scholarly journals Human microRNA similarity in breast cancer

2021 ◽  
Author(s):  
Ying Jing ◽  
Donghai Li
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Mirna Sequence ◽  
Disease Heterogeneity ◽  
Similarity Network ◽  
Novel Mirna ◽  
Functional Classes ◽  
Similarity Networks ◽  
Insight Into

MicroRNAs (miRNAs) play important roles in a variety of human diseases, including breast cancer. A number of miRNAs are up- and down-regulated in breast cancer. However, little is known about miRNA similarity and similarity network in breast cancer. Here, a collection of 272 breast cancer-associated miRNA precursors were utilized to calculate similarities of sequences, target genes, pathways and functions and construct a combined similarity network. Well-characterized miRNAs and their similarity network were highlighted. Interestingly, miRNA sequence-dependent similarity networks were not identified in spite of sequence-target gene association. Similarity networks with minimum and maximum number of miRNAs originate from pathway and mature sequence, respectively. The breast cancer-associated miRNAs were divided into 7 functional classes (classes I-VII) followed by disease enrichment analysis and novel miRNA-based disease similarities were found. The finding would provide insight into miRNA similarity, similarity network and disease heterogeneity in breast cancer.

scholarly journals Novel miRNA Targets and Therapies in the Triple-Negative Breast Cancer Microenvironment: An Emerging Hope for a Challenging Disease

2020 ◽  
Vol 21 (23) ◽  
pp. 8905
Author(s):  
Amal Qattan
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Epidermal Growth Factor Receptors ◽  
Mirna Regulation ◽  
Novel Mirna ◽  
Epidermal Growth ◽  
Cell Subpopulations ◽  
Insight Into

Treatment of triple-negative breast cancer (TNBC) remains challenging because of the heterogeneity of the disease and lack of single targetable driving mutations. TNBC does not rely on estrogen, progesterone or epidermal growth factor receptors and is associated with aggressive disease progression and poor prognosis. TNBC is also characterized by resistance to chemotherapeutics, and response to immunotherapies is limited despite promising results in a subset of TNBC patients. MicroRNAs (miRNAs) have emerged as significant drivers of tumorigenesis and tumor progression in triple-negative breast cancer (TNBC) and present unique opportunities to target various components of the TNBC microenvironment for improved efficacy against this difficult to treat cancer. Effects of miRNAs on multiple targets may improve response rates in the context of this genetically and biologically heterogeneous disease. In this review, we offer a comprehensive view of miRNA regulation in TNBC, treatment challenges presented by TNBC in the context of the tumor microenvironment and stem cell subpopulations, and current and emerging miRNA-based therapeutic strategies targeting various components of the TNBC microenvironment. In addition, we offer insight into novel targets that have potential for treating TNBC through multiple mechanisms in the tumor microenvironment simultaneously and those that may be synergistic with standard chemotherapies.

scholarly journals The Effect of Low Temperature Stress on the Leaves and MicroRNA Expression of Potato Seedlings

2021 ◽  
Vol 9 ◽  
Author(s):  
Chongchong Yan ◽  
Nan Zhang ◽  
Qianqian Wang ◽  
Yuying Fu ◽  
Feng Wang ◽  
...  
Keyword(s):  
Abscisic Acid ◽  
Low Temperature ◽  
Temperature Stress ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Potato Production ◽  
Low Temperature Stress ◽  
Pathway Enrichment Analysis ◽  
Novel Mirna ◽  
Potato Seedlings

In recent years, with the wanton destruction of the ecological environment by humans and the frequent occurrence of extreme bad weather, many places that should have been warm and blooming in spring have instead experienced the phenomenon of the “April blizzard,” which has seriously affected China's crops, especially spring potato production in most areas. Potato cultivars, especially potato seedlings, are sensitive to frost, and low temperature frost has become one of the most important abiotic stresses affecting potato production. Potato cold tolerance is regulated by a complex gene network. Although some low temperature resistant microRNAs have been identified, little is known about the role of miRNAs in response to low temperature stress in potato. Therefore, the objective of this study is to clarify the influence of low temperature stress on the miRNA expression of potato by comparing the expression differences of miRNA in potato which was treated with different low temperatures. For the study, 307 known miRNAs belonging to 73 small RNA families and 211 novel miRNAs were obtained. When the temperature decreased, the number of both known and novel miRNA decreased, and the minimum temperature was −2°C. Most of the miRNAs respond to low temperature, drought, and disease stress; some conserved miRNAs were first found to respond to low temperature stress in potato, such as stu-miR530, stu-miR156d, and stu-miR167b. The Gene Ontology, Kyoto Encyclopedia of Genes, and Genomes pathway enrichment analysis of 442 different expression miRNAs target genes indicated that there existed diversified low temperature responsive pathways, but Abscisic Acid was found likely to play a central coordinating role in response to low temperature stress in many metabolism pathways. Quantitative real-time PCR assays indicated that the related targets were negatively regulated by the tested different expression miRNAs during low temperature stress. The results indicated that miRNAs may play an important coordination role in response to low temperature stress in many metabolic pathways by regulating abscisic acid and gibberellin, which provided insight into the roles of miRNAs during low temperature stress and would be helpful for alleviating low temperature stress and promoting low temperature resistant breeding in potatoes.

