MiR-190b, the highest up-regulated miRNA in ERα-positive compared to ERα-negative breast tumors, a new biomarker in breast cancers?

MicroRNA-190b Targets RFWD3 in Estrogen Receptor-Positive Breast Cancer

Background

In the year 2020, breast cancer was the most common form of cancer worldwide. Roughly 70% of breast cancers are estrogen receptor-positive (ER+). MicroRNA-190b (miR-190b) has previously been reported to be upregulated in ER+ breast cancers. Previously, we have demonstrated that miR-190b is hypomethylated in ER+ breast cancers, potentially leading to its upregulation.

Objectives

To further study the role of miR-190b in ER+ breast cancer and to identify its clinically relevant targets in breast cancer.

Design

Patient cohort and cell line-based RNA-sequencing analysis.

Methods

The Cancer Genome Atlas was used to obtain gene expression data and clinical information on patients with breast cancer. To identify messenger RNA (mRNA) targets for miR-190b, the ER+ breast cancer cell line T-47D was used to immunoprecipitate biotin-labeled miR-190b followed by RNA sequencing. Western blot was used to confirm miR-190b target. Patient survival based on miR-190b and selected target was studied using the Cancer Genome Atlas.

Results

In this study, we confirm that miR-190b is overexpressed in breast cancer via differential expression analysis and show that high expression of miR-190b results in more favorable outcomes in Luminal A patients, hazard ratio (HR) = 0.29, 95% confidence interval [CI] = 0.12-0.71, P = .0063. MicroRNA-190b target analysis identified RING finger and WD repeat domain 3 (RFWD3) as one of miR-190b regulatory targets in ER+ breast cancer. Survival analysis of RFWD3 showed that elevated levels result in poorer overall survival in patients with Luminal A breast cancer (HR = 2.22, 95% CI = 1.33-3.71, P = .002). Gene ontology analysis of our sequencing results indicates that miR-190b may have a role in breast cancer development and/or tumorigenesis and that it may be a suitable tool in characterization between the ER+ subtypes, Luminal A, and Luminal B.

Conclusions

We show that miR-190b targets RFWD3 in ER+ breast cancers leading to lower RFWD3 protein expression. Low levels of RFWD3 are associated with better outcomes in patients with Luminal A breast cancer but not in patients with Luminal B breast cancer. These findings provide novel insights into miR-190b role in breast cancer and that its clinical relevance is subtype specific.

Integrated transcriptomics, proteomics, and functional analysis to characterize the tissue-specific small extracellular vesicle network of breast cancer

Small extracellular vesicles (sEVs) are essential mediators of intercellular communication within the tumor microenvironment (TME). Although the biological features of sEVs have been characterized based on in vitro culture models, recent evidence indicates significant differences between sEVs derived from tissue and those derived from in vitro models in terms of both content and biological function. However, comprehensive comparisons and functional analyses are still limited. Here, we collected sEVs from breast cancer tissues (T-sEVs), paired normal tissues (N-sEVs), corresponding plasma (B-sEVs), and tumor organoids (O-sEVs) to characterize their transcriptomic and proteomic profiles. We identified the actual cancer-specific sEV signatures characterized by enriched cell adhesion and immunomodulatory molecules. Furthermore, we revealed the significant contribution of cancer-associated fibroblasts in the sEV network within the TME. In vitro model-derived sEVs did not entirely inherit the extracellular matrix- and immunity regulation-related features of T-sEVs. Also, we demonstrated the greater immunostimulatory ability of T-sEVs on macrophages and CD8+ T cells compared to O-sEVs. Moreover, certain sEV biomarkers derived from noncancer cells in the circulation exhibited promising diagnostic potential. This study provides valuable insights into the functional characteristics of tumor tissue-derived sEVs, highlighting their potential as diagnostic markers and therapeutic agents for breast cancer.

Comprehensive characterization of RNA cargo of extracellular vesicles in breast cancer patients undergoing neoadjuvant chemotherapy

Extracellular vesicles (EVs) are g7aining increased attention as carriers of cancer-derived molecules for liquid biopsies. Here, we studied the dynamics of EV levels in the plasma of breast cancer (BC) patients undergoing neoadjuvant chemotherapy (NAC) and explored the relevance of their RNA cargo for the prediction of patients' response to the therapy. EVs were isolated from serial blood samples collected at the time of diagnosis, at the end of NAC, and 7 days, 6, and 12 months after the surgery from 32 patients with locally advanced BC, and 30 cancer-free healthy controls (HCs) and quantified by nanoparticle tracking analysis. The pre-treatment levels of EVs in BC patients were higher than in HCs, significantly increased during the NAC and surgery, and decreased to the levels found in HCs 6 months after surgery, thus showing that a substantial fraction of plasma EVs in BC patients are produced due to the disease processes and treatment. RNA sequencing analysis revealed that the changes in the EV levels were associated with the alterations in the proportions of various RNA biotypes in EVs. To search for RNA biomarkers that predict response to the NAC, patients were dichotomized as responders and non-responders based on Miller-Payne grades and differential expression analyses were carried out between responders and non-responders, and HCs. This resulted in the identification of 6 miRNAs, 4 lncRNAs, and 1 snoRNA that had significantly higher levels in EVs from non-responders than responders at the time of diagnosis and throughout the NAC, and significantly lower levels in HCs, thus representing biomarkers for the prediction of response to NAC at the time of diagnosis. In addition, we found 14 RNAs representing piRNA, miRNA, lncRNA, snoRNA, and snRNA biotypes that were induced by NAC in non-responders and 2 snoRNAs and 1 piRNA that were induced by NAC in patients with early disease progression, thus warranting further functional studies on their role in chemoresistance and metastasis.

MiRNA expression deregulation correlates with the Oncotype DX® DCIS score

Background

Current clinical criteria do not discriminate well between women who will or those who will not develop ipsilateral invasive breast cancer (IBC), or a DCIS recurrence after a ductal carcinoma in situ (DCIS) diagnosis. The 12-gene Oncotype DX® DCIS assay (RT qPCR gene-based scoring system) was established and shown to predict the risk of subsequent ipsilateral IBC or DCIS recurrence. Recent studies have shown that microRNA (miRNA) expression deregulation can contribute to the development of IBC, but very few have evaluated miRNA deregulation in DCIS lesions. In this study, we sought to determine whether specific miRNA expression changes may correlate with Oncotype DX® DCIS scores.

Methods

For this study, we used archived formalin-fixed, paraffin-embedded (FFPE) specimens from 41 women diagnosed with DCIS between 2012 and 2018. The DCIS lesions were stratified into low (n = 26), intermediate (n = 10), and high (n = 5) risk score groups using the Oncotype DX® DCIS assay. Total RNA was extracted from DCIS lesions by macro-dissection of unstained FFPE sections, and next-generation small-RNA sequencing was performed. We evaluated the correlation between miRNA expression data and Oncotype score, as well as patient age. RT-qPCR validations were performed to validate the topmost differentially expressed miRNAs identified between the different risk score groups.

