Regulation of the Effect of Physical Activity Through MicroRNAs in Breast Cancer

2021 ◽  
Author(s):  
Bok Sil Hong
Keyword(s):  
Breast Cancer ◽  
Physical Activity ◽  
Cancer Progression ◽  
Target Genes ◽  
Expression Profiles ◽  
Breast Cancer Progression ◽  
The Cancer Genome Atlas ◽  
Circulating Micrornas ◽  
Tumor Stages ◽  
Cancer Genome Atlas

AbstractPhysical activity and exercise can induce beneficial molecular and biological regulations that have been associated with an incidence of various diseases, including breast cancer. Recent studies demonstrated that the potential links between physical activity-induced circulating microRNAs (miRNAs) and cancer risk and progression. Here, we investigated whether altered miRNAs by exercise could influence breast cancer progression. After primary searching in PubMed and reviewing the full-text papers, candidate miRNAs altered by exercise in breast cancer were identified. Analysis of expression profiles and clinical outcomes of altered miRNAs using The Cancer Genome Atlas datasets showed altered miRNAs expressions were significantly associated with the patient's prognosis, whereas prognostic values of each miRNA varied in different stages and subtypes. In addition, altered miRNAs profiles regulated various target genes and key signaling pathways in tumorigenesis, including pathways in cancer and the PI3K-Akt signaling pathway; however, miRNAs regulated the expression of target genes differently according to tumor stages and subtypes. These results indicate that circulating miRNAs are promising noninvasive stable biomarkers for early detection, diagnosis, prognosis, and monitoring the response to clinical therapies of breast cancer. Moreover, stages and subtype-stratified approaches for breast cancer progression would be needed to evaluate the prognostic value of miRNAs for biomarkers and therapeutic targets.

scholarly journals Iron-Bound Lipocalin-2 from Tumor-Associated Macrophages Drives Breast Cancer Progression Independent of Ferroportin

Metabolites ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 180
Author(s):  
Christina Mertens ◽  
Matthias Schnetz ◽  
Claudia Rehwald ◽  
Stephan Grein ◽  
Eiman Elwakeel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Progression ◽  
Tumor Cells ◽  
Cancer Progression ◽  
Lung Metastases ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Lipocalin 2 ◽  
Tumor Associated Macrophages

Macrophages supply iron to the breast tumor microenvironment by enforced secretion of lipocalin-2 (Lcn-2)-bound iron as well as the increased expression of the iron exporter ferroportin (FPN). We aimed at identifying the contribution of each pathway in supplying iron for the growing tumor, thereby fostering tumor progression. Analyzing the expression profiles of Lcn-2 and FPN using the spontaneous polyoma-middle-T oncogene (PyMT) breast cancer model as well as mining publicly available TCGA (The Cancer Genome Atlas) and GEO Series(GSE) datasets from the Gene Expression Omnibus database (GEO), we found no association between tumor parameters and Lcn-2 or FPN. However, stromal/macrophage-expression of Lcn-2 correlated with tumor onset, lung metastases, and recurrence, whereas FPN did not. While the total iron amount in wildtype and Lcn-2−/− PyMT tumors showed no difference, we observed that tumor-associated macrophages from Lcn-2−/− compared to wildtype tumors stored more iron. In contrast, Lcn-2−/− tumor cells accumulated less iron than their wildtype counterparts, translating into a low migratory and proliferative capacity of Lcn-2−/− tumor cells in a 3D tumor spheroid model in vitro. Our data suggest a pivotal role of Lcn-2 in tumor iron-management, affecting tumor growth. This study underscores the role of iron for tumor progression and the need for a better understanding of iron-targeted therapy approaches.

scholarly journals An R Implementation of Tumor-Stroma-Immune Transcriptome Deconvolution Pipeline using DeMixT

2019 ◽  
Author(s):  
Shaolong Cao ◽  
Zeya Wang ◽  
Fan Gao ◽  
Jingxiao Chen ◽  
Feng Zhang ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Expression Profiles ◽  
Progression Free Survival ◽  
Tumor Stroma ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Biological Information ◽  
Computationally Efficient ◽  
Multiple Cancer ◽  
Cancer Genome Atlas

