miRNA Biomarkers in Breast Cancer Detection and Management

BRCA Mutations and MicroRNA Expression Patterns in the Peripheral Blood of Breast Cancer Patients

Breast cancer (BC) persists as the predominant malignancy globally, standing as the foremost cause of cancer-related mortality among women. Despite notable advancements in prevention and treatment, encompassing the incorporation of targeted immunotherapies, a continued imperative exists for the development of innovative methodologies. These methodologies would facilitate the identification of women at heightened risk, enhance the optimization of therapeutic approaches, and enable the vigilant monitoring of emergent treatment resistance. Circulating microRNAs (miRNAs), found either freely circulating in the bloodstream or encapsulated within extracellular vesicles, have exhibited substantial promise for diverse clinical applications. These applications range from diagnostic and prognostic assessments to predictive purposes. This study aimed to explore the potential associations between BRCA mutations and specific miRNAs (miR-21, miR-155, miR-126, and miR-200c) expression that are known to be dysregulated in BC patient samples. Our findings indicate a robust correlation between miRNA expression status and disease subtypes. We found a correlation between the expression status of miRNAs and distinct disease subtypes. Intriguingly, however, no significant associations were discerned between disease status, subtypes, or miRNA expression levels and the presence of BRCA mutations. To advance the validation of miRNAs as clinically relevant biomarkers, additional investigations within larger and meticulously selected patient cohorts are deemed imperative. These microRNA entities hold the potential to emerge as groundbreaking and readily accessible tools, poised for seamless integration into the landscape of clinical practice.

MicroRNA signatures differentiate types, grades, and stages of breast invasive ductal carcinoma (IDC): miRNA-target interacting signaling pathways

BACKGROUND

Invasive ductal carcinoma (IDC) is the most common form of breast cancer which accounts for 85% of all breast cancer diagnoses. Non-invasive and early stages have a better prognosis than late-stage invasive cancer that has spread to lymph nodes. The involvement of microRNAs (miRNAs) in the initiation and progression of breast cancer holds great promise for the development of molecular tools for early diagnosis and prognosis. Therefore, developing a cost effective, quick and robust early detection protocol using miRNAs for breast cancer diagnosis is an imminent need that could strengthen the health care system to tackle this disease around the world.

METHODS

We have analyzed putative miRNAs signatures in 100 breast cancer samples using two independent high fidelity array systems. Unique and common miRNA signatures from both array systems were validated using stringent double-blind individual TaqMan assays and their expression pattern was confirmed with tissue microarrays and northern analysis. In silico analysis were carried out to find miRNA targets and were validated with q-PCR and immunoblotting. In addition, functional validation using antibody arrays was also carried out to confirm the oncotargets and their networking in different pathways. Similar profiling was carried out in Brca2/p53 double knock out mice models using rodent miRNA microarrays that revealed common signatures with human arrays which could be used for future in vivo functional validation.

RESULTS

Expression profile revealed 85% downregulated and 15% upregulated microRNAs in the patient samples of IDC. Among them, 439 miRNAs were associated with breast cancer, out of which 107 miRNAs qualified to be potential biomarkers for the stratification of different types, grades and stages of IDC after stringent validation. Functional validation of their putative targets revealed extensive miRNA network in different oncogenic pathways thus contributing to epithelial-mesenchymal transition (EMT) and cellular plasticity.

CONCLUSION

This study revealed potential biomarkers for the robust classification as well as rapid, cost effective and early detection of IDC of breast cancer. It not only confirmed the role of these miRNAs in cancer development but also revealed the oncogenic pathways involved in different progressive grades and stages thus suggesting a role in EMT and cellular plasticity during breast tumorigenesis per se and IDC in particular. Thus, our findings have provided newer insights into the miRNA signatures for the classification and early detection of IDC.

Exosomal microRNA-92b Is a Diagnostic Biomarker in Breast Cancer and Targets Survival-Related MTSS1L to Promote Tumorigenesis

Exosomal microRNAs (miRNAs) are novel, non-invasive biomarkers for facilitating communication and diagnosing cancer. However, only a few studies have investigated their function and role in the clinical diagnosis of breast cancer. To address this gap, we established a stable cell line, MDA-MB-231-CD63-RFP, and recruited 112 female participants for serum collection. We screened 88 exosomal miRNAs identified through microarray analysis of 231-CD63 and literature screening using real-time PCR; only exosomal miR-92b-5p was significantly increased in patients with breast cancer. It had a significant correlation with stage and discriminated patients from the control with an AUC of 0.787. Exosomal miR-92b-5p impacted the migration, adhesion, and spreading ability of normal human mammary epithelial recipient cells through the downregulation of the actin dynamics regulator MTSS1L. In clinical breast cancer tissue, the expression of MTSS1L was significantly inversely correlated with tissue miR-92b-5p, and high expression of MTSS1L was associated with better 10-year overall survival rates in patients undergoing hormone therapy. In summary, our studies demonstrated that exosomal miR-92b-5p might function as a non-invasive body fluid biomarker for breast cancer detection and provide a novel therapeutic strategy in the axis of miR-92b-5p to MTSS1L for controlling metastasis and improving patient survival.

MHESMMR: a multilevel model for predicting the regulation of miRNAs expression by small molecules

According to the expression of miRNA in pathological processes, miRNAs can be divided into oncogenes or tumor suppressors. Prediction of the regulation relations between miRNAs and small molecules (SMs) becomes a vital goal for miRNA-target therapy. But traditional biological approaches are laborious and expensive. Thus, there is an urgent need to develop a computational model. In this study, we proposed a computational model to predict whether the regulatory relationship between miRNAs and SMs is up-regulated or down-regulated. Specifically, we first use the Large-scale Information Network Embedding (LINE) algorithm to construct the node features from the self-similarity networks, then use the General Attributed Multiplex Heterogeneous Network Embedding (GATNE) algorithm to extract the topological information from the attribute network, and finally utilize the Light Gradient Boosting Machine (LightGBM) algorithm to predict the regulatory relationship between miRNAs and SMs. In the fivefold cross-validation experiment, the average accuracies of the proposed model on the SM2miR dataset reached 79.59% and 80.37% for up-regulation pairs and down-regulation pairs, respectively. In addition, we compared our model with another published model. Moreover, in the case study for 5-FU, 7 of 10 candidate miRNAs are confirmed by related literature. Therefore, we believe that our model can promote the research of miRNA-targeted therapy.

Invention of 3Mint for feature grouping and scoring in multi-omics

Advanced genomic and molecular profiling technologies accelerated the enlightenment of the regulatory mechanisms behind cancer development and progression, and the targeted therapies in patients. Along this line, intense studies with immense amounts of biological information have boosted the discovery of molecular biomarkers. Cancer is one of the leading causes of death around the world in recent years. Elucidation of genomic and epigenetic factors in Breast Cancer (BRCA) can provide a roadmap to uncover the disease mechanisms. Accordingly, unraveling the possible systematic connections between-omics data types and their contribution to BRCA tumor progression is crucial. In this study, we have developed a novel machine learning (ML) based integrative approach for multi-omics data analysis. This integrative approach combines information from gene expression (mRNA), microRNA (miRNA) and methylation data. Due to the complexity of cancer, this integrated data is expected to improve the prediction, diagnosis and treatment of disease through patterns only available from the 3-way interactions between these 3-omics datasets. In addition, the proposed method bridges the interpretation gap between the disease mechanisms that drive onset and progression. Our fundamental contribution is the 3 Multi-omics integrative tool (3Mint). This tool aims to perform grouping and scoring of groups using biological knowledge. Another major goal is improved gene selection via detection of novel groups of cross-omics biomarkers. Performance of 3Mint is assessed using different metrics. Our computational performance evaluations showed that the 3Mint classifies the BRCA molecular subtypes with lower number of genes when compared to the miRcorrNet tool which uses miRNA and mRNA gene expression profiles in terms of similar performance metrics (95% Accuracy). The incorporation of methylation data in 3Mint yields a much more focused analysis. The 3Mint tool and all other supplementary files are available at https://github.com/malikyousef/3Mint/.

