scholarly journals Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Gu ◽  
Ying Sun ◽  
Xiong Zheng ◽  
Jin Ma ◽  
Xiao-Ying Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Microarray Analysis ◽  
Cancer Progression ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Circular Rnas ◽  
Target Mrnas

Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar’s home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network.

scholarly journals LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

2021 ◽  
Vol 11 (11) ◽  
pp. 1177
Author(s):  
Shao-Hua Yu ◽  
Jia-Hua Cai ◽  
De-Lun Chen ◽  
Szu-Han Liao ◽  
Yi-Zhen Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endometrial Cancer ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gynecologic Cancer ◽  
Functional Enrichment ◽  
Lasso Regression ◽  
Potential Biomarker ◽  
Study Gene Expression

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

scholarly journals Identification of Novel Hub Genes Associated With Gastric Cancer Using Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Xiao-Qing Lu ◽  
Jia-qian Zhang ◽  
Jun Qiao ◽  
Sheng-Xiao Zhang ◽  
Meng-Ting Qiu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
High Recurrence Rate ◽  
Hub Genes ◽  
Tissue Samples ◽  
Qrt Pcr

Abstract Background: Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.Methods: Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytoHubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs. Results: Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.Discussion: We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

scholarly journals Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiao-Qing Lu ◽  
Jia-Qian Zhang ◽  
Sheng-Xiao Zhang ◽  
Jun Qiao ◽  
Meng-Ting Qiu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
High Recurrence Rate ◽  
Hub Genes ◽  
Tissue Samples ◽  
Qrt Pcr

Abstract Background Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy. Methods Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs. Results Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients. Conclusions We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

Evaluation of the feasibility of expression microarray analysis in endoscopically obtained biopsies of gastric carcinoma and their clinical applicability

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 21164-21164
Author(s):  
M. P. Jhawer ◽  
L. Qin ◽  
H. Gerdes ◽  
D. Klimstra ◽  
M. Schattner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Gastric Carcinoma ◽  
Microarray Analysis ◽  
Expression Analysis ◽  
Expression Profiles ◽  
Endoscopic Biopsy ◽  
Expression Microarray ◽  
Lauren's Classification ◽  
Lauren’S Classification

21164 Background: The feasibility of extracting high quality RNA for expression microarray analysis from endoscopic biopsy in gastric carcinoma has not been previously established. Methods: Patients with histologically confirmed locally advanced gastric or gastroesophageal junction adenocarcinoma were screened for enrollment in an NCI-sponsored trial of neoadjuvant irinotecan and cisplatin chemotherapy (NC1–5917). All patients underwent a repeat endoscopic biopsy for the procurement of fresh tumor tissue. Gross microdissection was performed to enrich the sample to at least 80% malignancy. RNA was isolated from the tumor specimens using RNeasy columns (Qiagen) and its quality verified by RNA 6000 NanoAssay and Bioanalyzer 2100 (Agilent). Gene expression profiling was performed on Human Genome U133A GeneChip (Affymetrix) which contained 22,215 oligonucleotide-base probe-sets. Differential gene expression profiles for Lauren's classification were assessed using empirical Bayes t test, a threshold p < 0.001 was considered statistically significant. Results: Of 36 patients with previous biopsy confirmed gastric cancer, repeat endoscopic biopsy identified carcinoma in 28 patients (78%, 95%CI 61–90%). Adequate RNA for microarray analysis was obtained from 21 patients-representing 58% of those who presented for the procedure and 75% in whom endoscopic biopsies confirmed malignancy. This yield improved with increasing number of samples taken. Lauren's classification was available on 26 patients who underwent resection. From the total 54,613 gene probe-sets on the arrays, comparison of the expression profiles of diffuse-type and intestinal-type identified 167 genes that were differentially expressed. Diffuse gastric cancer demonstrated altered expression of genes related to cell-matrix interaction whereas intestinal gastric cancer expression analysis showed enhancement of cell growth. Conclusions: Endoscopic biopsy for expression analysis of gastric cancer is feasible with increasing yield with each core taken. Expression analysis at the time of endoscopic biopsy can differentiate Lauren's histology, a characteristic not routinely evaluable by pathologic review. No significant financial relationships to disclose.

scholarly journals Circular RNA hsa_circ_0000277 sequesters miR-4766-5p to upregulate LAMA1 and promote esophageal carcinoma progression

2021 ◽  
Vol 12 (7) ◽  
Author(s):  
Peng Li Zhou ◽  
Zhengyang Wu ◽  
Wenguang Zhang ◽  
Miao Xu ◽  
Jianzhuang Ren ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Epithelial Mesenchymal Transition ◽  
Expression Profiles ◽  
Luciferase Reporter ◽  
Migration And Invasion ◽  
Circular Rnas ◽  
Mesenchymal Transition ◽  
Dismal Prognosis ◽  
Advanced Tumor

