scholarly journals Integrative Multi−Omics Analysis Reveals Candidate Biomarkers for Oral Squamous Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Zhengqing Wan ◽  
Haofeng Xiong ◽  
Xian Tan ◽  
Tong Su ◽  
Kun Xia ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Therapeutic Targets ◽  
Differentially Expressed ◽  
Integrative Approach ◽  
Hub Genes ◽  
Ppi Networks

Oral squamous cell carcinoma (OSCC) is one of the most common types of cancer worldwide. Due to the lack of early detection and treatment, the survival rate of OSCC remains poor and the incidence of OSCC has not decreased during the past decades. To explore potential biomarkers and therapeutic targets for OSCC, we analyzed differentially expressed genes (DEGs) associated with OSCC using RNA sequencing technology. Methylation−regulated and differentially expressed genes (MeDEGs) of OSCC were further identified via an integrative approach by examining publicly available methylomic datasets together with our transcriptomic data. Protein−protein interaction (PPI) networks of MeDEGs were constructed and highly connected hub MeDEGs were identified from these PPI networks. Subsequently, expression and survival analyses of hub genes were performed using The Cancer Genome Atlas (TCGA) database and the Gene Expression Profiling Interactive Analysis (GEPIA) online tool. A total of 56 upregulated MeDEGs and 170 downregulated MeDEGs were identified in OSCC. Eleven hub genes with high degree of connectivity were picked out from the PPI networks constructed by those MeDEGs. Among them, the expression level of four hub genes (CTLA4, CDSN, ACTN2, and MYH11) were found to be significantly changed in the head and neck squamous carcinoma (HNSC) patients. Three hypomethylated hub genes (CTLA4, GPR29, and TNFSF11) and one hypermethylated hub gene (ISL1) were found to be significantly associated with overall survival (OS) of HNSC patients. Therefore, these hub genes may serve as potential DNA methylation biomarkers and therapeutic targets of OSCC.

scholarly journals Differentially expressed genes and lincRNAs throughout oral squamous cell carcinoma development

2012 ◽  
Vol 26 (S1) ◽  
Author(s):  
João Paulo Oliveira-Costa ◽  
Alex Fiorini Carvalho ◽  
Silvia Vanessa Lourenco ◽  
Luiz Paulo Kowalski ◽  
Dirce Maria Carraro ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Differentially Expressed

scholarly journals Identification of Differential Methylation Regions and Correspondence Targeted Genes in Oral Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Yan Niu ◽  
Qiusheng Shan ◽  
Yuanling Guo
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Biological Process ◽  
Enrichment Analysis ◽  
Differential Methylation ◽  
Differentially Expressed ◽  
Hub Genes ◽  
R Software

Abstract Background The differential methylation included hypermethylation and hypomethylation plays significant role in the progression of many kind of cancers but study little in oral squamous cell carcinoma (OSCC). Methods GSE123781 and GSE87053 was used to analysis the differential methylation regions (DMRs) and predict the target genes in OSCC by R software and wANNOVAR respectively. the biological process and cell pathways of common targeted genes between GSE123781 and GSE87053 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis. The hub genes (hub genes 1) in common targeted genes associated with cancer biological process was identified by protein to protein interaction network (PPI). In addition, GSE74530 and GSE30784 was used to identify common differentially expressed genes (DEGs) in OSCC by R software. The biological process and cell pathways of common DEGs was analyzed by GO and KEGG enrichment analysis. The hub genes (hub genes 2) in common DEGs associated with cancer biological process was identified by PPI network. The significant hub genes between hub genes 1 and hub genes 2 were identified by Venn picture. Finally, the expression level of significant hub genes and correspondence relationship with head and neck squamous cell carcinoma (HNSCC) patient survival were confirmed by The Cancer Genome Atlas (TCGA) dataset. Results There are 2146 common targeted genes regulated by DMRs between GSE123781 and GSE87053 and 278 hub genes in common targeted genes associated with cancer biological process. In addition, there are 895 common DEGs between GSE74530 and GSE30784 and 144 hub genes in common DEGs associated with cancer biological process. There are 9 significant hub genes between hub genes 1 and hub genes 2. Finally, these 9 significant hub genes differentially expressed in HNSCC tissues except CCR7 and quite associated with the survival of HNSCC patients. Conclusions CCR7, ETS1, RUNX3, CCR1, C3AR1, LAMB1, IRF7, LGALS3 and CDKN3 both are DEGs and regulated by DMRs in OSCC, which are quite associated with the progression of OSCC and the survival of HNSCC patients. All of these genes have much potential to be new biomarkers in targeted therapy of OSCC.

Identification of Potential Genes both Differentially Expressed and Regulated by Differential Methylation Regions in Oral Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Yan Niu ◽  
Changsheng Sun ◽  
Qiusheng Shan
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Patient Survival ◽  
Biological Process ◽  
Differential Methylation ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Hnscc Patient