Predicting miRNA-Disease Association Based on Improved Graph Regression

Recently, as a growing number of associations between microRNAs (miRNAs) and diseases are discovered, researchers gradually realize that miRNAs are closely related to several complicated biological processes and human diseases. Hence, it is especially important to construct availably models to infer associations between miRNAs and diseases. In this study, we presented Improved Graph Regression for miRNA-Disease Association Prediction (IGRMDA) to observe potential relationship between miRNAs and diseases. In order to reduce the inherent noise existing in the acquired biological datasets, we utilized matrix decomposition algorithm to process miRNA functional similarity and disease semantic similarity and then combining them with existing similarity information to obtain final miRNA similarity data and disease similarity data. Then, we applied miRNA-disease association data, miRNA similarity data and disease similarity data to form corresponding latent spaces. Furthermore, we performed improved graph regression algorithm in latent spaces, which included miRNA-disease association space, miRNA similarity space and disease similarity space. Non-negative matrix factorization and partial least squares were used in the graph regression process to obtain important related attributes. The cross validation experiments and case studies were also implemented to prove the effectiveness of IGRMDA, which showed that IGRMDA could predict potential associations between miRNAs and diseases.

Integrated Tissue and Blood miRNA Expression Profiles Identify Novel Biomarkers for Accurate Non-Invasive Diagnosis of Breast Cancer: Preliminary Results and Future Clinical Implications

We aimed to identify miRNAs that were closely related to breast cancer (BRCA). By integrating several methods including significance analysis of microarrays, fold change, Pearson’s correlation analysis, t test, and receiver operating characteristic analysis, we developed a decision-tree-based scoring algorithm, called Optimized Scoring Mechanism for Primary Synergy MicroRNAs (O-PSM). Five synergy miRNAs (hsa-miR-139-5p, hsa-miR-331-3p, hsa-miR-342-5p, hsa-miR-486-5p, and hsa-miR-654-3p) were identified using O-PSM, which were used to distinguish normal samples from pathological ones, and showed good results in blood data and in multiple sets of tissue data. These five miRNAs showed accurate categorization efficiency in BRCA typing and staging and had better categorization efficiency than experimentally verified miRNAs. In the Protein-Protein Interaction (PPI) network, the target genes of hsa-miR-342-5p have the most regulatory relationships, which regulate carcinogenesis proliferation and metastasis by regulating Glycosaminoglycan biosynthesis and the Rap1 signaling pathway. Moreover, hsa-miR-342-5p showed potential clinical application in survival analysis. We also used O-PSM to generate an R package uploaded on github (SuFei-lab/OPSM accessed on 22 October 2021). We believe that miRNAs included in O-PSM could have clinical implications for diagnosis, prognostic stratification and treatment of BRCA, proposing potential significant biomarkers that could be utilized to design personalized treatment plans in BRCA patients in the future.

Regulation of mitochondrial fusion and mitophagy by intra-tumoral delivery of membrane-fused mitochondria or Midiv-1 enhances sensitivity to doxorubicin in triple-negative breast cancer

Increasing mitochondrial fusion by intra-tumoral grafting of membrane-fused mitochondria created with Pep-1 conjugation (P-Mito) contributes to breast cancer treatment, but it needs to be validated. Using mitochondrial division inhibitor-1 (Mdivi-1, Mdi) to disturb mitochondrial dynamics, we showed that the antitumor action of P-Mito in a mouse model of triple-negative breast cancer depends upon mitochondrial fusion and that Mdi treatment alone is ineffective. P-Mito significantly enhanced Doxorubicin (Dox) sensitivity by inducing mitochondrial fusion and mitophagy, and the same efficiency was also achieved with Mdi by inhibiting mitophagy. Cell death was induced via the p53 pathway and AIF nuclear translocation in the case of P-Mito, versus the caspase-dependent pathway for Mdi. Notably, both mitochondrial treatments reduced oxidative stress and blood vessel density of xenograft tumors, especially P-Mito, which was accompanied by inhibition of nuclear factor kappa-B activation. Furthermore, through enrichment analysis, four microRNAs in serum microvesicles induced by P-Mito caused expression of predicted targets via the PI3K-Akt pathway, and significantly impacted regulation of nuclear processes and myeloid cell differentiation. Clustering of gene-sets implicated a major steroid catabolic network. This study showed diverse roles of mitochondria in breast cancer and revealed effective adjuvant therapy targeting mitochondrial fusion and mitophagy.

Epigenomic interplay in tumor heterogeneity: Potential of epidrugs as adjunct therapy

"Heterogeneity" in tumor mass has immense importance in cancer progression and therapy. The impact of tumor heterogeneity is an emerging field and not yet fully explored. Tumor heterogeneity is mainly considered as intra-tumor heterogeneity and inter-tumor heterogeneity based on their origin. Intra-tumor heterogeneity refers to the discrepancy within the same cancer mass while inter-tumor heterogeneity refers to the discrepancy between different patients having the same tumor type. Both of these heterogeneity types lead to variation in the histopathological as well as clinical properties of the cancer mass which drives disease resistance towards therapeutic approaches. Cancer stem cells (CSCs) act as pinnacle progenitors for heterogeneity development along with various other genetic and epigenetic parameters that are regulating this process. In recent times epigenetic factors are one of the most studied parameters that drive oxidative stress pathways essential during cancer progression. These epigenetic changes are modulated by various epidrugs and have an impact on tumor heterogeneity. The present review summarizes various aspects of epigenetic regulation in the tumor microenvironment, oxidative stress, and progression towards tumor heterogeneity that creates complications during cancer treatment. This review also explores the possible role of epidrugs in regulating tumor heterogeneity and personalized therapy against drug resistance.

MDSCMF: Matrix Decomposition and Similarity-Constrained Matrix Factorization for miRNA–Disease Association Prediction

MicroRNAs (miRNAs) are small non-coding RNAs that are related to a number of complicated biological processes, and numerous studies have demonstrated that miRNAs are closely associated with many human diseases. In this study, we present a matrix decomposition and similarity-constrained matrix factorization (MDSCMF) to predict potential miRNA–disease associations. First of all, we utilized a matrix decomposition (MD) algorithm to get rid of outliers from the miRNA–disease association matrix. Then, miRNA similarity was determined by utilizing similarity kernel fusion (SKF) to integrate miRNA function similarity and Gaussian interaction profile (GIP) kernel similarity, and disease similarity was determined by utilizing SKF to integrate disease semantic similarity and GIP kernel similarity. Furthermore, we added L₂ regularization terms and similarity constraint terms to non-negative matrix factorization to form a similarity-constrained matrix factorization (SCMF) algorithm, which was applied to make prediction. MDSCMF achieved AUC values of 0.9488, 0.9540, and 0.8672 based on fivefold cross-validation (5-CV), global leave-one-out cross-validation (global LOOCV), and local leave-one-out cross-validation (local LOOCV), respectively. Case studies on three common human diseases were also implemented to demonstrate the prediction ability of MDSCMF. All experimental results confirmed that MDSCMF was effective in predicting underlying associations between miRNAs and diseases.

