A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma

Abstract Background Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown. Methods We performed weighted g...

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Main Authors: Jian Zhang, Huaming Lin, Huali Jiang, Hualong Jiang, Tao Xie, Baiyao Wang, Xiaoting Huang, Jie Lin, Anan Xu, Rong Li, Jiexia Zhang, Yawei Yuan
Format: Article
Language:English
Published: BMC 2020-03-01
Series:BMC Cancer
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12885-020-06728-1
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author Jian Zhang
Huaming Lin
Huali Jiang
Hualong Jiang
Tao Xie
Baiyao Wang
Xiaoting Huang
Jie Lin
Anan Xu
Rong Li
Jiexia Zhang
Yawei Yuan
author_facet Jian Zhang
Huaming Lin
Huali Jiang
Hualong Jiang
Tao Xie
Baiyao Wang
Xiaoting Huang
Jie Lin
Anan Xu
Rong Li
Jiexia Zhang
Yawei Yuan
author_sort Jian Zhang
collection DOAJ
description Abstract Background Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown. Methods We performed weighted gene co-expression network analysis to construct gene co-expression networks and investigate the relationship between key modules and the LOI clinical phenotype. Functional enrichment and KEGG pathway analyses were performed with differentially expressed genes. A protein–protein interaction network was constructed using Cytoscape, and module analysis was performed using MCODE. Prognostic value, expression analysis, and survival analysis were conducted using hub genes; GEPIA and the Human Protein Atlas database were used to determine the mRNA and protein expression levels of hub genes, respectively. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. Finally, potential small molecular agents that could target LOI were identified with DrugBank. Results Ten co-expression modules in two key modules (turquoise and pink) associated with LOI were identified. Functional enrichment and KEGG pathway analysis revealed that turquoise and pink modules played significant roles in HNSCC progression. Seven hub genes (CNFN, KIF18B, KIF23, PRC1, CCNA2, DEPDC1, and TTK) in the two modules were identified and validated by survival and expression analyses, and the following prognostic risk formula was established: [risk score = EXPDEPDC1 * 0.32636 + EXPCNFN * (− 0.07544)]. The low-risk group showed better overall survival than the high-risk group (P < 0.0001), and the AUCs for 1-, 3-, and 5-year overall survival were 0.582, 0.634, and 0.636, respectively. Eight small molecular agents, namely XL844, AT7519, AT9283, alvocidib, nelarabine, benzamidine, L-glutamine, and zinc, were identified as novel candidates for controlling LOI in HNSCC (P < 0.05). Conclusions The two-mRNA signature (CNFN and DEPDC1) could serve as an independent biomarker to predict LOI risk and provide new insights into the mechanisms underlying LOI in HNSCC. In addition, the small molecular agents appear promising for LOI treatment.
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spelling doaj.art-ba28c0dd63dc4bfdb87e74dae3555fa22022-12-21T19:20:14ZengBMCBMC Cancer1471-24072020-03-0120111210.1186/s12885-020-06728-1A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinomaJian Zhang0Huaming Lin1Huali Jiang2Hualong Jiang3Tao Xie4Baiyao Wang5Xiaoting Huang6Jie Lin7Anan Xu8Rong Li9Jiexia Zhang10Yawei Yuan11Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseThe First Tumor Department, Maoming People’s HospitalDepartment of Cardiovascularology, Tungwah Hospital of Sun Yat-sen UniversityDepartment of Urology, Tungwah Hospital of Sun Yat-sen UniversityDepartment of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseDepartment of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseDepartment of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseDepartment of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseDepartment of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseDepartment of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical UniversityDepartment of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory DiseaseAbstract Background Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown. Methods We performed weighted gene co-expression network analysis to construct gene co-expression networks and investigate the relationship between key modules and the LOI clinical phenotype. Functional enrichment and KEGG pathway analyses were performed with differentially expressed genes. A protein–protein interaction network was constructed using Cytoscape, and module analysis was performed using MCODE. Prognostic value, expression analysis, and survival analysis were conducted using hub genes; GEPIA and the Human Protein Atlas database were used to determine the mRNA and protein expression levels of hub genes, respectively. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. Finally, potential small molecular agents that could target LOI were identified with DrugBank. Results Ten co-expression modules in two key modules (turquoise and pink) associated with LOI were identified. Functional enrichment and KEGG pathway analysis revealed that turquoise and pink modules played significant roles in HNSCC progression. Seven hub genes (CNFN, KIF18B, KIF23, PRC1, CCNA2, DEPDC1, and TTK) in the two modules were identified and validated by survival and expression analyses, and the following prognostic risk formula was established: [risk score = EXPDEPDC1 * 0.32636 + EXPCNFN * (− 0.07544)]. The low-risk group showed better overall survival than the high-risk group (P < 0.0001), and the AUCs for 1-, 3-, and 5-year overall survival were 0.582, 0.634, and 0.636, respectively. Eight small molecular agents, namely XL844, AT7519, AT9283, alvocidib, nelarabine, benzamidine, L-glutamine, and zinc, were identified as novel candidates for controlling LOI in HNSCC (P < 0.05). Conclusions The two-mRNA signature (CNFN and DEPDC1) could serve as an independent biomarker to predict LOI risk and provide new insights into the mechanisms underlying LOI in HNSCC. In addition, the small molecular agents appear promising for LOI treatment.http://link.springer.com/article/10.1186/s12885-020-06728-1Lymphovascular invasionHead and neck squamous cell carcinomaHub genesTCGAWeighted gene co-expression network analysis
spellingShingle Jian Zhang
Huaming Lin
Huali Jiang
Hualong Jiang
Tao Xie
Baiyao Wang
Xiaoting Huang
Jie Lin
Anan Xu
Rong Li
Jiexia Zhang
Yawei Yuan
A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma
BMC Cancer
Lymphovascular invasion
Head and neck squamous cell carcinoma
Hub genes
TCGA
Weighted gene co-expression network analysis
title A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma
title_full A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma
title_fullStr A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma
title_full_unstemmed A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma
title_short A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma
title_sort key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma
topic Lymphovascular invasion
Head and neck squamous cell carcinoma
Hub genes
TCGA
Weighted gene co-expression network analysis
url http://link.springer.com/article/10.1186/s12885-020-06728-1
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