MicroRNA expression and gene regulation drive breast cancer progression and metastasis in PyMT mice

Combination of furosemide, gold, and dopamine as a potential therapy for breast cancer

Breast cancer is one of the leading causes of death in women worldwide. Initially, it develops in the epithelium of the ducts or lobules of the breast glandular tissues with limited growth and the potential to metastasize. It is a highly heterogeneous malignancy; however, the common molecular mechanisms could help identify new targeted drugs for treating its subtypes. This study uses computational drug repositioning approaches to explore fresh drug candidates for breast cancer treatment. We also implemented reversal gene expression and gene expression-based signatures to explore novel drug candidates computationally. The drug activity profiles and related gene expression changes were acquired from the DrugBank, PubChem, and LINCS databases, and then in silico drug screening, molecular dynamics (MD) simulation, replica exchange MD simulations, and simulated annealing molecular dynamics (SAMD) simulations were conducted to discover and verify the valid drug candidates. We have found that compounds like furosemide, gold, and dopamine showed significant outcomes. Furthermore, the expression of genes related to breast cancer was observed to be reversed by these shortlisted drugs. Therefore, we postulate that combining furosemide, gold, and dopamine would be a potential combination therapy measurement for breast cancer patients.

LINC00174 Facilitates Cell Proliferation, Cell Migration and Tumor Growth of Osteosarcoma via Regulating the TGF-β/SMAD Signaling Pathway and Upregulating SSH2 Expression

Osteosarcoma (OS), a frequent malignant tumor which mainly occurs in the bone. The roles of long noncoding RNAs (lncRNAs) have been revealed in cancers, including OS. LncRNA long intergenic non-protein coding RNA (LINC00174) has been validated as an oncogene in several cancers. However, the role of LINC00174 in OS has not been explored. In our research, loss-of-function assays were conducted to explore the function of LINC00174 in OS cells. Then, we explored the downstream pathway of LINC00174 in OS cells. Bioinformatics, RNA pull-down and RIP experiments investigated the downstream mechanism of LINC00174 in OS cells. Finally, in vivo assays clarified the effect of LINC00174 on tumorigenesis. We found that LINC00174 was upregulated in OS tissues and cells. LINC00174 knockdown repressed OS cell growth. Mechanistically, LINC00174 knockdown suppressed the TGF-β/SMAD pathway. LINC00174 interacted with miR-378a-3p, and slingshot protein phosphatase 2 (SSH2) 3′UTR was targeted by miR-378a-3p in OS cells. Rescue assays showed that SSH2 upregulation or miR-378a-3p inhibition counteracted the inhibitory effect of LINC00174 depletion in OS cell growth. Additionally, LINC00174 depletion suppressed tumor growth in mice. In conclusion, LINC00174 promotes OS cellular malignancy and tumorigenesis via the miR-378a-3p/SSH2 axis and the TGF-β/SMAD pathway, which might provide a novel insight for OS treatment.

An Integrated Analysis of mRNAs and miRNAs Microarray Profiles to Screen miRNA Signatures Involved in Nasopharyngeal Carcinoma

OBJECTIVE

We aim to identify several microRNAs (miRNAs/miRs)-messenger RNAs (mRNAs) biomarkers correlated to nasopharyngeal carcinoma (NPC) based on an integrated analysis of miRNA and mRNAs microarray expression profiles.

METHODS

The available mRNA and miRNA microarray datasets were retrieved from Gene Expression Omnibus (GEO) database according to pre-determined screening criteria. Differentially expressed miRNA and mRNAs (DEmiRNAs and DEmRNAs) were extracted between NPC and noncancerous nasopharyngeal tissues. The target genes of DEmiRNAs were predicted with miRTarBase followed by the construction of DEmiRNAs-target DEmRNAs network, and functional analyses were performed. The DEmiRNAs expressions were validated and the performance of these DEmiRNAs was assessed by the area under the curve (AUC) values. Finally, the correlations between DEmiRNAs and specific clinical factors were analyzed.

RESULTS

There were 1140 interaction pairs (including let-7d/f-MYC/HMGA2 and miR-452-ITGA9) in DEmiRNAs-target DEmRNAs network. The GO annotation analysis showed that several genes such as MYC, HMGA2 and ITGA9 primarily participated in cellular process. KEGG analysis showed that these targets were associated with cell cycle and cancer-related pathways. Down-regulated let-7(-d and -f) and up-regulated miR-452 were verified in datasets. The AUC values of these 3 DEmiRNAs (let-7d, let-7-f and miR-452) was 0.803, 0.835 and 0.735, respectively. Besides, miR-452 was significantly related to survival rate of NPC patients.

CONCLUSION

The findings implied let-7d/f-MYC/HMGA2 and miR-452-ITGA9 might be promising targets for the detection and treatment of NPC.

