173 research outputs found

    Computational analysis of microRNA profiles and their target genes suggests significant involvement in breast cancer antiestrogen resistance

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    Motivation: Recent evidence shows significant involvement of microRNAs (miRNAs) in the initiation and progression of numerous cancers; however, the role of these in tumor drug resistance remains unknown

    Dysregulation of microRNA expression in acquired endocrine-resistant breast cancer.

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    MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level by repressing translation or stimulating mRNA degradation. In this study, I tested the hypothesis that miRNAs are differentially expressed in antiestrogen-sensitive MCF-7 versus -resistant L Y2 human breast cancer cells. Microarray analyses identified 97 miRNAs that are differentially expressed between two estrogen receptor alpha (ERa) -positive human breast cancer cell lines: endocrine-sensitive MCF-7 versus -resistant L Y2 cells under basal conditions. Opposite expression of miRs-lOa,-21, -22, -12Sb, -181, -200a, -200b, -200c, -221, and -222 was confirmed between MCF-7 and L Y2 cells. The ER antagonist ICI 182,780 (fulvestrant or Faslodex) generally blocked the effect of estradiol E2 and 4-hydroxytamoxifen (4-OHT) regulated miRs, i.e .. , miR-lOa, miR-21, miR-22, miR-200a, miR-221, and miR-222, indicating that these responses in MCF-7 cells are ER-mediated. Time dependent variation in basal (ethanol, the vehicle), E2, and 4-0HT regulation of the top 8 miRNAs was detected in MCF-7 cells. Bioinformatic analyses to impute the biological significance of the identified miRNAs by identifying their computationally predicted target genes in the human genome using TargetScan, Pic Tar, and the Sanger miRBase Targets databases was performed. Thirty six putative mRNA targets were identified. Agreement in the direction of anticipated regulation was detected for 12 putative targets. These miRNAs showing opposite expression between these two breast cancer cell lines may be involved in endocrine resistance. MiR-200 family includes two clusters i.e. miR-200 a/200 b/ 429 and miR-200c/141 encoded on chromosome 1 and chromosome 12, respectively. Lower miR-200a, miR-200 b and miR-200c expression was observed in estrogen-independent LCC1 and endocrine-resistant LCC2, LCC9, and LY2 compared to the parental, endocrine-sensitive MCF-7 human breast cancer cell line. ZEB 1 protein was found to be expressed in endocrine-resistant LY2 cells but not in endocrine-sensitive MCF-7 cells. L Y2 cells did not express E-cadherin, a ZEB 1 target which is a marker for epithelial phenotype. This is the first demonstration that L Y2 cells have undergone EMT as part of their endocrine-resistant phenotype. Concomitant with miR-200 decrease, there was an increase in ZEB 1 mRNA expression m L Y2 cells. Overexpression of miR-200b or miR-200c in LY2 cells changed the cellular morphology from a mesenchymal to an epithelial appearance and sensitized cells to inhibition by 4-0HT and fulvestrant. These studies indicate that reduced expression of miR-200 and a corresponding increase in ZEB 1 protein is an indicator of endocrine-resistance in breast cancer cells

    Prioritization of disease microRNAs through a human phenome-microRNAome network

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    <p>Abstract</p> <p>Background</p> <p>The identification of disease-related microRNAs is vital for understanding the pathogenesis of diseases at the molecular level, and is critical for designing specific molecular tools for diagnosis, treatment and prevention. Experimental identification of disease-related microRNAs poses considerable difficulties. Computational analysis of microRNA-disease associations is an important complementary means for prioritizing microRNAs for further experimental examination.</p> <p>Results</p> <p>Herein, we devised a computational model to infer potential microRNA-disease associations by prioritizing the entire human microRNAome for diseases of interest. We tested the model on 270 known experimentally verified microRNA-disease associations and achieved an area under the ROC curve of 75.80%. Moreover, we demonstrated that the model is applicable to diseases with which no known microRNAs are associated. The microRNAome-wide prioritization of microRNAs for 1,599 disease phenotypes is publicly released to facilitate future identification of disease-related microRNAs.</p> <p>Conclusions</p> <p>We presented a network-based approach that can infer potential microRNA-disease associations and drive testable hypotheses for the experimental efforts to identify the roles of microRNAs in human diseases.</p

