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    Cellular reprogramming

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    DNA-methylatie is een epigenetische modificatie. Dit type van modificaties verandert de genetische informatie zelf niet, maar wijzigt de laag erboven. Er worden chemische modificaties toegevoegd of gewijzigd op het DNA of de histonen (waarrond het DNA gewonden is). DNA-methylatie is die modificatie waarbij een methylgroep wordt aangebracht op het cytosine (C) residue en een CG dincucleotide. Als deze wijziging plaats vindt in een zogenaamd CpG eiland (waar deze CG dinucleotiden dens bij elkaar voorkomen) van de promoter van een gen, wordt dit gen niet meer afgeschreven en zal zijn functie verloren gaan. In dit proefschrift worden verschillende aspecten van DNA-methylatie en het belang ervan in de oncologie belicht. In het eerste onderzoeksdeel hebben we verschillende methodes en algoritmes ontwikkeld om methylatiemerkers te identificeren: genen die specifiek in kanker worden gemethyleerd maar niet in normale weefsels of genen die enkel worden gemethyleerd in bepaalde patiëntsubgroepen (bv. die respons vertonen voor een bepaalde chemotherapie). We hebben een databank en methodes gemaakt om kennis uit de literatuur in het snelgroeiende DNA-methylatie veld te halen. Deze databank (PubMeth) laat toe om het verband na te gaan tussen genen en hun methylatiepatroon in verschillende kanker (sub)types. Daarnaast werden verschillende sorterings- en selectiemethodieken ontwikkeld om zo een prioriteit toe te kennen aan de kandidaat DNA-methylatiemerkers. Al deze methodes werden ontwikkeld om data van genoom-wijde experimenten te kunnen verwerken. Nieuwe methylatiemerkers (gemethyleerd in kanker maar niet in normaal) kunnen worden gebruik bij vroegtijdige detectie van kanker. Er werden verschillende computationele oplossingen voorgesteld: - Relaxation ranking: sorteermethodiek gebaseerd op expressie micro-arrays van primair baarmoederhalskanker patiëntmateriaal en re-expressie experimenten op baarmoederhalskanker cellijnen. Deze methode is gebaseerd op lage expressie in kanker en re-expressie na behandeling met het de-methylerend agens DAC en de histondeacetylase inhibitor TSA. De methode gebruikt geen enkele (arbitrair te kiezen) grenswaarde - De deep approach: er werden verschillende DNA-motieven in de promoterregio van genen geïdentificeerd die discrimineren tussen kankerspecifiek gemethyleerde genen en genen die ook gemethyleerd worden in normale weefsels. - De broad approach maakt gebruik van een genoom-wijde alignering van promoterregio’s. Hieruit blijkt dat gekende methylatiemerkers meer dens geclusterd zijn dan verwacht. - Zowel ‘deep’ als ‘broad’ werden gecombineerd met re-expressie studies in cellijnen van verschillende kankertypes. De combinatie van deze experimentele filter en de computationele aanpak verhoogt de succesratio bij het vinden van kankerspecifiek gemethyleerde genen aanzienlijk. - Er werden ook merkers geïdentificeerd die mogelijks de respons op chemotherapie (platinum) kunnen voorspellen in eierstokkanker. Dit opent de weg naar gepersonaliseerde geneeskunde. De methodiek gebruikt een score-schema gebaseerd op zowel primaire kanker stalen (van zowel platinumgevoelige als resistente patiënten) als re-expressie experimenten op kanker cellijnen. De nieuwe identificatiestrategieën werden gevalideerd op primaire kankerstalen en presteren goed: ten opzichte van beschreven priorizatietechnieken is de succesratio verhoogd. Verscheidene nieuwe methylatie biomerkers in verschillende kankertypes (baarmoederhalskanker, eierstok-kanker, hoofd- en nekkanker, neuroblastoom,…) werden succesvol gevalideerd op primaire patiëntenstalen. Vervolgonderzoek op grotere patiëntengroepen zal het mogelijk diagnostische potentieel aantonen. De validatie van sommige studies is momenteel nog lopende. Dit toont de noodzaak aan van snelle en betrouwbare analysetechnieken die geschikt zijn voor validatiedoeleinden. Ten tweede werd er een uniek viraal infectiesysteem gecombineerd met een genoom-wijde methylatiegevoelige detectietechniek om epigenetische ‘herprogrammering’ van humane gastheercellen na infectie met