Suppressive and Hypermethylated MicroRNAs in the Pathogenesis of Breast Cancer

MicroRNAs (miRNAs) are involved in oncogenesis by suppression of proto-oncogenes or tumor suppressive genes. This review presents data of suppressive miRNAs role in the mechanisms of occurrence and development of malignant tumors of breast cancer as the example—that is the most widespread oncopathology in women. Targets and functions of suppressive and antimetastatic miRNAs have been illustrated, as well as for suppressive miRNAs with an oncogenic potential (such as miR-200a, miR-200c) that appears probably owing to the ability of miRNA to interact with a variety of targets depending on the cellular content. Based on the published and the authors’ own data, the role of hypermethylation of promoter regions in inhibition of expression and regulatory function of miRNA genes in breast cancer was characterized. In conclusion, the authors pointed future prospects of clinical application of suppressive miRNAs in diagnostics and treatment of breast cancer.     

乳腺癌转移相关基因的筛选与生物信息学分析

乳腺癌是女性最常见的恶性肿瘤,转移与复发是乳腺癌患者死亡的主要原因. 研究与乳腺癌细胞转移相关的分子靶点对预防乳腺癌术后复发、提高疗效有重要意义. 本研究以3组乳腺癌转移相关的基因表达谱数据(GSE2034, GSE2603, GSE12276)为分析材料,采用GeneSpring软件筛选乳腺癌原发瘤与转移瘤芯片数据的差异表达基因,结合生物信息学工具PATHER、STRING、pSTIING和文献挖掘工具iHOP对差异基因及其相互作用关系进行分析. 结果显示,共筛选出乳腺癌转移共同差异基因147个,其中表达上调93个,表达下调54个. 这些差异基因主要涉及细胞周期与增殖、细胞粘附、细胞迁移、血管形成及信号转导等生物通路和生物过程. 差异基因编码蛋白间的相互作用主要集中在14个蛋白,且在更为复杂的网络图谱中仍可见其中9个基因（CXCR4、MMP1、MMP2、MMP3、CTGF、COL1A1、MEF2C、PTGS2及SPARC）在重要的节点位置. 文献挖掘发现,COL1A1基因可能为新发现的乳腺癌转移候选基因,为乳腺癌转移的发病机制提供新的思路,也为转移性乳腺癌的分子诊断和个体化治疗奠定基础.     

Impact of miRNA Sequence on miRNA Expression and Correlation between miRNA Expression and Cell Cycle Regulation in Breast Cancer Cells

The miRNAs regulate cell functions by inhibiting expression of proteins. Research on miRNAs had usually focused on identifying targets by base pairing between miRNAs and their targets. Instead of identifying targets, this paper proposed an innovative approach, namely impact significance analysis, to study the correlation between mature sequence, expression across patient samples or time and global function on cell cycle signaling of miRNAs. With three distinct types of data: The Cancer Genome Atlas miRNA expression data for 354 human breast cancer specimens, microarray of 266 miRNAs in mouse Embryonic Stem cells (ESCs), and Reverse Phase Protein Array (RPPA) transfected by 776 miRNAs in MDA-MB-231 cell line, we linked the expression and function of miRNAs by their mature sequence and discovered systematically that the similarity of miRNA expression enhances the similarity of miRNA function, which indicates the miRNA expression can be used as a supplementary factor to predict miRNA function. The results also show that both seed region and 3'' portion are associated with miRNA expression levels across human breast cancer specimens and in ESCs; miRNAs with similar seed tend to have similar 3'' portion. And we discussed that the impact of 3'' portion, including nucleotides , is not significant for miRNA function. These results provide novel insights to understand the correlation between miRNA sequence, expression and function. They can be applied to improve the prediction algorithm and the impact significance analysis can also be implemented to similar analysis for other small RNAs such as siRNAs.     

Hierarchical Clustering of Breast Cancer Methylomes Revealed Differentially Methylated and Expressed Breast Cancer Genes

Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs) and the hypomethylation of the megabase-sized partially methylated domains (PMDs) are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI) was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma) dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.     