Mapping Research on miRNAs in Cancer: A Global DataAnalysis and Bibliometric Profiling Analysis

miRNAs biomarkers are emerging as an essential part of clinical oncology. Their oncogenic and tumour suppressor properties playing a role in malignancy has generated interest in their potential for use in disease prognosis. While several studies on miRNA have been carried out across the globe, evaluating the clinical implications of miRNAs in cancer diagnosis and prognosis research has currently not been attempted. A study delineating the area of miRNA research, including the topics presently being focused on, the seminal papers in this field, and the direction of research interest, does not exist. This study aims to conduct a large-scale, global data analysis and bibliometric profiling analysis of studies to evaluate the research output of clinical implications of miRNAs in cancer diagnosis and prognosis listed in the SCOPUS database. A systematic search strategy was followed to identify and extract all relevant studies, subsequently analysed to generate a bibliometric map. SPSS software (version 27) was used to calculate bibliometric indicators or parameters for analysis, such as year and country of affiliation with leading authors, journals, and institutions. It is also used to analyse annual research outputs, including total citations and the number of times it has been cited with productive nations and H-index. The number of global research articles retrieved for miRNA-Cancer research over the study period 2003 to 2019 was 18,636. Between 2012 and 2019, the growth rate of global publications is six times (n = 15,959; 90.71 percent articles) that of 2003 to 2011. (2704; 9.29 per cent articles). China published the most publications in the field of miRNA in cancer (n = 7782; 41%), while the United States had the most citations (n = 327,538; 48%) during the time span. Of these journals, Oncotarget has the highest percentage of article publications. The journal Cancer Research had the most citations (n = 41,876), with 6.20 per cent (n = 41,876). This study revealed a wide variety of journals in which miRNA-Cancer research are published; these bibliometric parameters exhibit crucial clinical information on performance assessment of research productivity and quality of research output. Therefore, this study provides a helpful reference for clinical oncologists, cancer scientists, policy decision-makers and clinical data researchers.

Molecular and docking studies of tetramethoxy hydroxyflavone compound from Artemisia absinthium against carcinogens found in cigarette smoke

Artemisia absinthium (AA) is an indigenous medicine used for treatment of inflammation of the liver and chronic fever, and is studied as an antimalarial and anticancer agent. The focus of the current investigation was to determine the action and effect of AA on microRNAs (miRNAs) from breast cancer cell lines. Molecular docking is a structure-based drug design process that studies the interaction of small molecule ligands with receptor biomacromolecules to predict binding mechanism and affinity. MiRNA expression profiling was done using microarray technology. Validation of transcripts with regulated expression pattern was done by SYBR-based quantitative real time PCR (qRT-PCR). AutoDock 4.2 programming allots polar hydrogens, bound together total Kollman charges, solvation borders, and fragmental volumes to the protein using auto dock devices in docking research (ADT). As confirmed by SYBR-based RT-PCR, our investigation discovered an upregulation of the miRNA-22 articulation and a downregulation of miRNA-199a*. These findings support and demonstrate the role of AA as a miRNA articulation-influencing factor in human breast cancer progression. AA’s tetramethoxy hydroxyflavone (p7F) molecule was found to be effective in the treatment of cancer. Changes in miRNA expression patterns could be a key pathogenic component in AA’s physiological action on cancer cells.

MicroRNAs Role in Breast Cancer: Theranostic Application in Saudi Arabia

Breast cancer is an aggressive silent disease, representing 11.7% of the diagnosed cancer worldwide, and it is also a leading cause of death in Saudi Arabia. Consequently, microRNAs have emerged recently as potential biomarkers to diagnose and monitor such cases at the molecular level, which tends to be problematic during diagnosis. MicroRNAs are highly conserved non- coding oligonucleotide RNA. Over the last two decades, studies have determined the functional significance of these small RNAs and their impact on cellular development and the interaction between microRNAs and messenger RNAs, which affect numerous molecular pathways and physiological functions. Moreover, many disorders, including breast cancer, are associated with the dysregulation of microRNA. Sparingly, many microRNAs can suppress cancer cell proliferation, apoptosis, angiogenesis, invasion, metastasis, and vice versa. Remarkably, microRNAs can be harvested from patients’ biofluids to predict disease progression that considered a non-invasive method. Nevertheless, MicroRNAs are currently utilized as anti- cancer therapies combined with other drug therapies or even as a single agents’ treatment. Therefore, this review will focus on microRNAs’ role in breast cancer as an indicator of disease progression. In addition, this review summarizes the current knowledge of drug sensitivity and methods in detecting microRNA and their application to improve patient care and identifies the current gaps in this field.

ILPMDA: Predicting miRNA-Disease Association Based on Improved Label Propagation

MicroRNAs (miRNAs) are small non-coding RNAs that have been demonstrated to be related to numerous complex human diseases. Considerable studies have suggested that miRNAs affect many complicated bioprocesses. Hence, the investigation of disease-related miRNAs by utilizing computational methods is warranted. In this study, we presented an improved label propagation for miRNA-disease association prediction (ILPMDA) method to observe disease-related miRNAs. First, we utilized similarity kernel fusion to integrate different types of biological information for generating miRNA and disease similarity networks. Second, we applied the weighted k-nearest known neighbor algorithm to update verified miRNA-disease association data. Third, we utilized improved label propagation in disease and miRNA similarity networks to make association prediction. Furthermore, we obtained final prediction scores by adopting an average ensemble method to integrate the two kinds of prediction results. To evaluate the prediction performance of ILPMDA, two types of cross-validation methods and case studies on three significant human diseases were implemented to determine the accuracy and effectiveness of ILPMDA. All results demonstrated that ILPMDA had the ability to discover potential miRNA-disease associations.

An overview on breast cancer genetics and recent innovations: Literature survey

Breast cancer is one of the leading cancers nowadays. The genetical mechanism behind breast cancer development is an intricate one. In this review, the genetical background of breast cancer, particularly BRCA 1 and BRCA 2 had been included. Moreover, to summarize the genetics of breast cancer, the recent and ongoing preclinical and clinical studies on the treatment of BRCA-associated breast cancer had also been included. A prime knowledge is that the BRCA gene is the basis of breast cancer risk. How it mediates cell proliferation and associated mechanisms are reviewed here. BRCA 1 gene can influence all phases of the cell cycle and regulate cell cycle progression. BRCA 1 gene can also respond to DNA damages and induce responsive mechanisms. The action of the BRCA gene on associated protein has a wide consideration in breast cancer development. Heterogeneity in breast cancer makes them a fascinating and challenging stream to diagnose and treat. Several clinical therapies are available for breast cancer treatments. Chemotherapy, endocrine therapy, radiation therapy and immunotherapy are the milestones in the cancer treatments. Ral binding protein 1 is a promising target for breast cancer treatment and the platinum-based chemotherapies are the other remarkable fields. In immunotherapy, the usage of anti-programmed death (PD)-1 antibody is a new class of cancer immunotherapy that hinders immune effecter inhibition and potentially expanding preexisting anticancer immune responses. Breast cancer genetics and treatment strategies are crucial in escalating survival rates.

Early detection breast cancer: role of circulating plasma miRNA-21 expression as a potential screening biomarker

Aim

To explore the potential of the circulating plasma miRNA-21 as an early detection biomarker by comparing early-stage breast cancer (BG) and healthy control (HG) in Indonesian population.