hoge-risico HPV (Humaan Papilloma Virus) te onderzoeken. In dit experi-ment geven we sterke indicaties dat het virus in staat is de gastheercel epigenetisch te wijzigen. Deze hr-HPV virustypes zijn duidelijk geassocieerd met de ontwikkeling van baarmoederhalskanker gezien meer dan 99 % van de patiënten besmet is. Momenteel is het uitstrijkje een wijdverspreide screening methodiek die wordt gebruikt bij vroegdetectie. Onlangs werden er ook vaccins op de markt gebracht die infectie met de meest voorkomende virustypes (ongeveer 80 % van de infecties) moet voorkomen. De vaccinatie zou moeten gebeuren bij meisjes voor het eerste seksueel contact. De ontdekking van biomerkers met hoge specificiteit en sensitiviteit bij baarmoederhalskanker blijft noodzakelijk voor de niet gevaccineerde groep en gezien de vaccins niet tegen alle virustypes bescherming bieden. DNA-methylatiemerkers zijn uitstekende kandida-ten voor vroegdetectie in een screeningsprogramma: ze kunnen op grote schaal en geautomatiseerd gebeuren. Gezien er aangenomen wordt dat verschillende kankertypes verwant zijn met virusinfecties, verhoogt dit onderzoek de kennis bij dit proces en opent dit de weg naar zeer vroege detectie. Momenteel zijn enkel delen van het ‘kanker epigenoom’ bekend. De komst van methodes die grote hoeveelheden data genereren (zoals volgende-generatie sequenering) zou de bestaande kennis in grote mate kunnen laten toenemen. Dit vereist echter grote collecties primaire kankerstalen (liefst nog in verschillende stadia). Een centraal beheerde, goed geannoteerde bibliotheek van patiëntenmateriaal die verschillende kankertypes bevat, zou het onderzoek in een stroomversnelling plaatsen. Bijkomende uitdaging is dat deze technieken het hoogste niveau van precisie hebben (op baseniveau van een enkele DNA-molecule) en tegelijkertijd een hoog aantal stalen verwerken. Dit betekent dat bij het proefopzet sequentiestukken moeten gekozen worden die aangerijkt zijn aan DNA-methylatie of histonmodificaties. De data-analyse strategie moet snel genoeg zijn maar toch nieuwe kennis extraheren uit de terabytes ruwe data die gegenereerd worden. Ons labo werkt zowel op de ontwikkeling van een goed proefopzet als de verwerking van de gegenereerde data.DNA-methylation is an epigenetic modification. These modifications of the DNA do not change the genetic sequence itself, but affect the level ‘above’ it: chemical modifications of the DNA or the histones (where the DNA is wound around) are added or altered. DNA-methylation is the modification where a methyl group is added on cytosine (C) residues in CG dinucleotides. If this takes place in the so-called CpG islands (where CG dinucleotides occur very densely) within the promoter of a gene, this gene is silenced, and will not be transcribed; its function is lost. In this thesis, different aspects of DNA-methylation and its importance in the field of oncology has been dealt with. First, we created different methodologies and algorithms to identify methylation markers: genes that are specifically methylated in cancer but not in normal tissue or genes, methylated in subgroups of patients (e.g. responders of a certain chemotherapy). We built a database and methodologies to discover existing publications in the fast-growing DNA-methylation field. This database (PubMeth) allows to screen which genes are reported methylated in the selected cancer (sub)types and vice versa. Different ranking, sorting and selection techniques were developed to prioritize promising methylation marker candidates. These methodologies were all developed to deal with data from genome-wide approaches. Novel methylation markers (methylated in cancer while not in normal) could be used as early detection markers. Different computational approaches are described here: - Relaxation ranking: ranking strategy based on expression micro-arrays of primary cervical cancer samples and re-expression experiments on cervical cancer cell lines. This methodology is based on low expression in cancer samples and re-expression after treatment with the demethylation agent DAC and the histone de-acetylase inhibitor TSA. The methodology involves no thresholds. - The deep approach: different