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Critical analysis of the potential for microRNA biomarkers in breast cancer management.

ABSTRACT: Breast cancer is a complex and heterogeneous disease. Signaling by estrogen receptor (ER), progesterone receptor (PR), and/or human EGF-like receptor 2 (HER2) is a main driver in the development and progression of a large majority of breast tumors. Molecular characterization of primary tumors has identified major subtypes that correlate with ER/PR/HER2 status, and also subgroup divisions that indicate other molecular and cellular features of the tumors. While some of these research findings have been incorporated into clinical practice, several challenges remain to improve breast cancer management and patient survival, for which the integration of novel biomarkers into current practice should be beneficial. microRNAs (miRNAs) are a class of short non-coding regulatory RNAs with an etiological contribution to breast carcinogenesis. miRNA-based diagnostic and therapeutic applications are rapidly emerging as novel potential approaches to manage and treat breast cancer. Rapid technological development enables specific and sensitive detection of individual miRNAs or the entire miRNome in tissues, blood, and other biological specimens from breast cancer patients. This review focuses on recent miRNA research and its potential to address unmet clinical needs and challenges. The four sections presented discuss miRNA findings in the context of the following clinical challenges: biomarkers for early detection; prognostic and predictive biomarkers for treatment decisions using targeted therapies against ER and HER2; diagnostic and prognostic biomarkers for subgrouping of triple-negative breast cancer, for which there are currently no targeted therapies; and biomarkers for monitoring and characterization of metastatic breast cancer. The review concludes with a critical analysis of the current state of miRNA breast cancer research and the need for further studies using large patient cohorts under well-controlled conditions before considering the clinical implementation of miRNA biomarkers.

SUBMITTER: Graveel CR

PROVIDER: S-EPMC4346363 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Critical analysis of the potential for microRNA biomarkers in breast cancer management.

Graveel Carrie R CR Calderone Heather M HM Westerhuis Jennifer J JJ Winn Mary E ME Sempere Lorenzo F LF

Breast cancer (Dove Medical Press) 20150223

Breast cancer is a complex and heterogeneous disease. Signaling by estrogen receptor (ER), progesterone receptor (PR), and/or human EGF-like receptor 2 (HER2) is a main driver in the development and progression of a large majority of breast tumors. Molecular characterization of primary tumors has identified major subtypes that correlate with ER/PR/HER2 status, and also subgroup divisions that indicate other molecular and cellular features of the tumors. While some of these research findings have ...[more]

PMID: 25759599

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Project description:Membrane vesicles released by neoplastic cells into extracellular medium contain potential of carrying arrays of oncogenic molecules including proteins and microRNAs (miRNA). Extracellular (exosome-like) vesicles play a major role in cell-to-cell communication. Thus, the characterization of miRNAs of exosome-like vesicles is imperative in clarifying intercellular signaling as well as identifying disease markers. microarray analysis identified several oncogenic miRNA between the two types vesicles. Exosome-like vesicles were isolated using gradient centrifugation from MCF-7 and MDA-MB 231 cultures. Sample-derived miRNA expression was analyzed on Miltenyi's miRXplore™ platform. The RNA was isolated from two replicate samples of MDA-MB231 and MCF7 cell lines. The miRNAs extracted from all four samples were labeled with Hy5 and hybridized against Hy3-labeled Universal Reference miRNA (UR). Candidate miRNAs were identified. In this report, the re-ratios of MDA1 or MDA2 relative to a virtual pool of both MCF7 samples 1 and 2 were used for further analyses. 1- Reratio No. 7 MDA 1 vs MCF7 1+2 reratios of (MDA 1 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970041, (7970039 + 7970040) 2- Reratio No. 8 MDA 2 vs MCF7 1+2 reratios of (MDA 2 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970042, (7970039 + 7970040) Exosome-like vesicles were isolated using gradient centrifugation from MCF-7 and MDA-MB 231 cultures. Sample-derived miRNA expression was analyzed on Miltenyi's miRXplore™ platform. The RNA was isolated from two replicate samples of MDA-MB231 and MCF7 cell lines. The miRNAs extracted from all four samples were labeled with Hy5 and hybridized against Hy3-labeled Universal Reference miRNA (UR). Candidate miRNAs were identified. In this report, the re-ratios of MDA1 or MDA2 relative to a virtual pool of both MCF7 samples 1 and 2 were used for further analyses. 1- Reratio No. 7 MDA 1 vs MCF7 1+2 reratios of (MDA 1 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970041, (7970039 + 7970040) 2- Reratio No. 8 MDA 2 vs MCF7 1+2 reratios of (MDA 2 vs UR) and (MCF7 1 vs UR + MCF7 2 vs UR) 7970042, (7970039 + 7970040)

Project description:BackgroundIdentification of specific biological functions, pathways, and appropriate prognostic biomarkers is essential to accurately predict the clinical outcomes of and apply efficient treatment for breast cancer patients.MethodsTo search for metastatic breast cancer-specific biological functions, pathways, and novel biomarkers in breast cancer, gene expression datasets of metastatic breast cancer were obtained from Oncomine, an online data mining platform. Over- and under-expressed genesets were collected and the differentially expressed genes were screened from four datasets with large sample sizes (N > 200). They were analyzed for gene ontology (GO), KEGG pathway, protein-protein interaction, and hub gene analyses using online bioinformatic tools (Enrichr, STRING, and Cytoscape) to find enriched functions and pathways in metastatic breast cancer. To identify novel prognostic biomarkers in breast cancer, differentially expressed genes were screened from the entire twelve datasets with any sample sizes and tested for expression correlation and survival analyses using online tools such as KM plotter and bc-GenExMiner.ResultsCompared to non-metastatic breast cancer, 193 and 144 genes were differentially over- and under-expressed in metastatic breast cancer, respectively, and they were significantly enriched in regulating cell death, epidermal growth factor receptor signaling, and membrane and cytoskeletal structures according to the GO analyses. In addition, genes involved in progesterone- and estrogen-related signalings were enriched according to KEGG pathway analyses. Hub genes were identified via protein-protein interaction network analysis. Moreover, four differentially over-expressed (CCNA2, CENPN, DEPDC1, and TTK) and three differentially under-expressed genes (ABAT, LRIG1, and PGR) were further identified as novel biomarker candidate genes from the entire twelve datasets. Over- and under-expressed biomarker candidate genes were positively and negatively correlated with the aggressive and metastatic nature of breast cancer and were associated with poor and good prognosis of breast cancer patients, respectively.ConclusionsTranscriptome datasets of metastatic breast cancer obtained from Oncomine allow the identification of metastatic breast cancer-specific biological functions, pathways, and novel biomarkers to predict clinical outcomes of breast cancer patients. Further functional studies are needed to warrant validation of their roles as functional tumor-promoting or tumor-suppressing genes.

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Critical analysis of the potential for microRNA biomarkers in breast cancer management.

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Critical analysis of the potential for microRNA biomarkers in breast cancer management.

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