Identifying Novel Therapeutic Targets by Combining Transcriptional Data with Ordinal Clinical Measurements
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE98740 | GEO | 2017/05/11
SECONDARY ACCESSION(S): PRJNA386152
REPOSITORIES: GEO
Similar Datasets
Project description:The immense and growing repositories of transcriptional data may contain critical insights for developing new therapies. Current approaches to mining these data largely rely on binary classifications of disease vs. control, and are not able to incorporate measures of disease severity. We report an analytical approach to integrate ordinal clinical information with transcriptomics. We apply this method to public data for a large cohort of Huntington's disease patients and controls, identifying and prioritizing phenotype-associated genes. We verify the role of a high-ranked gene in dysregulation of sphingolipid metabolism in the disease and demonstrate that inhibiting the enzyme, sphingosine-1-phosphate lyase 1 (SPL), has neuroprotective effects in Huntington's disease models. Finally, we show that one consequence of inhibiting SPL is intracellular inhibition of histone deacetylases, thus linking our observations in sphingolipid metabolism to a well-characterized Huntington's disease pathway. Our approach is easily applied to any data with ordinal clinical measurements, and may deepen our understanding of disease processes.Identifying gene subsets affecting disease phenotypes from transcriptome data is challenge. Here, the authors develop a method that combines transcriptional data with disease ordinal clinical measurements to discover a sphingolipid metabolism regulator involving in Huntington's disease progression.
| S-EPMC5606996 | biostudies-literature
Project description:The widespread adoption of transcriptional profiling has led to immense repositories of data that may contain critical insights for developing new therapies. Current approaches to mining these data largely rely on binary classifications of disease versus control. These methods are not able to incorporate measures of disease severity, which are often available. We report an analytical approach to integrate ordinal clinical information with transcriptomics. We have applied this method to public data for a large cohort of Huntington’s disease patients and controls, identifying and prioritizing phenotype-associated genes. To validate the approach, we have performed viability, siRNA knockdown, mRNA-seq, and ChIP-seq on striatal precursor cells expressing either full-length wild type (STHdh Q7) or mutant huntingtin (STHdh Q111). We have verified the role of a high-ranked gene in dysregulation of sphingolipid metabolism in the disease and demonstrated that inhibiting the enzyme, SPL, has neuroprotective effects in HD models. We have shown that one consequence of inhibiting SPL is the intracellular inhibition of HDACs, thus linking our observations in sphingolipid metabolism to a well-characterized HD pathway. Our approach is easily applied to any data with ordinal clinical measurements, and may deepen our understanding of disease processes.
2017-05-11 | GSE98739 | GEO
Project description:Identifying Novel Therapeutic Targets by Combining Transcriptional Data with Ordinal Clinical Measurements
| PRJNA386152 | ENA
Project description:The widespread adoption of transcriptional profiling has led to immense repositories of data that may contain critical insights for developing new therapies. Current approaches to mining these data largely rely on binary classifications of disease versus control. These methods are not able to incorporate measures of disease severity, which are often available. We report an analytical approach to integrate ordinal clinical information with transcriptomics. We have applied this method to public data for a large cohort of Huntington’s disease patients and controls, identifying and prioritizing phenotype-associated genes. To validate the approach, we have performed viability, siRNA knockdown, mRNA-seq, and ChIP-seq on striatal precursor cells expressing either full-length wild type (STHdh Q7) or mutant huntingtin (STHdh Q111). We have verified the role of a high-ranked gene in dysregulation of sphingolipid metabolism in the disease and demonstrated that inhibiting the enzyme, SPL, has neuroprotective effects in HD models. We have shown that one consequence of inhibiting SPL is the intracellular inhibition of HDACs, thus linking our observations in sphingolipid metabolism to a well-characterized HD pathway. Our approach is easily applied to any data with ordinal clinical measurements, and may deepen our understanding of disease processes.
2017-05-11 | GSE98738 | GEO
Project description:Adipose tissue (AT) is an active endocrine organ with the ability to dynamically secrete a wide range of adipocytokines. Importantly, its secretory profile is altered in various cardiovascular disease states. AT surrounding vessels, or perivascular AT (PVAT), is recognized in particular as an important local regulator of vascular function and dysfunction. Specifically, PVAT has the ability to sense vascular paracrine signals and respond by secreting a variety of vasoactive adipocytokines. Due to the crucial role of PVAT in regulating many aspects of vascular biology, it may constitute a novel therapeutic target for the prevention and treatment of vascular disease pathogenesis. Signalling pathways in PVAT, such as those using adiponectin, H2 S, glucagon-like peptide 1 or pro-inflammatory cytokines, are among the potential novel pharmacological therapeutic targets of PVAT. LINKED ARTICLES:This article is part of a themed section on Molecular Mechanisms Regulating Perivascular Adipose Tissue - Potential Pharmacological Targets? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.20/issuetoc.
