scholarly journals Integrated analysis of cancer stem cells-associated lncRNA-miRNA-mRNA network for ovarian cancer via microarray and Gene Expression Omnibus database

2020 ◽  
Author(s):  
Zheng Li ◽  
Zhijiao Wang ◽  
Yingying Zhou
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Signaling Pathway ◽  
Gene Expression Omnibus ◽  
Integrated Analysis ◽  
Cerna Network ◽  
Geo Database

Abstract Background: Cancer stem cells (CSCs) are associated with the recurrence, metastasis and chemoresistance of epithelial ovarian cancer. Competing endogenous RNAs (CeRNAs) play an important role in maintenance of ovarian cancer stem cell-like cells (OCSCs) characteristics. To construct a ceRNA regulatory network for OCSCs, microarray technology and Gene Expression Omnibus (GEO) database had been used. Human serous epithelial ovarian carcinoma cell line COC1 cells were treated with cisplatin and paclitaxel then maintained in stem cell conditions for 6 days to obtain CD117+/CD133+ cells (OCSCs). We identified the differentially expressed miRNAs (DEMs), lncRNA (DELs) and mRNA (DEGs) between OCSCs and COC1 by microarray and combined them with representative microarray profiles in GEO Database. Results: According to the combination, 28 DEMs were identified at first, and 452 DEGs were obtained combining with the predicted targets of these miRNAs and our mRNA microarray results. Up-regulated DEGs of them were significantly enriched in ‘p53 signaling pathway’, ‘FoxO signaling pathway’ and ‘MicroRNAs in cancer’, whereas down-regulated DEGs were significantly enriched in ‘Adherens junction’ and ‘Hepatitis C’ pathway. 29 transcripts of 17 lncRNAs should be the ceRNAs of 10 of these miRNAs according to bioinformatics predicted results and lncRNA microarray. Finally, we obtained ceRNA network with 10 DEMs, 21 DEGs, and 25 transcripts of 13 DELs which should play an important role in maintenance of OCSCs characteristics. LINC00665-miR-146a-5p-NRP2 should be one of ceRNA pathways of the network. The qPCR results indicated that the expression of miR-146a-5p in OCSCs was lower than that in COC1, and LINC00665 shows the opposite trend. These results were consistent with the results of microarray partially. When LINC00665 expression was up-regulated in COC1, the cell proliferation ability enhanced, apoptosis rate reduced, and the percentage of G2/M phase cells increased. Conclusions: The ceRNA network we constructed may be involved in the stem cell characteristics maintenance of OCSCs and provide directions for further OCSCs research in the future, so as to assist the development and treatment of ovarian cancer.

scholarly journals HER2 decreases drug sensitivity of ovarian cancer cells via inducing stem cell-like property in an NFκB-dependent way

2019 ◽  
Vol 39 (3) ◽  
Author(s):  
Wenxiang Wang ◽  
Yuxia Gao ◽  
Jing Hai ◽  
Jing Yang ◽  
Shufeng Duan
Keyword(s):  
Ovarian Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Cancer Cells ◽  
Drug Sensitivity ◽  
Ovarian Cancer Cells ◽  
Her2 Overexpression ◽  
Her2 Positive ◽  
Ovarian Cancer Stem Cells

