinoma; cuproptosis; long non-coding RNAs; prognostic signature; immunotherapy; targeted therapy; TUMOR MUTATIONAL BURDEN; LONG NONCODING RNAS; CANCER; COPPER; PROGRESSION; THAP9-AS1; GROWTH; GENE;
D O I
10.3389/fcell.2022.968590
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Head and neck squamous cell carcinoma (HNSCC) is a highly prevalent and heterogeneous malignancy with a dismal overall survival rate. Nevertheless, the effective biomarkers remain ambiguous and merit further investigation. Cuproptosis is a novel defined pathway of programmed cell death that contributes to the progression of cancers. Meanwhile, long non-coding RNAs (lncRNAs) play a crucial role in the biological process of tumors. Nevertheless, the prognostic value of cuproptosis-related lncRNAs in HNSCC is still obscure. This study aimed to develop a new cuproptosis-related lncRNAs (CRLs) signature to estimate survival and tumor immunity in patients with HNSCC. Herein, 620 cuproptosis-related lncRNAs were identified from The Cancer Genome Atlas database through the co-expression method. To construct a risk model and validate the accuracy of the results, the samples were divided into two cohorts randomly and equally. Subsequently, a prognostic model based on five CRLs was constructed by the Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm. In addition, the prognostic potential of the five-CRL signature was verified via Cox regression, survival analysis, the receiver operating characteristic (ROC) curve, nomogram, and clinicopathologic characteristics correlation analysis. Furthermore, we explored the associations between the signature risk score (RS) and immune landscape, somatic gene mutation, and drug sensitivity. Finally, we gathered six clinical samples and different HNSCC cell lines to validate our bioinformatics results. Overall, the proposed novel five-CRL signature can predict prognosis and assess the efficacy of immunotherapy and targeted therapies to prolong the survival of patients with HNSCC.
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页数:17
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