scholarly journals Characterization of the mechanism by which the RB/E2F pathway controls expression of the cancer genomic DNA deaminase APOBEC3B

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Pieter A Roelofs ◽  
Chai Yeen Goh ◽  
Boon Haow Chua ◽  
Matthew C Jarvis ◽  
Teneale A Stewart ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
T Antigen ◽  
Tumor Evolution ◽  
Reporter Construct ◽  
Cytosine Deamination ◽  
Normal Cells ◽  
Cis Element

APOBEC3B (A3B)-catalyzed DNA cytosine deamination contributes to the overall mutational landscape in breast cancer. Molecular mechanisms responsible for A3B upregulation in cancer are poorly understood. Here we show that a single E2F cis-element mediates repression in normal cells and that expression is activated by its mutational disruption in a reporter construct or the endogenous A3B gene. The same E2F site is required for A3B induction by polyomavirus T antigen indicating a shared molecular mechanism. Proteomic and biochemical experiments demonstrate the binding of wildtype but not mutant E2F promoters by repressive PRC1.6/E2F6 and DREAM/E2F4 complexes. Knockdown and overexpression studies confirm the involvement of these repressive complexes in regulating A3B expression. Altogether, these studies demonstrate that A3B expression is suppressed in normal cells by repressive E2F complexes and that viral or mutational disruption of this regulatory network triggers overexpression in breast cancer and provides fuel for tumor evolution.

scholarly journals The Emerging Role of Extracellular Vesicles in Endocrine Resistant Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1160
Author(s):  
Giusi La Camera ◽  
Luca Gelsomino ◽  
Amanda Caruso ◽  
Salvatore Panza ◽  
Ines Barone ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Endocrine Therapy ◽  
Extracellular Vesicles ◽  
Molecular Mechanisms ◽  
Endocrine Resistance ◽  
Disease Recurrence ◽  
Estrogen Receptor Α ◽  
Research Area ◽  
Tumor Evolution

Breast cancer is the most common solid malignancy diagnosed in females worldwide, and approximately 70% of these tumors express estrogen receptor α (ERα), the main biomarker of endocrine therapy. Unfortunately, despite the use of long-term anti-hormone adjuvant treatment, which has significantly reduced patient mortality, resistance to the endocrine treatments often develops, leading to disease recurrence and limiting clinical benefits. Emerging evidence indicates that extracellular vesicles (EVs), nanosized particles that are released by all cell types and responsible for local and systemic intercellular communications, might represent a newly identified mechanism underlying endocrine resistance. Unraveling the role of EVs, released by transformed cells during the tumor evolution under endocrine therapy, is still an open question in the cancer research area and the molecular mechanisms involved should be better defined to discover alternative therapeutic approaches to overcome resistance. In this review, we will provide an overview of recent findings on the involvement of EVs in sustaining hormonal resistance in breast cancer and discuss opportunities for their potential use as biomarkers to monitor the therapeutic response and disease progression.

scholarly journals Bioinformatics Identification of Prognostic Factors Associated With Breast Cancer

2020 ◽  
Author(s):  
wei ying ◽  
Shipeng Zhang ◽  
Li Xiao ◽  
Jing Zou ◽  
Yingqing Fu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Candidate Genes ◽  
Regulatory Network ◽  
Breast Cancer Cells ◽  
Ppi Network ◽  
Rt Pcr ◽  
Positive Regulation ◽  
Normal Cells ◽  
Kaplan Meier

