Identification of Key Biomarkers and Potential Molecular Mechanisms in Oral Squamous Cell Carcinoma by Bioinformatics Analysis

Bao, Yong-Rui; Dong, Ke-Qin; Guo, Peiyuan; Guo, Peng; Guo, Jie; Zhang, Guanhua; Li, Tianke

doi:10.1089/cmb.2019.0211

Cited by 21 publications

(4 citation statements)

References 45 publications

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“…Oral squamous cell carcinoma (OSCC) has the biological characteristics of uncontrollable invasiveness, high mortality and extensive hypoxia ( 1 ). Data from the Surveillance, Epidemiology, and End Results in 2000 suggested that 28,900 people in the US are diagnosed with OSCC every year, of which ~7,400 deaths are reported annually ( 2 ).…”

Section: Introductionmentioning

confidence: 99%

Maternally expressed 3 inhibits the biological activity of oral squamous cell carcinoma SCC25 and CAL27 cell lines

Wang

Li²,

Qiu

et al. 2021

Oncol Lett

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The abnormal expression of long non-coding RNA (lncRNA) maternally expressed 3 (MEG3) is closely related to several tumor diagnosis and progression, such as endometrial carcinoma and ovarian cancer. However, the role of MEG3 in oral squamous cell carcinoma (OSCC) is rarely reported. The current study aimed to evaluate the expression of lncRNA MEG3 in OSCC tissues and cell lines and its effect on the biological behavior of OSCC cell lines. The expression of lncRNA MEG3 in the OSCC tissues and cell lines was detected by reverse transcription-quantitative (RT-q) PCR. The relationship between MEG3 expression and the clinicopathologic characteristics and prognosis of patients with OSCC was analyzed. The lncRNA MEG3 overexpression plasmid and control plasmid were transfected into SCC25 and CAL27 cell lines using the lipofectin method. MTT assay was performed to detect the growth and proliferation of the cell lines. Transwell chamber test was used to detect changes in cell migration and invasion. Flow cytometry was employed to detect changes in apoptosis. Western blotting and RT-qPCR were conducted to detect the expression of the p53 gene. The expression of lncRNA MEG3 in the OSCC tissues and cell lines was significantly compared with normal tissues and cell lines, respectively. The expression level of MEG3 was related to clinical stage, lymph node metastasis, distant metastasis and survival status. Overexpression of lncRNA MEG3 inhibited the proliferation, migration, and invasion of SCC25 and CAL27 cell lines, induced apoptosis and promoted the expression of p53 gene. lncRNA MEG3 played the role of a tumor inhibitor gene and significantly inhibited the biological activity of OSCC cell lines, which may provide a novel idea for molecular targeted therapy of OSCC.

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Section: Introductionmentioning

confidence: 99%

Maternally expressed 3 inhibits the biological activity of oral squamous cell carcinoma SCC25 and CAL27 cell lines

Wang

Li²,

Qiu

et al. 2021

Oncol Lett

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“…The MAPK signaling pathway can regulate chondrocyte proliferation, apoptosis, extracellular matrix metabolism, inflammatory factor secretion, and other processes, and play an important role in the pathological process of OA. Khan et al (22) showed that the 3-phosphoinositol-dependent protein kinase (PDK) can promote chondrocyte apoptosis in OA through the p38 MAPK signaling pathway (23,24), while Yang et al (25) found DUal-specificity phosphatase (DUSP) overexpression in OA inhibited the activation of MAPK signaling and the expression of the OA-associated matrix. Zhang et al (26) revealed the JAK/STAT signaling pathway was regulated by significantly upregulated by proinflammatory cytokine gene expression, while MMP-13 expression in the IL-1treated human chondrosarcoma cell lines induced JAK2 and STAT1/STAT2 activation and MMP-13 gene expression which was blocked by the pan-tyrosine kinase inhibitor AG490 (27)(28)(29)(30).…”