AbstractThe deconvolution of transcriptomic data from heterogeneous tissues in cancer studies remains challenging. Available software faces difficulties for accurately estimating both component-specific proportions and expression profiles for individual samples. To address these challenges, we present a new R-implementation pipeline for the more accurate and efficient transcriptome deconvolution of high dimensional data from mixtures of more than two components. The pipeline utilizes the computationally efficient DeMixT R-package with OpenMP and additional cancer-specific biological information to perform three-component deconvolution without requiring data from the immune profiles. It enables a wide application of DeMixT to gene expression datasets available from cancer consortium such as the Cancer Genome Atlas (TCGA) projects, where, other than the mixed tumor samples, a handful of normal samples are profiled in multiple cancer types. We have applied this pipeline to two TCGA datasets in colorectal adenocarcinoma (COAD) and prostate adenocarcinoma (PRAD). In COAD, we found varying distributions of immune proportions across the Consensus Molecular Subtypes, from the highest to the lowest being CMS1, CMS3, CMS4 and CMS2. In PRAD, we found the immune proportions are associated with progression-free survival (p<0.01) and negatively correlated with Gleason scores (p<0.001). Our DeMixT-centered analysis protocol opens up new opportunities to investigate the tumor-stroma-immune microenvironment, by providing both proportions and component-specific expressions, and thus better define the underlying biology of cancer progression.Availability and implementation: An R package, scripts and data are available: https://github.com/wwylab/DeMixTallmaterials.

scholarly journals Cis-Compound Mutations are Prevalent in Triple Negative Breast Cancer and Can Drive Tumor Progression

2016 ◽  
Author(s):  
Nao Hiranuma ◽  
Jie Liu ◽  
Chaozhong Song ◽  
Jacob Goldsmith ◽  
Michael Dorschner ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Triple Negative ◽  
The Cancer Genome Atlas ◽  
Breast Cancers ◽  
Single Nucleotide Variants ◽  
Primary Tumors ◽  
Cancer Subtypes ◽  
Multiple Biopsies ◽  
Cancer Genome Atlas

About 16% of breast cancers fall into a clinically aggressive category designated triple negative (TNBC) due to a lack of ERBB2, estrogen receptor and progesterone receptor expression1-3. The mutational spectrum of TNBC has been characterized as part of The Cancer Genome Atlas (TCGA)4; however, snapshots of primary tumors cannot reveal the mechanisms by which TNBCs progress and spread. To address this limitation we initiated the Intensive Trial of OMics in Cancer (ITOMIC)-001, in which patients with metastatic TNBC undergo multiple biopsies over space and time5. Whole exome sequencing (WES) of 67 samples from 11 patients identified 426 genes containing multiple distinct single nucleotide variants (SNVs) within the same sample, instances we term Multiple SNVs affecting the Same Gene and Sample (MSSGS). We find that >90% of MSSGS result from cis-compound mutations (in which both SNVs affect the same allele), that MSSGS comprised of SNVs affecting adjacent nucleotides arise from single mutational events, and that most other MSSGS result from the sequential acquisition of SNVs. Some MSSGS drive cancer progression, as exemplified by a TNBC driven by FGFR2(S252W;Y375C). MSSGS are more prevalent in TNBC than other breast cancer subtypes and occur at higher-than-expected frequencies across TNBC samples within TCGA. MSSGS may denote genes that play as yet unrecognized roles in cancer progression.

scholarly journals Construction and Analysis of Competing Endogenous RNA Networks for Breast Cancer Based on TCGA Dataset

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Xue Wang ◽  
Chundi Gao ◽  
Fubin Feng ◽  
Jing Zhuang ◽  
Lijuan Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Metastasis ◽  
Target Genes ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Competing Endogenous Rna ◽  
Cerna Network ◽  
Competing Endogenous Rnas ◽  
Tcga Dataset

