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Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual geno

BackgroundOver 130 million people have been diagnosed with Coronavirus disease 2019 (COVID-19), and more than one million fatalities have been reported worldwide. South Africa is unique in having a quadruple disease burden of type 2 diabetes, hypertension, human immunodeficiency virus (HIV) and tuberculosis, making COVID-19-related mortality of particular interest in the country. The aim of this study was to investigate the clinical characteristics and associated mortality of COVID-19 patients admitted to an intensive care unit (ICU) in a South African setting.Methods and findingsWe performed a prospective observational study of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection admitted to the ICU of a South African tertiary hospital in Cape Town. The mortality and discharge rates were the primary outcomes. Demographic, clinical and laboratory data were analysed, and multivariable robust Poisson regression model was used to identify risk factors for mortality. Furthermore, Cox proportional hazards regression model was performed to assess the association between time to death and the predictor variables. Factors associated with death (time to death) at p-value < 0.05 were considered statistically significant. Of the 402 patients admitted to the ICU, 250 (62%) died, and another 12 (3%) died in the hospital after being discharged from the ICU. The median age of the study population was 54.1 years (IQR: 46.0-61.6). The mortality rate among those who were intubated was significantly higher at 201/221 (91%). After adjusting for confounding, multivariable robust Poisson regression analysis revealed that age more than 48 years, requiring invasive mechanical ventilation, HIV status, procalcitonin (PCT), Troponin T, Aspartate Aminotransferase (AST), and a low pH on admission all significantly predicted mortality. Three main risk factors predictive of mortality were identified in the analysis using Cox regression Cox proportional hazards regression model. HIV positive status, myalgia, and intubated in the ICU were identified as independent prognostic factors.ConclusionsIn this study, the mortality rate in COVID-19 patients admitted to the ICU was high. Older age, the need for invasive mechanical ventilation, HIV status, and metabolic acidosis were found to be significant predictors of mortality in patients admitted to the ICU.

A retrospective analysis of the violent incident forms returned over a one year period in a psychiatric hospital recorded 283 incidents involving 144 patients. Almost all were of a petty nature, none leading to lasting injuries. Compared with the average daily in-patient population, offending patients were more likely to be male, to be less than 45 years old, and to have a diagnosis of schizophrenia. [ABSTRACT FROM AUTHOR]

Compulsive water drinking is associated with a broad spectrum of psychopathology, from mild neurosis to psychosis. Since the normal kidney is capable of excreting large volumes of fluid rapidly, water intoxication requires both a pathological basis and a psychiatric explanation of why so much water is being taken. Excessive water consumption can be dangerous, so that the fluid intake of patients with a history of polyuria together with a low urinary specific gravity should be closely observed. Four cases of water intoxication resulting from psychogenic polydipsia are described, three of them in chronic schizophrenics, where inappropriate ADH secretion might represent part of the psychosis. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented about koro.

Natural Killer (NK) cells can target and destroy cancer cells, yet tumor microenvironments typically suppress NK cell recruitment and cytotoxicity. The epidermal growth factor receptor (EGFR) is a potent oncogene that can activate survival, migration, and proliferation pathways, and clinical data suggests it may also play an immunomodulating role in cancers. Recent work has demonstrated a novel role for nuclear EGFR (nEGFR) in regulating transcriptional events unique from the kinase domain. Using a novel peptide therapeutic (cSNX1.3) that inhibits retrograde trafficking of EGFR and an EGFR nuclear localization mutant, we discovered that nEGFR suppresses NK cell recruitment and cytotoxicity. RNA-Seq analysis of breast cancer cells treated with cSNX1.3 or modified to lack a nuclear localization sequence (EGFR ΔNLS ) revealed the EGF-dependent induction of NK activating receptor ligands, while kinase inhibition by erlotinib did not impact these genes. NanoString analysis of tumor-bearing WAP-TGFα transgenic mice treated with cSNX1.3 demonstrated an increase in immune cell populations and activating genes. Additionally, immunohistochemistry confirmed an increase in NK cells upon cSNX1.3 treatment. Finally, cSNX1.3 treatment was found to enhance NK cell recruitment and cytotoxicity in vitro. Together, the data demonstrate a unique immunomodulatory role for nEGFR., Competing Interests: Competing interests TAF has licensed patents, equity, consulting, and potential royalty interests in Wugen; equity interests in Indapta Therapeutics and Orca Bio; and serves as a consultant for Affimed, AI Proteins, and Smart Immune; and has research funding from HCW biologics, Wugen, and Affimed. Ethics approval and consent to participate All methods were performed in accordance with the relevant guidelines and regulations. No human subjects were involved in this research. All animal studies were approved by the University of Arizona Institutional Animal Care and Use Committee, protocol approval #18-427., (© 2024. The Author(s).)