Results

MiRNA sequencing of 32 FFPE DCIS specimens from the three different risk group scores identified a correlation between expression deregulation of 17 miRNAs and Oncotype scores. Our analyses also revealed a correlation between the expression deregulation of 9 miRNAs and the patient’s age. Based on these results, a total of 15 miRNAs were selected for RT-qPCR validation. Of these, miR-190b (p = 0.043), miR-135a (p = 0.05), miR-205 (p = 0.00056), miR-30c (p = 0.011), and miR-744 (p = 0.038) showed a decreased expression in the intermediate/high Oncotype group when compared to the low-risk score group. A composite risk score was established using these 5 miRNAs and indicated a significant association between miRNA expression deregulation and the Oncotype DX® DCIS Score (p < 0.0021), between high/intermediate and low risk groups.

Conclusions

Our analyses identified a subset of 5 miRNAs able to discriminate between Oncotype DX® DCIS score subgroups. Together, our data suggest that miRNA expression analysis may add value to the predictive and prognostic evaluation of DCIS lesions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01558-4.

Associations between the Levels of Estradiol-, Progesterone-, and Testosterone-Sensitive MiRNAs and Main Clinicopathologic Features of Breast Cancer

Despite the existing advances in the diagnosis and treatment of breast cancer (BC), the search for markers associated with the clinicopathological features of BC is still in demand. MiRNAs (miRs) have potential as markers, since a change in the miRNA expression profile accompanies the initiation and progression of malignant diseases. The receptors for estrogen, androgen, and progesterone (ER, AR, and PR) play an important role in breast carcinogenesis. Therefore, to search for miRNAs that may function as markers in BC, using bioinformatic analysis and the literature data, we selected 13 miRNAs whose promoter regions contain binding sites for ER or AR, or putative binding sites for ER, AR, and PR. We quantified their expression in MCF-7 cells treated with estradiol, progesterone, or testosterone. The levels of miRNAs sensitive to one or more of these hormones were quantified in BC samples (n = 196). We discovered that high expression levels of miR-190b in breast tumor tissue indicate a positive ER status, and miR-423 and miR-200b levels differ between patients with and without HER2 amplification. The miR-193b, -423, -190a, -324, and -200b levels were associated with tumor size or lymph node status in BC patients, but the presence of these associations depended on the status and expression level of ER, PR, HER2, and Ki-67. We also found that miR-21 expression depends on HER2 expression in ER- and/or PR-positive BC. The levels of miRNA were significantly different between HER2 0 and HER2 1+ tumors (p = 0.027), and between HER2 0 and HER2 2+, 3+ tumors (p = 0.005).

MicroRNAs in Molecular Classification and Pathogenesis of Breast Tumors

The current clinical practice of breast tumor classification relies on the routine immunohistochemistry-based expression analysis of hormone receptors, which is inadequate in addressing breast tumor heterogeneity and drug resistance. MicroRNA expression profiling in tumor tissue and in the circulation is an efficient alternative to intrinsic molecular subtyping that enables precise molecular classification of breast tumor variants, the prediction of tumor progression, risk stratification and also identifies critical regulators of the tumor microenvironment. This review integrates data from protein, gene and miRNA expression studies to elaborate on a unique miRNA-based 10-subtype taxonomy, which we propose as the current gold standard to allow appropriate classification and separation of breast cancer into a targetable strategy for therapy.

Identification of Key lncRNA-mRNA Pairs and Functional lncRNAs in Breast Cancer by Integrative Analysis of TCGA Data

Long non-coding RNAs (lncRNAs) play an important role in many diseases and are involved in the post-transcriptional regulatory network of tumors. The purpose of this study is to mine new lncRNA–mRNA regulatory pairs and analyze the new mechanism of lncRNA involvement in breast cancer progression. Using breast cancer miRNA and mRNA expression profiling from The Cancer Genome Atlas (TCGA), we identified 59 differentially expressed lncRNAs, 88 differentially expressed miRNAs, and 1,465 differentially expressed mRNAs between breast cancer tissue and adjacent normal breast cancer. Whereafter, four candidate lncRNAs (FGF14-AS2, LINC01235, AC055854.1, and AC124798.1) were identified by the Kaplan–Meier (K–M) plotter. Furthermore, we screened the hub lncRNA (LINC01235) through univariate Cox analysis, multivariate Cox analysis, and qPCR validation, which was significantly correlated with breast cancer stage, ER status, and pathological N. Subsequently, 107 LINC01235-related mRNAs were obtained by combining differentially expressed miRNAs, differentially expressed mRNAs, and LINC01235 targeting miRNAs and mRNAs. The protein–protein interaction (PPI) network was established by Cytoscape software, and 53 key genes were screened. Function and pathway enrichment showed that LINC01235-related key genes might be involved in the process of cell differentiation, cell proliferation, and p53 signal pathway. In addition, LINC01235 has been confirmed to regulate the proliferation, migration, and invasion of MCF-7 cells in in vitro experiments. Furthermore, we screened three mRNAs (ESR1, ADRA2A, and DTL) associated with breast cancer drug resistance from key genes. Through RNA interference experiments in vitro and correlation analysis, we found that there was a negative feedback mechanism between LINC01235 and ESR1/ADRA2A. In conclusion, our results suggest that LINC01235-ESR1 and LINC01235-ADRA2A could serve as important co-expression pairs in the progression of breast cancer, and LINC01235 plays a key role as an independent prognostic factor in patients with breast cancer. The findings of this work greatly increase our understanding of the molecular regulatory mechanisms of lncRNA in breast cancer.

Differential methylation and expression patterns of microRNAs in relation to breast cancer subtypes among American women of African and European ancestry

Aggressive high-grade, estrogen receptor negative (ER-) breast cancer is more common among American women of African ancestry (AA) than those of European ancestry (EA). Epigenetic mechanisms, particularly DNA methylation and altered microRNA (miRNA) expression, may contribute to racial differences in breast cancer. However, few studies have specifically characterized genome-wide DNA methylation-based modifications at the miRNA level in relation to ER+ and ER- subtype, and their functional role in the regulation of miRNA expression, especially among high risk AA women. In this study, we evaluated DNA methylation patterns of miRNA encoding genes and their effect on expression in breast tumors from both AA and EA women. The genome-wide methylation screen identified a total of 7,191 unique CpGs mapped to 1,292 miRNA genes, corresponding to 2,035 unique mature miRNAs. We identified differentially methylated loci (DMLs: (|delta β|)>0.10, FDR<0.05) between ER- and ER+ tumor subtypes, including 290 DMLs shared in both races, 317 and 136 were specific to AA and EA women, respectively. Integrated analysis identified certain DMLs whose methylation levels were significantly correlated with the expression of relevant miRNAs, such as multiple CpGs within miR-190b and miR-135b highly negatively correlated with their expression. These results were then validated in the TCGA dataset. Target prediction and pathway analysis showed that these DNA methylation-dysregulated miRNAs are involved in multiple cancer-related pathways, including cell cycle G1-S growth factor regulation, cytoskeleton remodeling, angiogenesis, EMT, and ESR1-mediated signaling pathways. In summary, our results suggest that DNA methylation changes within miRNA genes are associated with altered miRNA expression, which may contribute to the network of subtype- and race-related tumor biological differences in breast cancer. These findings support the involvement of epigenetic regulation of miRNA expression and provide insights into the relations of clinical-relevant miRNAs to their target genes, which may serve as potential preventative and therapeutic targets.