Abstract Increasing evidence shows that cancer stem cells are responsible for drug resistance and relapse of tumors. In breast cancer, human epidermal growth factor receptor 2 (HER2) induces Herceptin resistance by inducing cancer stem cells. In the present study, we explored the effect of HER2 on cancer stem cells induction and drug sensitivity of ovarian cancer cell lines. First, we found that HER2 overexpression (HER2 OE) induced, while HER2 knockdown (HER2 KD) decreased CD44+/CD24− population. Consistently, HER2 expression was closely correlated with the sphere formation efficiency (SFE) of ovarian cancer cells. Second, we found that NFκB inhibition by specific inhibitor JSH23 or siRNA targetting subunit p65 dramatically impaired the induction of ovarian cancer stem cells by HER2, indicating that NFκB mediated HER2-induced ovarian cancer stem cells. Third, we found that HER2 KD significantly attenuated the tumorigenicity of ovarian cancer cells. Further, we found that HER2 inhibition increased drastically the sensitivity of ovarian cancer cells to doxorubicin (DOX) or paclitaxel (PTX). Finally, we examined the correlation between HER2 status and stem cell-related genes expression in human ovarian tumor tissues, and found that expressions of OCT4, COX2, and Nanog were higher in HER2 positive tumors than in HER2 negative tumors. Consistently, the 5-year tumor-free survival rate of HER2 positive patients was dramatically lower than HER2 negative patients. Taken together, our data indicate that HER2 decreases drug sensitivity of ovarian cancer cells via inducing stem cell-like property.

scholarly journals mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 257 ◽  
Author(s):  
Yitong Zhang ◽  
Joseph Ta-Chien Tseng ◽  
I-Chia Lien ◽  
Fenglan Li ◽  
Wei Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Lung Adenocarcinoma ◽  
Tumor Necrosis Factor Receptor ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Clinical Stages ◽  
Key Genes ◽  
Geo Database

Cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, lead to therapeutic resistance in lung cancer. In this study, we aimed to investigate the expressions of stem cell-related genes in lung adenocarcinoma (LUAD). The stemness index based on mRNA expression (mRNAsi) was utilized to analyze LUAD cases in the Cancer Genome Atlas (TCGA). First, mRNAsi was analyzed with differential expressions, survival analysis, clinical stages, and gender in LUADs. Then, the weighted gene co-expression network analysis was performed to discover modules of stemness and key genes. The interplay among the key genes was explored at the transcription and protein levels. The enrichment analysis was performed to annotate the function and pathways of the key genes. The expression levels of key genes were validated in a pan-cancer scale. The pathological stage associated gene expression level and survival probability were also validated. The Gene Expression Omnibus (GEO) database was additionally used for validation. The mRNAsi was significantly upregulated in cancer cases. In general, the mRNAsi score increases according to clinical stages and differs in gender significantly. Lower mRNAsi groups had a better overall survival in major LUADs, within five years. The distinguished modules and key genes were selected according to the correlations to the mRNAsi. Thirteen key genes (CCNB1, BUB1, BUB1B, CDC20, PLK1, TTK, CDC45, ESPL1, CCNA2, MCM6, ORC1, MCM2, and CHEK1) were enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Eight of the thirteen genes have been reported to be associated with the CSC characteristics. However, all of them have been previously ignored in LUADs. Their expression increased according to the pathological stages of LUAD, and these genes were clearly upregulated in pan-cancers. In the GEO database, only the tumor necrosis factor receptor associated factor-interacting protein (TRAIP) from the blue module was matched with the stemness microarray data. These key genes were found to have strong correlations as a whole, and could be used as therapeutic targets in the treatment of LUAD, by inhibiting the stemness features.

scholarly journals Cancer Stem Cells and Epithelial Ovarian Cancer

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Sheetal Dyall ◽  
Simon A. Gayther ◽  
Dimitra Dafou
Keyword(s):  
Ovarian Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Cancer Stem Cell ◽  
Epithelial Ovarian Cancer ◽  
Primary Tumour ◽  
Cellular Level ◽  
Small Population ◽  
Novel Target

The cancer stem cell hypothesis is becoming more widely accepted as a model for carcinogenesis. Tumours are heterogeneous both at the molecular and cellular level, containing a small population of cells that possess highly tumourigenic “stem-cell” properties. Cancer stem cells (CSCs), or tumour-initiating cells, have the ability to self-renew, generate xenografts reminiscent of the primary tumour that they were derived from, and are chemoresistant. The characterisation of the CSC population within a tumour that drives its growth could provide novel target therapeutics against these cells specifically, eradicating the cancer completely. There have been several reports describing the isolation of putative cancer stem cell populations in several cancers; however, no defined set of markers has been identified that conclusively characterises “stem-like” cancer cells. This paper highlights the current experimental approaches that have been used in the field and discusses their limitations, with specific emphasis on the identification and characterisation of the CSC population in epithelial ovarian cancer.