scholarly journals Screening and Identification of Key Biomarkers in Breast Cancer with Brain Metastasis: Evidence from Bioinformatic Analysis

2020 ◽  
Author(s):  
tao ming Shao ◽  
zhi yang Hu ◽  
wen wei Li ◽  
long yun Pan
Keyword(s):  
Breast Cancer ◽  
Protein Interactions ◽  
Poor Prognosis ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Clinical Prognosis ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Purpose. Breast cancer (BC) has a poor prognosis when brain metastases (BM) occur, and the treatment effect is limited. In this study, we aim to identify representative candidate biomarkers for clinical prognosis of patients with BM and explore the mechanisms underlying the progression of BC.Methods. Herein, we examined the Microarray datasets (GSE125989) obtained from the Gene Expression Omnibus database to find the target genes in BC patients with BM. We employed the GEO2R tool to filter the differentially expressed genes (DEGs) that participate in primary BC and BC with BM. Subsequently, using the DAVID tool, we conducted an enrichment analysis with the screened DEGs based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) functional annotation. The STRING database was employed to analyze the protein-protein interactions of the DEGs and visualized using Cytoscape software. Lastly, the Kaplan-Meier plotter database was employed to determine the prognostic potential of hub genes in BC.Results. We screened out 311 upregulated DEGs and 104 downregulated DEGs. The enrichment analyses revealed that all the DEGs were` enriched in the biological process of extracellular matrix organization, cell adhesion, proteolysis, collagen catabolic process and immune response. The significant enrichment pathways were focal adhesion, protein absorption and digestion, ECM-receptor interaction, PI3K-Akt signalling pathway, and Pathways in cancer. The top ten hub nodes screened out included FN1, VEGFA, COL1A1, MMP2, COL3A1, COL1A2, POSTN, DCN, BGN and LOX. The Kaplan-Meier plotter results showed that the three hub genes (FN1, VEGFA and DCN) are candidate biomarkers for clinical prognosis of patients with BM.Conclusion. we identified seven genes related to poor prognosis in BCBM. FN1, VEGFA and DCN can be considered as potential prognostic markers for BCBM. Meantime, COL1A1, POSTN, BGN and LOX may be linked to the distant transformation of BC.

scholarly journals E3 Ubiquitin Ligase NEDD4L Negatively Regulates Breast Cancer Metastasis By Downregulating SNAI2

2021 ◽  
Author(s):  
Baile Zuo ◽  
Ying Lan ◽  
Xiaoyan Li ◽  
Liping Zhao ◽  
Kexin Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ubiquitin Ligase ◽  
Prognostic Model ◽  
Cancer Metastasis ◽  
Target Genes ◽  
Cox Regression ◽  
E3 Ubiquitin Ligase ◽  
Enrichment Analysis ◽  
Breast Cancer Metastasis ◽  
Independent Predictive Factor

Abstract Background Accumulating evidence demonstrated that the abnormal expression of E3-ubiquitin ligase NEDD4L plays an important role in the biological process of carcinomas. However, its role in breast cancer (BRCA) remains elusive. Methods The expression of NEDD4L was analyzed using BRCA datasets from public database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for enrichment analysis. Both transwell assay and pulmonary metastasis model of BRCA were used to detect metastatic ability of cells. Western blotting, immunohistochemistry and immunofluorescence assay were used to detect the protein expression of target genes. The riskScore and nomogram were used to evaluate the prognosis of patients. Results NEDD4L was significantly downregulated in cancer tissues and positively correlated with the overall survival of patients. Knocking down NEDD4L could enhance the migration and metastasis ability of BRCA cells. SP1 promotes NEDD4L expression, resulting in SNAI2 downregulation in BRCA. A NEDD4L related to the prognostic model developed by LASSO Cox regression could be an independent predictive factor for BRCA. A nomogram combining riskScore and clinical indicators was established to evaluate the prognosis of BRCA quantitatively. Conclusions This study first reveals the role of the SP1/NEDD4L/SNAI2 axis in BRCA and establishes a reliable prognostic model, which provides a novel target and basis for clinical treatment and prognosis evaluation of breast cancer.

scholarly journals Identifying of a Novel miR-98-5p/IGF1 Axis Contributes the Pathogenesis of Breast Cancer Using Comprehensive Bioinformatic Analyses Methods and Experiments Validation

