Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Inferring causal molecular networks: empirical assessment through a community-based effort.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.

Epigenetic inhibition of the tumor suppressor ARHI by light at night-induced circadian melatonin disruption mediates STAT3-driven paclitaxel resistance in breast cancer.

Disruption of circadian time structure and suppression of circadian nocturnal melatonin (MLT) production by exposure to dim light at night (dLAN), as occurs with night shift work and/or disturbed sleep-wake cycles, is associated with a significantly increased risk of breast cancer and resistance to tamoxifen and doxorubicin. Melatonin inhibition of human breast cancer chemoresistance involves mechanisms including suppression of tumor metabolism and inhibition of kinases and transcription factors which are often activated in drug-resistant breast cancer. Signal transducer and activator of transcription 3 (STAT3), frequently overexpressed and activated in paclitaxel (PTX)-resistant breast cancer, promotes the expression of DNA methyltransferase one (DNMT1) to epigenetically suppress the transcription of tumor suppressor Aplasia Ras homolog one (ARHI) which can sequester STAT3 in the cytoplasm to block PTX resistance. We demonstrate that breast tumor xenografts in rats exposed to dLAN and circadian MLT disrupted express elevated levels of phosphorylated and acetylated STAT3, increased DNMT1, but reduced sirtuin 1 (SIRT1) and ARHI. Furthermore, MLT and/or SIRT1 administration blocked/reversed interleukin 6 (IL-6)-induced acetylation of STAT3 and its methylation of ARH1 to increase ARH1 mRNA expression in MCF-7 breast cancer cells. Finally, analyses of the I-SPY 1 trial demonstrate that elevated MT1 receptor expression is significantly correlated with pathologic complete response following neo-adjuvant therapy in breast cancer patients. This is the first study to demonstrate circadian disruption of MLT by dLAN driving intrinsic resistance to PTX via epigenetic mechanisms increasing STAT3 expression and that MLT administration can reestablish sensitivity of breast tumors to PTX and drive tumor regression.

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study.

MOTIVATION: Molecular pathways and networks play a key role in basic and disease biology. An emerging notion is that networks encoding patterns of molecular interplay may themselves differ between contexts, such as cell type, tissue or disease (sub)type. However, while statistical testing of differences in mean expression levels has been extensively studied, testing of network differences remains challenging. Furthermore, since network differences could provide important and biologically interpretable information to identify molecular subgroups, there is a need to consider the unsupervised task of learning subgroups and networks that define them. This is a nontrivial clustering problem, with neither subgroups nor subgroup-specific networks known at the outset. RESULTS: We leverage recent ideas from high-dimensional statistics for testing and clustering in the network biology setting. The methods we describe can be applied directly to most continuous molecular measurements and networks do not need to be specified beforehand. We illustrate the ideas and methods in a case study using protein data from The Cancer Genome Atlas (TCGA). This provides evidence that patterns of interplay between signalling proteins differ significantly between cancer types. Furthermore, we show how the proposed approaches can be used to learn subtypes and the molecular networks that define them. AVAILABILITY AND IMPLEMENTATION: As the Bioconductor package nethet. CONTACT: staedler.n@gmail.com or sach.mukherjee@dzne.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Melatonin suppression of aerobic glycolysis (Warburg effect), survival signalling and metastasis in human leiomyosarcoma.