miRNA normalization enables joint analysis of several datasets to increase sensitivity and to reveal novel miRNAs differentially expressed in breast cancer

Different miRNA profiling protocols and technologies introduce differences in the resulting quantitative expression profiles. These include differences in the presence (and measurability) of certain miRNAs. We present and examine a method based on quantile normalization, Adjusted Quantile Normalization (AQuN), to combine miRNA expression data from multiple studies in breast cancer into a single joint dataset for integrative analysis. By pooling multiple datasets, we obtain increased statistical power, surfacing patterns that do not emerge as statistically significant when separately analyzing these datasets. To merge several datasets, as we do here, one needs to overcome both technical and batch differences between these datasets. We compare several approaches for merging and jointly analyzing miRNA datasets. We investigate the statistical confidence for known results and highlight potential new findings that resulted from the joint analysis using AQuN. In particular, we detect several miRNAs to be differentially expressed in estrogen receptor (ER) positive versus ER negative samples. In addition, we identify new potential biomarkers and therapeutic targets for both clinical groups. As a specific example, using the AQuN-derived dataset we detect hsa-miR-193b-5p to have a statistically significant over-expression in the ER positive group, a phenomenon that was not previously reported. Furthermore, as demonstrated by functional assays in breast cancer cell lines, overexpression of hsa-miR-193b-5p in breast cancer cell lines resulted in decreased cell viability in addition to inducing apoptosis. Together, these observations suggest a novel functional role for this miRNA in breast cancer. Packages implementing AQuN are provided for Python and Matlab: https://github.com/YakhiniGroup/PyAQN.

This work demonstrates a practical approach to the joint-analysis of multiple miRNA expression profiling datasets acquired with different measurement technologies. The use of different platforms in miRNA profiling can lead to major differences in results. In particular, some miRNA species are less amenable to detection and quantification by certain platforms or designs. Our approach, termed AQuN, combines quantile normalization with special attention to missing entities, to normalize miRNA expression across datasets, technologies, designs and platforms. As we show, our proposed approach uncovers patterns of interest that would not have emerged as statistically significant when analyzing the datasets individually or with other standard-practice normalization methods.

Amongst our findings, we noted a previously undocumented miRNA that is significantly over-expressed in samples from estrogen-receptor positive breast cancer patients as compared to samples from estrogen-receptor negative patients. We further investigated this miRNA, hsa-miR-193b-5p, and experimentally show, in cell lines, that its expression level impacts the viability of tumor cells. AQuN is available to the community in the form of Python and Matlab packages. The joint-processed data is also made available for further investigation.

Specific MiRNAs in naïve T cells associated with Hepatitis C Virus-induced Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer and the second leading cause of cancer-associated mortality worldwide. Hepatitis C virus (HCV) infection is the primary cause of hepatic fibrosis and cirrhosis, which in turn, notably increase the risk of developing HCC. The systematic immune response plays a vital role in protecting eukaryotic cells from exogenous antigens. In the present study, to determine the association between T cells and miRNAs in HCV-induced HCC (HCV-HCC), bulk mRNA and miRNA sequencing data from HCV-HCC tissues were combined, along with single-cell RNA sequencing (RNA-seq) data from T cells. Deconvoluted bulk RNA-seq data and miRNA profiles enabled the identification of naive CD4+ T cell-associated miRNAs, which may help to elucidate the underlying mechanism of the anti-HCV immune response. Using bulk RNA-seq data, the current analysis presents a feasible method for assessing the relationship between miRNAs and cell components, providing valuable insights into the effects of T cell-associated miRNAs in HCV-HCC.

In vivo miRNA knockout screening identifies miR-190b as a novel tumor suppressor

MicroRNAs (miRNAs) play important roles in the development of various cancers including lung cancer which is one of the devastating diseases worldwide. How miRNAs function in de novo lung tumorigenesis remains largely unknown. We here developed a CRISPR/Cas9-mediated dual guide RNA (dgRNA) system to knockout miRNAs in genetically engineered mouse model (GEMM). Through bioinformatic analyses of human lung cancer miRNA database, we identified 16 downregulated miRNAs associated with malignant progression and performed individual knockout with dgRNA system in KrasG12D/Trp53L/L (KP) mouse model. Using this in vivo knockout screening, we identified miR-30b and miR-146a, which has been previously reported as tumor suppressors and miR-190b, a new tumor-suppressive miRNA in lung cancer development. Over-expression of miR-190b in KP model as well as human lung cancer cell lines significantly suppressed malignant progression. We further found that miR-190b targeted the Hus1 gene and knockout of Hus1 in KP model dramatically suppressed lung tumorigenesis. Collectively, our study developed an in vivo miRNA knockout platform for functionally screening in GEMM and identified miR-190b as a new tumor suppressor in lung cancer.

MiR-891a-5p as a prognostic marker and therapeutic target for hormone receptor-positive breast cancer

Background: Breast cancer is one of the most frequent malignant tumors worldwide, with 1.67 million newly-diagnosed cases and 522,000 deaths each year. Therefore, seeking the novel biomarkers and therapeutic targets that contribute to postoperative recurrence and metastasis in patients with breast cancer is emerging and facilitates the development of innovative therapeutics. Methods: Retrieving the dataset of patients with hormone receptor (HR)-positive breast cancers from Gene Expression Omnibus (GEO) and collecting the data from the patients with HR-positive breast cancers enrolled in the First Affiliated Hospital of China Medical University are so as to identify the miRNAs associated with metastasis and distant metastasis-free survival (DMFS). Then MTT and Transwell migration assays were used to validate the effect of miRNAs on cell proliferation and migration of estrogen receptor-positive breast cancer T47D and MCF7 cells in vitro, respectively. Results: From GSE59829 dataset, the miRNA expression levels of miR-891a-5p, miR-383-5p and miR-1295a were significantly downregulated while the levels of miR-128-3p, miR-661 and miR-296-3p were significantly upregulated in breast cancers from patients with metastasis as compared to the matched non-metastatic group. Moreover, low expression levels of miR-891a-5p, miR-383-5p and miR-1295a or high expression levels of miR-128-3p, miR-661 and miR-296-3p were respectively associated with low DMFS in patients with breast cancer. Our clinical cohort study supported that the levels of miR-891a-5p, miR-383-5p and miR-1295a were significantly lower in breast cancers from the metastasis group when compared with non-metastatic group. However, there is no significant difference with regard to the levels of miR-128-3p, miR-661 and miR-296-3p in breast cancer between these two groups. Moreover, low expression levels of miR-891a-5p and miR-383-5p but not miR-1295a in breast cancer were significantly associated with low DMFS in patients, implying that the expression of miR-891a-5p and miR-383-5p were the potential prognosis markers for metastatic human breast cancers. Further investigation disclosed that miR-891a-5p but not miR-383-5p restrained both proliferation and migration of T47D and MCF7 cells. In silico analysis of miRNAs target gene through online computational algorithms revealed that A Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) is the downstream target for miR-891a-5p. Further study confirmed that miR-891a-5p impeded ADAM10 expression by directly binding to its 3'UTR, leading to the inhibition of breast cancer cells proliferation and migration. Moreover, silencing ADAM10 inhibited T47D and MCF7 cells growth and migration. Conclusion: miR-891a-5p is the vital prognostic marker for HR-positive breast cancer. In addition, miR-891a-5p and miR-383-5p are the potential targets for HR-positive breast cancer therapeutics.

