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 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 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 Salivary Circular RNAs Hsa_Circ_0001874 and Hsa_Circ_0001971 as Novel Biomarkers for the Diagnosis of Oral Squamous Cell Carcinoma

2018 ◽  
Vol 47 (6) ◽  
pp. 2511-2521 ◽  
Author(s):  
Si-Yu Zhao ◽  
Jun Wang ◽  
Shao-Bo Ouyang ◽  
Zi-Kun Huang ◽  
Lan Liao
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Roc Curve ◽  
Tnm Stage ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Healthy Controls ◽  
Novel Biomarkers

Background/Aims: Recent studies have demonstrated that circular RNAs (circRNAs) can serve as potential molecular markers for disease diagnosis. However, little is known about their diagnostic potential for oral squamous cell carcinoma (OSCC). This study aimed to determine the expression of circRNAs in the saliva of OSCC patients to identify novel biomarkers for OSCC screening. Methods: Microarray screening of circRNA was performed to identify differentially expressed circRNAs in saliva from 3 OSCC patients compared with 3 healthy controls. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to validate the results, and the association between these confirmed salivary circRNAs and clinicopathological features was analyzed using the chi-squared test. A receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of the circRNAs identified. Preoperative expression and postoperative expression (1 month after the surgery) of hsa_circ_0001874 and hsa_circ_0001971 was also determined. Results: Our results indicated 12 upregulated and 20 downregulated circRNAs in the saliva from the OSCC patients compared with that from the healthy controls. Among the differentially expressed circRNAs, hsa_circ_0001874, hsa_circ_0001971, and hsa_circ_0008068 were upregulated and hsa_circ_0000140, hsa_circ_0002632, and hsa_circ_0008792 were downregulated in the OSCC group versus the healthy group. Clinical data indicated that salivary hsa_circ_0001874 was correlated with TNM stage (P=0.006) and tumor grade (P=0.023) and that hsa_circ_0001971 was correlated with TNM stage (P=0.019). The combination of hsa_circ_0001874 and hsa_circ_0001971 showed an area under the ROC curve of 0.922 (95% confidence interval, 0.883-0.961; P< 0.001). The risk score based on the combination of hsa_circ_0001874 and hsa_circ_0001971 also discriminated patients with OSCC from patients with oral leukoplakia (P< 0.001). Moreover, the expression levels of salivary hsa_circ_0001874 and hsa_circ_0001971 were clearly decreased in the postoperative samples compared with preoperative samples (P< 0.001). Conclusions: This is the first study to demonstrate the potential of salivary hsa_circ_0001874 and hsa_circ_0001971 as biomarkers for the diagnosis of OSCC.

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