Transcriptional regulation plays a crucial role in determining cell fate and disease, yet inferring the key regulators from gene expression data remains a significant challenge. Existing methods for estimating transcription factor (TF) activity often rely on static TF-gene interaction databases and cannot adapt to changes in regulatory mechanisms across different cell types and disease conditions. Here, we present a new algorithm - Transcriptional Inference using Gene Expression and Regulatory data (TIGER) - that overcomes these limitations by flexibly modeling activation and inhibition events, up-weighting essential edges, shrinking irrelevant edges towards zero through a sparse Bayesian prior, and simultaneously estimating both TF activity levels and changes in the underlying regulatory network. When applied to yeast and cancer TF knock-out datasets, TIGER outperforms comparable methods in terms of prediction accuracy. Moreover, our application of TIGER to tissue- and cell-type-specific RNA-seq data demonstrates its ability to uncover differences in regulatory mechanisms. Collectively, our findings highlight the utility of modeling context-specific regulation when inferring transcription factor activities., (© 2024. The Author(s).)

HCMV genes UL135 and UL138 play opposing roles regulating latency and reactivation in CD34 + human progenitor cells (HPCs). Using the THP-1 cell line model for latency and reactivation, we designed an RNA sequencing study to compare the transcriptional profile of HCMV infection in the presence and absence of these genes. The loss of UL138 results in elevated levels of viral gene expression and increased differentiation of cell populations that support HCMV gene expression and genome synthesis. The loss of UL135 results in diminished viral gene expression during an initial burst that occurs as latency is established and no expression of eleven viral genes from the UL b ' region even following stimulation for differentiation and reactivation. Transcriptional network analysis revealed host transcription factors with potential to regulate the UL b ' genes in coordination with pUL135. These results reveal roles for UL135 and UL138 in regulation of viral gene expression and potentially hematopoietic differentiation., Competing Interests: Declaration of Interests: The authors declare no competing interests.

Salivary gland hypofunction is an adverse side effect associated with radiotherapy for head and neck cancer patients. This study delineated metabolic changes at acute, intermediate, and chronic radiation damage response stages in mouse salivary glands following a single 5 Gy dose. Ultra-high performance liquid chromatography-mass spectrometry was performed on parotid salivary gland tissue collected at 3, 14, and 30 days following radiation (IR). Pathway enrichment analysis, network analysis based on metabolite structural similarity, and network analysis based on metabolite abundance correlations were used to incorporate both metabolite levels and structural annotation. The greatest number of enriched pathways are observed at 3 days and the lowest at 30 days following radiation. Amino acid metabolism pathways, glutathione metabolism, and central carbon metabolism in cancer are enriched at all radiation time points across different analytical methods. This study suggests that glutathione and central carbon metabolism in cancer may be important pathways in the unresolved effect of radiation treatment., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Buss et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Dendritic spines are the postsynaptic compartment of a neuronal synapse and are critical for synaptic connectivity and plasticity. A developmental precursor to dendritic spines, dendritic filopodia (DF), facilitate synapse formation by sampling the environment for suitable axon partners during neurodevelopment and learning. Despite the significance of the actin cytoskeleton in driving these dynamic protrusions, the actin elongation factors involved are not well characterized. We identified the Ena/VASP protein EVL as uniquely required for the morphogenesis and dynamics of DF. Using a combination of genetic and optogenetic manipulations, we demonstrated that EVL promotes protrusive motility through membrane-direct actin polymerization at DF tips. EVL forms a complex at nascent protrusions and DF tips with MIM/MTSS1, an I-BAR protein important for the initiation of DF. We proposed a model in which EVL cooperates with MIM to coalesce and elongate branched actin filaments, establishing the dynamic lamellipodia-like architecture of DF., (© 2023 Parker et al.)