Abstract Background: Breast cancer (BRCA) remains one of the most common forms of cancer and is the most prominent driver of cancer-related death among women. The mechanistic basis for BRCA, however, remains incompletely understood. In particular, the relationships between driver mutations and signaling pathways in BRCA are poorly characterized, making it difficult to identify reliable clinical biomarkers that can be employed in diagnostic, therapeutic, or prognostic contexts.Methods: First, we downloaded publically available BRCA datasets (GSE45827, GSE42568, and GSE61304) from the Gene Expression Omnibus (GEO) database. We then compared gene expression profiles between tumor and control tissues in these datasets using Venn diagrams and the GEO2R analytical tool. We further explore the functional relevance of BRCA-associated differentially expressed genes (DEGs) via functional and pathway enrichment analyses using the DAVID tool, and we then constructed a protein-protein interaction network incorporating DEGs of interest using the Search Tool for the Retrieval of Interacting Genes (STRING) database. Modules within this PPI network were then identified using Cytoscape, leading to the identification of key candidate genes. The prognostic relevance of these candidate genes was then established through Kaplan-Meier survival analyses and further Gene Expression Profiling Interactive Analysis (GEPIA) validation. Then, key gene-target miRNA regulatory network and transcription factor-key gene regulatory relationships were established using the online miRWalk2.0, TargetScan7.2, miRDB and TRRUST tools. Moreover, four representative key molecules (AURKA, RRM2, BIRC5, and E2F1) were optionally chosen for verification by using quantitative real-time polymerase chain reaction (RT-PCR) and western blot.Results: We identified 85 BRCA-related DEGs across these three datasets. The 31 upregulated DEGs were found to be enriched for pathways and functions including mitotic nuclear division, cell division, G2/M transition of mitotic cell cycle, collagen catabolic process, endodermal cell differentiation, oocyte meiosis, ECM-receptor interactions, and p53 signaling pathway. The 54 downregulated DEGs were, in contrast, enriched in pathways and functions such as lipid metabolic processes, lipid transport, regulation of cardiac muscle contraction by regulation of the release of sequestered calcium ions, positive regulation of cell proliferation, positive regulation of cell-matrix adhesion, tyrosine metabolism, cytochrome P450 drug metabolism, protein digestion and absorption, and PPAR signaling. We were further able to select 16 upregulated candidate genes of interest from our PPI network, and in subsequent Kaplan-Meier analyses we were able to determine that elevated expression of 14 of these genes was associated with a poorer BRCA patient prognosis. We then employed GEPIA to validate these 14 gene candidates, confirming them to all be expressed at elevated levels in BRCA relative to normal tissue controls. In addition, a regulatory network consisting of 9 genes, 10 miRNAs and 3 TFs was constructed, enabling the identification of potential biomarkers of BRCA, including AURKA, RRM2, BIRC5, and E2F1. RT-PCR results suggested that significantly elevated AURKA, RRM2 and BIRC5 mRNAs expressed in the breast cancer cells than in the normal cells. Western blot results shown that E2F1 protein was highly expressed in breast cancer cells compared to normal cells. In conclusion, these candidate molecules may offer insight regarding the underlying pathogenesis of BRCA and highlight a number of potential therapeutic avenues for the treatment of breast cancer patients.

scholarly journals Comprehensive Analysis of lncRNA and miRNA Regulatory Network Reveals Potential Prognostic Non-coding RNA Involved in Breast Cancer Progression

2021 ◽  
Vol 12 ◽  
Author(s):  
Sheng Gao ◽  
Xun Lu ◽  
Jingjing Ma ◽  
Qian Zhou ◽  
RanRan Tang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Cancer Progression ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Malignant Tumors ◽  
Early Stage ◽  
Breast Cancer Progression ◽  
Poor Overall Survival ◽  
Non Coding Rna

Breast cancer is one of the most common malignant tumors in women and is the second leading cause of cancer deaths among women. The tumorigenesis and progression of breast cancer are not well understood. The existing researches have indicated that non-coding RNAs, which mainly include long non-coding RNA (lncRNA) and microRNA (miRNA), have gradually become important regulators of breast cancer. We aimed to screen the differential expression of miRNA and lncRNA in the different breast cancer stages and identify the key non-coding RNA using TCGA data. Based on series test of cluster (STC) analysis, bioinformatics analysis, and negatively correlated relationships, 122 lncRNAs, 67 miRNAs, and 119 mRNAs were selected to construct the regulatory network of lncRNA and miRNA. It was shown that the miR-93/20b/106a/106b family was at the center of the regulatory network. Furthermore, 6 miRNAs, 10 lncRNAs, and 15 mRNAs were significantly associated with the overall survival (OS, log-rank P < 0.05) of patients with breast cancer. Overexpressed miR-93 in MCF-7 breast cancer cells was associated with suppressed expression of multiple lncRNAs, and these downregulated lncRNAs (MESTIT1, LOC100128164, and DNMBP-AS1) were significantly associated with poor overall survival in breast cancer patients. Therefore, the miR-93/20b/106a/106b family at the core of the regulatory network discovered by our analysis above may be extremely important for the regulation of lncRNA expression and the progression of breast cancer. The identified key miRNA and lncRNA will enhance the understanding of molecular mechanisms of breast cancer progression. Targeting these key non-coding RNA may provide new therapeutic strategies for breast cancer treatment and may prevent the progression of breast cancer from an early stage to an advanced stage.

scholarly journals Constructing MRNA, miRNA, circRNA and lncRNA Regulatory Network by Analysis of Microarray Data in Breast Cancer

2021 ◽  
Author(s):  
Bita Hassani ◽  
Hasan Mollanoori ◽  
Farkhondeh Pouresmaeili ◽  
Yazdan Asgari ◽  
Soudeh Ghafouri-Fard
Keyword(s):  
Breast Cancer ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Interaction Network ◽  
Good Prognosis ◽  
Therapeutic Options ◽  
Circular Rnas ◽  
Breast Tumorigenesis

