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The underlying molecular mechanism and identification of transcription factor markers for laryngeal squamous cell carcinoma.

ABSTRACT: The screening and treatment of laryngeal squamous cell carcinoma (LSCC) still perplexes clinicians, making it necessary to explore new markers. To this end, this research examined the underlying molecular mechanism of LSCC based on high-throughput datasets (n = 249) from multiple databases. It also identified transcription factors (TFs) independently associated with LSCC prognosis. Through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, differential expression genes of LSCC were deemed relevant to the extracellular matrix and its related structures or pathways, suggesting that the extracellular matrix plays an important role in LSCC. At the same time, several hub genes that may also have important roles in LSCC were identified via protein-protein interaction analysis, including CDC45, TPX2, AURKA, KIF2C, NUF, MUC1, MUC7, MUC4, MUC15, and MUC21. Eight unreported LSCC prognostic TFs - BCAT1, CHD4, FOXA2, GATA6, HNF1A, HOXB13, MAFF, and TCF4 - were screened via Kaplan-Meier curves. Cox analysis determined for the first time that HOXB13 expression and gender were independently associated with LSCC prognosis. Compared to control tissues, elevated expression of HOXB13 was found in LSCC tissues (standardized mean difference = 0.44, 95% confidence interval [0.13-0.76]). HOXB13 expression also makes it feasible to screen LSCC from non-LSCC (area under the curve = 0.77), and HOXB13 may play an essential role in LSCC by regulating HOXB7. In conclusion, HOXB13 may be a novel marker for LSCC clinical screening and treatment.

SUBMITTER: Mo BY

PROVIDER: S-EPMC8291796 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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The underlying molecular mechanism and identification of transcription factor markers for laryngeal squamous cell carcinoma.

Mo Bin-Yu BY Li Guo-Sheng GS Huang Su-Ning SN He Wei-Ying WY Xie Li-Yuan LY Wei Zhu-Xin ZX Su Ya-Si YS Liang Yue Y Yang Li L Ye Cheng C Dai Wen-Bin WB Ruan Lin L

Bioengineered 20211201 1

The screening and treatment of laryngeal squamous cell carcinoma (LSCC) still perplexes clinicians, making it necessary to explore new markers. To this end, this research examined the underlying molecular mechanism of LSCC based on high-throughput datasets (<i>n</i> = 249) from multiple databases. It also identified transcription factors (TFs) independently associated with LSCC prognosis. Through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, differential expression genes of ...[more]

PMID: 33315534

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Project description:BackgroundLaryngeal squamous cell carcinoma (LSCC) is the prominent cancer in head and neck, which greatly affects life quality of patients. The pathogenesis of LSCC is not clear. Presently, the LSCC treatments include chemotherapy, surgery and radiotherapy; however, these methods have poor efficacy in patients with recurrent and persistent cancer. Therefore, the study identified the hub genes accompanied with LSCC, which may be a potential therapeutic target in the future.MethodsWe extracted whole transcriptome high-throughput sequencing (HTS) LSCC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and calculate differentially expressed genes (DEGs) between LSCC and normal samples using statistical software RStudio. Through weighted gene co-expression network analysis (WGCNA), enrichment examination of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) functions, and examination of protein-protein interaction (PPI) network, we obtained network hub genes and validated the hub genes prognostic value and expression levels of protein.ResultsThrough analysis of differential gene expression, from the GEO and TCGA databases 2,139 and 2,774 DEGs were obtained, respectively, 13 and 15 modules were screened from TCGA-LSCC and GSE127165 datasets by WGCNA, respectively. The most significant positive and negative correlation modules in the WGCNA and DEG lists were overlapped, and overall 36 co-expressed overlapping genes were retrieved. Through enrichment analysis of GO and KEGG, it was found that the gene functions were highly concentrated in cell junction assembly, basement membrane, extracellular matrix (ECM) structural constituent etc., and the pathways were mainly concentrated in ECM receptor interaction, focal adhesion, small cell lung cancer, and toxoplasmosis. Through analysis of PPI network analysis, 10 network hub genes (SNAI2, ITGA6, LAMB3, LAMC2, CAV1, COL7A1, GJA1, EHF, OAT, and GPT) were obtained. Finally, survival analysis and protein expression validation of these genes confirmed that low OAT expression and high CAV1 expression remarkably influenced the survival of patient's prognosis with LSCC.ConclusionsWe recognized the hub genes and key modules nearly associated to LSCC and these genes were validated by survival analysis and the database of Human Protein Atlas (HPA), which is of high importance for unveiling the pathogenesis of LSCC and probing for new precise biological marker and potential therapeutic targets.