Inference and analysis of gene regulatory networks (GRNs) require software that integrates multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is a collection of open-source methods to infer GRNs, conduct differential network analyses, estimate community structure, and explore the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages and between methods to allow better integration of these tools into analytical pipelines. We demonstrate the utility using multi-omic data from the Cancer Cell Line Encyclopedia. We will continue to expand the netZoo to incorporate additional methods., (© 2023. The Author(s).)

Consumption of cruciferous vegetables, rich in the isothiocyanate glucoraphanin, is associated with reduced risk of tobacco-related cancers. Sulforaphane, released by hydrolysis of glucoraphanin, potently induces cytoprotective phase II enzymes. Sulforaphane decreased the incidence of oral cancer in the 4NQO carcinogenesis model. In residents of Qidong, China, broccoli seed and sprout extracts (BSSE) increased detoxification of air pollutants benzene and acrolein, also found in tobacco smoke. This randomized, crossover trial evaluated detoxification of tobacco carcinogens by the BSSE Avmacol® in otherwise healthy smokers. Participants were treated for 2 weeks with both low and higher-dose BSSE (148 µmol vs. 296 µmol of glucoraphanin daily), separated by a 2-week washout, with randomization to low-high vs. high-low sequence. The primary endpoint was detoxification of benzene, measured by urinary excretion of its mercapturic acid, SPMA. Secondary endpoints included bioavailability, detoxification of acrolein and crotonaldehyde, modulation by GST genotype, and toxicity. Forty-nine participants enrolled, including 26 (53%) females with median use of 20 cigarettes/day. Low and higher-dose BSSE showed a mean bioavailability of 11% and 10%, respectively. Higher-dose BSSE significantly upregulated urinary excretion of the mercapturic acids of benzene (p = 0.04), acrolein (p < 0.01), and crotonaldehyde (p = 0.02), independent of GST genotype. Retention and compliance were high resulting in early study completion. In conclusion, BSSE significantly upregulated detoxification of the tobacco carcinogens benzene, acrolein, and crotonaldehyde in current tobacco smokers.

The microenvironment of solid tumors is dynamic and frequently contains pockets of low oxygen levels (hypoxia) surrounded by oxygenated tissue. Indeed, a compromised vasculature is a hallmark of the tumor microenvironment, creating both spatial gradients and temporal variability in oxygen availability. Notably, hypoxia associates with increased metastasis and poor survival in patients. Therefore, to aid therapeutic decisions and better understand hypoxia's role in cancer progression, it is critical to identify endogenous biomarkers of hypoxia to spatially phenotype oncogenic lesions in human tissue, whether precancerous, benign, or malignant. Here, we characterize the glucose transporter GLUT3/SLC2A3 as a biomarker of hypoxic prostate epithelial cells and prostate tumors. Transcriptomic analyses of non-tumorigenic, immortalized prostate epithelial cells revealed a highly significant increase in GLUT3 expression under hypoxia. Additionally, GLUT3 protein increased 2.4-fold in cultured hypoxic prostate cell lines and was upregulated within hypoxic regions of xenograft tumors, including two patient-derived xenografts (PDX). Finally, GLUT3 out-performs other established hypoxia markers; GLUT3 staining in PDX specimens detects 2.6-8.3 times more tumor area compared to a mixture of GLUT1 and CA9 antibodies. Therefore, given the heterogeneous nature of tumors, we propose adding GLUT3 to immunostaining panels when trying to detect hypoxic regions in prostate samples.