Abstract Background. Luminal tumors are the utmost frequent subtype of breast cancer (BC). Despite luminal BC has relatively good prognosis, in a subset of patients, disease relapse occurs to endocrine therapy ;hence, there is a critical need to identify new strategies to promote the early detection and more effective therapies. Noncoding RNAs including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) can interact with and modulate each other via diverse molecular mechanisms and make a complicated regulatory network. ncRNAs participate in diverse biological processes and disorders such as breast tumors. Therefore, understanding their regulatory mechanisms allow to develop new field of research and therapeutic options for BC patients. Methods. In this study, BC-specific RNA expression profiles including mRNAs, miRNAs, lncRNAs, and circRNAs were retrieved from Gene Expression Omnibus (GEO) microarray datasets, and differentially expressed (DE) items were obtained. Disease ontology, functional and pathway enrichment analyses were executed. The protein-protein interaction network was constructed, and hub mRNAs were extracted. The prognostic value of hub mRNAs in patients of BC were performed using GEPIA. Subsequently, a ceRNA network was established by Cytoscape.Results. In total, 691 DE genes, 122 DE lncRNAs, 60 DE miRNAs, and 38 DE circRNAs in breast tumor samples were compared with normal samples. Subsequently, 12 hub-genes including FOXO3, RHOA, EZH2, KIT, HSP90B1, NCOA3, RAC1, IGF1, CAV1, CXCR4, CCNB1, and ITGB1 were screened from the network. Kaplan-Meier Plotter results revealed that FOXO3 and RHOA were a suitable prognostic marker for patients with breast cancer. Finally, we determined possible ncRNAs (circ0007535, circ0002727, circ0005240, circ0014130, circ0044927, circ0007001, circ0089153, NORAD, MALAT1, TUG1, ZFAS1, OPI5-AS1, miR183, miR182, miR101, miR200c, miR200b, miR149, miR342, and miR1207) which could crosstalk with each other to regulate FOXO3 and RHOA through different regulatory patterns. Conclusion. These data might improve our perception of the breast tumorigenesis and could develop new field of research and therapeutic options for BC patients.

scholarly journals IPSC-derived neuronal cultures expressing the Alzheimer’s disease associated rare TREM2 R47H variant enables the construction of an Aβ-induced gene regulatory network

2019 ◽  
Author(s):  
Soraia Martins ◽  
Andreas Müller-Schiffmann ◽  
Martina Bohndorf ◽  
Wasco Wruck ◽  
Kristel Sleegers ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Immune Response ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Late Onset ◽  
Neuronal Cultures ◽  
Gene Regulatory

AbstractRecently, genes associated with immune response and inflammation have been identified as genetic risk factors for late-onset Alzheimer’s disease (LOAD). One of them is the rare p.Arg47His (R47H) variant within triggering receptor expressed on myeloid cells 2 (TREM2), which has been shown to increase the risk for developing AD 2-3-fold. Here, we report the generation and characterization of a model of LOAD using lymphoblast-derived iPSCs from patients harbouring the R47H mutation in TREM2 (AD TREM2 iPSCs), as well as from control individuals without dementia (CON iPSCs). iPSCs efficiently differentiate into mature neuronal cultures and comparative global transcriptome analysis identified a distinct gene expression profile in AD TREM2 neuronal cultures. Furthermore, manipulation of the iPSC-derived functional neuronal cultures with an Aβ-S8C dimer highlighted metabolic pathways, phagosome and immune response as the most perturbed pathways in AD TREM2 neuronal cultures. Through the construction of an Aβ-induced gene regulatory network, we were able to identify an Aβ signature linked to protein processing in the endoplasmic reticulum (ER) which emphasised ER-stress, as a potential causal role in LOAD. Overall, this study has shown that our AD-iPSC based model can be used for in-depth studies to better understand the molecular mechanisms underlying the etiology of LOAD and provides new opportunities for screening of potential therapeutic targets.

scholarly journals Identification of Breast Cancer-Associated Lipids in Scalp Hair

2012 ◽  
Vol 6 ◽  
pp. BCBCR.S9607 ◽  
Author(s):  
Dharmica A.H. Mistry ◽  
Joseph Haklani ◽  
Peter W. French
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Biological Samples ◽  
Molecular Mechanisms ◽  
Scalp Hair ◽  
Breast Cancer Patients ◽  
X Ray Diffraction ◽  
Xrd Pattern ◽  
X Ray

A correlation between the presence of breast cancer and a change in the synchrotron-generated X-ray diffraction (XRD) pattern of hair has been reported in several publications by different groups, and on average XRD-based assays detect around 75% of breast cancer patients in blinded studies. To date, the molecular mechanisms leading to this alteration are largely unknown. We have determined that the alteration is likely to be due to the presence of one or more breast cancer-associated phospholipids. Further characterization of these lipids could be used to develop a novel, sensitive and specific screening test for breast cancer, based on hair initially, and potentially extendable to other biological samples.