Leiomyosarcoma (LMS) represents a highly malignant, rare soft tissue sarcoma with high rates of morbidity and mortality. Previously, we demonstrated that tissue-isolated human LMS xenografts perfused in situ are highly sensitive to the direct anticancer effects of physiological nocturnal blood levels of melatonin which inhibited tumour cell proliferative activity, linoleic acid (LA) uptake and metabolism to 13-hydroxyoctadecadienoic acid (13-HODE). Here, we show the effects of low pharmacological blood concentrations of melatonin following oral ingestion of a melatonin supplement by healthy adult human female subjects on tumour proliferative activity, aerobic glycolysis (Warburg effect) and LA metabolic signalling in tissue-isolated LMS xenografts perfused in situ with this blood. Melatonin markedly suppressed aerobic glycolysis and induced a complete inhibition of tumour LA uptake, 13-HODE release, as well as significant reductions in tumour cAMP levels, DNA content and [(3) H]-thymidine incorporation into DNA. Furthermore, melatonin completely suppressed the phospho-activation of ERK 1/2, AKT, GSK3ß and NF-kB (p65). The addition of S20928, a nonselective melatonin antagonist, reversed these melatonin inhibitory effects. Moreover, in in vitro cell culture studies, physiological concentrations of melatonin repressed cell proliferation and cell invasion. These results demonstrate that nocturnal melatonin directly inhibited tumour growth and invasion of human LMS via suppression of the Warburg effect, LA uptake and other related signalling mechanisms. An understanding of these novel signalling pathway(s) and their association with aerobic glycolysis and LA metabolism in human LMS may lead to new circadian-based therapies for the prevention and treatment of LMS and potentially other mesenchymally derived solid tumours.

Regulation of L1 expression and retrotransposition by melatonin and its receptor: implications for cancer risk associated with light exposure at night.

Expression of long interspersed element-1 (L1) is upregulated in many human malignancies. L1 can introduce genomic instability via insertional mutagenesis and DNA double-strand breaks, both of which may promote cancer. Light exposure at night, a recently recognized carcinogen, is associated with an increased risk of cancer in shift workers. We report that melatonin receptor 1 inhibits mobilization of L1 in cultured cells through downregulation of L1 mRNA and ORF1 protein. The addition of melatonin receptor antagonists abolishes the MT1 effect on retrotransposition in a dose-dependent manner. Furthermore, melatonin-rich, but not melatonin-poor, human blood collected at different times during the circadian cycle suppresses endogenous L1 mRNA during in situ perfusion of tissue-isolated xenografts of human cancer. Supplementation of human blood with exogenous melatonin or melatonin receptor antagonist during the in situ perfusion establishes a receptor-mediated action of melatonin on L1 expression. Combined tissue culture and in vivo data support that environmental light exposure of the host regulates expression of L1 elements in tumors. Our data imply that light-induced suppression of melatonin production in shift workers may increase L1-induced genomic instability in their genomes and suggest a possible connection between L1 activity and increased incidence of cancer associated with circadian disruption.

Doxorubicin resistance in breast cancer is driven by light at night-induced disruption of the circadian melatonin signal.

Chemotherapeutic resistance, particularly to doxorubicin (Dox), represents a major impediment to successfully treating breast cancer and is linked to elevated tumor metabolism and tumor over-expression and/or activation of various families of receptor- and non-receptor-associated tyrosine kinases. Disruption of circadian time structure and suppression of nocturnal melatonin production by dim light exposure at night (dLEN), as occurs with shift work, and/or disturbed sleep-wake cycles, is associated with a significantly increased risk of an array of diseases, including breast cancer. Melatonin inhibits human breast cancer growth via mechanisms that include the suppression of tumor metabolism and inhibition of expression or phospho-activation of the receptor kinases AKT and ERK1/2 and various other kinases and transcription factors. We demonstrate in tissue-isolated estrogen receptor alpha-positive (ERα+) MCF-7 human breast cancer xenografts, grown in nude rats maintained on a light/dark cycle of LD 12:12 in which dLEN is present during the dark phase (suppressed endogenous nocturnal melatonin), a significant shortening of tumor latency-to-onset, increased tumor metabolism and growth, and complete intrinsic resistance to Dox therapy. Conversely, a LD 12:12 dLEN environment incorporating nocturnal melatonin replacement resulted in significantly lengthened tumor latency-to-onset, tumor regression, suppression of nighttime tumor metabolism, and kinase and transcription factor phosphorylation, while Dox sensitivity was completely restored. Melatonin acts as both a tumor metabolic inhibitor and circadian-regulated kinase inhibitor to reestablish the sensitivity of breast tumors to Dox and drive tumor regression, indicating that dLEN-induced circadian disruption of nocturnal melatonin production contributes to a complete loss of tumor sensitivity to Dox chemotherapy.