Insulin resistance in obese adolescents affects the expression of genes associated with immune response

OBJECTIVE

The development of obesity and its metabolic complications is associated with dysregulation of various intrinsic mechanisms, which control basic metabolic processes through changes in the expression of numerous regulatory genes.

METHODS

The expression level of HLA-DRA, HLA-DRB1, HLA-G, HLA-F, and NFX1 genes as well as miR-190b was measured in the blood of obese adolescents without signs of resistance to insulin and with insulin resistance in comparison with the group of relative healthy control individuals without signs of obesity.

RESULTS

It was shown that obesity without signs of insulin resistance is associated with upregulation of the expression level of HLA-DRA and HLA-DRB1 genes, but with down-regulation of HLA-G gene expression in the blood as compared to control group of relative healthy adolescents. At the same time, no significant changes were observed in the expression level of HLA-F and NFX1 genes in the blood of this group of obese adolescents. Development of insulin resistance in obese individuals leads to significant down-regulation of HLA-DRA, HLA-DRB1, HLA-G, and HLA-F gene expressions as well as to up-regulation of NFX1 gene as well as microRNA miR-190b in the blood as compared to obese patients without signs of insulin resistance.

CONCLUSIONS

Results of this study provide evidence that obesity affects the expression of the subset of genes related to immune response in the blood and that development of insulin resistance in obese adolescents is associated with strong down-regulation of the expressions of HLA-DRA, HLA-DRB1, HLA-F, and HLA-G genes, which may be contribute to the development of obesity complications. It is possible that transcription factor NFX1 and miR-190b participate in downregulation of HLA-DRA gene expression in the blood of obese adolescents with insulin resistance.

Long non-coding RNA TUSC8 inhibits breast cancer growth and metastasis via miR-190b-5p/MYLIP axis

The lncRNA tumor suppressor candidate 8 (TUSC8) plays a critical role in the development of several cancers. However, the biological functions and underlying molecular mechanisms of TUSC8 with respect to breast cancer remain largely unclear. Here, we found that TUSC8 was significantly down-regulated in breast cancer tissues and its high expression predicted better prognosis of breast cancer patients. Functionally, knock-down of TUSC8 drastically promoted the proliferation, migration and invasion of breast cancer cells in vitro and facilitated tumorigenicity and metastasis in vivo. Mechanistically, the results of luciferase reporter, RIP and RNA pull-down assays proved that TUSC8 functioned as molecular sponge for miR-190b-5p. Furthermore, we showed that TUSC8 served as a competing endogenous RNA (ceRNA) of myosin regulatory light chain interacting protein (MYLIP) through competitively binding with miR-190b-5p and suppressed breast cancer metastasis through regulating the expression of epithelial–mesenchymal transition (EMT) related markers. Clinically, the receiver operating characteristic curve (ROC) analyses revealed that the combination usage of TUSC8 and MYLIP might become novel promising diagnostic biomarkers for breast cancer. Taken together, these results suggested that TUSC8 inhibited breast cancer growth and metastasis via miR-190b-5p/MYLIP axis, providing us new insights into developing potential therapeutic targets for breast cancer patients.

MicroRNAs in breast cancer: Roles, functions, and mechanism of actions

Breast cancer is one of the most lethal malignancies in women in the world. Various factors are involved in the development and promotion of the malignancy; most of them involve changes in the expression of certain genes, such as microRNAs (miRNAs). MiRNAs can regulate signaling pathways negatively or positively, thereby affecting tumorigenesis and various aspects of cancer progression, particularly breast cancer. Besides, accumulating data demonstrated that miRNAs are a novel tool for prognosis and diagnosis of breast cancer patients. Herein, we will review the roles of these RNA molecules in several important signaling pathways, such as transforming growth factor, Wnt, Notch, nuclear factor-κ B, phosphoinositide-3-kinase/Akt, and extracellular-signal-regulated kinase/mitogen activated protein kinase signaling pathways in breast cancer.

miR-190b promotes colorectal cancer progression through targeting forkhead box protein P2

microRNA-190b (miR-190b) is abnormally expressed in multiple types of cancer, however, its role in colorectal cancer (CRC) is largely unknown. In the present study, it was demonstrated that miR-190b expression was upregulated in CRC cell lines compared with the normal epithelial colon cell line. Knockdown of miR-190b decreased proliferation, colony formation and invasion, and increased apoptosis of CRC cells. Furthermore, forkhead box protein P2 (FOXP2) was predicted as a target of miR-190b and further validated by luciferase activity reporter assay and western blotting. Rescue experiments showed that knockdown of FOXP2 reversed the inhibitory effects of miR-190b inhibitor on the behavior of the CRC cell lines. Taken together, the present study demonstrated the oncogenic role of miR-190b in CRC through regulation of FOXP2 expression.

Differences in microRNA expression in breast cancer between women of African and European ancestry

Breast cancer is a heterogeneous disease, characterized by molecularly and phenotypically distinct tumor subtypes, linked to disparate clinical outcomes. American women of African ancestry (AA) are more likely than those of European ancestry (EA) to be diagnosed with aggressive, estrogen receptor negative (ER-) or triple negative breast cancer, and to die of this disease. However, the underlying causes of AA predisposition to ER-/triple negative breast cancer are still largely unknown. In this study, we performed high-throughput whole-genome miRNA expression profiling in breast tissue samples from both AA and EA women. A number of differentially expressed miRNAs, i.e., DEmiRs defined as >2-fold change in expression and false discovery rate <0.05, were identified as up- or downregulated by tumor ER status or by ancestry. We found that among 102 ER-subtype-related DEmiRs identified in breast tumors, the majority of these DEmiRs were race specific, with only 23 DEmiRs shared in tumors from both AAs and EAs; this finding indicates that there are unique subsets of miRNAs differentially expressed between ER- and ER positive tumors within AAs versus EAs. Our overall results support the notion that miRNA expression patterns may differ not only by tumor subtype but by ancestry, indicating differences in tumor biology and heterogeneity of breast cancer between AAs and EAs. These results will provide the basis for further functional analysis to elucidate biological differences between AAs and EAs and to help develop targeted treatment strategies to reduce disparities in breast cancer.