Materials and methods

The enlisted patients were 26 adult female early-stage breast cancer patients (stage 1A, 1B, 2A, and 2B) of Airlangga University Hospital from August 2019 to October 2019. Sixteen volunteers were recruited as matching healthy subjects. MiRNA-21 expression was quantified by plasma qRT-PCR. Data analysis performed using IBM SPSS Statistics v.24 (IBM Corp., Armonk, NY, USA). MiRNA-21 cut-off, sensitivity, and specificity were analyzed using receiver operating characteristic (ROC) curve.

Results

The study included 26 BG and 16 HG subjects. The miRNA-21 expression in BG group was 3.933 (1.181-11.794) and 0.905 (0.164-4.532) in HG group (4.34 folds; P = 0.001), with 1.66 cut-off (92.3% sensitivity; 81.2% specificity). MiRNA-21 expression separated analysis in HG showed a 0.578 times lower expression in menopause subjects [0.651 (0.164-0.414)], compared to premenopause ones [(1.123 (0.758 - 4.532); P = 0.031]. Yet, in BG group, 1.729 times higher miRNA-21 expression was observed in menopause subjects (6.021 ± 3.583), compared to premenopause ones (3.500 ± 1.517; P = 0.022).

Conclusions

Circulating miRNA-21 expression is a potential biomarker for early detection of breast cancer and might act as a breast cancer risk predictor.

CEA, CA 15-3, and miRNA expression as potential biomarkers in canine mammary tumors

The most often detected tumor in intact bitches is mammary tumors and represents a significant clinical problem throughout the world. Mammary neoplasms in canine have heterogeneous morphology, so the choice of the most appropriate biomarker is the biggest challenge in CMT detection. We performed a retrospective analysis and evaluated the canine cancer antigens and miRNA expression profiles as potential biomarkers. Sixty dogs based on histological examination divided into three groups, viz., dogs with a benign mammary tumor, malignant mammary tumor, and control/healthy. The CA 15-3 was found more sensitive than CEA but detection of both will increase sensitivity. miR-21 expression differed significantly in all three groups. miR-29b expression differed significantly between the control and benign group and control and malignant group. The miR-21 overexpression and miR-29b downregulation with CMT are associated with clinical stage and can be used as non-invasive diagnostic and prognostic biomarkers. Hence, evaluation of CA 15-3 along with CEA would be a non-invasive technique for detecting canine mammary tumors. Evaluation of deregulated circulating miR-21 could be a valuable prognostic marker for early detection of mammary tumors in canines while miR-29b can add sensitivity in the detection of the canine mammary tumors if evaluated with miR-21.

SNFIMCMDA: Similarity Network Fusion and Inductive Matrix Completion for miRNA-Disease Association Prediction

MicroRNAs (miRNAs) that belong to non-coding RNAs are verified to be closely associated with several complicated biological processes and human diseases. In this study, we proposed a novel model that was Similarity Network Fusion and Inductive Matrix Completion for miRNA-Disease Association Prediction (SNFIMCMDA). We applied inductive matrix completion (IMC) method to acquire possible associations between miRNAs and diseases, which also could obtain corresponding correlation scores. IMC was performed based on the verified connections of miRNA-disease, miRNA similarity, and disease similarity. In addition, miRNA similarity and disease similarity were calculated by similarity network fusion, which could masterly integrate multiple data types to obtain target data. We integrated miRNA functional similarity and Gaussian interaction profile kernel similarity by similarity network fusion to obtain miRNA similarity. Similarly, disease similarity was integrated in this way. To indicate the utility and effectiveness of SNFIMCMDA, we both applied global leave-one-out cross-validation and five-fold cross-validation to validate our model. Furthermore, case studies on three significant human diseases were also implemented to prove the effectiveness of SNFIMCMDA. The results demonstrated that SNFIMCMDA was effective for prediction of possible associations of miRNA-disease.

GPER1 and microRNA: Two Players in Breast Cancer 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.

A review of clinical and emerging biomarkers for breast cancers: towards precision medicine for patients

Background:

Breast cancer is the most commonly diagnosed malignancy among women and accounts for about 25% of all new cancer cases and 13% of all cancer deaths in Canadian women. It is a highly heterogeneous disease, encompassing multiple tumour entities, each characterised by distinct morphology, behaviour and clinical implications. Moreover, different breast tumour subtypes have different risk factors, clinical presentation, histopathological features, outcome and response to systemic therapies. Therefore, any strategies capable of the stratification of breast cancer by clinically relevant subtypes are an important requirement for personalised and targeted treatment. Therefore, in the advancement towards the concept of precision medicine that takes individual patient variability into account, several investigators have focused on the identification of effective clinical breast cancer biomarkers that interrogate key aberrant pathways potentially targetable with molecular targeted or immunological therapies.

Methods and materials:

This paper reports on a review of 11 current clinical and emerging biomarkers used in screening for early detection and diagnosis, to stratify patients by disease subtype, to identify patients’ risk for metastatic disease and subsequent relapse, to monitor patient response to specific treatment and to provide clinicians the possibility of prospectively identifying groups of patients who will benefit from a particular treatment.

Conclusion:

The future holds promising for the use of effective clinical breast cancer biomarkers for early detection and personalised patient-specific targeted treatment and increased patient survival. Breast cancer biomarkers can potentially assist in early-staged, non-invasive, sensitive and specific breast cancer detection and screening, provide clinically useful information for identification of patients with a greater likelihood of benefiting from the specific treatment, offer a better understanding of the metastatic process in cancer patients, predict disease and for patients with the established disease can assist define the nature of the disease, monitor the success of treatment and guide the clinical management of the disease.

microRNA Expression Profile in Single Hormone Receptor-Positive Breast Cancers is Mainly Dependent on HER2 Status-A Pilot Study

Estrogen (ER) and progesterone (PgR) receptors and HER2 are crucial in the assessment of breast cancer specimens due to their prognostic and predictive significance. Single hormone receptor-positive breast cancers are less common and their clinical course is less favorable than ER(+)/PgR(+) tumors. Their molecular features, especially microRNA (miRNA) profiles, have not been investigated to date. Tumor specimens from 36 chemonaive breast cancer patients with known ER and PgR status (18 ER(+)/PgR(−) and 18 ER(−)/PgR(+) cases) were enrolled to the study. The expression of 829 miRNAs was evaluated with nCounter Human v3 miRNA expression Assay (NanoString). miRNAs differentiating between ER/PgR/HER2 phenotypes were selected based on fold change (FC) calculated for the mean normalized counts of each probe in compared groups. The differences were estimated with Student’s t-test or Two-Way ANOVA (considering also the HER2 status). The results were validated using The Cancer Genome Atlas (TCGA) dataset. Following quality control of raw data, fourcases were excluded due to low sample quality, leaving 14 ER(+)/PgR(−) and 18 ER(−)/PgR(+) cases. After correction for multiple comparisons, we did not find miRNA signature differentiating between ER(−)/PgR(+) and ER(+)/PgR(−) breast cancers. However, a trend for differing expression (p-value ≤ 0.05; FDR > 0.2; ANOVA) in eight miRNAs was observed. The ER(+)/PgR(−) group demonstrated elevated levels of four miRNAs—miR-30a-5p, miR-29c-3p, miR-141-3p and miR-423-5p—while the ER(−)/PgR(+) tumors were enriched in another four miRNAs—miR-514b-5p, miR-424-5p, miR-495-3p, and miR-92a-3p. For one of the miRNAs—miR-29c-3p—the association with the ER(+)/PgR(−) phenotype was confirmed in the TCGA cohort (p-value = 0.024; t-test). HER2 amplification/overexpression in the NanoString cohort was related to significant differences observed in 33 miRNA expression levels (FDR ≤ 0.2; ANOVA). The association with HER2 status was confirmed in the TCGA cohort for four miRNAs (miR-1180-3p, miR-223-3p, miR-30d-5p, and miR-195-5p). The main differences in miRNA expression amongst single hormone receptor-positive tumors were identified according to their HER2 status. However, ER(+)/PgR(−) cases tended to express higher levels of miRNAs associated with ER-positivity (miR-30a-5p, miR-29c-3p, miR-141-3p), whereas ER(−)/PgR(+) cancers showed elevated levels of miRNAs characteristic for double- and triple-negative tumors (miR-92a-3p, miR-424-5p). Further studies are necessary to comprehensively analyze miRNA signatures characteristic of ER(−)/PgR(+) and ER(+)/PgR(−) tumors.