Genetic Variants in Hormone-Related Genes and Risk of Breast Cancer

Sex hormones play a key role in the development of breast cancer. Certain polymorphic variants (SNPs and repeat polymorphisms) in hormone-related genes are associated with sex hormone levels. However, the relationship observed between these genetic variants and breast cancer risk has been inconsistent. We conducted a case-control study nested within two prospective cohorts to assess the relationship between specific genetic variants in hormone-related genes and breast cancer risk. In total, 1164 cases and 2111 individually-matched controls were included in the study. We did not observe an association between potential functional genetic polymorphisms in the estrogen pathway, SHBG rs6259, ESR1 rs2234693, CYP19 rs10046 and rs4775936, and UGT1A1 rs8175347, or the progesterone pathway, PGR rs1042838, with the risk of breast cancer. Our results suggest that these genetic variants do not have a strong effect on breast cancer risk.     

Expression of the Androgen Receptor,pAkt, and pPTEN in Breast Cancer and Their Potential in Prognostication

BACKGROUNDImportance of androgen receptor (AR) as an independent prognostic marker in Pakistani women with breast cancer (BCa) remains unexplored. Our aim was to identify the expression and potential prognostic value of AR, its upstream regulator (pAkt) and target gene (pPTEN) in invasive BCa.METHODSThis study used a cohort of 200 Pakistani women with invasive BCa diagnosed during 2002-2011. Expression of AR, pAkt and pPTEN was determined on formalin fixed paraffin embedded tissue sections by immunohistochemistry. The association of AR, pAkt and pPTEN with clinicopathological parameters was determined. Survival analyses were undertaken on patients with ≥ 5 years of follow-up (n = 82).RESULTSExpression of AR, pAkt and pPTEN was observed in 47.5%, 81.3% and 50.6% of patients, respectively. AR-expressing tumors were low or intermediate in grade (P < .001) and expressed ER (P = .002) and PR (P = .001). Patients with AR⁺ tumors had significantly higher OS (Mean OS = 10.2 ± 0.465 years) compared to patients with AR^? tumors (Mean OS = 5.8 ± 0.348 years) (P = .047). Furthermore, AR-positivity was associated with improved OS in patients receiving endocrine therapy (P = .020). Patients with AR⁺ /pAkt⁺ /pPTEN^? tumors, had increased OS (Mean OS = 7.1 ± 0.535 years) compared to patients with AR^?/pAkt⁺/pPTEN^? tumors (Mean OS = 5.1 ± 0.738 years).CONCLUSIONAR-expressing tumors are frequently characterized by low or intermediate grade tumors, expressing ER and PR. In addition, expression of AR, pAkt and pPTEN, could be considered in prognostication of patients with invasive BCa.     

Identification and Validation of Oncologic miRNA Biomarkers for Luminal A-like Breast Cancer

Introduction

Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting.

Methods

Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n = 54) and controls (n = 56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n = 10 Luminal A-like; n = 10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n = 44 Luminal A; n = 46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated.

Results

Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis (miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652). The biomarker potential of 4 miRNAs (miR-29a, miR-181a, miR-223 and miR-652) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p = 0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs (miR-29a, miR-181a and miR-652) could reliably differentiate between cancers and controls with an AUC of 0.80.

Conclusion

This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype-specific breast tumor detection.     