The tumor suppressor gene adenomatous polyposis coli (APC) is the initiating mutation in approximately 80% of all colorectal cancers (CRC), underscoring the importance of aberrant regulation of intracellular WNT signaling in CRC development. Recent studies have found that early-onset CRC exhibits an increased proportion of tumors lacking an APC mutation. We set out to identify mechanisms underlying APC mutation-negative (APC mut- ) CRCs. We analyzed data from The Cancer Genome Atlas to compare clinical phenotypes, somatic mutations, copy number variations, gene fusions, RNA expression, and DNA methylation profiles between APC mut- and APC mutation-positive (APC mut+ ) microsatellite stable CRCs. Transcriptionally, APC mut- CRCs clustered into two approximately equal groups. Cluster One was associated with enhanced mitochondrial activation. Cluster Two was strikingly associated with genetic inactivation or decreased RNA expression of the WNT antagonist RNF43, increased expression of the WNT agonist RSPO3, activating mutation of BRAF, or increased methylation and decreased expression of AXIN2. APC mut- CRCs exhibited evidence of increased immune cell infiltration, with significant correlation between M2 macrophages and RSPO3. APC mut- CRCs comprise two groups of tumors characterized by enhanced mitochondrial activation or increased sensitivity to extracellular WNT, suggesting that they could be respectively susceptible to inhibition of these pathways., (© 2021. The Author(s).)

While the immediate and transitory response of breast cancer cells to pathological stiffness in their native microenvironment has been well explored, it remains unclear how stiffness-induced phenotypes are maintained over time after cancer cell dissemination in vivo. Here, we show that fibrotic-like matrix stiffness promotes distinct metastatic phenotypes in cancer cells, which are preserved after transition to softer microenvironments, such as bone marrow. Using differential gene expression analysis of stiffness-responsive breast cancer cells, we establish a multigenic score of mechanical conditioning (MeCo) and find that it is associated with bone metastasis in patients with breast cancer. The maintenance of mechanical conditioning is regulated by RUNX2, an osteogenic transcription factor, established driver of bone metastasis, and mitotic bookmarker that preserves chromatin accessibility at target gene loci. Using genetic and functional approaches, we demonstrate that mechanical conditioning maintenance can be simulated, repressed, or extended, with corresponding changes in bone metastatic potential., Competing Interests: Declaration of interests A.W.W. and G.M. have equity in MeCo Diagnostics LLC, which is commercializing the MeCo score under license from the Arizona Board of Regents. G.M. has disclosed an outside interest in MeCo Diagnostics LLC to the University of Arizona. Conflicts of interest resulting from this are being managed by the University of Arizona in accordance with its policies. All of the other authors declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Radiation therapy for head and neck cancer causes damage to the surrounding salivary glands, resulting in salivary gland hypofunction and xerostomia. Current treatments do not provide lasting restoration of salivary gland function following radiation; therefore, a new mechanistic understanding of the radiation-induced damage response is necessary for identifying therapeutic targets. The purpose of the present study was to investigate the metabolic phenotype of radiation-induced damage in parotid salivary glands by integrating transcriptomic and metabolomic data. Integrated data were then analyzed to identify significant gene-metabolite interactions. Mice received a single 5 Gy dose of targeted head and neck radiation. Parotid tissue samples were collected 5 days following treatment for RNA sequencing and metabolomics analysis. Altered metabolites and transcripts significantly converged on a specific region in the metabolic reaction network. Both integrative pathway enrichment using rank-based statistics and network analysis highlighted significantly coordinated changes in glutathione metabolism, energy metabolism (TCA cycle and thermogenesis), peroxisomal lipid metabolism, and bile acid production with radiation. Integrated changes observed in energy metabolism suggest that radiation induces a mitochondrial dysfunction phenotype. These findings validated previous pathways involved in the radiation-damage response, such as altered energy metabolism, and identified robust signatures in salivary glands, such as reduced glutathione metabolism, that may be driving salivary gland dysfunction.