    The Role of GLI-1 in Endocrine Resistant Breast Cancer

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    Estrogen receptor positive (ER+) and estrogen receptor negative (ER-) are two major types of breast cancer. For women with ER+ positive breast cancer, patients are treated with the antiestrogenic compounds, tamoxifen or faslodex for five years, immediately after surgical resection of tumors. Unfortunately, 30-40% of these patients will develop resistance to endocrine therapy. Our recent study has shown that the Hedgehog (Hhg) signaling pathway plays a significant role in endocrine resistance and that the aberrantly activated transcription factor, GLI-1, is vital to the development of resistance. However, not much is known about the GLI-1 target genes that might contribute to endocrine resistance. Our goal is to determine novel target genes of GLI-1 and determine how these genes promote endocrine therapy resistance.PelotoniaA five-year embargo was granted for this item.Academic Major: Biomedical Scienc

    Computational analysis of genomic variants affecting predicted microRNA:target interactions in prostate cancer.

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    Prostate cancer (PCa) is the most common cancer of men in the United States and is third only to lung and colon as a cause of cancer death. Clinical behavior of the disease is variable and the combination of prostate-specific antigen (PSA) screening and Gleason score staging are currently the best available molecular and pathology tools to predict outcomes. Cancer biology research establishes microRNAs (miRNAs) as key molecular components in both normal and pathological states. Thus, elucidating miRNAs perturbed by genomic alterations will expand our understanding of the molecular taxonomy of PCa with the aim to complement current practices in the diagnosis, prognosis, and treatment of the disease. This study reports the computational analysis of genomic variants affecting the seed sequence of five miRNAs, changing the prediction of microRNA:target interactions in PC3, an androgen-independent cell line that closely resembles prostatic small cell neuroendocrine carcinoma (SCNC). Genomic variants were detected via deep-sequencing of PC3 and further computational work focused on mapping changes within the seed sequence of predicted mature miRNAs. Five microRNA candidates (from now on denominated microRNA*) with changes in the g2-g8 seed region were selected: miR-3161*-5p with rs35834266 G\u3einsA; miR-3620*-5p with rs2070960 C\u3eT; miR-1178*-5p with rs7311975 T\u3eG; miR-4804*-5pwith rs266435 C\u3eG; and miR-449c*-3p with rs35770269 A\u3eT. Subsequently, the computational prediction of miRNA*:target interactions revealed 643 new relationships. After functional enrichment analysis of new targets, seven genes were associated with endocrine resistance (ABCB11, CDKN1B, NOTCH2, SHC4, CCND1, SP1, ADCY2) and five genes with endocrine and other factor regulated calcium reabsorption (ATP1A2, ESR1, PRRKCB, AP2B1, SLC8A1) categories. A gene-disease association literature search was performed for each of the aforementioned genes in order to understand if they have been implicated in cancer, where CDKN1B, NOTCH2, CCND1 have been reported to participate in prostate cancer progression. Microarray gene expression analyses showed that few predicted microRNA* targets were underexpressed in untreated PC3 samples versus prostate epithelial cells from the GEO database. However, after assessing the frequency of observed underexpressed genes per candidate microRNA* using a Fisher’s exact test, miR-4804*-5p target genes (TNKS and GUCY1A3) were statistically significant. Next steps included the comparison between groups of genes subject to non-mutated microRNA and mutated microRNA* regulation using a Kruskal-Wallis non-parametric test. Results were consistent with the microRNA-gene expression regulation model despite the genomic variant in the seed region, nevertheless the effect of miR-3161*-5p, miR-3620*-5p, miR-1178*-5p, miR-4804*-5p, and miR-449c*-3p cannot be predicted solely with the indirect experimental approach that microarray gene expression platforms provide. For this reason, the assessment of recurrent pairwise microRNA-mRNA expression associations was performed using CancerMiner, an online tool from The Cancer Genome Atlas (TCGA) based on a multivariate linear model and rank transformations. Only the relationship of miRNA-3161:CDKN1B was retrieved as a recurrent expression association in uterine corpus endometrial carcinoma (UCEC). In the context of this study, results suggest that CDKN1B (p27Kip1)dysregulation by miR-3161*-5p would be leading to PC3 super proliferation due to the lack of cell cycle arrest from phase G1 to S. Prostate cancer cell line PC3 has shown to share features with prostatic small cell neuroendocrine carcinomas (SCNC) with the implication that molecular mechanisms and therapeutic efficacies observed with PC3 cells are likely applicable to SCNC1. Prostatic small cell neuroendocrine carcinoma is a variant form of prostate cancer often characterized by an aggressive course with a poor response to conventional androgen deprivation therapy (ADT), consistent with the lack of the androgen receptor in prostatic small cell carcinoma (SCC)2. In some men treated with ADT, development of small cell carcinoma might represent the “escape” of a subpopulation of hormone-independent cells resulting from the selective pressure of hormonal therapy3. Hence, the suggestion of CDKN1B dysregulation by miR-3161*-5p might go beyond the idiosyncrasy of the PC3 cell line, but rather an interesting future direction to investigate prostate cancer patients with SCNC rendering to an adverse disease outcome due to uncontrolled cell proliferation