The Selective Characterization of Nonthermal Atmospheric Pressure Plasma Jet on Treatment of Human Breast Cancer and Normal Cells

2014 ◽  
Vol 42 (2) ◽  
pp. 315-322 ◽  
Author(s):  
Shahriar Mirpour ◽  
Hamidreza Ghomi ◽  
Somayeh Piroozmand ◽  
Maryam Nikkhah ◽  
Seyed Hassan Tavassoli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Atmospheric Pressure ◽  
Human Breast Cancer ◽  
Atmospheric Pressure Plasma ◽  
Plasma Jet ◽  
Atmospheric Pressure Plasma Jet ◽  
Human Breast ◽  
Normal Cells ◽  
Pressure Plasma

scholarly journals Bioinformatics Identification of Prognostic Factors Associated with Breast Cancer

2020 ◽  
Author(s):  
Ying Wei ◽  
Shipeng Zhang ◽  
Li Xiao ◽  
Jing Zou ◽  
Yingqing Fu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Candidate Genes ◽  
Regulatory Network ◽  
Breast Cancer Cells ◽  
Ppi Network ◽  
Rt Pcr ◽  
Positive Regulation ◽  
Normal Cells ◽  
Kaplan Meier

Abstract Background: Breast cancer (BRCA) remains one of the most common forms of cancer and is the most prominent driver of cancer-related death among women. The mechanistic basis for BRCA, however, remains incompletely understood. In particular, the relationships between driver mutations and signaling pathways in BRCA are poorly characterized, making it difficult to identify reliable clinical biomarkers that can be employed in diagnostic, therapeutic, or prognostic contexts.Methods: First, we downloaded publically available BRCA datasets (GSE45827, GSE42568, and GSE61304) from the Gene Expression Omnibus (GEO) database. We then compared gene expression profiles between tumor and control tissues in these datasets using Venn diagrams and the GEO2R analytical tool. We further explore the functional relevance of BRCA-associated differentially expressed genes (DEGs) via functional and pathway enrichment analyses using the DAVID tool, and we then constructed a protein-protein interaction network incorporating DEGs of interest using the Search Tool for the Retrieval of Interacting Genes (STRING) database. Modules within this PPI network were then identified using Cytoscape, leading to the identification of key candidate genes. The prognostic relevance of these candidate genes was then established through Kaplan-Meier survival analyses and further Gene Expression Profiling Interactive Analysis (GEPIA) validation. Then, key gene-target miRNA regulatory network and transcription factor-key gene regulatory relationships were established using the online miRWalk2.0, TargetScan7.2, miRDB and TRRUST tools. Moreover, four representative key molecules (AURKA, RRM2, BIRC5, and E2F1) were optionally chosen for verification by using quantitative real-time polymerase chain reaction (RT-PCR) and western blot.Results: We identified 85 BRCA-related DEGs across these three datasets. The 31 upregulated DEGs were found to be enriched for pathways and functions including mitotic nuclear division, cell division, G2/M transition of mitotic cell cycle, collagen catabolic process, endodermal cell differentiation, oocyte meiosis, ECM-receptor interactions, and p53 signaling pathway. The 54 downregulated DEGs were, in contrast, enriched in pathways and functions such as lipid metabolic processes, lipid transport, regulation of cardiac muscle contraction by regulation of the release of sequestered calcium ions, positive regulation of cell proliferation, positive regulation of cell-matrix adhesion, tyrosine metabolism, cytochrome P450 drug metabolism, protein digestion and absorption, and PPAR signaling. We were further able to select 16 upregulated candidate genes of interest from our PPI network, and in subsequent Kaplan-Meier analyses we were able to determine that elevated expression of 14 of these genes was associated with a poorer BRCA patient prognosis. We then employed GEPIA to validate these 14 gene candidates, confirming them to all be expressed at elevated levels in BRCA relative to normal tissue controls. In addition, a regulatory network consisting of 9 genes, 10 miRNAs and 3 TFs was constructed, enabling the identification of potential biomarkers of BRCA, including AURKA, RRM2, BIRC5, and E2F1. RT-PCR results suggested that significantly elevated AURKA, RRM2 and BIRC5 mRNAs expressed in the breast cancer cells than in the normal cells. Western blot results shown that E2F1 protein was highly expressed in breast cancer cells compared to normal cells. In conclusion, these candidate molecules may offer insight regarding the underlying pathogenesis of BRCA and highlight a number of potential therapeutic avenues for the treatment of breast cancer patients.

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