The use of biological networks such as protein-protein interaction and transcriptional regulatory networks is becoming an integral part of genomics research. However, these networks are not static, and during phenotypic transitions like disease onset, they can acquire new "communities" (or highly interacting groups) of genes that carry out cellular processes. Disease communities can be detected by maximizing a modularity-based score, but since biological systems and network inference algorithms are inherently noisy, it remains a challenge to determine whether these changes represent real cellular responses or whether they appeared by random chance. Here, we introduce Constrained Random Alteration of Network Edges (CRANE), a method for randomizing networks with fixed node strengths. CRANE can be used to generate a null distribution of gene regulatory networks that can in turn be used to rank the most significant changes in candidate disease communities. Compared to other approaches, such as consensus clustering or commonly used generative models, CRANE emulates biologically realistic networks and recovers simulated disease modules with higher accuracy. When applied to breast and ovarian cancer networks, CRANE improves the identification of cancer-relevant GO terms while reducing the signal from non-specific housekeeping processes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lim, Chen, Grant and Padi.)

Despite significant progress in understanding the genetic landscape of T-cell acute lymphoblastic leukemia (T-ALL), the discovery of novel therapeutic targets has been difficult. Our results demonstrate that the levels of PIM1 protein kinase is elevated in early T-cell precursor ALL (ETP-ALL) but not in mature T-ALL primary samples. Small-molecule PIM inhibitor (PIMi) treatment decreases leukemia burden in ETP-ALL. However, treatment of animals carrying ETP-ALL with PIMi was not curative. To model other pathways that could be targeted to complement PIMi activity, HSB-2 cells, previously characterized as a PIMi-sensitive T-ALL cell line, were grown in increasing doses of PIMi. Gene set enrichment analysis of RNA sequencing data and functional enrichment of network modules demonstrated that the HOXA9, mTOR, MYC, NFκB, and PI3K-AKT pathways were activated in HSB-2 cells after long-term PIM inhibition. Reverse phase protein array-based pathway activation mapping demonstrated alterations in the mTOR, PI3K-AKT, and NFκB pathways, as well. PIMi-tolerant HSB-2 cells contained phosphorylated RelA-S536 consistent with activation of the NFκB pathway. The combination of NFκB and PIMis markedly reduced the proliferation in PIMi-resistant leukemic cells showing that this pathway plays an important role in driving the growth of T-ALL. Together these results demonstrate key pathways that are activated when HSB-2 cell line develop resistance to PIMi and suggest pathways that can be rationally targeted in combination with PIM kinases to inhibit T-ALL growth., (©2020 American Association for Cancer Research.)

Genetic alterations are essential for cancer initiation and progression. However, differentiating mutations that drive the tumor phenotype from mutations that do not affect tumor fitness remains a fundamental challenge in cancer biology. To better understand the impact of a given mutation within cancer, RNA-sequencing data was used to categorize mutations based on their allelic expression. For this purpose, we developed the MAXX (Mutation Allelic Expression Extractor) software, which is highly effective at delineating the allelic expression of both single nucleotide variants and small insertions and deletions. Results from MAXX demonstrated that mutations can be separated into three groups based on their expression of the mutant allele, lack of expression from both alleles, or expression of only the wild-type allele. By taking into consideration the allelic expression patterns of genes that are mutated in PDAC, it was possible to increase the sensitivity of widely used driver mutation detection methods, as well as identify subtypes that have prognostic significance and are associated with sensitivity to select classes of therapeutic agents in cell culture. Thus, differentiating mutations based on their mutant allele expression via MAXX represents a means to parse somatic variants in tumor genomes, helping to elucidate a gene's respective role in cancer.