CpG promoter hypo-methylation and up-regulation of microRNA-190b in hormone receptor-positive breast cancer

Estrogen receptor-positive breast cancer is subdivided into subtypes LuminalA and LuminalB, based on different expression patterns. MicroRNA-190b has been reported to be up-regulated in estrogen receptor-positive breast cancers. In this study we aimed to investigate the role of CpG promoter methylation in regulating miR-190b expression and its impact on clinical presentation and prognosis. DNA methylation analysis for the promotor of microRNA-190b was performed by pyrosequencing 549 primary breast tumors, of which 62 were carriers of the BRCA2 ^999del5 founder mutation, 71 proximal normal breast samples and 16 breast derived cell lines. MicroRNA-190b expression was analysed in 67 primary breast tumors, 14 paired normal breast samples and 16 breast derived cell lines. Tissue microarrays (TMAs) were available for ER (n = 436), PR (n = 436), HER-2 (N = 258) and Ki67 (n = 248). MiR-190b had reduced promoter methylation in estrogen receptor-positive breast cancers (P = 1.02e-12, Median values: ER+ 24.3, ER- 38.26) and miR-190b's expression was up-regulated in a correlative manner (P = 1.83e-06, Spearman's rho -0.62). Through breast cancer specific survival analysis, we demonstrated that LuminalA patients exhibiting miR-190b hypo-methylation had better survival than other patients (P = 0.034, HR = 0.29, 95% CI 0.09-0.91). We, furthermore, demonstrated that miR-190b hypo-methylation occurs less frequently in ER+ tumors from BRCA2 ^999del5 mutation carriers than in non-mutated individuals (P = 0.038, Χ ² = 4.32, n = 335). Our results suggest that upregulation of miR-190b may occur through loss of promoter DNA methylation during the development of estrogen-receptor (ER) positive breast cancers, and that miR-190b hypo-methylation leads to increased breast cancer specific survival within the LuminalA- subtype but not LuminalB.

Refinement of breast cancer molecular classification by miRNA expression profiles

Background

Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction.

Results

We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day’s signatures.

Conclusions

We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5887-7) contains supplementary material, which is available to authorized users.

miR-148b-3p, miR-190b, and miR-429 Regulate Cell Progression and Act as Potential Biomarkers for Breast Cancer

Purpose

Breast cancer is the most frequently diagnosed malignancy in women worldwide. MicroRNAs (miRNAs) are thought to serve as potential biomarkers in various cancers, including breast cancer.

Methods

We evaluated the miRNA expression profiles in 1,083 breast cancer samples and 104 normal breast tissues from The Cancer Genome Atlas database. We used the edgeR package of R software to analyze the differentially expressed miRNAs in normal and cancer tissues, and screened survival-related miRNAs by Kaplan-Meier analysis. A receiver operating characteristic curve was generated to evaluate the accuracy of these miRNAs as molecular markers for breast cancer diagnosis. Furthermore, the functional role of these miRNAs was verified using cell experiments. Targets of candidate miRNAs were predicted using 9 online databases, and Gene Ontology (GO) functional annotation and pathway analyses were conducted using Database for Annotation, Visualization and Integrated Discovery online tool.

Results

A total of 68 miRNAs showed significantly different expression patterns between the groups (p < 0.001), and 13 of these miRNAs were significantly associated with poor survival (p < 0.05). Three miRNAs with high specificity and sensitivity, namely, miR-148b-3p, miR-190b, and miR-429, were selected. In vitro experiments showed that the overexpression of these 3 miRNAs significantly promoted the proliferation and migration of MDA-MB-468 and T47D cells and reduced the apoptosis of T47D cells. GO and pathway enrichment analyses revealed that the targets of these dysregulated miRNAs were involved in many critical cancer-related biological processes and pathways.

Conclusion

The miR-148b-3p, miR-190b, and miR-429 may serve as potential diagnostic and prognostic markers for breast cancer. This study demonstrated the roles of these 3 miRNAs in the initiation and progression of breast cancer.

ACE: A Workbench Using Evolutionary Genetic Algorithms for Analyzing Association in TCGA

Modern methods of acquiring molecular data have improved rapidly in recent years, making it easier for researchers to collect large volumes of information. However, this has increased the challenge of recognizing interesting patterns within the data. Atlas Correlation Explorer (ACE) is a user-friendly workbench for seeking associations between attributes in The Cancer Genome Atlas (TCGA) database. It allows any combination of clinical and genomic data streams to be searched using an evolutionary algorithm approach. To showcase ACE, we assessed which RNA sequencing transcripts were associated with estrogen receptor (ESR1) in the TCGA breast cancer cohort. The analysis revealed already well-established associations with XBP1 and FOXA1, but also identified a strong association with CT62, a potential immunotherapeutic target with few previous associations with breast cancer. In conclusion, ACE can produce results for very large searches in a short time and will serve as an increasingly useful tool for biomarker discovery in the big data era. SIGNIFICANCE: ACE uses an evolutionary algorithm approach to perform large searches for associations between any combinations of data in the TCGA database.

Circulating miRNAs as a marker of metastatic disease and prognostic factor in metastatic breast cancer

Background

Circulating miRNAs (miRs) are increasingly recognized as potential biomarkers in cancer. We aimed to evaluate the differential expression of miR-23b and miR-190 which are involved in tumor dormancy, miR-21 involved in metastasis and miR-200b and miR-200c involved in epithelial-mesenchymal transition (EMT) and metastasis, in the plasma of patients with early and metastatic breast cancer (MBC). We also aimed to identify associations of the expression levels with patient and disease characteristics and outcomes in metastatic patients treated with first-line chemotherapy.

Results

miR-21 (p < 0.001), miR-23b (p = 0.033), miR-200b (p < 0.001) and miR-200c (p < 0.001) expression was higher in metastatic compared to early breast cancer. ROC curve analysis showed that miR-21 (AUC = 0.722; p < 0.001) and miR-200b (AUC = 0.720; p < 0.001) distinguished with high accuracy among the two disease states, whereas the combination of miR-21, miR-190, miR-200b and miR-200c, further improved accuracy (AUC = 0.797; p < 0.001). High miR-200b expression independently predicted for shorter OS (p = 0.026) in MBC. High expression of both miR23b and miR-190 emerged as a strong independent factor associated with shorter PFS (p = 0.001) in de novo metastatic patients and high miR-200b independently predicted for decreased OS in the HER2-negative subgroup (p = 0.007).

Materials and Methods

Blood samples were obtained from patients with early (n = 133) and MBC (n = 110) before adjuvant or first-line chemotherapy, respectively. Plasma miRNA expression levels were assessed by RT-qPCR and were classified as high or low according to the median values.

Conclusions

Our results are in support of the concept that circulating miRNAs represent a tool with significant diagnostic and prognostic implications in breast cancer.

