72 results match your criteria: "University of Pittsburgh Drug Discovery Institute[Affiliation]"

Article Synopsis
  • The study suggests that insulin resistance in the liver is a key factor leading to dysfunction in pancreatic islets, which is linked to Type 2 Diabetes Mellitus (T2DM) and Metabolic Associated Steatotic Liver Disease (MASLD).
  • Researchers developed a microphysiological system combining liver and pancreatic models to better understand how these organ dysfunctions relate to each other. This system allows for the investigation of changes that occur when metabolic syndrome is present.
  • Results showed that under metabolic syndrome conditions, the liver-pancreas system exhibited altered insulin secretion and signaling, indicating a direct connection between liver issues and islet dysfunction, which could help in developing personalized treatment strategies for affected patients.
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Despite clinical benefits of tyrosine kinase inhibitors (TKIs) in cancer, most tumors can reactivate proliferation under TKI therapy. Here we present transcriptional profiling of HER2+ breast cancer cells transitioning from dormant drug tolerant cells to re-proliferating cells under continuous HER2 inhibitor (HER2i) therapy. Focusing on phosphatases, expression of dual-specificity phosphatase DUSP6 was found inhibited in dormant cells, but strongly induced upon regrowth.

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Background And Aims: Chronic liver injury that results in cirrhosis and end-stage liver disease (ESLD) causes more than 1 million deaths annually worldwide. Although the impact of genetic factors on the severity of metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-related liver disease (ALD) has been previously studied, their contribution to the development of ESLD remains largely unexplored.

Methods: We genotyped 6 MASLD-associated polymorphisms in healthy (n = 123), metabolic dysfunction-associated steatohepatitis (MASH) (n = 145), MASLD-associated ESLD (n = 72), and ALD-associated ESLD (n = 57) cohorts and performed multinomial logistic regression to determine the combined contribution of genetic, demographic, and clinical factors to the progression of ESLD.

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Primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC), the most common types of cholestatic liver disease (CLD), result in enterohepatic obstruction, bile acid accumulation, and hepatotoxicity. The mechanisms by which hepatocytes respond to and cope with CLD remain largely unexplored. This study includes the characterization of hepatocytes isolated from explanted livers of patients with PBC and PSC.

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Advances in cellular engineering, as well as gene, and cell therapy, may be used to produce human tissues with programmable genetically enhanced functions designed to model and/or treat specific diseases. Fabrication of synthetic human liver tissue with these programmable functions has not been described. By generating human iPSCs with target gene expression controlled by a guide RNA-directed CRISPR-Cas9 synergistic-activation-mediator, we produced synthetic human liver tissues with programmable functions.

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Biomanufacturing in low Earth orbit for regenerative medicine.

Stem Cell Reports

January 2022

McGowan Institute for Regenerative Medicine, Pittsburgh, PA, USA; Departments of Surgery, Bioengineering, Chemical Engineering, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address:

Research in low Earth orbit (LEO) has become more accessible. The 2020 Biomanufacturing in Space Symposium reviewed space-based regenerative medicine research and discussed leveraging LEO to advance biomanufacturing for regenerative medicine applications. The symposium identified areas where financial investments could stimulate advancements overcoming technical barriers.

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Tumors are dynamic ecosystems comprising localized niches (microdomains), possessing distinct compositions and spatial configurations of cancer and non-cancer cell populations. Microdomain-specific network signaling coevolves with a continuum of cell states and functional plasticity associated with disease progression and therapeutic responses. We present LEAPH, an unsupervised machine learning algorithm for identifying cell phenotypes, which applies recursive steps of probabilistic clustering and spatial regularization to derive functional phenotypes (FPs) along a continuum.

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A systems-level study reveals host-targeted repurposable drugs against SARS-CoV-2 infection.

Mol Syst Biol

August 2021

Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

Understanding the mechanism of SARS-CoV-2 infection and identifying potential therapeutics are global imperatives. Using a quantitative systems pharmacology approach, we identified a set of repurposable and investigational drugs as potential therapeutics against COVID-19. These were deduced from the gene expression signature of SARS-CoV-2-infected A549 cells screened against Connectivity Map and prioritized by network proximity analysis with respect to disease modules in the viral-host interactome.

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Inhibition of RPS6K reveals context-dependent Akt activity in luminal breast cancer cells.

PLoS Comput Biol

June 2021

Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.

Aberrant signaling through insulin (Ins) and insulin-like growth factor I (IGF1) receptors contribute to the risk and advancement of many cancer types by activating cell survival cascades. Similarities between these pathways have thus far prevented the development of pharmacological interventions that specifically target either Ins or IGF1 signaling. To identify differences in early Ins and IGF1 signaling mechanisms, we developed a dual receptor (IGF1R & InsR) computational response model.

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Molecular chaperones, such as Hsp70, prevent proteotoxicity and maintain homeostasis. This is perhaps most evident in cancer cells, which overexpress Hsp70 and thrive even when harboring high levels of misfolded proteins. To define the response to proteotoxic challenges, we examined adaptive responses in breast cancer cells in the presence of an Hsp70 inhibitor.

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Metabolic syndrome is a complex disease that involves multiple organ systems including a critical role for the liver. Non-alcoholic fatty liver disease (NAFLD) is a key component of the metabolic syndrome and fatty liver is linked to a range of metabolic dysfunctions that occur in approximately 25% of the population. A panel of experts recently agreed that the acronym, NAFLD, did not properly characterize this heterogeneous disease given the associated metabolic abnormalities such as type 2 diabetes mellitus (T2D), obesity, and hypertension.