AbstractGrowing evidence has indicated that circular RNAs (circRNAs) play a pivotal role as functional RNAs in diverse cancers. However, most circRNAs involved in esophageal squamous cell carcinoma (ESCC) remain undefined, and the underlying molecular mechanisms mediated by circRNAs are largely unclear. Here, we screened human circRNA expression profiles in ESCC tissues and found significantly increased expression of hsa_circ_0000277 (termed circPDE3B) in ESCC tissues and cell lines compared to the normal controls. Moreover, higher circPDE3B expression in patients with ESCC was correlated with advanced tumor-node-metastasis (TNM) stage and dismal prognosis. Functional experiments demonstrated that circPDE3B promoted the tumorigenesis and metastasis of ESCC cells in vitro and in vivo. Mechanistically, bioinformatics analysis, a dual-luciferase reporter assay, and anti-AGO2 RNA immunoprecipitation showed that circPDE3B could act as a competing endogenous RNA (ceRNA) by harboring miR-4766-5p to eliminate the inhibitory effect on the target gene laminin α1 (LAMA1). In addition, LAMA1 was significantly upregulated in ESCC tissues and was positively associated with the aggressive oncogenic phenotype. More importantly, rescue experiments revealed that the oncogenic role of circPDE3B in ESCC is partly dependent on the miR-4766-5p/LAMA1 axis. Furthermore, bioinformatics analysis combined with validation experiments showed that epithelial-mesenchymal transition (EMT) activation was involved in the oncogenic functions of the circPDE3B–miR-4766-5p/LAMA1 axis in ESCC. Taken together, we demonstrate for the first time that the circPDE3B/miR-4766-5p/LAMA1 axis functions as an oncogenic factor in promoting ESCC cell proliferation, migration, and invasion by inducing EMT, implying its potential prognostic and therapeutic significance in ESCC.

scholarly journals Gene Expression and Transcriptome Profiling of Changes in a Cancer Cell Line Post-Exposure to Cadmium Telluride Quantum Dots: Possible Implications in Oncogenesis

Dose-Response ◽  
2021 ◽  
Vol 19 (2) ◽  
pp. 155932582110198
Author(s):  
Mohammed S. Aldughaim ◽  
Mashael R. Al-Anazi ◽  
Marie Fe F. Bohol ◽  
Dilek Colak ◽  
Hani Alothaid ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantum Dots ◽  
Cancer Cells ◽  
Cadmium Telluride ◽  
Cancer Progression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Dependent Manner ◽  
Cdte Qds ◽  
Cadmium Telluride Quantum Dots

Cadmium telluride quantum dots (CdTe-QDs) are acquiring great interest in terms of their applications in biomedical sciences. Despite earlier sporadic studies on possible oncogenic roles and anticancer properties of CdTe-QDs, there is limited information regarding the oncogenic potential of CdTe-QDs in cancer progression. Here, we investigated the oncogenic effects of CdTe-QDs on the gene expression profiles of Chang cancer cells. Chang cancer cells were treated with 2 different doses of CdTe-QDs (10 and 25 μg/ml) at different time intervals (6, 12, and 24 h). Functional annotations helped identify the gene expression profile in terms of its biological process, canonical pathways, and gene interaction networks activated. It was found that the gene expression profiles varied in a time and dose-dependent manner. Validation of transcriptional changes of several genes through quantitative PCR showed that several genes upregulated by CdTe-QD exposure were somewhat linked with oncogenesis. CdTe-QD-triggered functional pathways that appear to associate with gene expression, cell proliferation, migration, adhesion, cell-cycle progression, signal transduction, and metabolism. Overall, CdTe-QD exposure led to changes in the gene expression profiles of the Chang cancer cells, highlighting that this nanoparticle can further drive oncogenesis and cancer progression, a finding that indicates the merit of immediate in vivo investigation.

scholarly journals Comprehensive analysis of the gene expression profiles in human gastric cancer cell lines

Oncogene ◽  
2002 ◽  
Vol 21 (42) ◽  
pp. 6549-6556 ◽  
Author(s):  
Jiafu Ji ◽  
Xin Chen ◽  
Suet Yi Leung ◽  
Jen-Tsan A Chi ◽  
Kent Man Chu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gastric Cancer Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Comprehensive Analysis ◽  
Human Gastric Cancer ◽  
Gastric Cancer Cell Lines
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