Molecular deficiency (ies) in MT1 melatonin signaling pathway underlies the melatonin-unresponsive phenotype in MDA-MB-231 human breast cancer cells.

Melatonin has been shown repeatedly to inhibit the growth of human breast tumor cells in vitro and in vivo. Its antiproliferative effects have been well studied in MCF-7 human breast cancer cells and several other estrogen receptor α (ERα)-positive human breast cancer cell lines. However, the MDA-MB-231 breast cancer cell line, an ERα-negative cell line widely used in breast cancer research, has been shown to be unresponsive to melatonin's growth-suppressive effect in vitro. Here, we examined the effect of melatonin on the cell proliferation of several ERα-negative breast cancer cell lines including MDA-MB-231, BT-20, and SK-BR-3 cells. Although the MT1 G-protein-coupled receptor is expressed in all three cell lines, melatonin significantly suppressed the proliferation of SK-BR-3 cells without having any significant effect on the growth of MDA-MB-231 and BT-20 cells. We confirmed that the MT1-associated Gα proteins are expressed in MDA-MB-231 cells. Further studies demonstrated that the melatonin unresponsiveness in MDA-MB-231 cells may be caused by aberrant signaling downstream of the Gαi proteins, resulting in differential regulation of ERK1/2 activity.

Dynamics of cognitive variability with age and its genetic underpinning in NIHR BioResource Genes and Cognition cohort participants.

A leading explanation for translational failure in neurodegenerative disease is that new drugs are evaluated late in the disease course when clinical features have become irreversible. Here, to address this gap, we cognitively profiled 21,051 people aged 17-85 years as part of the Genes and Cognition cohort within the National Institute for Health and Care Research BioResource across England. We describe the cohort, present cognitive trajectories and show the potential utility. Surprisingly, when studied at scale, the APOE genotype had negligible impact on cognitive performance. Different cognitive domains had distinct genetic architectures, with one indicating brain region-specific activation of microglia and another with glycogen metabolism. Thus, the molecular and cellular mechanisms underpinning cognition are distinct from dementia risk loci, presenting different targets to slow down age-related cognitive decline. Participants can now be recalled stratified by genotype and cognitive phenotype for natural history and interventional studies of neurodegenerative and other disorders.

A cfDNA methylation-based tissue-of-origin classifier for cancers of unknown primary.

Cancers of Unknown Primary (CUP) remains a diagnostic and therapeutic challenge due to biological heterogeneity and poor responses to standard chemotherapy. Predicting tissue-of-origin (TOO) molecularly could help refine this diagnosis, with tissue acquisition barriers mitigated via liquid biopsies. However, TOO liquid biopsies are unexplored in CUP cohorts. Here we describe CUPiD, a machine learning classifier for accurate TOO predictions across 29 tumour classes using circulating cell-free DNA (cfDNA) methylation patterns. We tested CUPiD on 143 cfDNA samples from patients with 13 cancer types alongside 27 non-cancer controls, with overall sensitivity of 84.6% and TOO accuracy of 96.8%. In an additional cohort of 41 patients with CUP CUPiD predictions were made in 32/41 (78.0%) cases, with 88.5% of the predictions clinically consistent with a subsequent or suspected primary tumour diagnosis, when available (23/26 patients). Combining CUPiD with cfDNA mutation data demonstrated potential diagnosis re-classification and/or treatment change in this hard-to-treat cancer group.

Bayesian inference of signaling network topology in a cancer cell line.

MOTIVATION: Protein signaling networks play a key role in cellular function, and their dysregulation is central to many diseases, including cancer. To shed light on signaling network topology in specific contexts, such as cancer, requires interrogation of multiple proteins through time and statistical approaches to make inferences regarding network structure. RESULTS: In this study, we use dynamic Bayesian networks to make inferences regarding network structure and thereby generate testable hypotheses. We incorporate existing biology using informative network priors, weighted objectively by an empirical Bayes approach, and exploit a connection between variable selection and network inference to enable exact calculation of posterior probabilities of interest. The approach is computationally efficient and essentially free of user-set tuning parameters. Results on data where the true, underlying network is known place the approach favorably relative to existing approaches. We apply these methods to reverse-phase protein array time-course data from a breast cancer cell line (MDA-MB-468) to predict signaling links that we independently validate using targeted inhibition. The methods proposed offer a general approach by which to elucidate molecular networks specific to biological context, including, but not limited to, human cancers. AVAILABILITY: http://mukherjeelab.nki.nl/DBN (code and data).

