The Significance of MicroRNAs Expression in Regulation of Extracellular Matrix and Other Drug Resistant Genes in Drug Resistant Ovarian Cancer Cell Lines

Kaźmierczak, Dominika; Jopek, Karol; Sterzyńska, Karolina; Ginter-Matuszewska, Barbara; Nowicki, Michał; Ruciński, Marcin; Januchowski, Radosław

doi:10.3390/ijms21072619

Cited by 23 publications

(30 citation statements)

References 119 publications

(156 reference statements)

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“…As an initial effort to understand the potential involvement of hsa-miR-105 in paclitaxel resistance, we examined the expression of hsa-miR-105 in a microRNA profiling microarray expression dataset consisting of three pairs of parental EOC cells and their PTX-resistant sublines (GSE148251) ( 20 ). Student's t-test demonstrated that the expression of hsa-miR-105 was significantly downregulated in PTX-resistant sublines compared to their parental cell lines (percentage decrease >78.8%, P<0.0001, Fig.…”

Section: Resultsmentioning

confidence: 99%

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Role of hsa‑miR‑105 during the pathogenesis of paclitaxel resistance and its clinical implication in ovarian cancer

Mao

Zhang

et al. 2021

Oncol Rep

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More than 70% of patients with epithelial ovarian cancer (EOC), one of the leading cause of gynecological cancer-related deaths worldwide, are diagnosed at an advanced stage of the disease. Currently, the mainstay for treatment of advanced EOC is tumor debulking surgery followed by combined platinum-and paclitaxel (PTX)-based chemotherapy. However, most patients eventually develop chemoresistance, which remains a major obstacle to successful treatment. Herein, by using clinical specimens and experimentally induced cell models, we found that the expression levels of hsa-miR-105 were significantly decreased in PTX-resistant EOC tissues and cell lines. Follow-up functional experiments demonstrated that repression of hsa-miR-105 conferred resistance to paclitaxel in EOC cells, whereas restoration of hsa-miR-105 expression in situ via intratumoral injection of hsa-miR-105 micrON™ agomir potentiated in vivo sensitivity to PTX and thereafter significantly inhibited tumor growth in a PTX-challenged xenograft model. Mechanistically, hsa-miR-105 exerted its tumor suppressor function by directly inhibiting the zinc and ring finger 2 (ZNRF2) signaling pathway. Importantly, aberrant expression of hsa-miR-105 in both tumor and circulating samples predicted a poor post-chemotherapy prognosis in EOC patients. These findings collectively suggest that hsa-miR-105 may act as a potent tumor suppressor miRNA during the progression of EOC, likely affecting cell proliferation, invasiveness and chemosensitivity to PTX, and functioning at least in part via inhibition of ZNRF2 signaling. The stability and availability and ease in measurement of circulating hsa-miR-105 make it a valuable diagnostic/prognostic biomarker candidate for chemotherapy of EOC.

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Section: Resultsmentioning

confidence: 99%

“…A microRNA profiling microarray expression dataset consisting of three pairs of parental EOC cells and their PTX-resistant sublines (GSE148251) ( 20 ) was downloaded from Gene Expression Omnibus (GEO platform). The miRNA expression levels were analyzed using GEO2R bioconductor project and provided as log2 ratios ( 21 ).…”

Section: Methodsmentioning

confidence: 99%

Role of hsa‑miR‑105 during the pathogenesis of paclitaxel resistance and its clinical implication in ovarian cancer

Mao

Zhang

et al. 2021

Oncol Rep

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“…Maintaining the structural integrity of the arteries, uterus, and intestine is the main function of COL3A1. COL3A1 is negatively regulated by miR-29a, and a regulatory relationship is thought to be associated with the resistance of ovarian cancer cell lines to topotekan [34]. As a new translocation partner gene of PLAG1, COL3A1 could be used to distinguish lipomas by affecting PLAG1 rearrangement and overexpression [11].…”

Section: Discussionmentioning

confidence: 99%

Construction of Prognostic Prediction Model for Stomach Adenocarcinoma Based on the TCGA Database.