MicroRNA-4500 Inhibits Migration, Invasion, and Angiogenesis of Breast Cancer Cells via RRM2-Dependent MAPK Signaling Pathway

With the consideration of the dynamic role of microRNAs (miRNAs) in breast cancer, miRNAs may serve as therapeutic targets, helping to prevent development of therapy resistance, maintain stable disease, and prohibit metastatic spread. We identified the differentially expressed breast cancer-related gene ribonucleotide reductase subunit M2 (RRM2) as the study focus through microarray expression profiles. Next, the upstream regulatory microRNA (miR)-4500 of RRM2 was predicted using bioinformatics website analysis, and their binding was verified by a dual luciferase reporter gene assay. The regulatory effects of miR-4500 on breast cancer cell proliferation, apoptosis, migration, invasion, and capillary-like tube formation of endothelial cells were assessed by gain- and loss-of-function experiments. The experimental data revealed that miR-4500 was downregulated, whereas RRM2 was upregulated in breast cancer cells. Mechanistic analysis revealed that miR-4500 downregulated the RRM2 expression to inactivate the mitogen-activated protein kinase (MAPK) signaling pathway. Furthermore, miR-4500 exerted anti-tumor effects by targeting RRM2 through suppression of the MAPK signaling pathway in vitro, evidenced by attenuated cancer cell migration and invasion and capillary-like tube formation of endothelial cells. The in vivo experiments further corroborated in vitro results. Collectively, overexpressed miR-4500 could downregulate RRM2 and inhibit activation of the MAPK signaling pathway, thus attenuating breast cancer cell proliferation, invasion, migration, and angiogenesis and promoting breast cancer cell apoptosis.

Label-free characterization of different kinds of cells using optoelectrokinetic-based microfluidics

We report a novel, to the best of our knowledge, method to rapidly characterize different kinds of cells and drug-treated cancer cells using a label-free biomarker of self-rotation in an optoelectrokinetics (OEK)-based microfluidic platform. OEK incorporates optics and electrokinetics into microfluidics, thereby offering a contact-free, label-free, and rapid approach to the cellular manipulation community. Self-rotational behaviors of four different kinds of cells were experimentally investigated by the frequency-sweeping of an AC bias potential in an optically induced nonuniform and irrotational electric field. The results revealed that these kinds of cells displayed a Gaussian distribution versus the AC frequency as well as different self-rotational speeds under the same conditions. Furthermore, the peak self-rotational speed varied from one kind of cell to another, with that of cancer cells higher than that of normal cells. In addition, MCF-7 cells treated by various concentrations of drug showed remarkably different self-rotational speeds. This finding suggests a high potential of developing a new label-free biomarker to rapidly distinguish different kinds of cancer cells and quantitatively monitor the response of cancer patients to various treatments.

Genome wide identification, characterization and validation of novel miRNA-based SSR markers in pomegranate (Punica granatum L.)

A total of 17,439 mature miRNAs (~ 21 nt) earlier generated through RNA seq in the pomegranate were used for in silico analysis. After complexity reduction, a total of 1922 representative mature miRNAs were selected and used as query sequences against pomegranate genome to retrieve 2540 homologous contigs with flanking regions (~ 800). By using pre-miRNA prediction web server, a total of 1028 true contigs harbouring pri-miRNAs encoding 1162 pre-miRNAs were identified. Survey of these sequences for SSRs yielded a total of 1358 and 238 SSRs specific to pri-miRNA and pre-miRNAs, respectively. Of these, primer pairs were designed for 897 pri-miRNA and 168 pre-miRNA SSRs. In pri-miRNA sequences, hexa-nucleotides repeats were found to be most abundant (44.18%) followed by mono- (18.41%) and di-nucleotide (17.01%), which is also observed in pre-miRNA sequences. Further, a set of 51 randomly selected pre-miRNA-SSRs was examined for marker polymorphism. The experimental validation of these markers on eight pomegranate genotypes demonstrated 92.15% polymorphism. Utility of these functional markers was confirmed via examination of genetic diversity of 18 pomegranate genotypes using 15 miRNA-SSRs. Further, potential application of miRNA-SSRs for discovery of trait specific candidate genes was showed by validating 51 mature miRNA against publically available 2047 EST sequences of pomegranate by target and network analysis. In summary, the current study offers novel functional molecular markers for pomegranate genetic improvement.

MicroRNA-326 Functions as a Tumor Suppressor in Breast Cancer by Targeting ErbB/PI3K Signaling Pathway

Breast cancer represents the most common malignancy in women worldwide and the ErbB/PI3K pathway has been found to play a crucial role in regulation of the cancer cell growth. MicroRNAs have been implicated in regulating diverse cellular pathways and therefore, understanding the link between the regulatory microRNAs and the ErbB/PI3K signaling pathway could potentially be helpful for breast cancer prevention and treatment. The aim of this study is to examine the regulatory effect of miR-326 on ErbB/PI3K signaling pathway in breast cancer development and progression. The results of qRT-PCR, RNA seq, and array data indicated that miR-326 was remarkably down-regulated in breast tumor tissues and correlated with poor survival outcome. Importantly, very low levels of miR-326 expression were found in aggressive breast cells compared to less-aggressive cell types. Mechanistically, a gene network including EGFR, ErbB2, ErbB3, AKT1, AKT2, and AKT3 targeted by miR-326, thereby providing suppression of ErbB/PI3K pathway, detected by RT-qPCR, and dual luciferase assay. In addition, Western blot analysis revealed that miR-326 upregulation decreased PI3K signaling activity by decreasing total AKT and p-AKT protein level in SKBR3 cell lines. Interestingly, up regulation of ErbB2 rescued the effect of miR-326 on miR-326 target genes. Further functional assays demonstrated that up regulation of miR-326 significantly suppressed cell growth as evidenced by cell cycle, cell cycle associated genes expression, colony formation and MTT assays and induced apoptosis, detected by Annexin V-PI. In addition, EMT markers RT-qPCR, scratch, and Transwell assays showed inhibited cellular migration and invasion following miR-326 upregulation. Altogether, our results revealed that miR-326 play a tumor-suppressive role in breast cancer through inhibiting ErbB/PI3K pathway and miR-326 may serve as a potential therapeutic target for the treatment of patients with breast cancer.

