The development of precision medicine for the management of metastatic breast cancer is an appealing concept; however, major scientific and logistical challenges hinder its implementation in the ...clinic. The identification of driver mutational events remains the biggest challenge, because, with the few exceptions of ER, HER2, PIK3CA and AKT1, no validated oncogenic drivers of breast cancer exist. The development of bioinformatic tools to help identify driver mutations, together with assessment of pathway activation and dependency should help resolve this issue in the future. The occurrence of secondary resistance, such as ESR1 mutations, following endocrine therapy poses a further challenge. Ultra-deep sequencing and monitoring of circulating tumour DNA (ctDNA) could permit early detection of the genetic events underlying resistance and inform on combination therapy approaches. Beside these scientific challenges, logistical and operational issues are a major limitation to the development of precision medicine. For example, the low incidence of most candidate genomic alterations hinders randomized trials, as the number of patients to be screened would be too high. We discuss these limitations and the solutions, which include scaling-up the number of patients screened for identifying a genomic alteration, the clustering of genomic alterations into pathways, and the development of personalized medicine trials.
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NUK, OILJ, SBMB, UL, UM, UPUK
Abstract
To generate new mechanistic hypotheses on the pathogenesis and disease progression of neuroHIV and identify novel therapeutic targets to improve neuropsychological function in people with ...HIV, we investigated host genes and pathway dysregulations associated with brain HIV RNA load in gene expression profiles of the frontal cortex, basal ganglia, and white matter of HIV+ patients. Pathway analyses showed that host genes correlated with HIV expression in all three brain regions were predominantly related to inflammation, neurodegeneration, and bioenergetics. HIV RNA load directly correlated particularly with inflammation genesets representative of cytokine signaling, and this was more prominent in white matter and the basal ganglia. Increases in interferon signaling were correlated with high brain HIV RNA load in the basal ganglia and the white matter although not in the frontal cortex. Brain HIV RNA load was inversely correlated with genesets that are indicative of neuronal and synaptic genes, particularly in the cortex, indicative of synaptic injury and neurodegeneration. Brain HIV RNA load was inversely correlated with genesets that are representative of oxidative phosphorylation, electron transfer, and the tricarboxylic acid cycle in all three brain regions. Mitochondrial dysfunction has been implicated in the toxicity of some antiretrovirals, and these results indicate that mitochondrial dysfunction is also associated with productive HIV infection. Genes and pathways correlated with brain HIV RNA load suggest potential therapeutic targets to ameliorate neuropsychological functioning in people living with HIV.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms. Much of our present knowledge derives from high-throughput ...techniques such as the yeast two-hybrid assay and affinity purification, as well as from manual curation of experiments on individual systems. A variety of computational approaches based, for example, on sequence homology, gene co-expression and phylogenetic profiles, have also been developed for the genome-wide inference of protein-protein interactions (PPIs). Yet comparative studies suggest that the development of accurate and complete repertoires of PPIs is still in its early stages. Here we show that three-dimensional structural information can be used to predict PPIs with an accuracy and coverage that are superior to predictions based on non-structural evidence. Moreover, an algorithm, termed PrePPI, which combines structural information with other functional clues, is comparable in accuracy to high-throughput experiments, yielding over 30,000 high-confidence interactions for yeast and over 300,000 for human. Experimental tests of a number of predictions demonstrate the ability of the PrePPI algorithm to identify unexpected PPIs of considerable biological interest. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models combined with the exploitation of both close and remote geometric relationships between proteins.
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DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Unsustained enzyme inhibition is a barrier to targeted therapy for cancer. Here, resistance to a class I PI3K inhibitor in a model of metastatic breast cancer driven by PI3K and MYC was associated ...with feedback activation of tyrosine kinase receptors (RTKs), AKT, mTOR, and MYC. Inhibitors of bromodomain and extra terminal domain (BET) proteins also failed to affect tumor growth. Interestingly, BET inhibitors lowered PI3K signaling and dissociated BRD4 from chromatin at regulatory regions of insulin receptor and EGFR family RTKs to reduce their expression. Combined PI3K and BET inhibition induced cell death, tumor regression, and clamped inhibition of PI3K signaling in a broad range of tumor cell lines to provide a strategy to overcome resistance to kinase inhibitor therapy.