Background. Long noncoding RNAs (lncRNAs) act as competing endogenous RNAs for microRNAs in cancer metastasis. However, the roles of lncRNA-mediated competing endogenous RNA (ceRNA) networks for breast cancer (BC) are still unclear. Material and Methods. The expression profiles of mRNAs, lncRNAs, and miRNAs with BC were extracted from The Cancer Genome Atlas database. Weighted gene coexpression network analysis was conducted to extract differentially expressed mRNAs (DEmRNAs) that might be core genes. Through miRWalk, TargetScan, and miRDB to predict the target genes, an abnormal lncRNA-miRNA-mRNA ceRNA network with BC was constructed. The survival possibilities of mRNAs, miRNAs, and lncRNAs for patients with BC were determined by Kaplan-Meier survival curves and Oncomine. Results. We identified 2134 DEmRNAs, 1059 differentially expressed lncRNAs (DElncRNAs), and 86 differentially expressed miRNAs (DEmiRNAs). We then compose a ceRNA network for BC, including 72 DElncRNAs, 8 DEmiRNAs, and 12 DEmRNAs. After verification, 2 lncRNAs (LINC00466, LINC00460), 1 miRNA (Hsa-mir-204), and 5 mRNAs (TGFBR2, CDH2, CHRDL1, FGF2, and CHL1) were meaningful as prognostic biomarkers for BC patients. In the ceRNA network, we found that three axes were present in 10 RNAs related to the prognosis of BC, namely, LINC00466-Hsa-mir-204-TGFBR2, LINC00466-Hsa-mir-204-CDH2, and LINC00466-Hsa-mir-204-CHRDL1. Conclusion. This study highlighted lncRNA-miRNA-mRNA ceRNA related to the pathogenesis of BC, which might be used for latent diagnostic biomarkers and therapeutic targets for BC.

scholarly journals The YAP1–NMU Axis Is Associated with Pancreatic Cancer Progression and Poor Outcome: Identification of a Novel Diagnostic Biomarker and Therapeutic Target

Cancers ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1477 ◽  
Author(s):  
Yoo ◽  
Lee ◽  
Jun ◽  
Noh ◽  
Lee ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Progression ◽  
Target Genes ◽  
Epithelial Mesenchymal Transition ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Transition ◽  
Tumor Group ◽  
Cancer Genome Atlas

Yes-associated protein (YAP)-1 is highly upregulated in pancreatic cancer and associated with tumor progression. However, little is known about the role of YAP1 and related genes in pancreatic cancer. Here, we identified target genes regulated by YAP1 and explored their role in pancreatic cancer progression and the related clinical implications. Analysis of different pancreatic cancer databases showed that Neuromedin U (NMU) expression was positively correlated with YAP1 expression in the tumor group. The Cancer Genome Atlas data indicated that high YAP1 and NMU expression levels were associated with poor mean and overall survival. YAP1 overexpression induced NMU expression and transcription and promoted cell motility in vitro and tumor metastasis in vivo via upregulation of epithelial–mesenchymal transition (EMT), whereas specific inhibition of NMU in cells stably expressing YAP1 had the opposite effect in vitro and in vivo. To define this functional association, we identified a transcriptional enhanced associate domain (TEAD) binding site in the NMU promoter and demonstrated that YAP1–TEAD binding upstream of the NMU gene regulated its transcription. These results indicate that the identified positive correlation between YAP1 and NMU is a potential novel drug target and biomarker in metastatic pancreatic cancer.

scholarly journals Gene expression profiles of human breast cancer progression

2003 ◽  
Vol 100 (10) ◽  
pp. 5974-5979 ◽  
Author(s):  
X.-J. Ma ◽  
R. Salunga ◽  
J. T. Tuggle ◽  
J. Gaudet ◽  
E. Enright ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Progression ◽  
Human Breast Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Breast Cancer Progression ◽  
Human Breast

scholarly journals GPER1 and microRNA: Two Players in Breast Cancer Progression

2020 ◽  
Vol 22 (1) ◽  
pp. 98
Author(s):  
Adele Vivacqua
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Target Genes ◽  
Current Knowledge ◽  
Breast Cancer Progression ◽  
Non Coding Rna ◽  
Anti Cancer ◽  
G Protein Coupled ◽  
Breast Tumor Progression