Insulin and IGF1 enhance IL-17-induced chemokine expression through a GSK3B-dependent mechanism: a new target for melatonin's anti-inflammatory action.

Obesity is a chronic inflammation with increased serum levels of insulin, insulin-like growth factor 1 (IGF1), and interleukin-17 (IL-17). The objective of this study was to test a hypothesis that insulin and IGF1 enhance IL-17-induced expression of inflammatory chemokines/cytokines through a glycogen synthase kinase 3ß (GSK3B)-dependent mechanism, which can be inhibited by melatonin. We found that insulin/IGF1 and lithium chloride enhanced IL-17-induced expression of C-X-C motif ligand 1 (Cxcl1) and C-C motif ligand 20 (Ccl20) in the Gsk3b(+/+) , but not in Gsk3b(-/-) mouse embryonic fibroblast (MEF) cells. IL-17 induced higher levels of Cxcl1 and Ccl20 in the Gsk3b(-/-) MEF cells, compared with the Gsk3b(+/+) MEF cells. Insulin and IGF1 activated Akt to phosphorylate GSK3B at serine 9, thus inhibiting GSK3B activity. Melatonin inhibited Akt activation, thus decreasing P-GSK3B at serine 9 (i.e., increasing GSK3B activity) and subsequently inhibiting expression of Cxcl1 and Ccl20 that was induced either by IL-17 alone or by a combination of insulin and IL-17. Melatonin's inhibitory effects were only observed in the Gsk3b(+/+) , but in not Gsk3b(-/-) MEF cells. Melatonin also inhibited expression of Cxcl1, Ccl20, and Il-6 that was induced by a combination of insulin and IL-17 in the mouse prostatic tissues. Further, nighttime human blood, which contained high physiologic levels of melatonin, decreased expression of Cxcl1, Ccl20, and Il-6 in the PC3 human prostate cancer xenograft tumors. Our data support our hypothesis and suggest that melatonin may be used to dampen IL-17-mediated inflammation that is enhanced by the increased levels of insulin and IGF1 in obesity.

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology.

BACKGROUND: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. RESULTS: We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. CONCLUSIONS: The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge.

Network clustering: probing biological heterogeneity by sparse graphical models.

MOTIVATION: Networks and pathways are important in describing the collective biological function of molecular players such as genes or proteins. In many areas of biology, for example in cancer studies, available data may harbour undiscovered subtypes which differ in terms of network phenotype. That is, samples may be heterogeneous with respect to underlying molecular networks. This motivates a need for unsupervised methods capable of discovering such subtypes and elucidating the corresponding network structures. RESULTS: We exploit recent results in sparse graphical model learning to put forward a 'network clustering' approach in which data are partitioned into subsets that show evidence of underlying, subset-level network structure. This allows us to simultaneously learn subset-specific networks and corresponding subset membership under challenging small-sample conditions. We illustrate this approach on synthetic and proteomic data. AVAILABILITY: go.warwick.ac.uk/sachmukherjee/networkclustering.

Impaired mouse mammary gland growth and development is mediated by melatonin and its MT1G protein-coupled receptor via repression of ERα, Akt1, and Stat5.