    BioVLAB-MMIA-NGS: MicroRNA-mRNA Integrated Analysis using High Throughput Sequencing Data

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    Motivation: It is now well established that microRNAs (miRNAs) play a critical role in regulating gene expression in a sequence-specific manner, and genome-wide efforts are underway to predict known and novel miRNA targets. However, the integrated miRNA–mRNA analysis remains a major computational challenge, requiring powerful informatics systems and bioinformatics expertise. Results: The objective of this study was to modify our widely recognized Web server for the integrated mRNA–miRNA analysis (MMIA) and its subsequent deployment on the Amazon cloud (BioVLAB-MMIA) to be compatible with high-throughput platforms, including next-generation sequencing (NGS) data (e.g. RNA-seq). We developed a new version called the BioVLAB-MMIA-NGS, deployed on both Amazon cloud and on a high-performance publicly available server called MAHA. By using NGS data and integrating various bioinformatics tools and databases, BioVLAB-MMIA-NGS offers several advantages. First, sequencing data is more accurate than array-based methods for determining miRNA expression levels. Second, potential novel miRNAs can be detected by using various computational methods for characterizing miRNAs. Third, because miRNA-mediated gene regulation is due to hybridization of an miRNA to its target mRNA, sequencing data can be used to identify many-to-many relationship between miRNAs and target genes with high accuracy

    RNA Polymerase II Binding Patterns Reveal Genomic Regions Involved in MicroRNA Gene Regulation

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    MicroRNAs are small non-coding RNAs involved in post-transcriptional regulation of gene expression. Due to the poor annotation of primary microRNA (pri-microRNA) transcripts, the precise location of promoter regions driving expression of many microRNA genes is enigmatic. This deficiency hinders our understanding of microRNA-mediated regulatory networks. In this study, we develop a computational approach to identify the promoter region and transcription start site (TSS) of pri-microRNAs actively transcribed using genome-wide RNA Polymerase II (RPol II) binding patterns derived from ChIP-seq data. Based upon the assumption that the distribution of RPol II binding patterns around the TSS of microRNA and protein coding genes are similar, we designed a statistical model to mimic RPol II binding patterns around the TSS of highly expressed, well-annotated promoter regions of protein coding genes. We used this model to systematically scan the regions upstream of all intergenic microRNAs for RPol II binding patterns similar to those of TSS from protein coding genes. We validated our findings by examining the conservation, CpG content, and activating histone marks in the identified promoter regions. We applied our model to assess changes in microRNA transcription in steroid hormone-treated breast cancer cells. The results demonstrate many microRNA genes have lost hormone-dependent regulation in tamoxifen-resistant breast cancer cells. MicroRNA promoter identification based upon RPol II binding patterns provides important temporal and spatial measurements regarding the initiation of transcription, and therefore allows comparison of transcription activities between different conditions, such as normal and disease states

    Integrative analysis of miRNA and gene expression reveals regulatory networks in tamoxifen-resistant breast cancer