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Microphysiology systems (MPS), also called organs-on-chips and tissue chips, are miniaturized functional units of organs constructed with multiple cell types under a variety of physical and biochemical environmental cues that complement animal models as part of a new paradigm of drug discovery and development. Biomimetic human liver MPS have evolved from simpler 2D cell models, spheroids and organoids to address the increasing need to understand patient-specific mechanisms of complex and rare diseases, the response to therapeutic treatments, and the absorption, distribution, metabolism, excretion and toxicity of potential therapeutics. The parallel development and application of transdisciplinary technologies, including microfluidic devices, bioprinting, engineered matrix materials, defined physiological and pathophysiological media, patient-derived primary cells, and pluripotent stem cells as well as synthetic biology to engineer cell genes and functions, have created the potential to produce patient-specific, biomimetic MPS for detailed mechanistic studies.

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Article Synopsis
  • * Common mutations, such as those activating STAT5 and ERK proteins, typically do not occur together, which indicates competition between pathways that lead to cancer development, with each pathway engaging different biochemical responses mediated by transcription factors MYC and BCL6.
  • * Reactivating the suppressed divergent pathways can counteract the main oncogenic driver, suggesting that targeting these pathways could improve treatment strategies for leukaemia.
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An unmet clinical need in solid tumor cancers is the ability to harness the intrinsic spatial information in primary tumors that can be exploited to optimize prognostics, diagnostics and therapeutic strategies for precision medicine. Here, we develop a transformational spatial analytics computational and systems biology platform (SpAn) that predicts clinical outcomes and captures emergent spatial biology that can potentially inform therapeutic strategies. We apply SpAn to primary tumor tissue samples from a cohort of 432 chemo-naïve colorectal cancer (CRC) patients iteratively labeled with a highly multiplexed (hyperplexed) panel of 55 fluorescently tagged antibodies.

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Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we show that development of AH is characterized by defective activity of liver-enriched transcription factors (LETFs).

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Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm.

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Systematic unbiased high-throughput screening (HTS) of drug combinations (DCs) in well-characterized tumor cell lines is a data-driven strategy to identify novel DCs with potential to be developed into effective therapies. Four DCs from a DC HTS campaign were selected for confirmation; only one appears in clinicaltrials.gov and limited preclinical in vitro data indicates that the drug pairs interact synergistically.

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New neuroprotective therapies for severe traumatic brain injury (TBI) have not translated from pre-clinical to clinical success. Numerous explanations have been suggested in both the pre-clinical and clinical arenas. Coverage of TBI in the lay press has reinvigorated interest, creating a golden age of TBI research with innovative strategies to circumvent roadblocks.

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Animal and clinical studies demonstrate that cancer drug combinations (DCs) are more effective than single agents. However, it is difficult to predict which DCs will be more efficacious than individual drugs. Systematic DC high-throughput screening (HTS) of 100 approved drugs in the National Cancer Institute's panel of 60 cancer cell lines (NCI-60) produced data to help select DCs for further consideration.

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Zebrafish is the preferred vertebrate model for high throughput chemical screens to discover modulators of complex biological pathways. We adapted a transgenic zebrafish line, , which reports on fibroblast growth factor (Fgf)/Ras/Mapk activity, into a quantitative, high-content chemical screen to identify novel Fgf hyperactivators as chemical probes for zebrafish heart development and regeneration. We screened 10,000 compounds from the TimTec ActiProbe library, and identified several structurally distinct classes of molecules that enhanced Fgf/Ras/Mapk signaling.

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Designing effective therapeutic strategies for complex diseases such as cancer and neurodegeneration that involve tissue context-specific interactions among multiple gene products presents a major challenge for precision medicine. Safe and selective pharmacological modulation of individual molecular entities associated with a disease often fails to provide efficacy in the clinic. Thus, development of optimized therapeutic strategies for individual patients with complex diseases requires a more comprehensive, systems-level understanding of disease progression.

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The high-content interrogation of single cells with platforms optimized for the multiparameter characterization of cells in liquid and solid biopsy samples can enable characterization of heterogeneous populations of cells ex vivo. Doing so will advance the diagnosis, prognosis, and treatment of cancer and other diseases. However, it is important to understand the unique issues in resolving heterogeneity and variability at the single cell level before navigating the validation and regulatory requirements in order for these technologies to impact patient care.

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Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington's Disease Model through the Application of Quantitative Systems Pharmacology.

Sci Rep

December 2017

Department of Computational and Systems Biology, University of Pittsburgh, 3501 Fifth Ave, Suite 3064, Biomedical Science Tower 3, Pittsburgh, PA, 15260, USA.

Quantitative Systems Pharmacology (QSP) is a drug discovery approach that integrates computational and experimental methods in an iterative way to gain a comprehensive, unbiased understanding of disease processes to inform effective therapeutic strategies. We report the implementation of QSP to Huntington's Disease, with the application of a chemogenomics platform to identify strategies to protect neuronal cells from mutant huntingtin induced death. Using the STHdh cell model, we investigated the protective effects of small molecule probes having diverse canonical modes-of-action to infer pathways of neuronal cell protection connected to drug mechanism.

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In the canonical STAT3 signaling pathway, IL-6 receptor engagement leads to the recruitment of latent STAT3 to the activated IL-6 complex and the associated Janus kinase (JAK) phosphorylates STAT3 at Y705. pSTAT3-Y705 dimers traffic into the nucleus and bind to specific DNA response elements in the promoters of target genes to regulate their transcription. However, IL-6 receptor activation induces the phosphorylation of both the Y705 and S727 residues of STAT3, and S727 phosphorylation is required to achieve maximal STAT3 transcriptional activity.

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