Breast cancer is the main cause of morbidity and mortality in women worldwide. However, the molecular pathogenesis of breast cancer remains poorly defined due to its heterogeneity. Several studies have reported that G Protein-Coupled Estrogen Receptor 1 (GPER1) plays a crucial role in breast cancer progression, by binding to estrogens or synthetic agonists, like G-1, thus modulating genes involved in diverse biological events, such as cell proliferation, migration, apoptosis, and metastasis. In addition, it has been established that the dysregulation of short sequences of non-coding RNA, named microRNAs (miRNAs), is involved in various pathophysiological conditions, including breast cancer. Recent evidence has indicated that estrogens may regulate miRNA expression and therefore modulate the levels of their target genes, not only through the classical estrogen receptors (ERs), but also activating GPER1 signalling, hence suggesting an alternative molecular pathway involved in breast tumor progression. Here, the current knowledge about GPER1 and miRNA action in breast cancer is recapitulated, reporting recent evidence on the liaison of these two players in triggering breast tumorogenic effects. Elucidating the role of GPER1 and miRNAs in breast cancer might provide new tools for innovative approaches in anti-cancer therapy.

scholarly journals In Silico Evaluation of Natural Compounds for an Acidic Extracellular Environment in Human Breast Cancer

Cells ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2673
Author(s):  
YoungJoon Park ◽  
Jaekwang Jeong ◽  
Shin Seong ◽  
Wonnam Kim
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Information Gain ◽  
Therapeutic Potential ◽  
Expression Profiles ◽  
Survival Rates ◽  
Gene Expression Profiles ◽  
Natural Compounds ◽  
The Cancer Genome Atlas ◽  
Potential Candidate

The survival rates for breast cancer (BC) have improved in recent years, but resistance, metastasis, and recurrence still remain major therapeutic challenges for BC. The acidic tumor microenvironment (TME) has attracted attention because of its association with tumorigenesis, metastasis, drug resistance, and immune surveillance. In this study, we evaluated natural compounds from traditional herbal medicine used to treat cancer that selectively target genes regulated by extracellular acidosis. We integrated four transcriptomic data including BC prognostic data from The Cancer Genome Atlas database, gene expression profiles of MCF-7 cells treated with 102 natural compounds, patterns of gene profiles by acidic condition, and single-cell RNA-sequencing from BC patient samples. Bruceine D (BD) was predicted as having the highest therapeutic potential, having an information gain (IG) score of 0.24, to regulate reprogrammed genes driven by acidosis affecting the survival of BC patients. BD showed the highest IG on EMT (IG score: 0.11) and invasion (IG score: 0.1) compared to the other phenotypes with the CancerSEA database. BD also demonstrated therapeutic potential by interfering with the tumor cell–TME interactions by reducing the amyloid beta precursor protein and CD44 expression. Therefore, BD is a potential candidate to target the acidic TME induced metastatic process in BC.

The Low Expression of MEOX2 is Associated With Poorer Survival in Breast Cancer

2021 ◽  
Author(s):  
Huxia Wang ◽  
Yanan Tang ◽  
Meixia Wang ◽  
Caixia Ding ◽  
Xiaomin Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Cancer Progression ◽  
Cox Regression ◽  
Histological Grade ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Patients ◽  
Normal Tissues ◽  
Cancer Genome Atlas ◽  
And Function

Abstract The regulation of vertebrate limb myogenesis gene, Mesenchyme Homeobox 2 (MEOX2), has been reported to be associated with most cancer progression closely. However, its role and function in breast cancer are unidentified. Here, we aim to investigate the association of MEOX2 expression with clinicopathological features and the survival probability of breast cancer. The MEOX2 expression in breast cancer was first analyzed from The Cancer Genome Atlas (TCGA) database. Then, the association of MEOX2 with patients’ clinicopathological variables and prognostic probability were detected by bioinformatics analysis. Moreover, a high-throughput tissue microarray containing 135 cases of breast cancer was used to further clarify the expression of MEOX2 in breast cancer patients. The expression of MEOX2 is inhibited in breast cancer than in normal tissues, and the lower MEOX2 expression indicates the poorer prognosis of breast cancer patients. In addition, the histological grade of MEOX2 expression is negatively correlated with the Ki67 level. Multivariate COX regression also verified that MEOX2 was an independent prognostic factor in breast cancer patients. Based on our results, we can conclude that lower MEOX2 expression was related to tumor proliferation and could be a new diagnostic and prognostic biomarker of breast cancer.

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