It has been previously reported that ursodeoxycholic acid (UDCA), a therapeutic bile acid, reduced risk for advanced colorectal adenoma in men but not women. Interactions between the gut microbiome and fecal bile acid composition as a factor in colorectal cancer neoplasia have been postulated but evidence is limited to small cohorts and animal studies. Using banked stool samples collected as part of a phase III randomized clinical trial of UDCA for the prevention of colorectal adenomatous polyps, we compared change in the microbiome composition after a 3-year intervention in a subset of participants randomized to oral UDCA at 8-10 mg/kg of body weight per day (n = 198) or placebo (n = 203). Study participants randomized to UDCA experienced compositional changes in their microbiome that were statistically more similar to other individuals in the UDCA arm than to those in the placebo arm. This reflected a UDCA-associated shift in microbial community composition (P < 0.001), independent of sex, with no evidence of a UDCA effect on microbial richness (P > 0.05). These UDCA-associated shifts in microbial community distance metrics from baseline to end-of-study were not associated with risk of any or advanced adenoma (all P > 0.05) in men or women. Separate analyses of microbial networks revealed an overrepresentation of Faecalibacterium prausnitzii in the post-UDCA arm and an inverse relationship between F prausnitzii and Ruminococcus gnavus. In men who received UDCA, the overrepresentation of F prausnitzii and underrepresentation of R gnavus were more prominent in those with no adenoma recurrence at follow-up compared to men with recurrence. This relationship was not observed in women. Daily UDCA use modestly influences the relative abundance of microbial species in stool and affects the microbial network composition with suggestive evidence for sex-specific effects of UDCA on stool microbial community composition as a modifier of colorectal adenoma risk., (© 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS p -values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study. We identified variants regulating gene expression (expression quantitative loci, eQTL) of HiCc pathway genes in islet samples. These eQTL genes showed higher levels of differential expression compared to non-eQTL genes in low, medium, and high glucose concentrations in rat islets. Among genes with highly significant eQTL evidence, NFATC4 belonged to four HiCc pathways. We asked if the expressions of T2D-associated candidate genes from GWAS and literature are regulated by Nfatc4 in rat islets. Extensive in vitro silencing of Nfatc4 in rat islet cells displayed reduced expression of 16, and increased expression of four putative downstream T2D genes. Overall, our approach uncovers the mechanistic connection of NFATC4 with downstream targets including a previously unknown one, TCF7L2, and establishes the HiCc pathways' relationship to T2D., Competing Interests: In the past three years, E.K.S. received honoraria and consulting fees from Merck, grant support and consulting fees from GlaxoSmithKline, and honoraria and travel support from Novartis. J.L. discloses a relevant conflict for his founder’s role with Scipher, Inc. (a network medicine company).

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes., Competing Interests: The authors declare no competing financial interests.

Merkel cell carcinoma (MCC) frequently contains integrated copies of Merkel cell polyomavirus DNA that express a truncated form of Large T antigen (LT) and an intact Small T antigen (ST). While LT binds RB and inactivates its tumor suppressor function, it is less clear how ST contributes to MCC tumorigenesis. Here we show that ST binds specifically to the MYC homolog MYCL (L-MYC) and recruits it to the 15-component EP400 histone acetyltransferase and chromatin remodeling complex. We performed a large-scale immunoprecipitation for ST and identified co-precipitating proteins by mass spectrometry. In addition to protein phosphatase 2A (PP2A) subunits, we identified MYCL and its heterodimeric partner MAX plus the EP400 complex. Immunoprecipitation for MAX and EP400 complex components confirmed their association with ST. We determined that the ST-MYCL-EP400 complex binds together to specific gene promoters and activates their expression by integrating chromatin immunoprecipitation with sequencing (ChIP-seq) and RNA-seq. MYCL and EP400 were required for maintenance of cell viability and cooperated with ST to promote gene expression in MCC cell lines. A genome-wide CRISPR-Cas9 screen confirmed the requirement for MYCL and EP400 in MCPyV-positive MCC cell lines. We demonstrate that ST can activate gene expression in a EP400 and MYCL dependent manner and this activity contributes to cellular transformation and generation of induced pluripotent stem cells.