Identification of Disease-miRNA Networks Across Different Cancer Types Using SWIM

MicroRNAs (miRNAs) are small noncoding RNAs (ncRNAs) involved in several biological processes and diseases. MiRNAs regulate gene expression at the posttranscriptional level, mostly downregulating their targets by binding specific regions of transcripts through imperfect sequence complementarity. Prediction of miRNA-binding sites is challenging, and target prediction algorithms are usually based on sequence complementarity. In the last years, it has been shown that by adding miRNA and protein coding gene expression, we are able to build tissue-, cell line-, or disease-specific networks improving our understanding of complex biological scenarios. In this chapter, we present an application of a recently published software named SWIM, that allows to identify key genes in a network of interactions by defining appropriate "roles" of genes according to their local/global positioning in the overall network. Furthermore, we show how the SWIM software can be used to build miRNA-disease networks, by applying the approach to tumor data obtained from The Cancer Genome Atlas (TCGA).

Role of miRNA in the Regulatory Mechanisms of Estrogens in Cardiovascular Ageing

Cardiovascular diseases are a worldwide health problem and are the leading cause of mortality in developed countries. Together with experimental data, the lower incidence of cardiovascular diseases in women than in men of reproductive age points to the influence of sex hormones at the cardiovascular level and suggests that estrogens play a protective role against cardiovascular disease and that this role is also modified by ageing. Estrogens affect cardiovascular function via their specific estrogen receptors to trigger gene expression changes at the transcriptional level. In addition, emerging studies have proposed a role for microRNAs in the vascular effects mediated by estrogens. miRNAs regulate gene expression by repressing translational processes and have been estimated to be involved in the regulation of approximately 30% of all protein-coding genes in mammals. In this review, we highlight the current knowledge of the role of estrogen-sensitive miRNAs, and their influence in regulating vascular ageing.

regQTLs: Single nucleotide polymorphisms that modulate microRNA regulation of gene expression in tumors

Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with trait diversity and disease susceptibility, yet their functional properties often remain unclear. It has been hypothesized that SNPs in microRNA binding sites may disrupt gene regulation by microRNAs (miRNAs), short non-coding RNAs that bind to mRNA and downregulate the target gene. While several studies have predicted the location of SNPs in miRNA binding sites, to date there has been no comprehensive analysis of their impact on miRNA regulation. Here we investigate the functional properties of genetic variants and their effects on miRNA regulation of gene expression in cancer. Our analysis is motivated by the hypothesis that distinct alleles may cause differential binding (from miRNAs to mRNAs or from transcription factors to DNA) and change the expression of genes. We previously identified pathways—systems of genes conferring specific cell functions—that are dysregulated by miRNAs in cancer, by comparing miRNA–pathway associations between healthy and tumor tissue. We draw on these results as a starting point to assess whether SNPs on dysregulated pathways are responsible for miRNA dysregulation of individual genes in tumors. Using an integrative regression analysis that incorporates miRNA expression, mRNA expression, and SNP genotype data, we identify functional SNPs that we term “regulatory QTLs (regQTLs)”: loci whose alleles impact the regulation of genes by miRNAs. We apply the method to breast, liver, lung, and prostate cancer data from The Cancer Genome Atlas, and provide a tool to explore the findings.

Genomics studies have identified single nucleotide polymorphisms (SNPs) associated with trait diversity and disease susceptibility, yet the mechanism of action of many genetic variants remains unclear. MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that base-pair coding mRNAs to regulate gene transcription. We hypothesize that SNP variants may affect the ability of miRNAs to bind their target genes, thus influencing gene regulation. To identify these “regulatory QTLs” (regQTLs), we integrate miRNA expression, mRNA expression, and SNP data to identify miRNAs that are associated with pathway dysregulation in tumors, and assess whether SNPs on these pathways are responsible for disrupted miRNA-gene regulation. This data-driven approach enables the discovery of SNPs whose alleles impact gene regulation by miRNAs, with functional consequences for tumor biology. We detail the method, apply it to data from The Cancer Genome Atlas, and provide a tool to explore the findings.

Tree-based machine learning algorithms identified minimal set of miRNA biomarkers for breast cancer diagnosis and molecular subtyping

Breast cancer is a complex disease and its effective treatment needs affordable diagnosis and subtyping signatures. While the use of machine learning approach in clinical computation biology is still in its infancy, the prevalent approach in identifying molecular biomarkers remains to be screening of all biomarkers by differential expression analysis. Many of these attempts used miRNAs expression data in breast cancer and amounted to the multitude of differentially expressed miRNAs in this cancer; hence, the minimal set of miRNA biomarkers to classify breast cancer is yet to be identified. Availability of diverse and vast amount of cancer datasets like The Cancer Genome Atlas facilitated the molecular profiling of patients' tumors and introduced new challenges like clinical grade interpretations from big data. In this study, miRNA expression dataset of breast cancer patients from TCGA database was used to develop prediction models from which miRNA biomarkers were identified for diagnosis and molecular subtyping of this cancer. I took the advantage of interpretability of tree-based classification models to extract their rules and identify minimal set of biomarkers in this cancer. Empirical negative control miRNAs in breast cancer obtained and used to normalize the dataset. Tree-based machine learning models trained in my analysis used hsa-miR-139 with hsa-miR-183 to classify breast tumors from normal samples, and hsa-miR4728 with hsa-miR190b to further classify these tumors into three major subtypes of breast cancer. In addition to the proposed biomarkers, the most important miRNAs in breast cancer classification were also presented.

Nonredundant, Highly Connected MicroRNAs Control Functionality in Breast Cancer Networks

Alterations to transcriptional regulation are an important factor in breast cancer. Noncoding RNA, such as microRNA (miR), have very influential roles in the transcriptional regulation of genes. Transcriptional regulation can be successfully modeled and analyzed using complex network theory. Particularly, interactions between two distinct classes of biological elements, such as miR and genes, can be approached through the bipartite network formalism. Based on bipartite network properties, it is possible to identify highly influential miRs in the network, such as those that have a large number of connections indicating regulation of a large set of genes. Some miRs in a network are nonredundant, which indicates that they are solely responsible of the regulation of a particular set of genes, which in turn may be associated to a particular biological process. We hypothesize that highly influential, nonredundant miRs, which we call Commodore miRs (Cdre-miRs), have an important role on the control of biological functions through transcriptional networks. In this work, we analyze the regulation of gene expression by miRs in healthy and cancerous breast tissue using bipartite miR-gene networks inferred from the Cancer Genome Atlas (TCGA) expression data. We observe differences in the degree, clustering coefficient and redundancy distributions for miRs and genes in the network, indicating differences in the way that these elements interact with each other. Furthermore, we identify a small set of five Cdre-miRs in the breast cancer network: miR-190b, miR-let7i, miR-292-b, miR-511, and miR-141. The neighborhood of genes controlled by each of these miRs is involved in particular biological functions such as dynein structure-associated processes, immune response, angiogenesis, cytokine activity, and cell motility. We propose that these Cdre-miRs are important control elements of biological functions deregulated in breast cancer.