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•BET inhibitors lower the expression of RTKs and the PI3K signal•BET inhibition blocks BRD4 binding at the promoter of several RTKs•Activation of AKT, mTOR, and MYC due to PI3K inhibition is blocked by BET inhibitors•Targeting BRD4 and PI3K together, but not alone, inhibits growth of many tumor cells
Inhibition of PI3K induces feedback activation of upstream RTKs and quick rebound of the pathway activity. Stratikopoulos et al. show that BRD4 is important for the feedback activation of many RTKs and that combined PI3K and BET inhibition sustains PI3K pathway inhibition and enhances tumor cell killing.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as ...evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The pathogenesis and nosology of HIV-associated neurological disease (HAND) remain incompletely understood. Here, to provide new insight into the molecular events leading to neurocognitive ...impairments (NCI) in HIV infection, we analyzed pathway dysregulations in gene expression profiles of HIV-infected patients with or without NCI and HIV encephalitis (HIVE) and control subjects. The Gene Set Enrichment Analysis (GSEA) algorithm was used for pathway analyses in conjunction with the Molecular Signatures Database collection of canonical pathways (MSigDb). We analyzed pathway dysregulations in gene expression profiles of patients from the National NeuroAIDS Tissue Consortium (NNTC), which consists of samples from 3 different brain regions, including white matter, basal ganglia and frontal cortex of HIV-infected and control patients. While HIVE is characterized by widespread, uncontrolled inflammation and tissue damage, substantial gene expression evidence of induction of interferon (IFN), cytokines and tissue injury is apparent in all brain regions studied, even in the absence of NCI. Various degrees of white matter changes were present in all HIV-infected subjects and were the primary manifestation in patients with NCI in the absence of HIVE. In particular, NCI in patients without HIVE in the NNTC sample is associated with white matter expression of chemokines, cytokines and β-defensins, without significant activation of IFN. Altogether, the results identified distinct pathways differentially regulated over the course of neurological disease in HIV infection and provide a new perspective on the dynamics of pathogenic processes in the course of HIV neurological disease in humans. These results also demonstrate the power of the systems biology analyses and indicate that the establishment of larger human gene expression profile datasets will have the potential to provide novel mechanistic insight into the pathogenesis of neurological disease in HIV infection and identify better therapeutic targets for NCI.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Motivation: An increasingly common application of gene expression profile data is the reverse engineering of cellular networks. However, common procedures to normalize expression profiles generated ...using the Affymetrix GeneChips technology were originally developed for a rather different purpose, namely the accurate measure of differential gene expression between two or more phenotypes. As a result, current evaluation strategies lack comprehensive metrics to assess the suitability of available normalization procedures for reverse engineering and, in general, for measuring correlation between the expression profiles of a gene pair. Results: We benchmark four commonly used normalization procedures (MAS5, RMA, GCRMA and Li-Wong) in the context of established algorithms for the reverse engineering of protein–protein and protein–DNA interactions. Replicate sample, randomized and human B-cell data sets are used as an input. Surprisingly, our study suggests that MAS5 provides the most faithful cellular network reconstruction. Furthermore, we identify a crucial step in GCRMA responsible for introducing severe artifacts in the data leading to a systematic overestimate of pairwise correlation. This has key implications not only for reverse engineering but also for other methods, such as hierarchical clustering, relying on accurate measurements of pairwise expression profile correlation. We propose an alternative implementation to eliminate such side effect. Contect: califano@c2b2.columbia.edu
Alzheimer's disease (AD) is a complex multifactorial disorder with poorly characterized pathogenesis. Our understanding of this disease would thus benefit from an approach that addresses this ...complexity by elucidating the regulatory networks that are dysregulated in the neural compartment of AD patients, across distinct brain regions. Here, we use a Systems Biology (SB) approach, which has been highly successful in the dissection of cancer related phenotypes, to reverse engineer the transcriptional regulation layer of human neuronal cells and interrogate it to infer candidate Master Regulators (MRs) responsible for disease progression. Analysis of gene expression profiles from laser-captured neurons from AD and controls subjects, using the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe), yielded an interactome consisting of 488,353 transcription-factor/target interactions. Interrogation of this interactome, using the Master Regulator INference algorithm (MARINa), identified an unbiased set of candidate MRs causally responsible for regulating the transcriptional signature of AD progression. Experimental assays in autopsy-derived human brain tissue showed that three of the top candidate MRs (YY1, p300 and ZMYM3) are indeed biochemically and histopathologically dysregulated in AD brains compared to controls. Our results additionally implicate p53 and loss of acetylation homeostasis in the neurodegenerative process. This study suggests that an integrative, SB approach can be applied to AD and other neurodegenerative diseases, and provide significant novel insight on the disease progression.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Assembly of a transcriptional and post‐translational molecular interaction network in B cells, the human B‐cell interactome (HBCI), reveals a hierarchical, transcriptional control module, where MYB ...and FOXM1 act as synergistic master regulators of proliferation in the germinal center (GC). Eighty percent of genes jointly regulated by these transcription factors are activated in the GC, including those encoding proteins in a complex regulating DNA pre‐replication, replication, and mitosis. These results indicate that the HBCI analysis can be used for the identification of determinants of major human cell phenotypes and provides a paradigm of general applicability to normal and pathologic tissues.
