scholarly journals Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis

2019 ◽  
Author(s):  
Jun Man ◽  
Xiaomei Zhang ◽  
Huan Dong ◽  
Simin Li ◽  
Xiaolin Yu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
Screening And Identification

scholarly journals Diagnosis value of aberrantly expressed microRNA profiles in lung squamous cell carcinoma: a study based on the Cancer Genome Atlas

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4101 ◽  
Author(s):  
Sheng Yang ◽  
Jing Sui ◽  
Geyu Liang
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background Lung cancer is considered as one of the most frequent and deadly cancers with high mortality all around the world. It is critical to find new biomarkers for early diagnosis of lung cancer, especially lung squamous cell carcinoma (LUSC). The Cancer Genome Atlas (TCGA) is a database which provides both cancer and clinical information. This study is a comprehensive analysis of a novel diagnostic biomarker for LUSC, based on TCGA. Methods and Results The present study investigated LUSC-specific key microRNAs (miRNAs) from large-scale samples in TCGA. According to exclusion criteria and inclusion criteria, the expression profiles of miRNAs with related clinical information of 332 LUSC patients were obtained. Most aberrantly expressed miRNAs were identified between tumor and normal samples. Forty-two LUSC-specific intersection miRNAs (fold change >2, p < 0.05) were obtained by an integrative computational method, among them six miRNAs were found to be aberrantly expressed concerning characteristics of patients (gender, lymphatic metastasis, patient outcome assessment) through Student t-test. Five miRNAs correlated with overall survival (log-rank p < 0.05) were obtained through the univariate Cox proportional hazards regression model and Mantel–Haenszel test. Then, five miRNAs were randomly selected to validate the expression in 47 LUSC patient tissues using quantitative real-time polymerase chain reaction. The results showed that the test findings were consistent with the TCGA findings. Also, the diagnostic value of the specific key miRNAs was determined by areas under receiver operating characteristic curves. Finally, 577 interaction mRNAs as the targets of 42 LUSC-specific intersection miRNAs were selected for further bioinformatics analysis. Conclusion This study indicates that this novel microRNA expression signature may be a useful biomarker of the diagnosis for LUSC patients, based on bioinformatics analysis.

scholarly journals Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis

2020 ◽  
Vol 21 (8) ◽  
pp. 2994
Author(s):  
Miaomiao Gao ◽  
Weikaixin Kong ◽  
Zhuo Huang ◽  
Zhengwei Xie
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Good Prediction ◽  
Good Prediction Accuracy ◽  
Key Genes

Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.

scholarly journals MiR-497-5p down-regulates CDCA4 to restrains lung squamous cell carcinoma progression

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jiangwei Hu ◽  
Xinqin Xiang ◽  
Wei Guan ◽  
Weihua Lou ◽  
Junming He ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cancer Progression ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
Cell Behaviors ◽  
Qrt Pcr ◽  
Related Cell ◽  
Rescue Experiment

Abstract Background So far, few have concerned miR-497-5p in lung squamous cell carcinoma (LUSC). Methods MiR-497-5p expression in LUSC was measured by qRT-PCR. Its impacts on tumor-related cell behaviors were investigated by CCK8 assay, scratch healing assay, flow cytometry and Transwell invasion methods. In addition, interaction between miR-497-5p and CDCA4 in LUSC was also elucidated through rescue experiment, western blot, dual-luciferase, and bioinformatics analysis. Results Low level of miR-497-5p was confirmed in LUSC tissue and cells. Overexpressed miR-497-5p markedly inhibited cancer progression. miR-497-5p restrained CDCA4 expression. Rescue assay showed that overexpressing miR-497-5p eliminated effect of overexpressed CDCA4. Conclusion By targeting CDCA4, miR-497-5p restrained development of LUSC.

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