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Project description:Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by interacting unexpectedly on the same cryptic targets. By constructing and mining an Alzheimer's disease (AD) drug-oriented chemical-protein interactome (CPI) using a matrix of 10 drug molecules known to treat AD towards 401 human protein pockets, we found that such cryptic targets exist. We recovered from CPI the only validated therapeutic target of AD, acetylcholinesterase (ACHE), and highlighted several other putative targets. For example, we discovered that estrogen receptor (ER) and histone deacetylase (HDAC), which have recently been identified as two new therapeutic targets of AD, might already have been targeted by the marketed AD drugs. We further established that the CPI profile of a drug can reflect its interacting character towards multi-protein sets, and that drugs with the same therapeutic attribute will share a similar interacting profile. These findings indicate that the CPI could represent the landscape of chemical-protein interactions and uncover "behind-the-scenes" aspects of the therapeutic mechanisms of existing drugs, providing testable hypotheses of the key nodes for network pharmacology or brand new drug targets for one-target pharmacology paradigm.
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Project description:Prioritizing genes for translation to therapeutics for common diseases has been challenging. Here, we propose an approach to identify drug targets with high probability of success by focusing on genes with both gain of function (GoF) and loss of function (LoF) mutations associated with opposing effects on phenotype (Bidirectional Effect Selected Targets, BEST). We find 98 BEST genes for a variety of indications. Drugs targeting those genes are 3.8-fold more likely to be approved than non-BEST genes. We focus on five genes (IGF1R, NPPC, NPR2, FGFR3, and SHOX) with evidence for bidirectional effects on stature. Rare protein-altering variants in those genes result in significantly increased risk for idiopathic short stature (ISS) (OR = 2.75, p = 3.99 × 10-8). Finally, using functional experiments, we demonstrate that adding an exogenous CNP analog (encoded by NPPC) rescues the phenotype, thus validating its potential as a therapeutic treatment for ISS. Our results show the value of looking for bidirectional effects to identify and validate drug targets.
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Project description:Introduction: Cholangiocarcinoma (CCA) is a liver cancer derived from the biliary tree with a less than 30% five-year survival rate. Early diagnosis of CCA is challenging and treatment options are limited. Some CCA patients have genetic mutations and several therapeutic drugs or antibodies have been introduced to target abnormally expressed proteins. However, CCA is heterogeneous and patients often present with drug resistance which is attributed to multiple mutations or other factors. Novel approaches and methodologies for CCA treatments are in demand.Area covered: This review summarizes current approaches for CCA treatments leading to the development of novel therapeutic drugs or tools for human CCA patients. A literature search was conducted in PubMed utilizing the combination of the searched term 'cholangiocarcinoma' with other keywords such as 'miRNA', 'FGFR', 'immunotherapy' or 'microenvironment'. Papers published within 2015-2019 were obtained for reading.Expert opinion: Preclinical studies have demonstrated promising therapeutic approaches that target various cells or pathways. Recent studies have revealed that hepatic cells coordinate to promote CCA tumor progression in the tumor microenvironment, which may be a new therapeutic target. Although further studies are required, novel therapeutic tools such as extracellular vesicles could be utilized to manage CCA and its microenvironment.
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Project description:Lennert lymphoma (LL) is a lymphoepithelioid morphological variant of peripheral T-cell lymphoma-not otherwise specified (PTCL/NOS), clinically characterized by better prognosis if compared with other PTCL/NOS. Although well characterized as far as morphology and phenotype are concerned, very little is known regarding its molecular features. In this study, we investigated the transcriptional profile of this tumor aiming 1) to identify its cellular counterparts; 2) to better define its relation with other PTCLs-and, therefore, its possible position in lymphoma classification; and 3) to define pathogenetic mechanisms, possibly unveiling novel therapeutic targets. To address these issues, we performed gene and microRNA expression profiling on LL and other PTCL/NOS cases; we identified different genes and microRNAs that discriminated LL from other PTCL/NOS. Particularly, LL revealed a molecular signature significantly enriched in helper function and clearly distinguishable from other PTCL/NOS. Furthermore, PI3K/Akt/mTOR pathway emerged as novel potential therapeutic target. In conclusion, based on the already known particular morphological and clinical features, the new molecular findings support the hypothesis that LL might be classified as a separate entity. Preclinical and clinical studies testing the efficacy of PI3K/MTOR inhibitors in this setting are warranted.
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Project description:This SuperSeries is composed of the SubSeries listed below.
2019-12-27 | GSE134605 | GEO