Microarray Analysis of Serum mRNA in Patients with Head and Neck Squamous Cell Carcinoma at Whole-Genome Scale

With the increasing demand for noninvasive approaches in monitoring head and neck cancer, circulating nucleic acids have been shown to be a promising tool. We focused on the global transcriptome of serum samples of head and neck squamous cell carcinoma (HNSCC) patients in comparison with healthy individuals. We compared gene expression patterns of 36 samples. Twenty-four participants including 16 HNSCC patients (from 12 patients we obtained blood samples 1 year posttreatment) and 8 control subjects were recruited. The Illumina HumanWG-6 v3 Expression BeadChip was used to profile and identify the differences in serum mRNA transcriptomes. We found 159 genes to be significantly changed (Storey’sPvalue<0.05) between normal and cancer serum specimens regardless of factors including p53 and B-cell lymphoma family members (Bcl-2, Bcl-XL). In contrast, there was no difference in gene expression between samples obtained before and after surgery in cancer patients. We suggest that microarray analysis of serum cRNA in patients with HNSCC should be suitable for refinement of early stage diagnosis of disease that can be important for development of new personalized strategies in diagnosis and treatment of tumours but is not suitable for monitoring further development of disease.

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Bioinformatics analysis of DNMT1 expression and its role in head and neck squamous cell carcinoma prognosis

Scientific Reports ◽

10.1038/s41598-021-81971-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jili Cui ◽

Lian Zheng ◽

Yuanyuan Zhang ◽

Miaomiao Xue

Keyword(s):

Gene Expression ◽

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Immune Cell ◽

Neck Squamous Cell Carcinoma ◽

Hub Genes ◽

Significant Difference ◽

Dnmt1 Expression

AbstractHead and neck squamous cell carcinoma (HNSCC) is the sixth most common type of malignancy in the world. DNA cytosine-5-methyltransferase 1 (DNMT1) play key roles in carcinogenesis and regulation of the immune micro-environment, but the gene expression and the role of DNMT1 in HNSCC is unknown. In this study, we utilized online tools and databases for pan-cancer and HNSCC analysis of DNMT1 expression and its association with clinical cancer characteristics. We also identified genes that positively and negatively correlated with DNMT1 expression and identified eight hub genes based on protein–protein interaction (PPI) network analysis. Enrichment analyses were performed to explore the biological functions related with of DNMT1. The Tumor Immune Estimation Resource (TIMER) database was performed to explore the relationship between DNMT1 expression and immune-cell infiltration. We demonstrated that DNMT1 gene expression was upregulated in HNSCC and associated with poor prognosis. Based on analysis of the eight hub genes, we determined that DNMT1 may be involved in cell cycle, proliferation and metabolic related pathways. We also found that significant difference of B cells infiltration based on TP 53 mutation. These findings suggest that DNMT1 related epigenetic alterations have close relationship with HNSCC progression, and DNMT1 could be a novel diagnostic biomarker and a promising therapeutic target for HNSCC.

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Functional Genomics Screen with Pooled shRNA Library and Gene Expression Profiling with Extracts of Azadirachta indica Identify Potential Pathways for Therapeutic Targets in Head and Neck Squamous Cell Carcinoma

10.1101/381749 ◽

2018 ◽

Author(s):

Neeraja M Krishnan ◽

Hiroto Katoh ◽

Vinayak Palve ◽

Manisha Pareek ◽

Reiko Sato ◽

...

Keyword(s):

Gene Expression ◽

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Head And Neck ◽

Cancer Cell ◽

Squamous Cell ◽

Azadirachta Indica ◽

Neck Squamous Cell Carcinoma ◽

Neem Extract ◽

Infected Cells

AbstractTumor suppression by the extracts of Azadirachta indica (neem) works via anti-proliferation, cell cycle arrest, and apoptosis, demonstrated previously using cancer cell lines and live animal models. However, very little is known about the molecular targets and pathways that the neem extracts and the associated compounds act through. Here, we address this using a genome-wide functional pooled shRNA screen on head and neck squamous cell carcinoma cell line treated with crude neem leaf extracts, known for their anti-tumorigenic activity. By analyzing differences in global clonal sizes of the shRNA-infected cells cultured under no treatment and treatment with neem leaf extract conditions, assayed using next-generation sequencing, we found 225 genes affected the cancer cell growth in the shRNA-infected cells treated with neem extract. Pathway enrichment analyses of whole-genome gene expression data from cells temporally treated with neem extract revealed important roles played by the TGF-β pathway and HSF-1-related gene network. Our results indicate that neem extract simultaneously affects various important molecular signaling pathways in head and neck cancer cells, some of which may be therapeutic targets for this devastating tumor.

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Identification of Expression Patterns and Potential Prognostic Significance of m5C-Related Regulators in Head and Neck Squamous Cell Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.592107 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhenyuan Han ◽

Biao Yang ◽

Yu Wang ◽

Xiuxia Zeng ◽

Zhen Tian

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Expression Patterns ◽

Critical Role ◽

Low Risk ◽

Neck Squamous Cell Carcinoma ◽

Differentially Expressed ◽

Rna Modification

5-Methylcytosine (m5C) methylation is a major epigenetic technique of RNA modification and is dynamically mediated by m5C “writers,” “erasers,” and “readers.” m5C RNA modification and its regulators are implicated in the onset and development of many tumors, but their roles in head and neck squamous cell carcinoma (HNSCC) have not yet been completely elucidated. In this study, we examined expression patterns of core m5C regulators in the publicly available HNSCC cohort via bioinformatic methods. The differentially expressed m5C regulators could divide the HNSCC cohort into four subgroups with distinct prognostic characteristics. Furthermore, a three-gene expression signature model, comprised of NSUN5, DNMT1, and DNMT3A, was established to identify individuals with a high or low risk of HNSCC. To explore the underlying mechanism in the prognosis of HNSCC, screening of differentially expressed genes, followed by the analysis of functional and pathway enrichment, from individuals with high- or low-risk HNSCC was performed. The results revealed a critical role for m5C RNA modification in two aspects of HNSCC: (1) dynamic m5C modification contributes to the regulation of HNSCC progression and (2) expression patterns of NSUN5, DNMT1, and DNMT3A help to predict the prognosis of HNSCC.

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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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