Validation of miRNAs as Breast Cancer Biomarkers with a Machine Learning Approach

Certain small noncoding microRNAs (miRNAs) are differentially expressed in normal tissues and cancers, which makes them great candidates for biomarkers for cancer. Previously, a selected subset of miRNAs has been experimentally verified to be linked to breast cancer. In this paper, we validated the importance of these miRNAs using a machine learning approach on miRNA expression data. We performed feature selection, using Information Gain (IG), Chi-Squared (CHI2) and Least Absolute Shrinkage and Selection Operation (LASSO), on the set of these relevant miRNAs to rank them by importance. We then performed cancer classification using these miRNAs as features using Random Forest (RF) and Support Vector Machine (SVM) classifiers. Our results demonstrated that the miRNAs ranked higher by our analysis had higher classifier performance. Performance becomes lower as the rank of the miRNA decreases, confirming that these miRNAs had different degrees of importance as biomarkers. Furthermore, we discovered that using a minimum of three miRNAs as biomarkers for breast cancers can be as effective as using the entire set of 1800 miRNAs. This work suggests that machine learning is a useful tool for functional studies of miRNAs for cancer detection and diagnosis.

Single-Step Incubation Determination of miRNAs in Cancer Cells Using an Amperometric Biosensor Based on Competitive Hybridization onto Magnetic Beads

This work reports an amperometric biosensor for the determination of miRNA-21, a relevant oncogene. The methodology involves a competitive DNA-target miRNA hybridization assay performed on the surface of magnetic microbeads (MBs) and amperometric transduction at screen-printed carbon electrodes (SPCEs). The target miRNA competes with a synthetic fluorescein isothiocyanate (FITC)-modified miRNA with an identical sequence for hybridization with a biotinylated and complementary DNA probe (b-Cp) immobilized on the surface of streptavidin-modified MBs (b-Cp-MBs). Upon labeling, the FITC-modified miRNA attached to the MBs with horseradish peroxidase (HRP)-conjugated anti-FITC Fab fragments and magnetic capturing of the MBs onto the working electrode surface of SPCEs. The cathodic current measured at −0.20 V (versus the Ag pseudo-reference electrode) was demonstrated to be inversely proportional to the concentration of the target miRNA. This convenient biosensing method provided a linear range between 0.7 and 10.0 nM and a limit of detection (LOD) of 0.2 nM (5 fmol in 25 μL of sample) for the synthetic target miRNA without any amplification step. An acceptable selectivity towards single-base mismatched oligonucleotides, a high storage stability of the b-Cp-MBs, and usefulness for the accurate determination of miRNA-21 in raw total RNA (RNA_t) extracted from breast cancer cells (MCF-7) were demonstrated.

ATF-3/miR-590/GOLPH3 signaling pathway regulates proliferation of breast cancer

Background

Breast cancer is one of the leading causes of death in women worldwide. Fast growth is the important character of breast cancer, which makes sure the subsequent metastasize and invasion breast cancer. Golgi related genes GOLPH3 has been reported to regulate many kinds of cancers proliferation. However, its upregulator remains largely unknown. miRNA modulate gene expression by post-transcriptional repression to participate in many signaling pathway of breast cancer cell proliferation. miR-590 has been reported to regulate tumorgenesis and could be regulated by its own target ATF-3. But whether miR-590 can be the modulator of Golgi related genes to regulate the breast cancer proliferation is unclear.

Methods

We performed the bioinformatics analysis of survival rate and expression differences of patients using the data of The Cancer Genome Atlas (TCGA).Both of MTS and BrdU assays were used for cell proliferation analysis. Cell cycle was detected by flow cytometry .qRT-PCR was used for detecting the cell cycle related gene expression. Student’s t-test or One way anova was used for statistics.

Results

We found the upregulation of GOLPH3 in breast cancer samples compared with normal breast tissues, which also was related to the poor prognosis. Overexpression of GOLPH3 significantly promoted proliferation both of MDA-MB-231 cells (ER negative) and MCF-7 cells (ER positive). We further found that miRNA-590-3p could directly target the 3′-UTR of GOLPH3 mRNA to repress its expression. Overexpression of miR-590-3p inhibited the proliferation of MDA-MB-231 and MCF-7 cells. The rescue experiments indicated that overexpression of GOLPH3 significantly resorted the proliferation inhibited by miR-590-3p. We also found that ATF-3 repressed miR-590-3p expression to modulate miR-590/GOLPH3 pathway to regulate breast cancer cells proliferation.

Conclusions

This study not only suggests that the ATF-3/miR-590/GOLPH3 signaling pathway is critically involved in the proliferation of breast cancer cells, but provides a novel therapeutic target and new insight base on epigenetic regulation for future breast cancer diagnosis and clinical treatment.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4031-4) contains supplementary material, which is available to authorized users.

Evaluation of MiR-21 and MiR-10b Expression of Human Breast Cancer in West Sumatera

BACKGROUND

Abnormal expression of several microRNAs (miRNAs) has been demonstrated in many types of cancer tumor tissue. The miR-10b and miR-21 are an oncogenic miRNAs which play role in proliferation and invasion of Breast Cancer (BC) tumorigenesis. The aim of this study was to evaluate the miR-21 and miR-10b expression in BC in West Sumatran women, Indonesia.

MATERIALS AND METHODS

A total of 40 samples, consisting of 30 samples of breast cancer tissues (BC) and 10 samples of fibroadenoma tissues (FATs) as control and non-cancerous were analyzed. The miR-21 and miR-10b expression of each sample were investigated by using realtime PCR, followed by universal Reverse Transcription (RT) then real-time PCR amplification with specific primers. Hsa-miR-16-5p LNA PCR primer was used as an endogenous control.

RESULTS

The results showed that the expression level of miR-21 was more than 4 times higher in BC than in FATs. The expression level of miR-10b was lower in BC than FATs, by a factor of 3.34 fold. Both these differences were statistically different (p = 0.001).

CONCLUSION

In this study it was concluded that for this sample of West Sumatran Women miR-21 expression in BC was higher than in FATs, whereas miR-10b was lower in BC than in FATs.

LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction

Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs’ potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computationally infer new disease-related miRNAs. Yet researchers face the challenge of how to effectively integrate diverse datasets and make reliable predictions. In this study, we presented a computational model named Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction (LRSSLMDA), which projected miRNAs/diseases’ statistical feature profile and graph theoretical feature profile to a common subspace. It used Laplacian regularization to preserve the local structures of the training data and a L₁-norm constraint to select important miRNA/disease features for prediction. The strength of dimensionality reduction enabled the model to be easily extended to much higher dimensional datasets than those exploited in this study. Experimental results showed that LRSSLMDA outperformed ten previous models: the AUC of 0.9178 in global leave-one-out cross validation (LOOCV) and the AUC of 0.8418 in local LOOCV indicated the model’s superior prediction accuracy; and the average AUC of 0.9181+/-0.0004 in 5-fold cross validation justified its accuracy and stability. In addition, three types of case studies further demonstrated its predictive power. Potential miRNAs related to Colon Neoplasms, Lymphoma, Kidney Neoplasms, Esophageal Neoplasms and Breast Neoplasms were predicted by LRSSLMDA. Respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predictions were validated by experimental evidences. Therefore, we conclude that LRSSLMDA would be a valuable computational tool for miRNA-disease association prediction.

Discovering miRNA-disease associations promotes the understanding towards the molecular mechanisms of various human diseases at the miRNA level, and contributes to the development of diagnostic biomarkers and treatment tools for diseases. Computational models can make the discovery more efficient and experiments more productive. LRSSLMDA was proposed to computationally infer potential miRNA-disease associations via adopting sparse subspace learning with Laplacian regularization on the known miRNA-disease association network and the informative feature profiles extracted from the integrated miRNA/disease similarity networks. Experimental results in global and local leave-one-out cross validation and 5-fold cross validation showed a superior prediction performance of LRSSLMDA over previous models. Moreover, three types of case studies on five important human diseases were carried out to further demonstrate the model’s predictive power: respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predicted miRNAs were confirmed by experimental literatures. So, we believe that LRSSLMDA could make reliable predictions and might guide future experimental studies on miRNA-disease associations.