采用蛋白质组学技术筛选鼻咽癌细胞的甲基化沉默基因

为筛选鼻咽癌的甲基化沉默基因,采用二维凝胶电泳(2-DE)技术分离甲基转移酶抑制剂5-杂氮-2'-脱氧胞苷(5-aza-2-dC)处理与未处理鼻咽癌细胞5-8F的蛋白质,PDquest图像分析软件识别差异蛋白质点,基质辅助激光解吸电离飞行时间质谱(MALDI-TOF-MS)鉴定差异蛋白质.然后采用Western blotting和RT-PCR检测差异蛋白质nm23-H1在药物处理与未处理5.8F细胞中的表达水平,采用甲基化特异性PCR(MS-PCR)检测nm23-H1基因在药物处理与未处理5-8F细胞中的甲基化水平.建立了5-aza-2-dC处理与未处理5.8F细胞蛋白质的2-DE图谱,识别了49个差异表达的蛋白质点,鉴定了33个差异表达的蛋白质,其中包括rim23.H1在内的15个蛋白质在5-aza-2-dC处理后的5-8F细胞中表达上调,而18个蛋白质表达下调.Western blotting和RT-PCR结果显示,nm23-H1在5-aza-2-dC处理5-8F细胞后表达上调,MS-PCR结果显示,在5-aza-2-dC处理5-8F细胞后nm23-H1基因甲基化水平下降,结果证实,nm23-H1基因是5-8F细胞中的甲基化沉默基因.15个5-aza.2-dC处理后表达上调的基因可能是5-8F细胞中的甲基化沉默基因,为筛选鼻咽癌甲基化失活基因提供了科学依据.     

Exome Sequencing Identifies Rare Deleterious Mutations in DNA Repair Genes FANCC and BLM as Potential Breast Cancer Susceptibility Alleles

Despite intensive efforts using linkage and candidate gene approaches, the genetic etiology for the majority of families with a multi-generational breast cancer predisposition is unknown. In this study, we used whole-exome sequencing of thirty-three individuals from 15 breast cancer families to identify potential predisposing genes. Our analysis identified families with heterozygous, deleterious mutations in the DNA repair genes FANCC and BLM, which are responsible for the autosomal recessive disorders Fanconi Anemia and Bloom syndrome. In total, screening of all exons in these genes in 438 breast cancer families identified three with truncating mutations in FANCC and two with truncating mutations in BLM. Additional screening of FANCC mutation hotspot exons identified one pathogenic mutation among an additional 957 breast cancer families. Importantly, none of the deleterious mutations were identified among 464 healthy controls and are not reported in the 1,000 Genomes data. Given the rarity of Fanconi Anemia and Bloom syndrome disorders among Caucasian populations, the finding of multiple deleterious mutations in these critical DNA repair genes among high-risk breast cancer families is intriguing and suggestive of a predisposing role. Our data demonstrate the utility of intra-family exome-sequencing approaches to uncover cancer predisposition genes, but highlight the major challenge of definitively validating candidates where the incidence of sporadic disease is high, germline mutations are not fully penetrant, and individual predisposition genes may only account for a tiny proportion of breast cancer families.     

Enpp1: A Potential Facilitator of Breast Cancer Bone Metastasis

Bone is the most common site of breast cancer metastasis and once established, it is frequently incurable. Critical to our ability to prevent and treat bone metastasis is the identification of the key factors mediating its establishment and understanding their biological function. To address this issue we previously carried out an in vivo selection process to isolate murine mammary tumor sublines possessing an enhanced ability to colonize the bone. A comparison of gene expression between parental cells and sublines by genome-wide cDNA microarray analysis revealed several potential mediators of bone metastasis, including the pyrophosphate-generating ectoenzyme Enpp1. By qRT-PCR and Western analysis we found that expression of Enpp1 was elevated in human breast cancer cell lines known to produce bone metastasis in animal models compared to non-metastatic and normal mammary epithelial cell lines. Further, in clinical specimens, levels of Enpp1 were significantly elevated in human primary breast tumors relative to normal mammary epithelium, with highest levels observed in breast-bone metastasis as determined by qRT-PCR and immunohistochemical analysis. To examine the potential role of Enpp1 in the development of bone metastasis, Enpp1 expression was stably increased in the breast cancer cell line MDA-MB-231 and the ability to colonize the bone following intracardiac and direct intratibial injection of athymic nude mice was determined. By both routes of administration, increased expression of Enpp1 enhanced the ability of MDA-MB-231 cells to form tumors in the bone relative to cells expressing vector alone, as determined by digital radiography and histological analysis. Taken together, these data suggest a potential role for Enpp1 in the development of breast cancer bone metastasis.     