scholarly journals Ovarian cancer stem cells express ROR1, which can be targeted for anti–cancer-stem-cell therapy

2014 ◽  
Vol 111 (48) ◽  
pp. 17266-17271 ◽  
Author(s):  
Suping Zhang ◽  
Bing Cui ◽  
Hsien Lai ◽  
Grace Liu ◽  
Emanuela M. Ghia ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Cell Therapy ◽  
Cancer Stem Cell ◽  
Stem Cell Therapy ◽  
Ovarian Cancer Stem Cells ◽  
Anti Cancer

scholarly journals IQGAP1 Is Involved in Enhanced Aggressive Behavior of Epithelial Ovarian Cancer Stem Cell-Like Cells During Differentiation

2015 ◽  
Vol 25 (4) ◽  
pp. 559-565 ◽  
Author(s):  
Lu Huang ◽  
Shanshan Xu ◽  
Dongxiao Hu ◽  
Weiguo Lu ◽  
Xing Xie ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Cancer Stem Cell ◽  
Messenger Rna ◽  
De Novo ◽  
Invasion And Metastasis ◽  
Spheroid Culture ◽  
Interfering Rna

BackgroundWide metastasis is one of characteristics of ovarian cancer. Cancer stem cells, as a source in cancer invasion and metastasis, possess powerful potential of differentiation. Scaffolding IQ domain GTPase-activating protein 1 (IQGAP1) plays a key role in the invasion and metastasis of cancer cells, but IQGAP1’s role in cancer stem cells including ovarian cancer was unclear.MethodsSpheroid culture with serum-free medium was used for enriching ovarian cancer stem cell-like cells (CSC-LCs) from 3AO cell line, and a medium with 10% fetal bovine serum was used to induce the differentiation of CSC-LCs. Immunofluorescence was for detecting the stem markers OCT4 and SOX2. The quantitative real-time-polymerase chain reaction and Western blotting were performed to determine the messenger RNA and protein expression of IQGAP1, respectively. The capacity of cell invasion was evaluated by transwell chamber assay.ResultsOvarian CSC-LCs obtained through spheroid culture showed irregularly elongated appearance, CD24 negative, and OCT4 and SOX2 positive. IQGAP1 expression was decreased in ovarian CSC-LCs compared with parental 3AO cells, but increased de novo during the differentiation of CSC-LCs. Knockdown of IQGAP1 by specific small interfering RNA remarkably weakened invasion capacity of 2-day differentiated ovarian CSC-LCs.ConclusionsIncreased IQGAP1 expression during the differentiation of CSC-LCs is involved in an aggressive cell behavior, which may contribute to metastasis of ovarian cancer.

scholarly journals Integrated analysis of lncRNA–miRNA–mRNA ceRNA network and the potential prognosis indicators in sarcomas

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Lu Gao ◽  
Yu Zhao ◽  
Xuelei Ma ◽  
Ling Zhang
Keyword(s):  
Gene Expression ◽  
Survival Analysis ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Integrated Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Cerna Network

Abstract Background Competitive endogenous RNA (ceRNA) networks have revealed a new mechanism of interaction between RNAs, and play crucial roles in multiple biological processes and development of neoplasms. They might serve as diagnostic and prognosis markers as well as therapeutic targets. Methods In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas by comparing the gene expression profiles between sarcoma and normal muscle samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed using Cytoscape software. In addition, the protein–protein interaction (PPI) network and survival analysis were performed. Results A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA–miRNA–mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients. Conclusions Overall, we constructed a ceRNA network in sarcomas, which might provide insights for further research on the molecular mechanism and potential prognosis biomarkers.