Project description:Background: Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignancy in the respiratory tract and could reduce the quality of life seriously like dyspnea, dysphonia and dysphagia. Moreover, 5-year survival rate has decreased over the past 40 years. This study was designed to identify mRNAs that related to prognosis in LSCC to enable early detection and outcome improvement. Methods: Gene expression profiles from Gene Expression Omnibus (GEO) (GSE59102, GSE84957) and The Cancer Genome Atlas (TCGA) were analyzed to identify differentially expressed genes (DEGs) with the help of bioinformatics tools. Functional enrichment analyses including Gene Ontology (GO) and pathway analysis were carried out to investigate the role of those genes and underlying molecular mechanisms in LSCC. Cox's regression analyses (univariate, LASSO and multivariate in order) were utilized to identify DEGs related with patients' overall survival and a 4-mRNA-based prognostic risk score model was established. Univariate and multivariate Cox's regression analyses were then performed on LSCC data (90 patients left) to identify independent predictors of OS, including the signature and clinicopathologic variables. The prognostic value of the gene signature was further validated and the genes were analyzed by GEPIA to get pan-cancer expression profiles. Results: 444 differentially expressed mRNAs (250 up-regulated, 194 down-regulated) were identified based on the threshold of fold change > 2 and adjusted p value < 0.05. Univariate Cox's regression analysis showed that high risk score (HR: 3.056, 95% confidence interval [CI]: 0.135-0.649, p<0.001) and female (HR: 0.296, 95% CI: 2.020-4.624, p=0.002) were associated with relatively poor prognosis. Further multivariate Cox's regression analysis indicated that risk score and gender were independent prognostic factors (p<0.05). The risk score model could stratify patients into high- and low‑risk groups, which presents significantly differential overall survival (p= 8.252e-04). The AUCs of 1-, 3- and 5-year OS were 0.724, 0.783 and 0.818, respectively. Conclusions: Our study provides evidence that the four-mRNA signature could serve as a biomarker to predict prognosis in LSCC, especially in long-term.

Project description:BackgroundThis study is aimed at investigating the expressions and prognostic values of secreted or membrane-located proteins (SMPs) in laryngeal squamous cell carcinoma (LSCC). The correlations between the expressions of SMPs and immune cells' infiltrations were also investigated.MethodsThe expression data of normal laryngeal and LSCC samples were obtained from the TCGA and GEO datasets. The differentially expressed SMPs were identified, and their prognostic values were analyzed. The biological functions of differentially expressed and worse-survival-related SMPs were explored. LASSO regression, Cox multivariate analysis, and nomogram were used to construct a model to predict the survival. Then, the infiltrations of the 24 immune cell populations were calculated using the GSVA method, and the correlations between the expression of SMPs and the immune infiltration were investigated.Results122 samples (12 normal and 120 LSCC) of the TCGA database and 114 samples (57 normal and 57 LSCC) of GSE127165 were included. We identified that 138 SMPs were significantly upregulated in LSCC samples of both the TCGA and GEO datasets, among which 52 SMPs were significantly correlated with worse survival. GO and KEGG analyses revealed those 52 SMPs significantly participate in tumor microenvironment and immune cells' communication. Nine of 52 SMPs (ABCC5, ATP1B3, CLEC11A, FLNA, FSTL3, MMP1, NME1, OAS3, and PHLDB2) were included in the nomogram to effectively and accurately predict the LSCC patients' survival. The expressions of most SMPs, such as MMP1 and FSTL3, were significantly positively correlated with the immune infiltration of LSCC.ConclusionsIn this study, the expression, prognostic values, and correlations with immune infiltration of SMPs were analyzed in LSCC samples. Our analyses identified several significant SMPs differentially expressed between normal laryngeal and LSCC samples, correlated with worse survival, and related to the immune infiltration.

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The underlying molecular mechanism and identification of transcription factor markers for laryngeal squamous cell carcinoma.

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The underlying molecular mechanism and identification of transcription factor markers for laryngeal squamous cell carcinoma.

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