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    Tamoxifen is an effective anti-estrogen treatment for patients with estrogen receptor-positive (ER+) breast cancer, however, tamoxifen resistance is frequently observed. To elucidate the underlying molecular mechanisms of tamoxifen resistance, we performed a systematic analysis of miRNA-mediated gene regulation in three clinically-relevant tamoxifen-resistant breast cancer cell lines (TamRs) compared to their parental tamoxifen-sensitive cell line. Alterations in the expression of 131 miRNAs in tamoxifen-resistant vs. parental cell lines were identified, 22 of which were common to all TamRs using both sequencing and LNA-based quantitative PCR technologies. Although the target genes affected by the altered miRNA in the three TamRs differed, good agreement in terms of affected molecular pathways was observed. Moreover, we found evidence of miRNA-mediated regulation of ESR1, PGR1, FOXM1 and 14-3-3 family genes. Integrating the inferred miRNA-target relationships, we investigated the functional importance of 2 central genes, SNAI2 and FYN, which showed increased expression in TamR cells, while their corresponding regulatory miRNA were downregulated. Using specific chemical inhibitors and siRNA-mediated gene knockdown, we showed that both SNAI2 and FYN significantly affect the growth of TamR cell lines. Finally, we show that a combination of 2 miRNAs (miR-190b and miR-516a-5p) exhibiting altered expression in TamR cell lines were predictive of treatment outcome in a cohort of ER+ breast cancer patients receiving adjuvant tamoxifen mono-therapy. Our results provide new insight into the molecular mechanisms of tamoxifen resistance and may form the basis for future medical intervention for the large number of women with tamoxifen-resistant ER+ breast cancer

    Role of MIR-29B-1 and MIR-29A in endocrine-resistant breast cancer.

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    Therapies targeting estrogen receptor α (ERα) including selective estrogen receptor modulators (SERMs), e.g., tamoxifen (TAM); selective estrogen receptor downregulators (SERDs), e.g., fulvestrant (ICI 182,780); and aromatase inhibitors (AI), e.g., letrozole, are successfully used in treating breast cancer patients whose initial tumor expresses ERα. Unfortunately, the effectiveness of endocrine therapies is limited as ~ 40% of breast cancer patients will eventually acquire resistance to them. The role of miRNAs in the progression of endocrine-resistant breast cancer is of keen interest in developing biomarkers and therapies to counter metastatic disease. This dissertation begins with a review on miRNAs implicated in breast cancer, their bona fide gene targets, and associated pathways promoting endocrine resistance. Although microRNAs are dysregulated in breast cancer, their contribution to endocrine-resistance is not yet fully understood. Previous microarray analysis identified miR-29a and miR-29b-1 as repressed by TAM in MCF-7 endocrine-sensitive breast cancer cells but stimulated by TAM in LY2 endocrine-resistant breast cancer cells. Here we examined the mechanism for the differential regulation of these miRs by TAM in MCF-7 versus TAM-resistant LY2 and LCC9 breast cancer cells and the functional role of these microRNAs in these cells. Knockdown studies revealed that ERα is responsible for TAM regulation of miR-29b-1/a transcription. Transient overexpression of miR-29b-1/a decreased MCF-7, LCC9, and LY2 proliferation and inhibited LY2 cell migration and colony formation but did not sensitize LCC9 or LY2 cells to TAM. Furthermore, TAM reduced DICER1 mRNA and protein in LY2 cells, a known target of miR-29. Supporting this observation, anti-miR-29b-1 or anti-miR-29a inhibited the suppression of DICER by 4-OHT. These results suggest that miR-29b-1/a have tumor suppressor activity in TAM-resistant cells and do not appear to play a role in mediating TAM resistance. The target genes mediating miR-29b-1/a tumor suppressor activity were unknown. Here, using RNA sequencing, we identify miR-29b-1 and miR-29a target transcripts in both MCF-7 and LCC9 cells. We find that miR-29b-1 and miR-29a regulate common and unique transcripts in each cell line. The cell-specific and common downregulated genes were characterized using the MetaCore Gene Ontology (GO) enrichment analysis algorithm. LCC9-sepecific miR-29b-1/a-regulated GO processes include oxidative phosphorylation, ATP metabolism, and apoptosis. Extracellular flux analysis of cells transfected with anti- or pre- miR-29a confirmed that miR-29a inhibits mitochondrial bioenergetics in LCC9 cells. qPCR and luciferase reporter assays also verified the ATP synthase subunit genes ATP5G1 and ATPIF1 as bona fide miR29b-1/a targets. Our results suggest that miR-29 repression of TAM-resistant breast cancer cell proliferation is mediated in part through repression of genes important in mitochondrial bioenergetics. There is a critical need to develop sensitive circulating biomarkers that accurately identify signaling pathways altered in breast cancer patients resistant to endocrine therapies. Serum miRNAs have the potential to serve as biomarkers of the progression of endocrine-resistant breast cancer due to their cancer-specific expression and stability. Exosomal transfer of miRNAs has been implicated in metastasis and endocrine-resistance. This dissertation ends with a review on miRNAs in breast tumors and in serum, including exosomes, from breast cancer patients that are associated with resistance to tamoxifen