Jasmine: a Java pipeline for isomiR characterization in miRNA-Seq Data

MOTIVATION

The existence of complex subpopulations of miRNA isoforms, or isomiRs, is well established. While many tools exist for investigating isomiR populations, they differ in how they characterize an isomiR, making it difficult to compare results across different tools. Thus, there is a need for a more comprehensive and systematic standard for defining isomiRs. Such a standard would allow investigation of isomiR population structure in progressively more refined sub-populations, permitting the identification of more subtle changes between conditions and leading to an improved understanding of the processes that generate these differences.

RESULTS

We developed Jasmine, a software tool that incorporates a hierarchal framework for characterizing isomiR populations. Jasmine is a Java application that can process raw read data in fastq/fasta format, or mapped reads in SAM format to produce a detailed characterization of isomiR populations. Thus, Jasmine can reveal structure not apparent in a standard miRNA-Seq analysis pipeline.

AVAILABILITY

Jasmine is implemented in Java and R and freely available at bitbucket https://bitbucket.org/bipous/jasmine/src/master/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Systematical Identification of Breast Cancer-Related Circular RNA Modules for Deciphering circRNA Functions Based on the Non-Negative Matrix Factorization Algorithm

Circular RNA (circRNA), a kind of special endogenous RNA, has been shown to be implicated in crucial biological processes of multiple cancers as a gene regulator. However, the functional roles of circRNAs in breast cancer (BC) remain to be poorly explored, and relatively incomplete knowledge of circRNAs handles the identification and prediction of BC-related circRNAs. Towards this end, we developed a systematic approach to identify circRNA modules in the BC context through integrating circRNA, mRNA, miRNA, and pathway data based on a non-negative matrix factorization (NMF) algorithm. Thirteen circRNA modules were uncovered by our approach, containing 4164 nodes (80 circRNAs, 2703 genes, 63 miRNAs and 1318 pathways) and 67,959 edges in total. GO (Gene Ontology) function screening identified nine circRNA functional modules with 44 circRNAs. Within them, 31 circRNAs in eight modules having direct relationships with known BC-related genes, miRNAs or disease-related pathways were selected as BC candidate circRNAs. Functional enrichment results showed that they were closely related with BC-associated pathways, such as ‘KEGG (Kyoto Encyclopedia of Genes and Genomes) PATHWAYS IN CANCER’, ‘REACTOME IMMUNE SYSTEM’ and ‘KEGG MAPK SIGNALING PATHWAY’, ‘KEGG P53 SIGNALING PATHWAY’ or ‘KEGG WNT SIGNALING PATHWAY’, and could sever as potential circRNA biomarkers in BC. Comparison results showed that our approach could identify more BC-related functional circRNA modules in performance. In summary, we proposed a novel systematic approach dependent on the known disease information of mRNA, miRNA and pathway to identify BC-related circRNA modules, which could help identify BC-related circRNAs and benefits treatment and prognosis for BC patients.

Regulatory mechanisms of miR-96 and miR-184 abnormal expressions on otic vesicle development of zebrafish following exposure to β-diketone antibiotics

Chronic ototoxicity of β-diketone antibiotics (DKAs) to zebrafish (Danio rerio) was explored in detail by following abnormal expressions of two hearing-related miRNAs. Dose-dependent down-regulation of miR-96 and miR-184 was observed in otoliths during embryonic-larval development. Continuous DKA exposure to 120-hpf larva decreased sensitivity to acoustic stimulation. Development of otolith was delayed in treatment groups, showing unclear boundaries and vacuolization at 72-hpf, and utricular enlargement as well as decreased saccular volume in 96-hpf or latter larval otoliths. If one miRNA was knocked-down and another over-expressed, only a slight influence on morphological development of the otic vesicle occurred, but knocked-down or over-expressed miRNA both significantly affected zebrafish normal development. Injection of miR-96, miR-184 or both micRNA mimics to yolk sac resulted in marked improvement of otic vesicle phenotype. However, hair cell staining showed that only the injected miR-96 mimic restored hair cell numbers after DKA exposure, demonstrating that miR-96 played an important role in otic vesicle development and formation of hearing, while miR-184 was only involved in otic vesicle construction during embryonic development. These observations advance our understanding of hearing loss owing to acute antibiotic exposure and provide theoretical guidance for early intervention and gene therapy for drug-induced diseases.