2020 ◽  
Author(s):  
Dapeng Sun ◽  
Xigang Luo ◽  
Lingling Ma ◽  
Yi Wang ◽  
Fengxiang Zhang
Keyword(s):  
Breast Cancer ◽  
Messenger Rna ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Differentially Expressed Mirnas ◽  
Limma Package ◽  
Microarray Datasets ◽  
Geo Database

Abstract Background: Breast cancer (BC) is a huge threat for the health of women worldwide. Although the numerous microRNAs (miRNA) have been identified to be aberrantly expressed in BC, the construction of a comprehensive miRNA-messenger RNA (mRNA) network is still needed. This study was aimed to identify BC-associated miRNAs through analyzing microarray datasets obtained from GEO database and to construct a miRNA-mRNA network for BC. Methods: Limma package was used to identify differentially expressed miRNAs (DEMs) in microarray datasets. Genes targeted by DEMs were analyzed with mirTarBase. Gene Ontology and pathway enrichment analysis for the predicted target genes were performed at DAVID. Correlation of DEMs and target genes was analyzed at ENCORI. Based on these results, a miRNA-mRNA regulatory network was constructed. Results: A total of 17 overlapping DEMs were identified at these two microarray datasets. Expression of DEMs in BC were further validated by ENCORI. By utilizing miRTarBase, a total of 167 target genes for DEMs were obtained. 10 hub genes (AKT1, MYC, VEGFA, CCND1, PTEN, IL6, CASP3, KRAS, IGF1, ESR1) were identified after network analysis at STRING and CytoScape. Through analyzing the effects of hub genes on overall survival of BC patients and correlation of DEMs and hub genes, we found hsa-miR-98-5p/IGF1 axis may play a crucial role in BC progression. The connections of hsa-miR-98-5p and IGF1 were further validated by luciferase activity reporter assay and functional assays. Conclusion: In this work, a miRNA-mRNA network related to BC progression was built, and identified one important miRNA-mRNA axis in BC.

scholarly journals Screening and identification of key biomarkers in breast cancer with brain metastasis: Evidence from bioinformatic analysis

2020 ◽  
Author(s):  
Tao Ming Shao ◽  
Zhi Yang Hu ◽  
Wen Wei Li ◽  
Long Yun Pan
Keyword(s):  
Breast Cancer ◽  
Protein Interactions ◽  
Poor Prognosis ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Clinical Prognosis ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Purpose. Breast cancer (BC) has a poor prognosis when brain metastases (BM) occur, and the treatment effect is limited. In this study, we aim to identify representative candidate biomarkers for clinical prognosis of patients with BM and explore the mechanisms underlying the progression of BC.Methods. Herein, we examined the Microarray datasets (GSE125989) obtained from the Gene Expression Omnibus database to find the target genes in BC patients with BM. We employed the GEO2R tool to filter the differentially expressed genes (DEGs) that participate in primary BC and BC with BM. Subsequently, using the DAVID tool, we conducted an enrichment analysis with the screened DEGs based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) functional annotation. The STRING database was employed to analyze the protein-protein interactions of the DEGs and visualized using Cytoscape software. Lastly, the Kaplan-Meier plotter database was employed to determine the prognostic potential of hub genes in BC.Results. We screened out 311 upregulated DEGs and 104 downregulated DEGs. The enrichment analyses revealed that all the DEGs were` enriched in the biological process of extracellular matrix organization, cell adhesion, proteolysis, collagen catabolic process and immune response. The significant enrichment pathways were focal adhesion, protein absorption and digestion, ECM-receptor interaction, PI3K-Akt signalling pathway, and Pathways in cancer. The top ten hub nodes screened out included FN1, VEGFA, COL1A1, MMP2, COL3A1, COL1A2, POSTN, DCN, BGN and LOX. The Kaplan-Meier plotter results showed that the three hub genes (FN1, VEGFA and DCN) are candidate biomarkers for clinical prognosis of patients with BM.Conclusion. we identified seven genes related to poor prognosis in BCBM. FN1, VEGFA and DCN can be considered as potential prognostic markers for BCBM. Meantime, COL1A1, POSTN, BGN and LOX may be linked to the distant transformation of BC.

scholarly journals Discovery of Novel Leaf Rust Responsive microRNAs in Wheat and Prediction of Their Target Genes

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Dhananjay Kumar ◽  
Dharmendra Singh ◽  
Pulkit Kanodia ◽  
Kumble Vinod Prabhu ◽  
Manish Kumar ◽  
...  
Keyword(s):  
Leaf Rust ◽  
Target Genes ◽  
Sequence Data ◽  
Puccinia Triticina ◽  
Homology Search ◽  
Small Noncoding Rnas ◽  
Cellular Processes ◽  
Novel Mirna ◽  
Transcriptome Sequence Data ◽  
Insight Into