MicroRNA-190b regulates lipid metabolism and insulin sensitivity by targeting IGF-1 and ADAMTS9 in non-alcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is characterized by ectopic lipid accumulation and insulin resistance, yet the underlying molecular mechanisms are poorly understood. MiR-190b is thought to play a role in hepatocellular carcinoma by modulating insulin resistance; however, its role in NAFLD remains unknown. Here, we found that miR-190b expression was significantly increased in the liver tissues of patients with NAFLD, compared to normal tissues. Moreover, miR-190b was upregulated in a high-fat diet NAFLD mouse model and a free fatty acid-induced NAFLD cellular model. Knockdown of miR-190b decreased aspartate transaminase (AST), alanine transaminase (ALT), triglyceride (TG), and total cholesterol (TC). It also reduced expression of the lipogenic genes fatty acid synthase (FAS) and 3-hydroxy-3-methylglutarylCoA reductase (HMGCR), alleviated hepatic steatosis, improved glucose tolerance, elevated insulin sensitivity, and activated insulin receptor substrate (IRS)2/Akt signaling in vivo and/or in vitro. Furthermore, we confirmed that miR-190b directly targeted IGF-1 and ADAMTS9. MiR-190b overexpression suppressed expression of IGF-1 and ADAMTS9, which were increased by miR-190b inhibition. Expression of IGF-1 and ADAMTS9 was inversely correlated with miR-190b in liver tissues of patients with NAFLD, respectively. We also found that IGF-1 or ADAMTS9 inhibition partially reversed the effects of miR-190b on lipid metabolism and insulin signaling in vitro. Taken together, the data reveal that miR-190b inhibition suppressed lipid accumulation and improved insulin sensitivity by targeting IGF-1 and ADAMTS9, suggesting that miR-190b inhibition may be a therapeutic strategy against NAFLD.

Immunoglobulin superfamily genes are novel prognostic biomarkers for breast cancer

Breast cancer progression is associated with dysregulated expression of the immunoglobulin superfamily (IgSF) genes that are involved in cell-cell recognition, binding and adhesion. Despite widespread evidence that many IgSF genes could serve as effective biomarkers, this potential has not been realized because the studies have focused mostly on individual genes and not the entire network. To gain a global perspective of the IgSF-related biomarkers, we constructed an IgSF-directed neighbor network (IDNN) and an IgSF-directed driver network (IDDN) by integrating multiple levels of data, including IgSF genes, breast cancer driver genes, protein-protein interaction (PPI) networks and gene expression profiling data. Our study shows that IgSF genes in the PPI network have important topological features related to cancer. Most IgSF genes are either cancer driver genes themselves or associated with them. We also identified a 21-gene IgSF network module with enriched mutations that are associated with overall survival based on 450 breast cancer patient samples extracted from The Cancer Genome Atlas (TCGA) and multiple independent microarray validation datasets. These results highlight the potential of IgSF genes as novel diagnostic, prognostic and therapeutic targets for breast cancer.

miRNA as a New Regulatory Mechanism of Estrogen Vascular Action

The beneficial effects of estrogen on the cardiovascular system have been reported extensively. In fact, the incidence of cardiovascular diseases in women is lower than in age-matched men during their fertile stage of life, a benefit that disappears after menopause. These sex-related differences point to sexual hormones, mainly estrogen, as possible cardiovascular protective factors. The regulation of vascular function by estrogen is mainly related to the maintenance of normal endothelial function and is mediated by both direct and indirect gene transcription through the activity of specific estrogen receptors. Some of these mechanisms are known, but many remain to be elucidated. In recent years, microRNAs have been established as non-coding RNAs that regulate the expression of a high percentage of protein-coding genes in mammals and are related to the correct function of human physiology. Moreover, within the cardiovascular system, miRNAs have been related to physiological and pathological conditions. In this review, we address what is known about the role of estrogen-regulated miRNAs and their emerging involvement in vascular biology.

miRNA signatures can predict acute liver failure in hepatitis E infected pregnant females

Background

Acute viral hepatitis E (AVH-E) can often result in acute liver failure (ALF) during pregnancy. microRNAs serve as mediators in drug induced liver failure. We investigated their role as a biomarker in predicting ALF due to HEV (ALF-E).

Methods

We performed next generation sequencing and subsequent validation studies in PBMCs of pregnant (P) self limiting AVH-E, ALF due to HEV (ALF-E) and compared with AVH-E in non-pregnant (NP) females and healthy controls.

Findings

Eleven microRNAs were significantly expressed in response to HEV infection; importantly, miR- 431, 654, 1468 and 4435, were distinctly expressed in pregnant self-limiting AVH-E and healthy females (p = 0.0005), but not in ALF-E. Sixteen exclusive microRNAs differentiated ALF-E from self limiting AVH-E in pregnant females. miR-450b which affects cellular proliferation and metabolic processes through RNF20 and SECB was predominanlty upregulated and correlated with poor outcome (ROC 0.958, p = 0.001).

Interpretation

Our results reveal that a specific microRNA profile can predict fatality in ALF-E in pregnancy. These microRNAs could be exploited as prognostic biomarkers and help in the development of new therapeutic interventions.

Evaluation of microRNA Expression in Patients with Herpes Zoster

Reactivated varicella-zoster virus (VZV), which lies latent in the dorsal root ganglions and cranial nerves before its reactivation, is capable of causing herpes zoster (HZ), but the specific mechanism of virus reactivation and latency remains unknown. It was proposed that circulating microRNAs (miRNAs) in body fluids could potentially indicate infection. However, the connection between herpes zoster and circulating miRNAs has not been demonstrated. In this study, 41 HZ patients without superinfection were selected. The serum miRNA levels were analyzed by TaqMan low density array (TLDA) and confirmed individually by quantitative reverse transcription PCR (RT-qPCR) analysis. Thirty-five age-matched subjects without any infectious diseases or inflammation were selected as controls. The results showed that the serum miRNA expression profiles in 41 HZ patients were different from those of control subjects. Specifically, 18 miRNAs were up-regulated and 126 were down-regulated more than two-fold in HZ patients compared with controls. The subsequent confirmation of these results by qRT-PCR, as well as receiver operating characteristic (ROC) curve analysis, revealed that six kinds of miRNAs, including miR-190b, miR-571, miR-1276, miR-1303, miR-943, and miR-661, exhibited statistically significant enhanced expression levels (more than four-fold) in HZ patients, compared with those of healthy controls and herpes simplex virus (HSV) patients. Subsequently, it is proposed that these circulating miRNAs are capable of regulating numerous pathways and some may even participate in the inflammatory response or nervous system activity. This study has initially demonstrated that the serum miRNA expression profiles in HZ patients were different from those of uninfected individuals. Additionally, these findings also suggest that six of the altered miRNA could be potentially used as biomarkers to test for latent HZ infection.

Oestrogen receptor negativity in breast cancer: a cause or consequence?