DNA-patterns in the promoter region of genes were identified that seem to discriminate between cancer-specifically methylated genes and genes that also are me-thylated in normal tissues. - The broad approach makes use of a genome-wide alignment of promoter regions. Apparently, genes described as methylation markers, are more densely clustered together. - Both the deep approach and the broad approach were combined with data from re-expression studies in cancer cell lines. The combination of this experimental filter and the computational approaches drastically improves the success rate in finding cancer-specific methylation markers in various cancer types. - There were also markers discovered, that may be able to predict chemotherapy (platinum) response in ovarian cancer, clearing the roads towards personalized medicine. The methodology uses a score-scheme, based on both primary cancer samples (from patients sensitive and resistant to platinum therapies) as re-expression experiments of ovarium cancer cell lines (both cisplatin resistant and sensitive). The novel identification strategies were validated on primary cancer samples and perform well: the success rate was improved in comparison with other prioritization attempts. Several novel methylation markers were discovered in different cancer types (cervical cancer, ovarian cancer, head-and-neck cancer, neuroblastoma, …) and were validated on primary samples. Follow-up research on larger clinical cohorts will demonstrate their potential diagnostic power. For some studies, the validation effort is still in progress; this illustrates the need for fast and accurate analysis techniques, suitable for validation purposes. Secondly, a unique viral infection system, combined with a ge-nome-wide methylation detection methodology was used to investigate the epigenetic ‘reprogramming’ of human host cells after infection with high-risk HPV (Human Papilloma Virus). In this experiment, we prove that a virus is able to epigenetically program their host cell. The high-risk HPV types are clearly related with the development of cervical cancer as more than 99 % of the patients is infected with such a virus type. For the moment, the cytological Pap-smear screening technique is widespread and used for early detection. Recently, vaccines were developed in order to prevent infection with the most prominent virus types (about 80 % of infections covered). The vaccination strategy must be applied in young girls (before sexual contact). The discovery of cervical cancer biomarkers with high sensitivity and specificity remains necessary for the non-vaccinated group and screening programs remain needed as the vaccines do not cover all hr-HPV virus types. DNA-methylation markers that seem to be related with infection with the virus, are ideal candidates for very early detection in a screening program: large scale analysis can be automated. As it is believed that multiple cancers may occur after viral infec-tion, or at least that these infections plays a key role in the development, this broadens the knowledge in this process and opens ways to very early detection. Currently, only fractions of the cancer epigenome are known. The introduction of methods that generate significantly large amounts of data (such as next generation sequencing) might be able to greatly expand the current knowledge. However, large collections of primary cancer samples (preferentially of different stages) will be needed. A centrally managed, well described and annotated library of patient material containing different cancer types would be extremely beneficial. In addition, the highest level of precision (base pair level of single DNA-molecules) will be reached for a high number of samples at the same time with sequencing techniques. The initial set-up of such an experiment must be chosen so that the sequenced parts of the genome are enriched in DNA-methylation or histone modifications. The data analysis pipeline for the interpretation of the generated data must perform fast and extract new knowledge out of the terabytes of raw data generated. Both the experimental set-up and the downstream data analysis, our laboratory is working on