Section: Discussionmentioning

confidence: 99%

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

You¹,

Liu²,

Tan³

2022

Ann Transl Med

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Background: Searching for the production mechanism of synovial lesions helps to find precise therapeutic targets and improve prognosis. The previous identification and screening of differential genes in osteoarthritis (OA) pathogenesis were well combined to further build a risk prognosis model of OA, which is beneficial to the diagnosis and treatment of patients with OA. Methods:The synovia-related chip data sets GSE82107, GSE12021, GSE55457, and GSE55235 were downloaded from the public database of Gene Expression Omnibus (GEO), and 40 cases of synovial tissues of OA and 36 cases of normal synovial tissues were included. R software was used to screen differentially expressed genes (DEGs), Gene Ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The STRING online analysis tool and Cytoscape software were used to further screen key genes, and a prognostic model of OA susceptibility risk was constructed. Results:The results showed 1,921 differential genes, including 762 upregulated genes and 1,159 downregulated genes, which were mainly involved cell growth, cell adhesion, skeletal muscle growth, iron ion binding, ubiquitin protein ligase binding, and hormone receptor binding. Co-acquisition based on 10 key target genes of the protein interaction network, containing CTNNB1, GSK3B, STAT1, RHOC, HDAC9, PSEN1, KDM5C, BACE1, JAK3, and CUL1. The area under the concentration-time curve (AUC) was used to evaluate the prognostic model of OA risk, and the curve results showed that the prognostic model had high accuracy and validity (AUC =0.690).Conclusions: Bioinformatics analysis was applied to screen out the DEG profiles of OA. This may provide functional predictions to provide new ideas for treatment of the disease and may be a biological marker for its diagnosis and a potential target for treatment. The construction of the risk and prognosis model is beneficial to the risk assessment of rehabilitation function recovery of patients with OA, the evaluation of the severity of the disease and the subsequent treatment guidance.

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“…Moreover, the MMP1 gene might be used as a potential target to improve diagnosis and as an oral cancer marker for OSCC ( Hashimoto et al., 2004 ; Yen et al., 2009 ; Yang et al., 2020 ). Functional enrichment analysis revealed that MMP13, MMP7, and MMP1 were related to ECM organization, ECM disassembly, extracellular structure organization, and endoderm development.…”

Section: Discussionmentioning

confidence: 99%

Evolutionary Relationships Between Dysregulated Genes in Oral Squamous Cell Carcinoma and Oral Microbiota

Fang

Yang

Liu

2022

Front. Cell. Infect. Microbiol.

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Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers in the world. Changes in the composition and abundance of oral microbiota are associated with the development and metastasis of OSCC. To elucidate the exact roles of the oral microbiota in OSCC, it is essential to reveal the evolutionary relationships between the dysregulated genes in OSCC progression and the oral microbiota. Thus, we interrogated the microarray and high-throughput sequencing datasets to obtain the transcriptional landscape of OSCC. After identifying differentially expressed genes (DEGs) with three different methods, pathway and functional analyses were also performed. A total of 127 genes were identified as common DEGs, which were enriched in extracellular matrix organization and cytokine related pathways. Furthermore, we established a predictive pipeline for detecting the coevolutionary of dysregulated host genes and microbial proteomes based on the homology method, and this pipeline was employed to analyze the evolutionary relations between the seven most dysregulated genes (MMP13, MMP7, MMP1, CXCL13, CRISPO3, CYP3A4, and CRNN) and microbiota obtained from the eHOMD database. We found that cytochrome P450 3A4 (CYP3A4), a member of the cytochrome P450 family of oxidizing enzymes, was associated with 45 microbes from the eHOMD database and involved in the oral habitat of Comamonas testosteroni and Arachnia rubra. The peptidase M10 family of matrix metalloproteinases (MMP13, MMP7, and MMP1) was associated with Lacticaseibacillus paracasei, Lacticaseibacillus rhamnosus, Streptococcus salivarius, Tannerella sp._HMT_286, and Streptococcus infantis in the oral cavity. Overall, this study revealed the dysregulated genes in OSCC and explored their evolutionary relationship with oral microbiota, which provides new insight for exploring the microbiota–host interactions in diseases.

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Identification of Key Biomarkers and Potential Molecular Mechanisms in Oral Squamous Cell Carcinoma by Bioinformatics Analysis

Cited by 21 publications

References 45 publications

Maternally expressed 3 inhibits the biological activity of oral squamous cell carcinoma SCC25 and CAL27 cell lines

Maternally expressed 3 inhibits the biological activity of oral squamous cell carcinoma SCC25 and CAL27 cell lines

Screening and identification of osteoarthritis related differential genes and construction of a risk prognosis model based on bioinformatics analysis

Evolutionary Relationships Between Dysregulated Genes in Oral Squamous Cell Carcinoma and Oral Microbiota

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