Functional Role of miRNAs in the Progression of Breast Ductal Carcinoma in Situ

miRNAs are small RNAs that influence gene expression by targeting mRNAs. Depending on the function of their target genes, miRNAs may regulate the expression of oncogenes and tumor suppressors, thereby contributing to the promotion or inhibition of tumor progression. Ductal carcinoma in situ (DCIS), although often diagnosed as breast cancer, is a potential precursor to invasive ductal carcinoma. Many of the genetic events required for the invasive progression of DCIS occur at the preinvasive stage, and these events include changes in the expression of miRNAs. Aberrant expression of miRNAs can influence specific oncogenic or tumor-suppressive pathways required for breast cancer progression. miRNAs in DCIS have been shown to influence hormone signaling, cell-cell adhesion, epithelial-to-mesenchymal transition, transforming growth factor β signaling, maintenance of cancer stem cells, and modulation of the extracellular matrix. Additionally, extracellular DCIS miRNAs, such as those found in exosomes, may promote invasive progression by modifying the tumor microenvironment. Here, we review the miRNAs that have been identified in DCIS and how they may contribute to the progression to invasive disease. We also touch on the current state of miRNA therapy development, including the current challenges, and discuss the key future perspectives for research into miRNA function for the purpose of miRNA therapy development for DCIS.

Mixomics analysis of breast cancer: Long non-coding RNA linc01561 acts as ceRNA involved in the progression of breast cancer

OBJECTIVE

This study aimed at finding the long non-coding RNA (lncRNA), miRNA and mRNA which played critical roles in breast cancer (BrCa) by using mixOmics R package.

METHOD

The BrCa dataset were obtained from TCGA and then analyzed using "DESeq2" R package. Multivariate analyses were performed with the "mixOmics" R package and the first component of the stacked partial least-Squares discriminant analysis results were used for searching the interested lncRNA, miRNA and mRNA. qRT-PCR was applied to identify the bioinformatics results in four BrCa cell lines (MCF7, BT-20, ZR-75-1, and MX-1) and the breast epithelial cell line MCF-10 A. Then cells (MCF-1 and MX-1) were transfected with si-linc01561, miR-145-5p mimics and si-MMP11 to further investigate the effects of linc01561, miR-145-5p and MMP11 on the BrCa cells proliferation and apoptosis.

RESULTS

MixOmics results showed that linc01561, miR-145-5p and MMP11 might play important roles in BrCa. qRT-PCR results identified that in BrCa cell lines, linc01561 and MMP11 were higher expressed while miR-145-5p was lower expressed compared with those in epithelial cell line. The linc01561 inhibition elevated miR-145-5p expression and then suppressed MMP11 expression. Moreover, linc01561 inhibition suppressed the BrCa cells proliferation and promoted the apoptosis, which was realized by up-regulating expression of miR-145-5p and down-regulating expression of MMP11.

CONCLUSION

In summary, the findings of this study, based on ceRNA theory, combining the research foundation of miR-145-5p and MMP11, and taking linc01561 as a new study point, provide new insight into molecular-level reversing proliferation and apoptosis of BrCa.

Comprehensive integrated analysis of gene expression datasets identifies key anti-cancer targets in different stages of breast cancer

Breast cancer is one of the primary threats to women's health worldwide. However, the molecular mechanisms underlying the development of breast cancer remain to be fully elucidated. The present study aimed to investigate specific target gene expression profiles in breast cancer tissues in general and in different breast cancer stages, as well as to explore their functions in tumor development. For integrated analysis, a total of 5 gene expression profiling datasets for 3 different stages of breast cancer (stages I-III) were downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information. Pre-processing of these datasets was performed using the Robust Multi-array Average algorithm and global renormalization was performed for all studies. Differentially expressed genes between breast cancer patients and controls were estimated using the empirical Bayes algorithm. The Database for Annotation, Visualization and Integrated Discovery web server was used for analyzing the enrichment of the differentially expressed genes in Gene Ontology terms of the category biological process and in Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, breast cancer target genes were downloaded from the Thomson Reuters Integrity Database. We merged these target genes with the genes in breast cancer datasets. Analysis of anti-breast cancer gene networks was performed using the Genome-scale Integrated Analysis of Gene Networks in Tissues web server. The results demonstrated that the normal functions of the cell cycle, cell migration and cell adhesion were altered in all stages of breast cancer. Furthermore, 12 anti-breast cancer genes were identified to be dysregulated in at least one of the three stages. Among all of these genes, ribonucleotide reductase regulatory subunit M2 (RRM2) exhibited the highest degree of interaction with other interacting genes. Analysis of the network interactions revealed that the transcription factor of RRM2 is crucial for cancer development. Other genes, including mucin 1, progesterone receptor and cyclin-dependent kinase 5 regulatory subunit associated protein 3, also exhibited a high degree of interaction with the associated genes. In conclusion, several key anti-breast cancer genes identified in the present study are mainly associated with the regulation of the cell cycle, cell migration, cell adhesion and other cancer-associated cell functions, particularly RRM2.