    Successful reprogramming of epiblast stem cells by blocking nuclear localization of β-catenin.

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    Epiblast stem cells (EpiSCs) in mice and rats are primed pluripotent stem cells (PSCs). They barely contribute to chimeric embryos when injected into blastocysts. Reprogramming of EpiSCs to embryonic stem cell (ESC)-like cells (rESCs) may occur in response to LIF-STAT3 signaling; however, low reprogramming efficiency hampers potential use of rESCs in generating chimeras. Here, we describe dramatic improvement of conversion efficiency from primed to naive-like PSCs through upregulation of E-cadherin in the presence of the cytokine LIF. Analysis revealed that blocking nuclear localization of β-CATENIN with small-molecule inhibitors significantly enhances reprogramming efficiency of mouse EpiSCs. Although activation of Wnt/β-catenin signals has been thought desirable for maintenance of naive PSCs, this study provides the evidence that inhibition of nuclear translocation of β-CATENIN enhances conversion of mouse EpiSCs to naive-like PSCs (rESCs). This affords better understanding of gene regulatory circuits underlying pluripotency and reprogramming of PSCs

    Reprogramming glioblastoma multiforme cells into neurons by protein kinase inhibitors

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    Abstract Background Reprogramming of cancers into normal-like tissues is an innovative strategy for cancer treatment. Recent reports demonstrate that defined factors can reprogram cancer cells into pluripotent stem cells. Glioblastoma multiforme (GBM) is the most common and aggressive malignant brain tumor in humans. Despite multimodal therapy, the outcome for patients with GBM is still poor. Therefore, developing novel therapeutic strategy is a critical requirement. Methods We have developed a novel reprogramming method that uses a conceptually unique strategy for GBM treatment. We screened a kinase inhibitor library to find which candidate inhibitors under reprogramming condition can reprogram GBM cells into neurons. The induced neurons are identified whether functional and loss of tumorigenicity. Results We have found that mTOR and ROCK kinase inhibitors are sufficient to reprogram GBM cells into neural-like cells and “normal” neurons. The induced neurons expressed neuron-specific proteins, generated action potentials and neurotransmitter receptor-mediated currents. Genome-wide transcriptional analysis showed that the induced neurons had a profile different from GBM cells and were similar to that of control neurons induced by established methods. In vitro and in vivo tumorigenesis assays showed that induced neurons lost their proliferation ability and tumorigenicity. Moreover, reprogramming treatment with ROCK-mTOR inhibitors prevented GBM local recurrence in mice. Conclusion This study indicates that ROCK and mTOR inhibitors-based reprogramming treatment prevents GBM local recurrence. Currently ROCK-mTOR inhibitors are used as anti-tumor drugs in patients, so this reprogramming strategy has significant potential to move rapidly toward clinical trials

    Rationale and Methodology of Reprogramming for Generation of Induced Pluripotent Stem Cells and Induced Neural Progenitor Cells.

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    Great progress has been made regarding the capabilities to modify somatic cell fate ever since the technology for generation of induced pluripotent stem cells (iPSCs) was discovered in 2006. Later, induced neural progenitor cells (iNPCs) were generated from mouse and human cells, bypassing some of the concerns and risks of using iPSCs in neuroscience applications. To overcome the limitation of viral vector induced reprogramming, bioactive small molecules (SM) have been explored to enhance the efficiency of reprogramming or even replace transcription factors (TFs), making the reprogrammed cells more amenable to clinical application. The chemical induced reprogramming process is a simple process from a technical perspective, but the choice of SM at each step is vital during the procedure. The mechanisms underlying cell transdifferentiation are still poorly understood, although, several experimental data and insights have indicated the rationale of cell reprogramming. The process begins with the forced expression of specific TFs or activation/inhibition of cell signaling pathways by bioactive chemicals in defined culture condition, which initiates the further reactivation of endogenous gene program and an optimal stoichiometric expression of the endogenous pluri- or multi-potency genes, and finally leads to the birth of reprogrammed cells such as iPSCs and iNPCs. In this review, we first outline the rationale and discuss the methodology of iPSCs and iNPCs in a stepwise manner; and then we also discuss the chemical-based reprogramming of iPSCs and iNPCs

    Cellular decision-making bias: the missing ingredient in cell functional diversity

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    Cell functional diversity is a significant determinant on how biological processes unfold. Most accounts of diversity involve a search for sequence or expression differences. Perhaps there are more subtle mechanisms at work. Using the metaphor of information processing and decision-making might provide a clearer view of these subtleties. Understanding adaptive and transformative processes (such as cellular reprogramming) as a series of simple decisions allows us to use a technique called cellular signal detection theory (cellular SDT) to detect potential bias in mechanisms that favor one outcome over another. We can apply method of detecting cellular reprogramming bias to cellular reprogramming and other complex molecular processes. To demonstrate scope of this method, we will critically examine differences between cell phenotypes reprogrammed to muscle fiber and neuron phenotypes. In cases where the signature of phenotypic bias is cryptic, signatures of genomic bias (pre-existing and induced) may provide an alternative. The examination of these alternates will be explored using data from a series of fibroblast cell lines before cellular reprogramming (pre-existing) and differences between fractions of cellular RNA for individual genes after drug treatment (induced). In conclusion, the usefulness and limitations of this method and associated analogies will be discussed.Comment: 18 pages; 6 figures, 2 tables, 4 supplemental figure

    Direct Cardiac Reprogramming: Progress and Promise.

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    The human adult heart lacks a robust endogenous repair mechanism to fully restore cardiac function after insult; thus, the ability to regenerate and repair the injured myocardium remains a top priority in treating heart failure. The ability to efficiently generate a large number of functioning cardiomyocytes capable of functional integration within the injured heart has been difficult. However, the ability to directly convert fibroblasts into cardiomyocyte-like cells both in vitro and in vivo offers great promise in overcoming this problem. In this review, we describe the insights and progress that have been gained from the investigation of direct cardiac reprogramming. We focus on the use of key transcription factors and cardiogenic genes as well as on the use of other biological molecules such as small molecules, cytokines, noncoding RNAs, and epigenetic modifiers to improve the efficiency of cardiac reprogramming. Finally, we discuss the development of safer reprogramming approaches for future clinical application
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