Circulating Long Noncoding RNAs as Biomarkers for Predicting Head and Neck Squamous Cell Carcinoma

Background/Aims: The anatomical complexity of the head and neck region and the lack of sufficiently specific and sensitive biomarkers often lead to the diagnosis of head and neck squamous cell carcinoma (HNSCC) at advanced stages. To identify novel biomarkers for early diagnosis of primary HNSCC through a minimally invasive method, we investigated circulating long noncoding RNA (lncRNA) levels in plasma of HNSCC patients. Methods: The global lncRNA expression profiles of HNSCC patients were measured using microarray and next-generation RNA-sequencing (RNA-seq) data from both circulating and tissue samples. The diagnosis prediction model based on the lncRNA signatures and clinical features was evaluated by multi-stage validation and risk score analysis. Results: The data showed that 432 lncRNA transcripts were differentially expressed by fold changes of > 4 in circulating samples and 333 in tissues samples, respectively. Only 12 lncRNAs consistently emerged in these two kinds of samples. After the risk score analysis including a multistage validation, we identified three lncRNAs, namely, HOXA11-AS, LINC00964 and MALAT1, which were up-regulated in the plasma of HNSCC patients compared with those in healthy controls with merged areas under the curve (AUCs) in training and validation sets of 0.925 and 0.839, respectively. Conclusion: HOXA11-AS, LINC00964 and MALAT1 might be potential circulating biomarkers for the early detection of HNSCC in the future.

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MicroRNA expression profiles of cancer stem cells in head and neck squamous cell carcinoma

International Journal of Oncology ◽

10.3892/ijo.2015.3145 ◽

2015 ◽

Vol 47 (4) ◽

pp. 1249-1256 ◽

Cited By ~ 8

Author(s):

KAZUYA YATA ◽

LEVENT BEKIR BEDER ◽

SHUNJI TAMAGAWA ◽

MUNEKI HOTOMI ◽

YOSHIHIKO HIROHASHI ◽

...

Keyword(s):

Stem Cells ◽

Squamous Cell Carcinoma ◽

Cancer Stem Cells ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Expression Profiles ◽

Microrna Expression ◽

Neck Squamous Cell Carcinoma

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Salivary MicroRNAs for Early Detection of Head and Neck Squamous Cell Carcinoma: A Case-Control Study in the High Altitude Mestizo Ecuadorian Population

BioMed Research International ◽

10.1155/2018/9792730 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 9

Author(s):

Carolina Salazar-Ruales ◽

Jessica-Viviana Arguello ◽

Andrés López-Cortés ◽

Alejandro Cabrera-Andrade ◽

Jennyfer M. García-Cárdenas ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

High Altitude ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Expression Profiles ◽

Neck Squamous Cell Carcinoma ◽

Altered Expression ◽

Mortality And Morbidity ◽

Tumor Stages

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer with the highest incidence worldwide. HNSCC is often diagnosed at advanced stages, incurring significant high mortality and morbidity. The use of saliva, as a noninvasive tool for the diagnosis of cancer, has recently increased. Salivary microRNAs (miRNAs) have emerged as a promising molecular tool for early diagnosis of HNSCC. The aim was to identify the differential expression of salivary miRNAs associated with HNSCC in the high altitude mestizo Ecuadorian population. Using PCR Arrays, miR-122-5p, miR-92a-3p, miR-124-3p, miR-205-5p, and miR-146a-5p were found as the most representative ones. Subsequently, miRNAs expression was confirmed in saliva samples from 108 cases and 108 controls. miR-122-5p, miR-92a-3p, miR-124-3p, and miR-146a-5p showed significant statistical difference between cases and controls with areas under the curve (AUC) of 0.73 (p < 0.001), 0.70 (p < 0.001), 0.71 (p = 0.002), and 0.66 (p = 0.008), respectively. miRNAs were also deregulated in between HNSCC localizations. A differentiated expression of miR-122-5p between oral cancer and oropharynx cancer (AUC of 0.96 p = 0.01) was found: miR-124-3p between larynx and pharynx (AUC = 0.97, p < 0.01) and miR-146a-5p between larynx, oropharynx, and oral cavity (AUC = 0.96, p = 0.01). Moreover, miR-122-5p, miR-124-3p, miR-205-5p, and miR-146a-5p could differentiate between HPV+ and HPV- (p=0.004). Finally, the expression profiles of the five miRNAs were evaluated to discriminate HNSCC patient’s tumor stages (TNM 2-4). miR-122-5p differentiates TNM 2 and 3 (p = 0.002, AUC = 0.92), miR-124-3p TNM 2, 3, and 4 (p < 0.001, AUC = 98), miR-146a-5p TNM 2 and 3 (p < 0.001, AUC = 0.97), and miR-92a-3p TNM 3 (p < 0.001, AUC = 0.99). Taken together, these findings show that altered expression of miRNAs could be used as biomarkers for HNSCC diagnosis in the high altitude mestizo Ecuadorian population.

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

Frontiers in Oncology ◽

10.3389/fonc.2021.688545 ◽

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.

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