Endocrine resistance, which occurs either by de novo or acquired route, is posing a major challenge in treating hormone-dependent breast cancers by endocrine therapies. The loss of oestrogen receptor α (ERα) expression is the vital cause of establishing endocrine resistance in this subtype. Understanding the mechanisms that determine the causes of this phenomenon are therefore essential to reduce the disease efficacy. But how we negate oestrogen receptor (ER) negativity and endocrine resistance in breast cancer is questionable. To answer that, two important approaches are considered: (1) understanding the cellular origin of heterogeneity and ER negativity in breast cancers and (2) characterization of molecular regulators of endocrine resistance. Breast tumours are heterogeneous in nature, having distinct molecular, cellular, histological and clinical behaviour. Recent advancements in perception of the heterogeneity of breast cancer revealed that the origin of a particular mammary tumour phenotype depends on the interactions between the cell of origin and driver genetic hits. On the other hand, histone deacetylases (HDACs), DNA methyltransferases (DNMTs), miRNAs and ubiquitin ligases emerged as vital molecular regulators of ER negativity in breast cancers. Restoring response to endocrine therapy through re-expression of ERα by modulating the expression of these molecular regulators is therefore considered as a relevant concept that can be implemented in treating ER-negative breast cancers. In this review, we will thoroughly discuss the underlying mechanisms for the loss of ERα expression and provide the future prospects for implementing the strategies to negate ER negativity in breast cancers.

How interacting pathways are regulated by miRNAs in breast cancer subtypes

BACKGROUND

An important challenge in cancer biology is to understand the complex aspects of the disease. It is increasingly evident that genes are not isolated from each other and the comprehension of how different genes are related to each other could explain biological mechanisms causing diseases. Biological pathways are important tools to reveal gene interaction and reduce the large number of genes to be studied by partitioning it into smaller paths. Furthermore, recent scientific evidence has proven that a combination of pathways, instead than a single element of the pathway or a single pathway, could be responsible for pathological changes in a cell.

RESULTS

In this paper we develop a new method that can reveal miRNAs able to regulate, in a coordinated way, networks of gene pathways. We applied the method to subtypes of breast cancer. The basic idea is the identification of pathways significantly enriched with differentially expressed genes among the different breast cancer subtypes and normal tissue. Looking at the pairs of pathways that were found to be functionally related, we created a network of dependent pathways and we focused on identifying miRNAs that could act as miRNA drivers in a coordinated regulation process.

CONCLUSIONS

Our approach enables miRNAs identification that could have an important role in the development of breast cancer.

Decoding the usefulness of non-coding RNAs as breast cancer markers

Although important advances in the management of breast cancer (BC) have been recently accomplished, it still constitutes the leading cause of cancer death in women worldwide. BC is a heterogeneous and complex disease, making clinical prediction of outcome a very challenging task. In recent years, gene expression profiling emerged as a tool to assist in clinical decision, enabling the identification of genetic signatures that better predict prognosis and response to therapy. Nevertheless, translation to routine practice has been limited by economical and technical reasons and, thus, novel biomarkers, especially those requiring non-invasive or minimally invasive collection procedures, while retaining high sensitivity and specificity might represent a significant development in this field. An increasing amount of evidence demonstrates that non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are aberrantly expressed in several cancers, including BC. miRNAs are of particular interest as new, easily accessible, cost-effective and non-invasive tools for precise management of BC patients because they circulate in bodily fluids (e.g., serum and plasma) in a very stable manner, enabling BC assessment and monitoring through liquid biopsies. This review focus on how ncRNAs have the potential to answer present clinical needs in the personalized management of patients with BC and comprehensively describes the state of the art on the role of ncRNAs in the diagnosis, prognosis and prediction of response to therapy in BC.

Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics

Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

miR-190 Enhances HIF-Dependent Responses to Hypoxia in Drosophila by Inhibiting the Prolyl-4-hydroxylase Fatiga

Cellular and systemic responses to low oxygen levels are principally mediated by Hypoxia Inducible Factors (HIFs), a family of evolutionary conserved heterodimeric transcription factors, whose alpha- and beta-subunits belong to the bHLH-PAS family. In normoxia, HIFα is hydroxylated by specific prolyl-4-hydroxylases, targeting it for proteasomal degradation, while in hypoxia the activity of these hydroxylases decreases due to low oxygen availability, leading to HIFα accumulation and expression of HIF target genes. To identify microRNAs required for maximal HIF activity, we conducted an overexpression screen in Drosophila melanogaster, evaluating the induction of a HIF transcriptional reporter. miR-190 overexpression enhanced HIF-dependent biological responses, including terminal sprouting of the tracheal system, while in miR-190 loss of function embryos the hypoxic response was impaired. In hypoxic conditions, miR-190 expression was upregulated and required for induction of HIF target genes by directly inhibiting the HIF prolyl-4-hydroxylase Fatiga. Thus, miR-190 is a novel regulator of the hypoxia response that represses the oxygen sensor Fatiga, leading to HIFα stabilization and enhancement of hypoxic responses.

miR-655 suppresses epithelial-to-mesenchymal transition by targeting Prrx1 in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype that lacks effective targeted therapies. The epithelial-to-mesenchymal transition (EMT) is a key contributor in the metastatic process. In this study, we found that miR-655 was down-regulated in TNBC, and its expression levels were associated with molecular-based classification and lymph node metastasis in breast cancer. These findings led us to hypothesize that miR-655 overexpression may inhibit EMT and its associated traits of TNBC. Ectopic expression of miR-655 not only induced the up-regulation of cytokeratin and decreased vimentin expression but also suppressed migration and invasion of mesenchymal-like cancer cells accompanied by a morphological shift towards the epithelial phenotype. In addition, we found that miR-655 was negatively correlated with Prrx1 in cell lines and clinical samples. Overexpression of miR-655 significantly suppressed Prrx1, as demonstrated by Prrx1 3'-untranslated region luciferase report assay. Our study demonstrated that miR-655 inhibits the acquisition of the EMT phenotype in TNBC by down-regulating Prrx1, thereby inhibiting cell migration and invasion during cancer progression.

Six Serum miRNAs Fail to Validate as Myotonic Dystrophy Type 1 Biomarkers

Myotonic dystrophy type 1 (DM1) is an autosomal dominant genetic disease caused by expansion of a CTG microsatellite in the 3' untranslated region of the DMPK gene. Despite characteristic muscular, cardiac, and neuropsychological symptoms, CTG trinucleotide repeats are unstable both in the somatic and germinal lines, making the age of onset, clinical presentation, and disease severity very variable. A molecular biomarker to stratify patients and to follow disease progression is, thus, an unmet medical need. Looking for a novel biomarker, and given that specific miRNAs have been found to be misregulated in DM1 heart and muscle tissues, we profiled the expression of 175 known serum miRNAs in DM1 samples. The differences detected between patients and controls were less than 2.6 fold for all of them and a selection of six candidate miRNAs, miR-103, miR-107, miR-21, miR-29a, miR-30c, and miR-652 all failed to show consistent differences in serum expression in subsequent validation experiments.