scholarly journals Screening the key genes of hepatocellular adenoma via microarray analysis of DNA expression and methylation profiles

2017 ◽  
Vol 14 (4) ◽  
pp. 3975-3980 ◽  
Author(s):  
Dan Liu ◽  
Pengfei Liu ◽  
Liye Cao ◽  
Quan Zhang ◽  
Yaqing Chen
Keyword(s):  
Microarray Analysis ◽  
Hepatocellular Adenoma ◽  
Key Genes

MicroRNA Microarray Analysis to Investigate the Key Genes and microRNAs Regulated by Amomum cardamomum in Nephropathy Rat Model

2018 ◽  
Vol 14 (3) ◽  
pp. 310-319
Author(s):  
M.M. Hongmei Chen ◽  
M.D. Xiulan Wang ◽  
M.M. Enhesuren ◽  
B.M. Chang Chun ◽  
B.M. Wenjie Jin ◽  
...  
Keyword(s):  
Microarray Analysis ◽  
Rat Model ◽  
Key Genes ◽  
Microrna Microarray

Uncovering potential key genes associated with the pathogenesis of asthma: A microarray analysis of asthma-relevant tissues

2017 ◽  
Vol 45 (2) ◽  
pp. 152-159 ◽  
Author(s):  
Y. Guan ◽  
X. Jin ◽  
X. Liu ◽  
Y. Huang ◽  
M. Wang ◽  
...  
Keyword(s):  
Microarray Analysis ◽  
Key Genes

scholarly journals Identification of Differentially Expressed Genes in Cervical Cancer Patients by Comparative Transcriptome Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Annapurna S. D. ◽  
Deepthi Pasumarthi ◽  
Akbar Pasha ◽  
Ravinder Doneti ◽  
Sheela B. ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cancer Patients ◽  
Microarray Analysis ◽  
Mrna Level ◽  
Principal Component ◽  
Cancer Prognosis ◽  
Youden Index ◽  
Clinical Samples ◽  
Therapeutic Drug ◽  
Key Genes

Cervical cancer is one of the most malignant reproductive diseases seen in women worldwide. The identification of dysregulated genes in clinical samples of cervical cancer may pave the way for development of better prognostic markers and therapeutic targets. To identify the dysregulated genes (DEGs), we have retrospectively collected 10 biopsies, seven from cervical cancer patients and three from normal subjects who underwent a hysterectomy. Total RNA isolated from biopsies was subjected to microarray analysis using the human Clariom D Affymetrix platform. Based on the results of principal component analysis (PCA), only eight samples are qualified for further studies; GO and KEGG were used to identify the key genes and were compared with TCGA and GEO datasets. Identified genes were further validated by quantitative real-time PCR and receiver operating characteristic (ROC) curves, and the highest Youden index was calculated in order to evaluate cutoff points (COPs) that allowed distinguishing of tissue samples of cervical squamous carcinoma patients from those of healthy individuals. By comparative microarray analysis, a total of 108 genes common across the six patients’ samples were chosen; among these, 78 genes were upregulated and 26 genes were downregulated. The key genes identified were SPP1, LYN, ARRB2, COL6A3, FOXM1, CCL21, TTK, and MELK. Based on their relative expression, the genes were ordered as follows: TTK > ARRB2 > SPP1 > FOXM1 > LYN > MELK > CCL21 > COL6A3; this generated data is in sync with the TCGA datasets, except for ARRB2. Protein-protein interaction network analysis revealed that TTK and MELK are closely associated with SMC4, AURKA, PLK4, and KIF18A. The candidate genes SPP1, FOXM1, LYN, COL6A3, CCL21, TTK and MELK at mRNA level, emerge as promising candidate markers for cervical cancer prognosis and also emerge as potential therapeutic drug targets.

Identification of Key Genes Potentially Related to Intervertebral Disk Degeneration by Microarray Analysis

2019 ◽  
Vol 23 (9) ◽  
pp. 610-617 ◽  
Author(s):  
Yi Wang ◽  
Guogang Dai ◽  
Lanjie Wang ◽  
Fangru Shang ◽  
Ling Jiang ◽  
...  
Keyword(s):  
Microarray Analysis ◽  
Intervertebral Disk ◽  
Intervertebral Disk Degeneration ◽  
Disk Degeneration ◽  
Key Genes
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