MicroRNAs are endogenous small noncoding RNAs which play critical roles in gene regulation. Few wheat (Triticum aestivumL.) miRNA sequences are available in miRBase repertoire and knowledge of their biological functions related to biotic stress is limited. We identified 52 miRNAs, belonging to 19 families, from next-generation transcriptome sequence data based on homology search. One wheat specific novel miRNA was identified but could not be ascribed or assigned to any known miRNA family. Differentially expressed 22 miRNAs were found between susceptible and resistant wheat near-isogenic lines inoculated with leaf rust pathogenPuccinia triticinaand compared with mock inoculated controls. Most miRNAs were more upregulated in susceptible NIL compared to resistant NIL. We identified 1306 potential target genes for these 52 miRNAs with vital roles in response to stimuli, signaling, and diverse metabolic and cellular processes. Gene ontology analysis showed 66, 20, and 35 target genes to be categorized into biological process, molecular function, and cellular component, respectively. A miRNA-mediated regulatory network revealed relationships among the components of the targetome. The present study provides insight into potential miRNAs with probable roles in leaf rust pathogenesis and their target genes in wheat which establish a foundation for future studies.

scholarly journals Identification of Potential Target Genes in HER-2 Positive Breast Cancer by Bioinformatics Analysis.

2020 ◽  
Author(s):  
Song Wang ◽  
Yi Quan ◽  
Hongying Lyu ◽  
Jian Deng
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Her 2 ◽  
Positive Breast Cancer

Abstract Background: HER-2 positive breast cancer has a high risk of for relapse, metastasis and drug resistance, and is correlated with a poor prognosis. Thus, the study objective was to reveal target genes and key pathways in HER-2 subtype breast cancer. Methods: The gene expression dataset (GSE29431) was downloaded from the Gene Expression Omnibus database(GEO), and the differentially expressed genes (DEGs) were determined using LIMMA package in R software. Subsequently, Functional enrichment analysis were performed in ClusterProfiler package of R platform. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to construct a Protein-Protein Interaction (PPI) network of DEGs. Module analysis and target genes were identified by Cytoscape software. Further more, The influence of target genes on overall survival (OS) was assessed using the Kaplan-Meier plotter database.Results: The differential expression analysis revealed 96 genes were up-regulated while 407 genes were down-regulated in HER-2 positive breast cancer tissue compared to normal breast tissue. Functional enrichment analysis showed that the DEGs were mainly involved in regulation of lipid metabolic process, PPAR signaling pathway and PI3K-Akt signaling pathway. PPI network construction revealed a total of 199 nodes and 560 edges, and 12 target genes were identified by the highest value of degree. In addition, target genes were associated with worse overall prognosis, including NUSAP1, PTTG1, CEP55, TOP2A, CCNB1, CENPF, MELK, AURKA, UBE2C, BUB1B, KIF20A and RRM2.Conclusion: The present study identified 12 target genes associated with the development of HER-2 subtype breast cancer, which may help to provide new biomarkers and therapeutic targets.

scholarly journals Study on the mechanism of Erzhi Pill in the treatment of breast cancer based on network pharmacology

2021 ◽  
Vol 245 ◽  
pp. 03055
Author(s):  
Fahu Yuan ◽  
Xinghua Liao ◽  
Tongcun Zhang
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Suppressor Gene ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Annotation Database ◽  
Amino Terminal ◽  
Target Network

Objective: To explore the possible mechanism of Erzhi Pill in the treatment of breast cancer based on network pharmacology. Methods: Through systematic pharmacology database and analysis platform of Traditional Chinese medicine (TCMSP) and literature review, the candidate active ingredients and corresponding targets of Erzhi Pill were retrieved and collected. The UniProt database and the Human Genome Annotation Database (Genecards) were used to compare the results, and the potential target genes were obtained for the coincidence of Erzhi Pill and breast cancer. Cytoscape was used to construct the “candidate component - action target” network of Erzhi Pill. Generate Style from Statistics tool in String database and Cytoscape software was combined to construct protein interaction network.The Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway enrichment analysis and GO classification enrichment analysis for targets of Erzhi Pill were conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID ) bioinformation resource Database. Results: A total of 21 candidate active components, including Beta-sitosterol, Quercetin, Luteolin, Demethylwedelolactone, Kaempferol and so on, were screened from Erzhi Pill, corresponding to 158 target genes, including vascular endothelial growth factor (VEGF), amino-terminal kinase (C-Jun), proto-oncogene (C-MYC), matrix metalloproteinase-9 (MMP-9), and mainly involved in TNF-α, phosphatidylinositol-3-kinase/protein kinase B(PI3K/Akt), tumor suppressor gene p53, toll-like receptor family and other signaling pathways. Conclusion: This study predicted the possible mechanism of action of Erzhi Pill in the treatment of breast cancer based on the method of network pharmacology, and provided a direction for further research.

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