    Exploring the genome-wide impact of estrogen receptor alpha and estrogen receptor beta in breast and colon cancer cells

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    Estrogen signaling is involved in the development and progression of breast cancer and is implicated to be protective in colon cancer. Estrogenic actions are conveyed through transcriptional regulation by ligand stimulated estrogen receptors (ERα and ERβ). ERα is upregulated in most breast cancers and is responsible for the proliferative effect of estrogen. ERβ on the other hand is usually downregulated, and studies indicate an antiproliferative function. Therapies targeting ERα are available and commonly used in the treatment of breast cancer. In the normal colonic epithelia, however, ERβ is the most abundant estrogen receptor and the suggested mediator of the protective effects of estrogen in colon cancer. The role of ERβ in breast cancer and colon cancer is not well understood. Thus, exploring the genome-wide impact and contribution of both receptors in estrogen responsive cancers would substantially help to identify novel therapeutic and preventive strategies for these cancers. In Paper 1, we examined differences in transcriptional regulation between ERα and ERβ in the breast cancer cell line T47D. We could show that ERβ often exhibited an opposing effect on ERα-regulated genes within proliferation and regulation of cell cycle. We also demonstrated a set of genes only regulated by ERβ, indicating that, despite the high homology between the two receptors, there are differences in their transcriptional targets. The fact that ERβ opposed ERα indicates that ERβ activation may be of value in the treatment of breast cancer. To further explore the transcriptional role of ERα in breast cancer, we performed large-scale analyses of microRNA in 24 hours estrogen treated ERα-expressing T47D cells, Paper II. However, we found no evidence of direct and rapid regulation of mature miRNAs by ERα. In Paper III, we studied ERβ gene regulation in colon cancer cells. We could show that ERβ-expressing xenografts grew significantly slower than those lacking ERβ. Further we demonstrated that ERβ induced a transcriptional response independently of ERα and induced inhibition of the proto-oncogene MYC and other G1-phase cell cycle genes. In Paper IV, we dissected the regulatory networks of ERβ-induced transcriptional changes in human colon cancer cells. The set of genes changed by ERβ varied in different colon cancer cell lines, however, corresponded to the same biological processes such as cell cycle regulation and kinase activity. In addition, we identified the ERβ-driven downregulation of the transcription factor PROX1 as a key mechanism behind a large proportion of the transcriptional changes. In Paper V, we studied the effect of long term expression of ERβ on the miRNA pool in SW480 colon cancer cells. While we could not show a direct and rapid effect of ERα on the miRNome, we showed that long term expression of ERβ did induce large changes in the miRNA pool in colon cancer cells. In particular, we found the oncogenic miR-17-92 cluster to be downregulated and proposed this to be a consequence of the ERβ-induced downregulation of MYC. In conclusion, we have shown that ERβ is antiproliferative in breast and colon cancer cells, both when co-expressed with ERα and alone, as well as identified key signaling pathways. We suggest that activation of ERβ will have a beneficial effect for treatment or prevention of estrogen dependent cancers
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