To determine whether melatonin, via its MT(1) G protein-coupled receptor, impacts mouse mammary gland development, we generated a mouse mammary tumor virus (MMTV)-MT1-Flag-mammary gland over-expressing (MT1-mOE) transgenic mouse. Increased expression of the MT(1) -Flag transgene was observed in the mammary glands of pubescent MT1-mOE transgenic female mice, with further significant increases during pregnancy and lactation. Mammary gland whole mounts from MT1-mOE mice showed significant reductions in ductal growth, ductal branching, and terminal end bud formation. Elevated MT(1) receptor expression in pregnant and lactating female MT1-mOE mice was associated with reduced lobulo-alveolar development, inhibition of mammary epithelial cell proliferation, and significant reductions in body weights of suckling pups. Elevated MT(1) expression in pregnant and lactating MT1-mOE mice correlated with reduced mammary gland expression of Akt1, phospho-Stat5, Wnt4, estrogen receptor alpha, progesterone receptors A and B, and milk proteins ß-casein and whey acidic protein. Estrogen- and progesterone-stimulated mammary gland development was repressed by elevated MT(1) receptor expression and exogenous melatonin administration. These studies demonstrate that the MT(1) melatonin receptor and its ligand melatonin play an important regulatory role in mammary gland development and lactation in mice through both growth suppression and alteration of developmental paradigms.

Melatonin and associated signaling pathways that control normal breast epithelium and breast cancer.

This review article discusses recent work on the melatonin-mediated circadian regulation and integration of molecular and metabolic signaling mechanisms involved in human breast cancer growth and the associated consequences of circadian disruption by exposure to light-at-night (LAN). The anti-proliferative effects of the circadian melatonin signal are, in general, mediated through mechanisms involving the activation of MT(1) melatonin receptors expressed in human breast cancer cell lines and xenografts. In estrogen receptor-positive (ERα+) human breast cancer cells, melatonin suppresses both ERα mRNA expression and estrogen-induced transcriptional activity of the ERα via MT(1)-induced activation of G(αi2) signaling and reduction of cAMP levels. Melatonin also regulates the transcriptional activity of additional members of the nuclear receptor super-family, enzymes involved in estrogen metabolism, and the expression of core clock and clock-related genes. The anti-invasive/anti-metastatic actions of melatonin involve the blockade of p38 phosphorylation and matrix metalloproteinase expression. Melatonin also inhibits the growth of human breast cancer xenografts via MT(1)-mediated suppression of cAMP leading to a blockade of linoleic acid (LA) uptake and its metabolism to the mitogenic signaling molecule 13-hydroxyoctadecadienoic acid (13-HODE). Down-regulation of 13-HODE reduces the activation of growth factor pathways supporting cell proliferation and survival. Finally, studies in both rats and humans indicate that light-at-night (LAN) induced circadian disruption of the nocturnal melatonin signal activates human breast cancer growth, metabolism, and signaling, providing the strongest mechanistic support, thus far, for epidemiological studies demonstrating the elevated breast cancer risk in night shift workers and other individuals increasingly exposed to LAN.

A Method for Perfusion of Tissue-Isolated Human Tumor Xenografts in Nude Rats to Investigate the Oncostatic Role of the Physiological Nocturnal Melatonin Signal.

The tissue-isolated human tumor perfusion methodology enables the elucidation of physiological melatonin's oncostatic impact on cancer metabolism and physiology. Here we describe an apparatus and surgical technique for perfusing tissue-isolated human tumor xenografts in nude rats in situ that ensures continuous blood flow to and from the tissue. This system and methodology have proven quite successful in examining the receptor-mediated oncostatic effects of the physiological nocturnal melatonin signal on metabolism and physiology in a variety of epithelial and mesenchymal human tumors.

A Method for Growing Tissue-Isolated Human Tumor Xenografts in Nude Rats for Melatonin/Cancer Studies.

The tissue-isolated tumor model permits the investigation of melatonin's influence on human tumor growth and metabolism in laboratory rats in vivo. Here we describe a unique surgical technique for implanting and growing human tumor xenografts on a vascular stalk composed of the nude rat epigastric artery and vein that provides a continuous blood supply from a single source to the tissue-isolated tumor while insuring the absence of extraneous vascular connections. A variety of human tumor types may be implanted and grown utilizing this unique model that may provide a plethora of scientific data from a single tumor examined.

cfDNA methylome profiling for detection and subtyping of small cell lung cancers.

Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients' circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.