Abstract Background: The aberrant methylation included hypermethylation and hypomethylation plays significant role in the progression of many kind of cancers but poorly investigated in oral squamous cell carcinoma (OSCC). Methods: GSE123781 and GSE87053 were used to identify the differential methylation regions (DMRs) by R software. the targeted genes regulated by DMRs were predicted by wANNOVAR. The biological process, cellular component, molecular function and cell pathways of common targeted genes between GSE123781 and GSE87053 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis. The hub genes in common targeted genes both associated with cancer biological process and cancer cell pathways were identified by protein to protein interaction network (PPI). Finally, the expression level of hub genes and correspondence relationship with head and neck squamous cell carcinoma (HNSCC) patient survival were confirmed by The Cancer Genome Atlas (TCGA) dataset. Results: There are 372 common targeted genes regulated by DMRs between GSE123781 and GSE87053 and RUNX family transcript factor 1 (RUNX1), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit gamma (PIK3CG), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta (PIK3CD), laminin subunit beta 1 (LAMB1), integrin subunit alpha M (ITGAM), interleukin 2 receptor subunit alpha (IL2RA), interleukin 10 (IL10), FYN proto-oncogene, Src family tyrosine kinase (FYN), cholinergic receptor muscarinic 1 (CHRM1) and C-C motif chemokine receptor 1 (CCR1) are hub genes in common targeted genes. Furthermore, RUNX1, PIK3R1, PIK3CD, LAMB1, ITGAM, IL2RA, IL10, FYN, CHRM1 and CCR1 differentially expressed in HNSCC tissues and the overexpressed genes PIK3CD, LAMB1 and IL10 could lead to the decrease of HNSCC patient survival. Conclusions: PIK3CD, LAMB1 and IL10 both differentially expressed and regulated by DMRs are quite associated with the progression of OSCC and the survival of HNSCC patients, which has much potential to be new biomarkers in targeted therapy of OSCC.

scholarly journals Laplacian Likelihood based Generalized Additive Model for RNA-Seq Analysis of Oral Squamous Cell Carcinoma

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Non Linear

The study's objective is to identify the non-linear relationship of differentially expressed genes that vary in terms of the tumour and normal tissue and correct for any variations among the RNA-Seq experiment focused on Oral squamous cell carcinoma samples from patients. A Laplacian Likelihood version of the Generalized Additive Model is proposed and compared with the regular GAM models in terms of the non-linear fitting. The Non-Linear machine learning approach of Laplacian Likelihood-based GAM could complement RNA-Seq Analysis mainly to interpret, validate, and prioritize the patient samples data of differentially expressed genes. The analysis eases the standard parametric presumption and helps discover complexity in the association between the dependent and the independent variable and parameter smoothing that might otherwise be neglected. Concurvity, standard error, deviance, and other statistical verification have been carried out to confirm Laplacian Likelihood-based GAM efficiency.

Identification of differentially expressed genes in oral squamous cell carcinoma

2005 ◽  
Vol 42 (2) ◽  
pp. 97-108 ◽  
Author(s):  
Shilpi Arora ◽  
Ajay Matta ◽  
Nootan Kumar Shukla ◽  
S.V.S. Deo ◽  
Ranju Ralhan
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Differentially Expressed

scholarly journals Identifying an lncRNA-Related ceRNA Network to Reveal Novel Targets for a Cutaneous Squamous Cell Carcinoma

Biology ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 432
Author(s):  
Yaqin Xu ◽  
Yingying Dong ◽  
Yunhua Deng ◽  
Qianrong Qi ◽  
Mi Wu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Biological Process ◽  
Normal Skin ◽  
Expression Patterns ◽  
Therapeutic Targets ◽  
Cutaneous Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Cerna Network

A cutaneous squamous cell carcinoma (cSCC) derived from keratinocytes is the second most common cause of non-melanoma skin cancer. The accumulation of the mutational burden of genes and cellular DNA damage caused by the risk factors (e.g., exposure to ultraviolet radiation) contribute to the aberrant proliferation of keratinocytes and the formation of a cSCC. A cSCC encompasses a spectrum of diseases that range from recursor actinic keratosis (AK) and squamous cell carcinoma (SCC) in situ (SCCIS) to invasive cSCCs and further metastatic SCCs. Emerging evidence has revealed that lncRNAs are involved in the biological process of a cSCC. According to the ceRNA regulatory theory, lncRNAs act as natural miRNA sponges and interact with miRNA response elements, thereby regulating the mRNA expression of their down-stream targets. This study was designed to search for the potential lncRNAs that may become potential therapeutic targets or biomarkers of a cSCC. Considering the spirit of the study to be adequately justified, we collected microarray-based datasets of 19 cSCC tissues and 12 normal skin samples from the GEO database (GSE42677 and GSE45164). After screening the differentially expressed genes via a limma package, we identified 24 differentially expressed lncRNAs (DElncRNAs) and 3221 differentially expressed mRNAs (DEmRNAs). The miRcode, miRTarBase, miRDB and TargetScan databases were used to predict miRNAs that could interact with DElncRNAs and DEmRNAs. A total of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs were retained in the ceRNA network, consisting of 31 miRNAs, 11 DElncRNAs and 155 DEmRNAs. For the functional analysis, the top enriched biological process was enhancer sequence-specific DNA binding in Gene Ontology (GO) terms. The FoxO signaling pathway, autophagy and cellular senescence were the top enrichment terms based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The combination of a STRING tool and Cytoscape software (plug-in MCODE) identified five core mRNAs and built a core mRNA-associated ceRNA network. The expression for five identified core mRNAs and their related nine lncRNAs was validated using the external dataset GSE7553. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 were validated with the same expression patterns. We speculate that lncRNA HLA-F-AS1 may sponge miR-17-5p or miR-20b-5p to regulate the expression of CCND1 and E2F1 in the cSCC. The present study may provide potential diagnostic and therapeutic targets for cSCC patients.

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