Merkel cell polyomavirus (MCPyV) is an etiological agent of Merkel cell carcinoma (MCC), a highly aggressive skin cancer. The MCPyV small tumor antigen (ST) is required for maintenance of MCC and can transform normal cells. To gain insight into cellular perturbations induced by MCPyV ST, we performed transcriptome analysis of normal human fibroblasts with inducible expression of ST. MCPyV ST dynamically alters the cellular transcriptome with increased levels of glycolytic genes, including the monocarboxylate lactate transporter SLC16A1 (MCT1). Extracellular flux analysis revealed increased lactate export reflecting elevated aerobic glycolysis in ST expressing cells. Inhibition of MCT1 activity suppressed the growth of MCC cell lines and impaired MCPyV-dependent transformation of IMR90 cells. Both NF-κB and MYC have been shown to regulate MCT1 expression. While MYC was required for MCT1 induction, MCPyV-induced MCT1 levels decreased following knockdown of the NF-κB subunit RelA, supporting a synergistic activity between MCPyV and MYC in regulating MCT1 levels. Several MCC lines had high levels of MYCL and MYCN but not MYC. Increased levels of MYCL was more effective than MYC or MYCN in increasing extracellular acidification in MCC cells. Our results demonstrate the effects of MCPyV ST on the cellular transcriptome and reveal that transformation is dependent, at least in part, on elevated aerobic glycolysis., Competing Interests: The authors have declared that no competing interests exist.

Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Pluripotent cells give rise to distinct cell types during development and are regulated by often self-reinforcing molecular networks. How such networks allow cells to differentiate is less well understood. Here, we use integrative methods to show that external signals induce reorganization of the mouse embryonic stem cell pluripotency network and that a sub-network of four factors, Nac1, Oct4, Tcf3, and Sox2, regulates their differentiation into the alternative mesendodermal and neuroectodermal fates. In the mesendodermal fate, Nac1 and Oct4 were constrained within quantitative windows, whereas Sox2 and Tcf3 were repressed. In contrast, in the neuroectodermal fate, Sox2 and Tcf3 were constrained while Nac1 and Oct4 were repressed. In addition, we show that Nac1 coordinates differentiation by activating Oct4 and inhibiting both Sox2 and Tcf3. Reorganization of progenitor cell networks around shared factors might be a common differentiation strategy and our integrative approach provides a general methodology for delineating such networks., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Genome-wide libraries of yeast deletion strains have been used to screen for genes that drive phenotypes such as stress response. A surprising observation emerging from these studies is that the genes with the largest changes in mRNA expression during a state transition are not those that drive that transition. Here, we show that integrating gene expression data with context-independent protein interaction networks can help prioritize master regulators that drive biological phenotypes., Results: Genes essential for survival had previously been shown to exhibit high centrality in protein interaction networks. However, the set of genes that drive growth in any specific condition is highly context-dependent. We inferred regulatory networks from gene expression data and transcription factor binding motifs in Saccharomyces cerevisiae, and found that high-degree nodes in regulatory networks are enriched for transcription factors that drive the corresponding phenotypes. We then found that using a metric combining protein interaction and transcriptional networks improved the enrichment for drivers in many of the contexts we examined. We applied this principle to a dataset of gene expression in normal human fibroblasts expressing a panel of viral oncogenes. We integrated regulatory interactions inferred from this data with a database of yeast two-hybrid protein interactions and ranked 571 human transcription factors by their combined network score. The ranked list was significantly enriched in known cancer genes that could not be found by standard differential expression or enrichment analyses., Conclusions: There has been increasing recognition that network-based approaches can provide insight into critical cellular elements that help define phenotypic state. Our analysis suggests that no one network, based on a single data type, captures the full spectrum of interactions. Greater insight can instead be gained by exploring multiple independent networks and by choosing an appropriate metric on each network. Moreover we can improve our ability to rank phenotypic drivers by combining the information from individual networks. We propose that such integrative network analysis could be used to combine clinical gene expression data with interaction databases to prioritize patient- and disease-specific therapeutic targets.