scholarly journals Investigation of the expression of RIF1 gene on head and neck, pancreatic and brain cancer and cancer stem cells

2016 ◽  
Vol 39 (6) ◽  
pp. 43 ◽  
Author(s):  
Hacer E GursesCila ◽  
Muradiye Acar ◽  
Furkan B Barut ◽  
Mehmet Gunduz ◽  
Reidar Grenman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Head And Neck ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines

Purpose: Recent studies have shown that cancer stem cells are resistant to chemotherapy. The aim of this study was to compare RIF1 gene expression in head and neck, pancreatic cancer and glioma cell lines and the cancer stem cells isolated from these cell lines. Methods: UT-SCC-74 from Turku University and UT-SCC-74B primary tumor metastasis and neck cancer cell lines, YKG-1 glioma cancer cell line from RIKEN, pancreatic cancer cell lines and ASPC-1 cells from ATCC were grown in cell culture. To isolate cancer stem cells, ALDH-1 for UT-SCC-74 and UT-SCC-74B cell line, CD-133 for YKG-1 cell line and CD-24 for ASPC-1 cell line, were used as markers of cancer stem cells. RNA isolation was performed for both cancer lines and cancer stem cells. RNAs were converted to cDNA. RIF1 gene expression was performed by qRT-PCR analysis. RIF1 gene expression was compared with cancer cell lines and cancer stem cells isolated from these cell lines. The possible effect of RIF1 gene was evaluated. Results: In the pancreatic cells, RIF1 gene expression in the stem cell-positive cell line was 256 time that seen in the stem cell-negative cell line. Conclusion: Considering the importance of RIF1 in NHEJ and of NHEJ in pancreatic cancer, RIF1 may be one of the genes that plays an important role in the diagnoses and therapeutic treatment of pancreatic cancer. The results of head and neck and brain cancers are inconclusive and further studies are required to elucidate the connection between RIF1 gene and these other types of cancers.

scholarly journals Prognostic Value of Genes Related with Tumor Microenvironment in Ovarian Cancer

2020 ◽  
Author(s):  
Shimei Li ◽  
Jiyi Yao ◽  
Shen Zhang ◽  
Xinchuan Zhou ◽  
Xinbao Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Tumor Microenvironment ◽  
Poor Prognosis ◽  
External Validation ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Gene Expression Signatures ◽  
Poor Outcomes ◽  
Geo Database

Abstract Background Ovarian cancer (OV) is the fifth leading cause of cancer death among females. Growing evidence supports a key role of tumor microenvironment in growth, progress, and metastasis of OV. However, the impacts of gene expression signatures related with OV microenvironment on prognosis have not been well-established . This study aimed to apply ESTIMATE algorithm to extract genes related with tumor microenvironment that predicted poor outcomes in OV patients. Methods The gene expression profile of OV samples were downloaded from The Cancer Genome Atlas (TCGA) database. The immune scores and stromal scores of 469 OV samples were available based on the ESTIMATE algorithm. To better understand impacts of gene expression signatures related with OV microenvironment on prognosis, these samples were categorized based on their ESTIMATE scores into high and low score groups. A different OV cohort from the Gene Expression Omnibus (GEO) database was used for external validation. Results The molecular subtypes in OV patients were correlated with stromal scores, in which the mesenchymal subtype had the highest stromal scores (p < 0.0001). Poor prognosis were found in patients (especially for patients with overall survivals (OS) < 5 years) with higher stromal score (p = 0.0376). 449 differentially expressed genes (DEGs) in stromal scores group were identified and 26 DEGs were significantly associated with poor prognosis in OV patients (p < 0.05). Eventually, 6 genes have further validated to be significantly associated with poor outcomes in 40 patients from a different OV cohort of GEO database (p < 0.05). Conclusion In this study, several genes related with tumor microenvironment that predicted poor prognosis in OV patients were extracted. In addition, some previously overlooked genes could be potential prognostic biomarkers for OV.

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