A Stack-based Ensemble Framework for Detecting Cancer MicroRNA Biomarkers

MicroRNA (miRNA) plays vital roles in biological processes like RNA splicing and regulation of gene expression. Studies have revealed that there might be possible links between oncogenesis and expression profiles of some miRNAs, due to their differential expression between normal and tumor tissues. However, the automatic classification of miRNAs into different categories by considering the similarity of their expression values has rarely been addressed. This article proposes a solution framework for solving some real-life classification problems related to cancer, miRNA, and mRNA expression datasets. In the first stage, a multiobjective optimization based framework, non-dominated sorting genetic algorithm II, is proposed to automatically determine the appropriate classifier type, along with its suitable parameter and feature combinations, pertinent for classifying a given dataset. In the second page, a stack-based ensemble technique is employed to get a single combinatorial solution from the set of solutions obtained in the first stage. The performance of the proposed two-stage approach is evaluated on several cancer and RNA expression profile datasets. Compared to several state-of-the-art approaches for classifying different datasets, our method shows supremacy in the accuracy of classification.

Systematic Prediction of the Impacts of Mutations in MicroRNA Seed Sequences

MicroRNAs are a class of small non-coding RNAs that are involved in many important biological processes and the dysfunction of microRNA has been associated with many diseases. The seed region of a microRNA is of crucial importance to its target recognition. Mutations in microRNA seed regions may disrupt the binding of microRNAs to their original target genes and make them bind to new target genes. Here we use a knowledge-based computational method to systematically predict the functional effects of all the possible single nucleotide mutations in human microRNA seed regions. The result provides a comprehensive reference for the functional assessment of the impacts of possible natural and artificial single nucleotide mutations in microRNA seed regions.

The Effect of Snail1 Gene Silencing by siRNA in Metastatic Breast Cancer Cell Lines

BACKGROUND

Breast cancer is the most common diagnosed cancer among women in the world. Snail1 plays a role in the development of the invasive phenotypes of cancer, neural cell differentiation, cell division and apoptosis in tumor cells. Traces of snail1 in metastasis of breast cancer to bone are observed. The aim of this study was to investigate the effect of specific snail1 siRNAs on the proliferation, migration, induction of apoptosis and cell cycle arrest of MDA-MB-468 cells.

METHODS

In 2015, this experimental study was performed on the MDA-MB-468 cell lines in Immunology Research Center, Tabriz University of Medical Sciences. After the design and construction of siRNA, transfection was performed with transfection reagent. The expression levels of mRNA and protein were measured by qRT-PCR and western blot analysis, respectively. The survival of cells was determined by using MTT assay cells, apoptosis using Tunel assay, Cell migration using scratch assay, Cell cycle analysis by Propidium Iodide (PI) DNA staining method using flow cytometry on the MDA-MB-468.

RESULTS

Transfection with siRNA significantly suppressed the expression of snail1 gene in dose-dependent manner after 48 h (P<0.0001). Surprisingly, treatment with snail1 siRNA arrested cell cycle in S phases (P<0.0001). Moreover, siRNA transfection had effects on breast adenocarcinoma cells and inhibited the migration (P<0.0001), proliferation (P<0.0001) and induced apoptosis (P<0.0016).

CONCLUSION

The snail1 can be considered as a potent adjuvant in breast cancer therapy.

Silencing of bach1 gene by small interfering RNA–mediation regulates invasive and expression level of miR-203, miR-145, matrix metalloproteinase-9, and CXCR4 receptor in MDA-MB-468 breast cancer cells

Background:

Recently experimental validation of the networks revealed bach1, a basic leucine zipper transcription factor, as the common regulator of several functional invasive genes. The expression of bach1 and its target genes was linked to the higher risk of breast cancer recurrence in patients. The aim of this study was to investigate the effect of specific bach1 small interfering RNAs, on the invasive and expression level of miR-203, miR-145, matrix metalloproteinase-9, and CXCR4 receptor which play a role in cancer metastasis, in MDA-MB-468 cell lines.

Methods:

Small interfering RNA transfection was performed with transfection regent. The survival effects of small interfering RNA were determined using trypan blue assay cells. The expression level of messenger RNA and matrix metalloproteinase-9 to assess cell invasion and the expression level of miR-203, miR-145, and CXCR4 receptor were measured by quantitative real-time polymerase chain reaction analysis on the MDA-MB-468 cell lines.

Results:

Transfection with small interfering RNA significantly suppressed the expression of bach1 gene in dose-dependent manner after 48 h ( p < 0.0001). A significant reduction in cell invasion and CXCR4 receptor, matrix metalloproteinase-9 expression were observed ( p < 0.0001). It was also a dramatic increase in the expression level of miR-203 and miR-145 ( p < 0.0001).

Conclusions:

Our results suggest that the bach1-specific small interfering RNA effectively decrease CXCR4 receptor, matrix metalloproteinase-9 expression and breast adenocarcinoma cells invasive, also increased the expression of tumor-suppressive microRNA-203 and miR-145. Thus, these microRNAs may play a role in invasive/metastasis of carcinogenic breast cancer cells. Therefore, bach1 knockdown can be considered as a potent adjuvant in breast cancer therapy.

Role of Runx2 in breast cancer-mediated bone metastasis

Breast cancer is one of the most prevalent forms of cancer in women. The currently available treatment for breast cancer is mostly curative except when it becomes metastatic. One of the major sites for metastasis of breast cancer is the bone. Homing of the circulating tumor cells is tightly regulated including a number of factors present in the cells and their microenvironment. Runx2, a transcription factor plays an important role in osteogenesis and breast cancer mediated bone metastases. One of the recent advances in molecular therapy includes the discovery of the small, non-coding microRNAs (miRNAs) and they target specific genes to reduce their expression at the post-transcriptional level. This review provides an outline of breast cancer mediated bone metastasis and summarizes the recent development on the regulation of Runx2 expression by miRNAs which can lead to novel molecular therapeutics for the same.

miR-671-5p inhibits epithelial-to-mesenchymal transition by downregulating FOXM1 expression in breast cancer

MicroRNA (miRNA) dysfunction is associated with a variety of human diseases, including cancer. Our previous study showed that miR-671-5p was deregulated throughout breast cancer progression. Here, we report for the first time that miR-671-5p is a tumor-suppressor miRNA in breast tumorigenesis. We found that expression of miR-671-5p was decreased significantly in invasive ductal carcinoma (IDC) compared to normal in microdissected formalin-fixed, paraffin-embedded (FFPE) tissues. Forkhead Box M1 (FOXM1), an oncogenic transcription factor, was predicted as one of the direct targets of miR-671-5p, which was subsequently confirmed by luciferase assays. Forced expression of miR-671-5p in breast cancer cell lines downregulated FOXM1 expression, and attenuated the proliferation and invasion in breast cancer cell lines. Notably, overexpression of miR-671-5p resulted in a shift from epithelial-to-mesenchymal transition (EMT) to mesenchymal-to-epithelial transition (MET) phenotypes in MDA-MB-231 breast cancer cells and induced S-phase arrest. Moreover, miR-671-5p sensitized breast cancer cells to cisplatin, 5-fluorouracil (5-FU) and epirubicin exposure. Host cell reactivation (HCR) assays showed that miR-671-5p reduces DNA repair capability in post-drug exposed breast cancer cells. cDNA microarray data revealed that differentially expressed genes when miR-671-5p was transfected are associated with cell proliferation, invasion, cell cycle, and EMT. These data indicate that miR-671-5p functions as a tumor suppressor miRNA in breast cancer by directly targeting FOXM1. Hence, miR-671-5p may serve as a novel therapeutic target for breast cancer management.