Therapeutic Potential of Matrix Metalloproteinase Inhibition in Breast Cancer

Matrix metalloproteinases (MMPs) are a family of zinc endopeptidases that cleave nearly all components of the extracellular matrix as well as many other soluble and cell‐associated proteins. MMPs have been implicated in normal physiological processes, including development, and in the acquisition and progression of the malignant phenotype. Disappointing results from a series of clinical trials testing small molecule, broad spectrum MMP inhibitors as cancer therapeutics led to a re‐evaluation of how MMPs function in the tumor microenvironment, and ongoing research continues to reveal that these proteins play complex roles in cancer development and progression. It is now clear that effective targeting of MMPs for therapeutic benefit will require selective inhibition of specific MMPs. Here, we provide an overview of the MMP family and its biological regulators, the tissue inhibitors of metalloproteinases (TIMPs). We then summarize recent research from model systems that elucidate how specific MMPs drive the malignant phenotype of breast cancer cells, including acquisition of cancer stem cell features and induction of the epithelial–mesenchymal transition, and we also outline clinical studies that implicate specific MMPs in breast cancer outcomes. We conclude by discussing ongoing strategies for development of inhibitors with therapeutic potential that are capable of selectively targeting the MMPs most responsible for tumor promotion, with special consideration of the potential of biologics including antibodies and engineered proteins based on the TIMP scaffold. J. Cell. Biochem. 118: 3531–3548, 2017. © 2017 The Authors. Journal of Cellular Biochemistry Published by Wiley Periodicals, Inc.     

Molecular Characteristics and Metastasis Predictor Genes of Triple-Negative Breast Cancer: A Clinical Study of Triple-Negative Breast Carcinomas

Background

Triple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible.

Methodology/Principal Findings

Clinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04–5.06, Cox P = 0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer.

Conclusions/Significance

Gene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.     

Unraveling the Hidden Heterogeneities of Breast Cancer Based on Functional miRNA Cluster

It has become increasingly clear that the current taxonomy of clinical phenotypes is mixed with molecular heterogeneity, which potentially affects the treatment effect for involved patients. Defining the hidden molecular-distinct diseases using modern large-scale genomic approaches is therefore useful for refining clinical practice and improving intervention strategies. Given that microRNA expression profiling has provided a powerful way to dissect hidden genetic heterogeneity for complex diseases, the aim of the study was to develop a bioinformatics approach that identifies microRNA features leading to the hidden subtyping of complex clinical phenotypes. The basic strategy of the proposed method was to identify optimal miRNA clusters by iteratively partitioning the sample and feature space using the two-ways super-paramagnetic clustering technique. We evaluated the obtained optimal miRNA cluster by determining the consistency of co-expression and the chromosome location among the within-cluster microRNAs, and concluded that the optimal miRNA cluster could lead to a natural partition of disease samples. We applied the proposed method to a publicly available microarray dataset of breast cancer patients that have notoriously heterogeneous phenotypes. We obtained a feature subset of 13 microRNAs that could classify the 71 breast cancer patients into five subtypes with significantly different five-year overall survival rates (45%, 82.4%, 70.6%, 100% and 60% respectively; p = 0.008). By building a multivariate Cox proportional-hazards prediction model for the feature subset, we identified has-miR-146b as one of the most significant predictor (p = 0.045; hazard ratios = 0.39). The proposed algorithm is a promising computational strategy for dissecting hidden genetic heterogeneity for complex diseases, and will be of value for improving cancer diagnosis and treatment.     

Search for Frequent Mutations in Genes Predisposing to Breast Cancer

DNA of oncological patients, including Ashkenazi Jews and Slavs, living in St. Petersburg was collected, and the resultant collection was screened for three common mutations of genes BRCA1andBRCA2by means of heteroduplex analysis. The mutation 5382insC in exon 20 of the BRCA1gene was found in four unrelated patients, including three Slavs and one Ashkenazi Jew, with a positive family history of breast cancer. The mutations 185delAG and 6174delT in the BRCA1and BRCA2genes, respectively, which are typical of Ashkenazi Jewish patients with breast cancer, were not found in the patients of either ethnicity living in St. Petersburg, although the 6174delT mutation was found in the control group of Ashkenazi Jews. A new 12-nucleotide duplication g.71741ins12nt found in intron 20 of the BRCA1gene was described. The high frequency of the 5382insC mutation in the BRCA1gene in patients with familial breast cancer in both St. Petersburg and Moscow indicates that Russian families with the history of breast cancer should be primarily tested for this mutation.     

