DNA methylation-based chromatin compartments and ChIP-seq profiles reveal transcriptional drivers of prostate carcinogenesis

Simmonds, Poppy; Loomis, Erick; Curry, Ed

doi:10.1186/s13073-017-0443-z

Cited by 19 publications

(13 citation statements)

References 40 publications

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“…Moreover, TRIM28 has been shown to interact with ligand-dependent corepressor (LCoR), SETDB1, and HDAC1 to facilitate transcriptional repression 23 , 24 . In agreement with this, TRIM28 was found to be depleted from open chromatin and enriched in tumor-specific closed chromatin in prostate cancer cells 25 . TRIM28 has also been shown to interact with AR and induce AR activity in a reporter assay 26 .…”

Section: Introductionsupporting

confidence: 78%

“…Using luciferase reporter assays TRIM28 has been shown as a coactivator of AR that induces PSA promoter activity 26 . However, TRIM28 cistrome and regulation of gene expression in PCa cells remain to be studied, despite a recently study suggesting TRIM28 enrichment at tumor-specific closed chromatin in prostate cancer cells 25 . As TRIM24-AR signature genes are equally activated in TRIM28-high tumors as in SPOP-mutant PCa, TRIM28 expression, easily monitored at mRNA level, could be used to select CRPC patients that might not have SPOP mutation for TRIM24-targeted therapeutics that was previously proposed 19 .…”

Section: Discussionmentioning

confidence: 99%

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TRIM28 protects TRIM24 from SPOP-mediated degradation and promotes prostate cancer progression

et al. 2018

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TRIM24 is an effector substrate of the E3 ubiquitin ligase adaptor SPOP and becomes stabilized in prostate cancer (PCa) with SPOP mutations. However, how TRIM24 protein is regulated in the vast majority of SPOP-wildtype PCa is unknown. Here we report TRIM28 as a critical upstream regulator of TRIM24. TRIM28 protein interacts with TRIM24 to prevent its ubiquitination and degradation by SPOP. Further, TRIM28 facilitates TRIM24 occupancy on the chromatin and, like TRIM24, augments AR signaling. TRIM28 promotes PCa cell proliferation in vitro and xenograft tumor growth in vivo. Importantly, TRIM28 is upregulated in aggressive PCa and associated with elevated levels of TRIM24 and worse clinical outcome. TRIM24 and AR coactivated gene signature of SPOP-mutant PCa is similarly activated in human PCa with high TRIM28 expression. Taken together, this study provides a novel mechanism to broad TRIM24 protein stabilization and establishes TRIM28 as a promising therapeutic target.

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Section: Introductionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 99%

TRIM28 protects TRIM24 from SPOP-mediated degradation and promotes prostate cancer progression

et al. 2018

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“…The development of novel and unrivalled technologies, allowing genome-wide analysis, has enabled the unbiased discovery of drug targets. These technologies together with the availability of huge databases of chemicals or compounds have enabled the shortening of the time required for the whole process of drug discovery from drug design all the way to clinical trials [ 103 , 104 , 105 , 106 , 107 , 108 , 109 ].…”

Section: Natural Products Drug Discovery Research and Development mentioning

confidence: 99%

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

Thomford

Senthebane

Rowe

et al. 2018

IJMS

925

556

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The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of “active compound” has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of ‘organ-on chip’ and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review discusses plant-based natural product drug discovery and how innovative technologies play a role in next-generation drug discovery.

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“…We examined how to train and test models to infer a good approximation of the first eigenvector of the Hi-C matrix using only methylation and sequence information. The models need only one WGBS experiment to work, in contrast to many tens or hundreds of microarrays as in [6] and [7]; they are also simple to implement, unlike the more convoluted solution presented in [8]. Note that the form we chose for the regression does not imply causality: in fact, there are indications that methylation is established in already formed compartments [18].…”

Section: Discussionmentioning

confidence: 99%

“…Simmonds et.al. [7] also use methylation 450k microarrays to predict A/B compartments and to study differences between healthy and cancerous genomes. Jenkinson et al [8] classify compartments from a single WGBS experiment by way of segmenting DNA methylation via an Ising model.…”

Section: Introductionmentioning

confidence: 99%

Inference of genomic spatial organization from a whole genome bisulfite sequencing sample

Raineri¹,

Serra²,

Beekman³

et al. 2018

Preprint

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Common approaches to characterize the structure of the DNA in the nucleus, such as the different Chromosome Conformation Capture methods, have not currently been widely applied to different tissue types due to several practical difficulties including the requirement for intact cells to start the sample preparation. In contrast, techniques based on sodium bisulfite conversion of DNA to assay DNA methylation, have been widely applied to many different tissue types in a variety of organisms. Recent work has shown the possibility of inferring some aspects of the three dimensional DNA structure from DNA methylation data, raising the possibility of three dimensional DNA structure prediction using the large collection of already generated DNA methylation datasets. We propose a simple method to predict the values of the first eigenvector of the Hi-C matrix of a sample (and hence the positions of the A and B compartments) using only the GC content of the sequence and a single whole genome bisulfite sequencing (WGBS) experiment which yields information on the methylation levels and their variability along the genome. We train and test our model on 10 samples for which we have data from both bisulfite sequencing and chromosome conformation experiments and our most relevant finding is that the variability of DNA methylation along the sequence is often a better predictor than methylation itself. We then run a prediction on 206 DNA methylation profiles produced by the Blueprint project and use ChIP-Seq and RNA-Seq data to confirm that the forecasted eigenvector delineates correctly the physical chromatin compartments observed with the Hi-C experiment.

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DNA methylation-based chromatin compartments and ChIP-seq profiles reveal transcriptional drivers of prostate carcinogenesis

Cited by 19 publications

References 40 publications

TRIM28 protects TRIM24 from SPOP-mediated degradation and promotes prostate cancer progression

TRIM28 protects TRIM24 from SPOP-mediated degradation and promotes prostate cancer progression

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

Inference of genomic spatial organization from a whole genome bisulfite sequencing sample

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