Gu¹,

Chen²,

Wang³

2020

Preprint

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Background: Prognostic prediction models have been developed to detect new biomarkers of gastric cancer (GC). The identification of new biomarkers could provide theoretical foundations for the application of molecular targeted therapy in advanced GC. The aim of this study was to construct a prognostic prediction model for stomach adenocarcinoma (STAD) based on The Cancer Genome Atlas (TCGA) database. Methods: First, we used the "limma" package to screen differentially expressed genes (DEGs) based on TCGA database. Gene ontology (GO) analysis was performed using the "ClusterProfiler" package. The interactions between proteins and the relationships between differentially expressed genes and clinical features were analyzed by protein-protein interaction (PPI) network analysis and weighted gene coexpression network analysis (WGCNA), respectively. Then, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to identify differentially enriched pathways. The GenVisR package and CIBERSORT were used to identify mutations and assess immune infiltration. Finally, the expression of COL3A1 in STAD tissues was verified by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blotting.Results: Six differentially expressed genes were screened out, namely, COL3A1, ADAMTS12, BGN, FNDC1, AEBP1 and HTRA3. The enrichment results showed that differentially expressed genes were involved in multiple pathways in STAD, such as those related to the extracellular matrix, extracellular structure organization, and extracellular matrix organization. The differentially expressed genes were related to immune infiltration via the mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathways. The western blotting and RT-qPCR results suggested that COL3A1 was overexpressed in STAD tissues compared with normal tissues.Conclusion: COL3A1, ADAMTS12, BGN, FNDC1, AEBP1 and HTRA3 could play important roles in the tumorigenesis and progression of STAD via various pathways, including those involving the extracellular matrix, extracellular structure organization, and extracellular matrix organization. COL3A1, ADAMTS12, BGN, FNDC1, AEBP1, and HTRA3 act as oncogenes in most cancers and may be biomarkers. Additionally, the identification of COL3A1 as a candidate biomarker provides a direction for further research on the role of tumor immunity in gastric cancer.

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“…We screened the gene chip data by using the Gene expression omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo ) database [ 14 ]. Cisplatin resistant ovarian cancer public gene expression data sets (GSE58470 and GSE45553) and miRNA expression data sets (GSE58469 and GSE148251) were selected and downloaded from GEO, with the keywords “ovarian cancer” and “cisplatin resistant” [ 15 – 17 ]. The GSE58470 and GSE45553 datasets, which are two mRNA datasets, contain 2 ovarian cancer cell lines (IGROV-1, OVCAR-8) and 14 samples, including 7 cisplatin resistant cell samples and 7 parental cell samples.…”

Section: Methodsmentioning

confidence: 99%

Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer

Bai

Jin

et al. 2021

BMC Cancer

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Background Ovarian cancer (OC) is a gynecological malignancy with the highest mortality rate. Cisplatin (DDP) based chemotherapy is a standard strategy for ovarian cancer. Despite good response rates for initial chemotherapy, almost 80% of the patients treated with DDP based chemotherapy will experience recurrence due to drug-resistant, which will ultimately result in fatality. The aim of the present study was to examine the pathogenesis and potential molecular markers of cisplatin-resistant OC by studying the differential expression of mRNAs and miRNAs between cisplatin resistant OC cell lines and normal cell lines. Methods Two mRNA datasets (GSE58470 and GSE45553) and two miRNA sequence datasets (GSE58469 and GSE148251) were downloaded from the Gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were screened by the NetworkAnalyst. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. The protein-protein interaction network was constructed using STRING and Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities. FunRich and MiRNATip databases were used to identify the target genes of the DEMs. Results A total of 380 DEGs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs containing 379 nodes and 1049 edges was constructed, and 4 key modules and 24 hub genes related to cisplatin-resistant OC were screened. Two hundred ninety-nine target genes of the 5 DEMs were found out. Subsequently, one of these 299 target genes (UBB) belonging to the hub genes of GSE58470 and GSE45553 was identified by MCODE and CytoHubba,which was regulated by one miRNA (mir-454). Conclusions One miRNA–mRNA regulatory pairs (mir-454-UBB) was established. Taken together, our study provided evidence concerning the alteration genes involved in cisplatin-resistant OC, which will help to unravel the mechanisms underlying drug resistant.

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The Significance of MicroRNAs Expression in Regulation of Extracellular Matrix and Other Drug Resistant Genes in Drug Resistant Ovarian Cancer Cell Lines

Cited by 23 publications

References 119 publications

Role of hsa‑miR‑105 during the pathogenesis of paclitaxel resistance and its clinical implication in ovarian cancer

Role of hsa‑miR‑105 during the pathogenesis of paclitaxel resistance and its clinical implication in ovarian cancer

Construction of Prognostic Prediction Model for Stomach Adenocarcinoma Based on the TCGA Database.

Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer

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