Screening key lncRNAs with diagnostic and prognostic value for head and neck squamous cell carcinoma based on machine learning and mRNA-lncRNA co-expression network analysis

2020 ◽  
Vol 27 (2) ◽  
pp. 195-206 ◽  
Author(s):  
Ying Hu ◽  
Geyang Guo ◽  
Junjun Li ◽  
Jie Chen ◽  
Pingqing Tan
Keyword(s):  
Machine Learning ◽  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Neck Squamous Cell Carcinoma ◽  
Diagnostic And Prognostic Value

scholarly journals Diagnostic and prognostic value of FOXD1 expression in head and neck squamous cell carcinoma

2021 ◽  
Vol 12 (3) ◽  
pp. 693-702
Author(s):  
Shijie Qiu ◽  
Dan Li ◽  
Zhisen Shen ◽  
Qun Li ◽  
Yi Shen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Neck Squamous Cell Carcinoma ◽  
Diagnostic And Prognostic Value

scholarly journals Differential expression and prognostic value of long non-coding RNA in HPV-negative head and neck squamous cell carcinoma

Head & Neck ◽  
2018 ◽  
Vol 40 (7) ◽  
pp. 1555-1564 ◽  
Author(s):  
Sulsal-Ul Haque ◽  
Liang Niu ◽  
Damaris Kuhnell ◽  
Jacob Hendershot ◽  
Jacek Biesiada ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Differential Expression ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Neck Squamous Cell Carcinoma ◽  
Non Coding Rna ◽  
Long Non Coding Rna

PROGNOSTIC VALUE OF MX1 IN HEAD AND NECK SQUAMOUS CELL CARCINOMA

2017 ◽  
Vol 124 (3) ◽  
pp. e220
Author(s):  
C. DONNELLY ◽  
L. DONNELLY ◽  
Y. XIE ◽  
OKEMOS E. BELLILE ◽  
G. WOLF ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Neck Squamous Cell Carcinoma

scholarly journals The Identification of Stemness-Related Genes in the Risk of Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Guanying Feng ◽  
Feifei Xue ◽  
Yingzheng He ◽  
Tianxiao Wang ◽  
Hua Yuan
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Potential Biomarker ◽  
Score Model

ObjectivesThis study aimed to identify genes regulating cancer stemness of head and neck squamous cell carcinoma (HNSCC) and evaluate the ability of these genes to predict clinical outcomes.Materials and MethodsThe stemness index (mRNAsi) was obtained using a one-class logistic regression machine learning algorithm based on sequencing data of HNSCC patients. Stemness-related genes were identified by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis (LASSO). The coefficient of LASSO was applied to construct a diagnostic risk score model. The Cancer Genome Atlas database, the Gene Expression Omnibus database, Oncomine database and the Human Protein Atlas database were used to validate the expression of key genes. Interaction network analysis was performed using String database and DisNor database. The Connectivity Map database was used to screen potential compounds. The expressions of stemness-related genes were validated using quantitative real‐time polymerase chain reaction (qRT‐PCR).ResultsTTK, KIF14, KIF18A and DLGAP5 were identified. Stemness-related genes were upregulated in HNSCC samples. The risk score model had a significant predictive ability. CDK inhibitor was the top hit of potential compounds.ConclusionStemness-related gene expression profiles may be a potential biomarker for HNSCC.

Prognostic value of lymph node ratio in head and neck squamous cell carcinoma

Head & Neck ◽  
2018 ◽  
Vol 40 (5) ◽  
pp. 1082-1090 ◽  
Author(s):  
Yoav P. Talmi ◽  
Robert P. Takes ◽  
Eran E. Alon ◽  
Iain J. Nixon ◽  
Fernando López ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Lymph Node Ratio ◽  
Neck Squamous Cell Carcinoma ◽  
Node Ratio

Prognostic value of partial EMT‐related genes in head and neck squamous cell carcinoma by a bioinformatic analysis

Oral Diseases ◽  
2020 ◽  
Vol 26 (6) ◽  
pp. 1149-1156 ◽  
Author(s):  
Satoru Kisoda ◽  
Wenhua Shao ◽  
Natsumi Fujiwara ◽  
Yasuhiro Mouri ◽  
Takaaki Tsunematsu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Bioinformatic Analysis ◽  
Neck Squamous Cell Carcinoma

scholarly journals The Prognostic Value of Toll-Like Receptors in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 21 (19) ◽  
pp. 7255
Author(s):  
Shrabon Hasnat ◽  
Roosa Hujanen ◽  
Bright I. Nwaru ◽  
Tuula Salo ◽  
Abdelhakim Salem
Keyword(s):  
Systematic Review ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Meta Analysis ◽  
Small Sample ◽  
Neck Squamous Cell Carcinoma ◽  
Toll Like Receptors

Head and neck squamous cell carcinoma (HNSCC) is a group of tumours which exhibit low 5 year survival rates. Thus, there is an urgent need to identify biomarkers that may improve the clinical utility of patients with HNSCC. Emerging studies support a role of toll-like receptors (TLRs) in carcinogenesis. Therefore, this systematic review and meta-analysis was performed to assess the prognostic value of TLR immunoexpression in HNSCC patients. We compiled the results of thirteen studies comprising 1825 patients, of which six studies were deemed qualified for quantitative synthesis. The higher immunoexpression of TLR-1 to 5 and 9 was associated with a worsening of the clinical parameters of patients with HNSCC. Furthermore, induced levels of TLR-3, 4, 5, 7 and 9 were found to predict the patients’ survival time. The meta-analysis revealed that TLR-7 overexpression is associated with a decreased mortality risk in HNSCC patients (HR 0.51; 95%CI 0.13–0.89; I2 34.6%), while a higher expression of TLR-5 predicted shorter, but non-significant, survival outcome. In conclusion, this review suggests that TLRs may represent some prognostic value for patients with HNSCC. However, due to small sample sizes and other inherent methodological limitations, more well designed studies across different populations are still needed before TLRs can be recommended as a reliable clinical risk-stratification tool.

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