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Cell cycle-dependent gene expression is often controlled on the transcriptional level. Genes like cyclin B, CDC2 and CDC25C are regulated by cell cycle-dependent element (CDE) and cell cycle genes homology region (CHR) promoter elements mainly through repression in G(0)/G(1). It had been suggested that E2F4 binding to CDE sites is central to transcriptional regulation. However, some promoters are only controlled by a CHR. We identify the DREAM complex binding to the CHR of mouse and human cyclin B2 promoters in G(0). Association of DREAM and cell cycle-dependent regulation is abrogated when the CHR is mutated. Although E2f4 is part of the complex, a CDE is not essential but can enhance binding of DREAM. We show that the CHR element is not only necessary for repression of gene transcription in G(0)/G(1), but also for activation in S, G(2) and M phases. In proliferating cells, the B-myb-containing MMB complex binds the CHR of both promoters independently of the CDE. Bioinformatic analyses identify many genes which contain conserved CHR elements in promoters binding the DREAM complex. With Ube2c as an example from that screen, we show that inverse CHR sites are functional promoter elements that can bind DREAM and MMB. Our findings indicate that the CHR is central to DREAM/MMB-dependent transcriptional control during the cell cycle.

The small genome of polyomaviruses encodes a limited number of proteins that are highly dependent on interactions with host cell proteins for efficient viral replication. The SV40 large T antigen (LT) contains several discrete functional domains including the LXCXE or RB-binding motif, the DNA binding and helicase domains that contribute to the viral life cycle. In addition, the LT C-terminal region contains the host range and adenovirus helper functions required for lytic infection in certain restrictive cell types. To understand how LT affects the host cell to facilitate viral replication, we expressed full-length or functional domains of LT in cells, identified interacting host proteins and carried out expression profiling. LT perturbed the expression of p53 target genes and subsets of cell-cycle dependent genes regulated by the DREAM and the B-Myb-MuvB complexes. Affinity purification of LT followed by mass spectrometry revealed a specific interaction between the LT C-terminal region and FAM111A, a previously uncharacterized protein. Depletion of FAM111A recapitulated the effects of heterologous expression of the LT C-terminal region, including increased viral gene expression and lytic infection of SV40 host range mutants and adenovirus replication in restrictive cells. FAM111A functions as a host range restriction factor that is specifically targeted by SV40 LT.

Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases), are also associated with viral infections (virally implicated diseases), either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV) and human papillomavirus (HPV), we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.

Epstein-Barr virus (EBV) latent membrane protein 1 (LMP1) transforms rodent fibroblasts and is expressed in most EBV-associated malignancies. LMP1 (transformation effector site 2 [TES2]/C-terminal activation region 2 [CTAR2]) activates NF-κB, p38, Jun N-terminal protein kinase (JNK), extracellular signal-regulated kinase (ERK), and interferon regulatory factor 7 (IRF7) pathways. We have investigated LMP1 TES2 genome-wide RNA effects at 4 time points after LMP1 TES2 expression in HEK-293 cells. By using a false discovery rate (FDR) of <0.001 after correction for multiple hypotheses, LMP1 TES2 caused >2-fold changes in 1,916 mRNAs; 1,479 RNAs were upregulated and 437 were downregulated. In contrast to tumor necrosis factor alpha (TNF-α) stimulation, which transiently upregulates many target genes, LMP1 TES2 maintained most RNA effects through the time course, despite robust and sustained induction of negative feedback regulators, such as IκBα and A20. LMP1 TES2-regulated RNAs encode many NF-κB signaling proteins and secondary interacting proteins. Consequently, many LMP1 TES2-regulated RNAs encode proteins that form an extensive interactome. Gene set enrichment analyses found LMP1 TES2-upregulated genes to be significantly enriched for pathways in cancer, B- and T-cell receptor signaling, and Toll-like receptor signaling. Surprisingly, LMP1 TES2 and IκBα superrepressor coexpression decreased LMP1 TES2 RNA effects to only 5 RNAs, with FDRs of <0.001-fold and >2-fold changes. Thus, canonical NF-κB activation is critical for almost all LMP1 TES2 RNA effects in HEK-293 cells and a more significant therapeutic target than previously appreciated.