乳腺癌发生的特征基因筛选及模式识别

本文选取癌症基因组图谱数据库的乳腺癌样本作为数据集,在全基因组的水平上研究乳腺癌病人从正常到发病Ⅰ期基因表达的变化,寻找与乳腺癌发病密切相关的特征基因,建立乳腺癌发生的模式识别分类方法,为乳腺癌预防及早期诊断提供理论支持.研究中,综合利用相关性、t检验、置信区间等统计学方法,建立乳腺癌发生特征基因筛选方法,获得与乳腺癌发生具有显著性差异的特征基因336个.通过机器学习方法建模,得到的分类准确率能达到98%以上,与之前乳腺癌相关的研究相比,准确率更高.同时采用KEGG(kyoto encyclopedia of genes and genomes)通路分析得到与基因显著相关(P0.05)的通路有8个,GO(gene ontology)基因功能富集分析显示与基因显著相关(P0.05)的功能有18个.最后对映射在8个通路中的一部分基因进行简要功能分析,说明了其在调控水平上的密切关系,表明识别的特征基因在乳腺癌的发生过程中有重要的作用,这对了解乳腺癌发病机理以及乳腺癌的早期诊断非常重要.     

Comprehensive Analysis of MicroRNA (miRNA) Targets in Breast Cancer Cells

MicroRNAs (miRNAs) regulate mRNA stability and translation through the action of the RNAi-induced silencing complex. In this study, we systematically identified endogenous miRNA target genes by using AGO2 immunoprecipitation (AGO2-IP) and microarray analyses in two breast cancer cell lines, MCF7 and MDA-MB-231, representing luminal and basal-like breast cancer, respectively. The expression levels of ∼70% of the AGO2-IP mRNAs were increased by DROSHA or DICER1 knockdown. In addition, integrated analysis of miRNA expression profiles, mRNA-AGO2 interaction, and the 3′-UTR of mRNAs revealed that >60% of the AGO2-IP mRNAs were putative targets of the 50 most abundantly expressed miRNAs. Together, these results suggested that the majority of the AGO2-associated mRNAs were bona fide miRNA targets. Functional enrichment analysis uncovered that the AGO2-IP mRNAs were involved in regulation of cell cycle, apoptosis, adhesion/migration/invasion, stress responses (e.g. DNA damage and endoplasmic reticulum stress and hypoxia), and cell-cell communication (e.g. Notch and Ephrin signaling pathways). A role of miRNAs in regulating cell migration/invasion and stress response was further defined by examining the impact of DROSHA knockdown on cell behaviors. We demonstrated that DROSHA knockdown enhanced cell migration and invasion, whereas it sensitized cells to cell death induced by suspension culture, glucose depletion, and unfolding protein stress. Data from an orthotopic xenograft model showed that DROSHA knockdown resulted in reduced growth of primary tumors but enhanced lung metastasis. Taken together, these results suggest that miRNAs collectively function to promote survival of tumor cells under stress but suppress cell migration/invasion in breast cancer cells.     

Abnormal Methylation of Several Tumor Suppressor Genes in Sporadic Breast Cancer

Multiplex methylation-sensitive PCR was employed in studying the methylation of CpG islands in the R1, p16/CDKN2, p15/CDKN2, p14/ARF, DH1, MGMT, HIC1, and N33 promoter regions in breast cancer (105 tumors). Methylation was often observed for the two major suppressor genes involved in controlling the cell cycle through the Cdk–Rb–E2F signaling pathway, R1 (18/105, 17%) and p16 (59/105, 56%); both genes were methylated in 13 tumors. Methylation involved p15 in two (2%) tumors; CDH1, in 83 (79%) tumors; MGMT, in eight (8%) tumors, and N33, in nine (9%) tumors. The p14 promoter was not methylated in the tumors examined.