2,217 research outputs found

    A novel epigenetic AML1-ETO/THAP10/miR-383 mini-circuitry contributes to t(8;21) leukaemogenesis

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    DNA methylation patterns are frequently deregulated in t(8;21) acute myeloid leukaemia (AML), but little is known of the mechanisms by which specific gene sets become aberrantly methylated. Here, we found that the promoter DNA methylation signature of t(8;21)(+) AML blasts differs from that of t(8;21)(-) AMLs. This study demonstrated that a novel hypermethylated zinc finger-containing protein, THAP10, is a target gene and can be epigenetically suppressed by AML1-ETO at the transcriptional level in t(8;21) AML. Our findings also show that THAP10 is a bona fide target of miR-383 that can be epigenetically activated by the AML1-ETO recruiting co-activator p300. In this study, we demonstrated that epigenetic suppression of THAP10 is the mechanistic link between AML1-ETO fusion proteins and tyrosine kinase cascades. In addition, we showed that THAP10 is a nuclear protein that inhibits myeloid proliferation and promotes differentiation both in vitro and in vivo Altogether, our results revealed an unexpected and important epigenetic mini-circuit of AML1-ETO/THAP10/miR-383 in t(8;21) AML, in which epigenetic suppression of THAP10 predicts a poor clinical outcome and represents a novel therapeutic target

    DNMT Inhibitors Increase Methylation in the Cancer Genome

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    DNA methyltransferase inhibitors (DNMTi) decitabine and azacytidine are approved therapies for myelodysplastic syndrome and acute myeloid leukemia, and their combinations with other anticancer agents are being tested as therapeutic options for multiple solid cancers such as colon, ovarian, and lung cancer. However, the current therapeutic challenges of DNMTis include development of resistance, severe side effects and no or partial treatment responses, as observed in more than half of the patients. Therefore, there is a critical need to better understand the mechanisms of action of these drugs. In order to discover molecular targets of DNMTi therapy, we identified 638 novel CpGs with an increased methylation in response to decitabine treatment in HCT116 cell lines and validated the findings in multiple cancer types (e.g., bladder, ovarian, breast, and lymphoma) cell lines, bone marrow mononuclear cells from primary leukemia patients, as well as peripheral blood mononuclear cells and ascites from platinum resistance epithelial ovarian cancer patients. Azacytidine treatment also increased methylation of these CpGs in colon, ovarian, breast, and lymphoma cancer cell lines. Methylation at 166 identified CpGs strongly correlated (vertical bar r vertical bar >= 0.80) with corresponding gene expression in HCT116 cell line. Differences in methylation at some of the identified CpGs and expression changes of the corresponding genes was observed in TCGA colon cancer tissue as compared to adjacent healthy tissue. Our analysis revealed that hypermethylated CpGs are involved in cancer cell proliferation and apoptosis by P53 and olfactory receptor pathways, hence influencing DNMTi responses. In conclusion, we showed hypermethylation of CpGs as a novel mechanism of action for DNMTi agents and identified 638 hypermethylated molecular targets (CpGs) common to decitabine and azacytidine therapy. These novel results suggest that hypermethylation of CpGs should be considered when predicting the DNMTi responses and side effects in cancer patients.Peer reviewe

    ITIH5 mediates epigenetic reprogramming of breast cancer cells

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    Extracellular matrix (ECM) is known to maintain epithelial integrity. In carcinogenesis ECM degradation triggers metastasis by controlling migration and differentiation including cancer stem cell (CSC) characteristics. The ECM-modulator inter- α-trypsin inhibitor heavy chain family member five (ITIH5) was recently identified as tumor suppressor potentially involved in impairing breast cancer progression but molecular mechanisms underlying its function are still elusive

    Regulators Associated with Clinical Outcomes Revealed by Dna Methylation Data in Breast Cancer

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    The regulatory architecture of breast cancer is extraordinarily complex and gene misregulation can occur at many levels, with transcriptional malfunction being a major cause. This dysfunctional process typically involves additional regulatory modulators including DNA methylation. Thus, the interplay between transcription factor (TF) binding and DNA methylation are two components of a cancer regulatory interactome presumed to display correlated signals. As proof of concept, we performed a systematic motif-based in silico analysis to infer all potential TFs that are involved in breast cancer prognosis through an association with DNA methylation changes. Using breast cancer DNA methylation and clinical data derived from The Cancer Genome Atlas (TCGA), we carried out a systematic inference of TFs whose misregulation underlie different clinical subtypes of breast cancer. Our analysis identified TFs known to be associated with clinical outcomes of p53 and ER (estrogen receptor) subtypes of breast cancer, while also predicting new TFs that may also be involved. Furthermore, our results suggest that misregulation in breast cancer can be caused by the binding of alternative factors to the binding sites of TFs whose activity has been ablated. Overall, this study provides a comprehensive analysis that links DNA methylation to TF binding to patient prognosis

    Identifying the molecular components that matter: a statistical modelling approach to linking functional genomics data to cell physiology

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    Functional genomics technologies, in which thousands of mRNAs, proteins, or metabolites can be measured in single experiments, have contributed to reshape biological investigations. One of the most important issues in the analysis of the generated large datasets is the selection of relatively small sub-sets of variables that are predictive of the physiological state of a cell or tissue. In this thesis, a truly multivariate variable selection framework using diverse functional genomics data has been developed, characterized, and tested. This framework has also been used to prove that it is possible to predict the physiological state of the tumour from the molecular state of adjacent normal cells. This allows us to identify novel genes involved in cell to cell communication. Then, using a network inference technique networks representing cell-cell communication in prostate cancer have been inferred. The analysis of these networks has revealed interesting properties that suggests a crucial role of directional signals in controlling the interplay between normal and tumour cell to cell communication. Experimental verification performed in our laboratory has provided evidence that one of the identified genes could be a novel tumour suppressor gene. In conclusion, the findings and methods reported in this thesis have contributed to further understanding of cell to cell interaction and multivariate variable selection not only by applying and extending previous work, but also by proposing novel approaches that can be applied to any functional genomics data

    Method of identifying and treating invasive carcinomas (CIP)

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    Prostasin protein has been found to be a useful marker for determination of the invasiveness of and as a means to treat human carcinomas. Using RT-PCR and western blot analyses, prostasin protein and mRNA expression were found in normal human prostate epithelial cells and the human prostate cancer cell line LNCaP, but not in the highly invasive human prostate cancer cell lines DU-145 and PC-3. Imunohistochemistry studies of human prostate cancer specimens revealed a down-regulation of prostasin in high-grade tumors. Using RT-PCR and western blot analyses, prostasin protein and mRNA expression were found in a non-invasive human breast cancer cell line, MCF-7, while invasive human breast cancer cell lines MDA-MB-231 and MDA-MB-435s were found not to express either the prostasin protein or the mRNA. A non-invasive human breast cancer cell line, MDA-MB-453, was shown to express prostasin mRNA but not prostasin protein. Transfection of DU-145 and PC-3 cells with a full-length human prostas
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