One Step Assembly of Thin Films of Carbon Nanotubes on Screen Printed Interface for Electrochemical Aptasensing of Breast Cancer Biomarker

Thin films of organic moiety functionalized carbon nanotubes (CNTs) from a very well-dispersed aqueous solution were designed on a screen printed transducer surface through a single step directed assembly methodology. Very high density of CNTs was obtained on the screen printed electrode surface, with the formation of a thin and uniform layer on transducer substrate. Functionalized CNTs were characterized by X-ray diffraction spectroscopy (XRD), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA) and Brunauer–Emmett–Teller (BET) surface area analyzer methodologies, while CNT coated screen printed transducer platform was analyzed by scanning electron microscopy (SEM), atomic force microscopy (AFM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The proposed methodology makes use of a minimum amount of CNTs and toxic solvents, and is successfully demonstrated to form thin films over macroscopic areas of screen printed carbon transducer surface. The CNT coated screen printed transducer surface was integrated in the fabrication of electrochemical aptasensors for breast cancer biomarker analysis. This CNT coated platform can be applied to immobilize enzymes, antibodies and DNA in the construction of biosensor for a broad spectrum of applications.

Novel and simple electrochemical biosensor monitoring attomolar levels of miRNA-155 in breast cancer

This work, describes for the first time, a simple biosensing design to yield an ultrasensitive electrochemical biosensor for a cancer biomarker detection, miRNA-155, with linear response down to the attomolar range. MiRNA-155 was selected for being overexpressed in breast cancer. The biosensor was assembled in two stages: (1) the immobilization of the anti-miRNA-155 that was thiol modified on an Au-screen printed electrode (Au-SPE), followed by (2) blocking the areas of non-specific binding with mercaptosuccinic acid. Atomic force microscopy (AFM) and electrochemical techniques including cyclic voltammetry (CV), impedance spectroscopy (EIS) and square wave voltammetry (SWV) confirmed the surface modification of these devices and their ability to hybridize successfully and stably with miRNA-155. The final biosensor provided a sensitive detection of miRNA-155 from 10 aM to 1.0 nM with a low detection limit (LOD) of 5.7 aM in real human serum samples. Good results were obtained in terms of selectivity towards breast cancer antigen CA-15.3 and bovine serum albumin (BSA). Raw fluid extracts from cell-lines of melanoma did not affect the biosensor response (no significant change of the blank), while raw extracts from breast cancer yielded a positive signal against miRNA-155. This simple and sensitive strategy is a promising alternative for simultaneous quantitative analysis of multiple miRNA in physiological fluids for biomedical research and point-of-care (POC) diagnosis.

miR-548d-3p/TP53BP2 axis regulates the proliferation and apoptosis of breast cancer cells

Fast growth and hardly any apoptosis are important characteristics of breast cancer, which assure the spread via invasion and metastasis of breast cancer cells. Inhibition of fast proliferation and induction of apoptosis are critical way to cure this cancer. microRNAs (miRNAs) had been increasingly reported to be the critical regulator of tumorigenesis. In our study, we found that increasing copy number of miR-548d-2-3p is critically involved poor prognosis. We overexpressed miR-548d-3p in MDA-MB-231cells and found that the proliferation was promoted significantly, whereas the inhibition of miR-548d-3p repressed the proliferation of MDA-MB-231 cells and also induced the increase in apoptosis. Additionally, we found that miR-548d-3p downregulated the expression of TP53BP2 by directly targeting the 3'UTR. We also found that knockdown of TP53BP2 significantly resorted the proliferation and apoptosis regulated by miR-548d-3p inhibitor. Our study showed that miR-548d-3p/TP53BP2 pathway is critically involved in the proliferation and apoptosis of breast cancer cells and may be new therapeutic target of breast cancer cells.

Over-expression of miR-675 in formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer patients

BACKGROUND

Dysregulation of miR-675 has been found in a variety of solid tumors. MiR-675 has been suggested as having both oncogenic and tumor suppression properties in cancer. However, there is no evidence whether miR-675 is involved in breast cancer. The objective of this study was to evaluate the expression status of miR-675 and its clinical relevance in breast cancer patients.

METHODS

The expression level of miR-675 was detected in 100 breast cancer patients and 38 cancer-free controls using real-time quantitative PCR. The clinicopathological characteristics of miR-675 in breast cancer were also investigated. All statistical analyses were performed using SPSS 20.0.

RESULTS

The study showed that miR-675 was significantly up-regulated in breast cancer patients compared with controls (P < 0.01). There was no significant difference in age, lymph nodes stage, ER status and PR status between patients with and without miR-675 over-expression (P > 0.05). The frequency of miR-675 over-expression was higher in the patients of histological grade I-II than in others (50% versus 9%, P = 0.011). The expression level of miR-675 had a high correlation with miR-24/93/98/378 in breast cancer patients.

CONCLUSIONS

Taken together, our study demonstrated that miR-675 in formalin-fixed paraffin-embedded (FFPE) tissues might serve as a good source for biomarker discovery and breast cancer validation.

MicroRNA-196a post-transcriptionally upregulates the UBE2C proto-oncogene and promotes cell proliferation in breast cancer

Accumulating evidence has shown that miR-196a plays an important role in tumorigenesis and tumor progression in various types of cancer. miRNA profiling studies have suggested that miR-196a is highly overexpressed in breast cancer. However, the functional mechanism of miR-196a in breast cancer remains unclear. In the present study, we first showed that the expression of miR-196a was significantly upregulated in human breast cancer samples and breast cancer cell lines. Using a loss-of-function approach, we showed that the downregulation of miR-196a inhibited the proliferation of breast cancer cells in vitro and in vivo. Ubiquitin-conjugating enzyme E2C (UBE2C) gene as a cellular proto-oncogene, which was overexpressed and positively correlated with miR-196a expression in breast cancer tissues, was identified as a direct target of miR-196a. Moreover, in order to investigate whether miR-196a regulated cell growth in breast cancer cells by targeting UBE2C, rescue studies were performed in breast cancer cells. The restoration of UBE2C by transfecting UBE2C cDNA in anti-miR-196a-transfected breast cancer cells rescued the suppression of cell proliferation. In conclusion, the present study showed that miR-196a promoted cell proliferation by targeting UBE2C in breast cancer. Thus, miR-196a may be a potential oncogene in breast cancer and a promising therapeutic target in breast cancer treatment.

Analysis of circulating microRNAs during adjuvant chemotherapy in patients with luminal A breast cancer

Breast cancer is a complex disease displaying different profiles involving genetic as well as epigenetic factors. MicroRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression. Recent studies demonstrated that miRNAs may display great potential for the development of novel biomarkers and therapeutic targets. In the present study, the levels of miR-21 and miR-145 were analyzed in the peripheral blood of 52 patients with luminal A breast cancer. miRNA expression was determined in serum samples from matched pre- and post-treatment patients with breast cancer by quantitative polymerase chain reaction. There were no statistically significant differences in miR-145 and miR-21 levels between pre- and post-treatment samples. In addition, the miRNA levels were not found to be associated with the clinical parameters.