Epigenetic alterations to Polycomb targets precede malignant transition in a mouse model of breast cancer

Malignant breast cancer remains a major health threat to women of all ages worldwide and epigenetic variations on DNA methylation have been widely reported in cancers of different types. We profiled DNA methylation with ERRBS (Enhanced Reduced Representation Bisulfite Sequencing) across four main stages of tumor progression in the MMTV-PyMT mouse model (hyperplasia, adenoma/mammary intraepithelial neoplasia, early carcinoma and late carcinoma), during which malignant transition occurs. We identified a large number of differentially methylated cytosines (DMCs) in tumors relative to age-matched normal mammary glands from FVB mice. Despite similarities, the methylation differences of the premalignant stages were distinct from the malignant ones. Many differentially methylated loci were preserved from the first to the last stage throughout tumor progression. Genes affected by methylation gains were enriched in Polycomb repressive complex 2 (PRC2) targets, which may present biomarkers for early diagnosis and targets for treatment.

Inferring MicroRNA Targets Based on Restricted Boltzmann Machines

Predicting the miRNA-target interactions (MTIs) is a critical task for elucidating mechanistic roles of miRNAs in pathophysiology. However, most existing techniques have a higher false positive because the precise miRNA target mechanisms are poorly known. Considering that ensemble methods can take advantage of the complementary knowledge in different methods, we propose an alternative optimization framework, Inferring MiRNA Targets based on Restricted Boltzmann Machines (IMTRBM), to enhance the accuracy of previous prediction results. First, the proposed method directly constructs a weighted MTI network though the results predicted by individual methods and each miRNA target pair is weighted based on the frequency appearing in these results. Second, we transform the miRNA-target prediction problem into a complete bipartite graph model, named restricted Boltzmann machine, and utilize a practical learning procedure to train our model and make predictions. Our results show that the algorithm outperforms individual miRNA-target prediction approach in the number of validated miRNA targets at cutoffs of top list. Moreover, our framework can tolerate the decrease and increase of predicted MTIs and even discover new miRNA targets, which have been a challenge to predict for any individual methods. Finally, for the miRNAs that are not appearing in IMTRBM, we design a new method to supplement IMTRBM based on the intuition that similar miRNAs have similar functions, which also achieves a comparable result. The source code of IMTRBM is available at https://github.com/liuying201705/IMTRBM.

A new method to study the change of miRNA-mRNA interactions due to environmental exposures

MOTIVATION

Integrative approaches characterizing the interactions among different types of biological molecules have been demonstrated to be useful for revealing informative biological mechanisms. One such example is the interaction between microRNA (miRNA) and messenger RNA (mRNA), whose deregulation may be sensitive to environmental insult leading to altered phenotypes. The goal of this work is to develop an effective data integration method to characterize deregulation between miRNA and mRNA due to environmental toxicant exposures. We will use data from an animal experiment designed to investigate the effect of low-dose environmental chemical exposure on normal mammary gland development in rats to motivate and evaluate the proposed method.

RESULTS

We propose a new network approach-integrative Joint Random Forest (iJRF), which characterizes the regulatory system between miRNAs and mRNAs using a network model. iJRF is designed to work under the high-dimension low-sample-size regime, and can borrow information across different treatment conditions to achieve more accurate network inference. It also effectively takes into account prior information of miRNA-mRNA regulatory relationships from existing databases. When iJRF is applied to the data from the environmental chemical exposure study, we detected a few important miRNAs that regulated a large number of mRNAs in the control group but not in the exposed groups, suggesting the disruption of miRNA activity due to chemical exposure. Effects of chemical exposure on two affected miRNAs were further validated using breast cancer human cell lines.

AVAILABILITY AND IMPLEMENTATION

R package iJRF is available at CRAN.

CONTACTS

pei.wang@mssm.edu or susan.teitelbaum@mssm.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

miR-145 inhibits proliferation and migration of breast cancer cells by directly or indirectly regulating TGF-β1 expression

Studies have demonstrated low expression of miR-145 associated with cell proliferation and migration in a wide variety of tumors. Here, we studied the expression of miR-145 in relation to the occurrence and development of breast cancer. Total RNA from breast cancer tissue and corresponding adjacent normal tissue was extracted and used to detect miR-145 expression by quantitative real-time polymerase chain reaction (qRT-PCR). We also transfected breast cancer cells with hsa-miR-145 mimics, hsa-miR-145 inhibitor, mimics negative control (mimics NC) or inhibitor negative control (inhibitor NC). Cell proliferation was analyzed by colony formation assays and methyl thiazolyl tetrazolium assays. Cell proliferation in breast cancer cells was decreased after overexpression of miR-145 and increased following miR-145 suppression. Cell migration and invasion were assessed using Transwell and wound healing assays, respectively, and were also decreased after overexpression of miR-145 and increased after miR-145 suppression in breast cancer cells. Finally, western blot assays showed that overexpression of miR-145 inhibited expression of transforming growth factor-β1 (TGF-β1). Collectively, these data suggest that miR-145 may inhibit TGF-β1 protein expression which may in turn contribute to tumor formation.