Synopsis
We have assembled an interaction network specific to human B cells (the human B‐cell interactome or HBCI), containing protein–DNA and protein–protein interactions using an evidence integration approach. The integration of different interaction layers in one network allowed us to elucidate master regulator (MR) genes controlling specific cellular processes as well as transcriptional regulation of proteins in complexes whose availability must be regulated in context‐dependent manner. The latter is a poorly understood process, as transcriptional networks and protein–protein interaction networks are usually studied in isolation. We have developed a new algorithm called master regulator inference analysis (MARINa) for discovering MRs of specific phenotypes and applied it to the HBCI to infer MRs of germinal center (GC) formation. GCs are structures where antigen‐stimulated B cells highly proliferate, undergo somatic hypermutation of immunoglobulin genes, and are selected based on the production of high‐affinity antibodies. GC B cells (centroblasts) derive from naive B cells, from which they differ for the activation of genetic programs controlling cell proliferation, DNA metabolism, and pro‐apoptotic programs and for the repression of anti‐apoptotic, cell‐cycle arrest, DNA repair, and signal transduction programs from cytokines and chemokines. MARINa recovered known MRs of GC B cells and also revealed a new transcription factor module controlling their proliferation. In particular, we identified MYB and FOXM1 as being key MRs of GC B cells. Indeed, 80% of the genes jointly regulated by these transcription factors are activated in the GC, including those encoding proteins in a predicted complex regulating DNA pre‐replication, replication, and mitosis. We first tested whether MYB and FOXM1 may regulate each other as predicted in the HBCI, and show that MYB is a transcriptional activator of FOXM1, suggesting that they form a feed‐forward loop, involved in the synergistic activation of a large subset of GC‐specific genes. We then validated that common MYB/FOXM1 targets and other predicted MRs were affected by the silencing of either TF, using gene expression profiling. Furthermore, we showed that downregulated targets (AURKA, BUBR1, CCNB2, FANCI, MCM3, and PTTG1) and MRs (NFYB, E2F1, and E2F5) after MYB or FOXM1 silencing are indeed directly bound by them in their promoter region. Silencing of FOXM1 and MYB showed a decrease in proliferating cells and an increase in apoptotic cells, indicating that MYB and FOXM1 are necessary for viability and rapid proliferation of GC B cells. To gain more insight into the control of GC‐proliferation phenotype by MYB and FOXM1, we further examined specific targets involved in the formation of a predicted protein complex. Approximately half of MYB/FOXM1 targets cluster within a complex, including new interactions between pre‐replication and mitotic proteins. We experimentally validate that two mitotic kinases in the inferred complex, BUBR1 and AURKA, physically interact with MCM3, all of them being confirmed to be direct targets of FOXM1 and MYB. In summary, these results document that coordinated analysis of both transcriptional and post‐translational interactions in the HBCI can identify synergistic MRs of human phenotypes, as well as provide insight on the functional regulatory role of these proteins. These results indicate that the HBCI analysis can be used for the identification of determinants of major human cell phenotypes and provides a paradigm of general applicability to normal and pathologic tissues.
Assembly of a mixed interaction network specific to human B cells.
Identification and validation of master regulators of germinal center reaction.
MYB and FOXM1 are synergistic master regulators of proliferation in germinal center B cells and control a new protein complex involving replication and mitotic‐related genes.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
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