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1.
Exp Dermatol ; 2021 Oct 25.
Artigo em Inglês | MEDLINE | ID: mdl-34694680

RESUMO

Chronic wounds present a major disease burden in people with recessive dystrophic epidermolysis bullosa (RDEB), an inherited blistering skin disorder caused by mutations in COL7A1 encoding type VII collagen, the major component of anchoring fibrils at the dermal-epidermal junction. Treatment of RDEB wounds is mostly symptomatic, and there is considerable unmet need in trying to improve and accelerate wound healing. In this study, we defined transcriptomic profiles and gene pathways in RDEB wounds and compared these to intact skin in RDEB and healthy control subjects. We then used a reverse transcriptomics approach to discover drugs or compounds, which might restore RDEB wound profiles towards intact skin. Differential expression analysis identified >2000 differences between RDEB wounds and intact skin, with RDEB wounds displaying aberrant cytokine-cytokine interactions, Toll-like receptor signalling, and JAK-STAT signalling pathways. In-silico prediction for compounds that reverse gene expression signatures highlighted methotrexate as a leading candidate. Overall, this study provides insight into the molecular profiles of RDEB wounds and underscores the possible clinical value of reverse transcriptomics data analysis in RDEB, and the potential of this approach in discovering or repurposing drugs for other diseases.

2.
Kidney Int ; 100(6): 1250-1267, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34634362

RESUMO

Loss of fatty acid ß-oxidation (FAO) in the proximal tubule is a critical mediator of acute kidney injury and eventual fibrosis. However, transcriptional mediators of FAO in proximal tubule injury remain understudied. Krüppel-like factor 15 (KLF15), a highly enriched zinc-finger transcription factor in the proximal tubule, was significantly reduced in proximal tubule cells after aristolochic acid I (AAI) treatment, a proximal tubule-specific injury model. Proximal tubule specific knockout of Klf15 exacerbated proximal tubule injury and kidney function decline compared to control mice during the active phase of AAI treatment, and after ischemia-reperfusion injury. Furthermore, along with worsening proximal tubule injury and kidney function decline, knockout mice exhibited increased kidney fibrosis as compared to control mice during the remodeling phase after AAI treatment. RNA-sequencing of kidney cortex demonstrated increased transcripts involved in immune system and integrin signaling pathways and decreased transcripts encompassing metabolic pathways, specifically FAO, and PPARα signaling, in knockout versus control mice after AAI treatment. In silico and experimental chromatin immunoprecipitation studies collectively demonstrated that KLF15 occupied the promoter region of key FAO genes, CPT1A and ACAA2, in close proximity to transcription factor PPARα binding sites. While the loss of Klf15 reduced the expression of Cpt1a and Acaa2 and led to compromised FAO, induction of KLF15 partially rescued loss of FAO in AAI-treated cells. Klf15, Ppara, Cpt1a, and Acaa2 expression was also decreased in other mouse kidney injury models. Tubulointerstitial KLF15 independently correlated with eGFR, PPARA and CPT1A appearance in expression arrays from human kidney biopsies. Thus, proximal tubule-specific loss of Klf15 exacerbates acute kidney injury and fibrosis, likely due to loss of interaction with PPARα leading to loss of FAO gene transcription.

3.
Front Med (Lausanne) ; 8: 666554, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34485323

RESUMO

Lyme disease (also known as Lyme borreliosis) is the most common vector-borne disease in the United States with an estimated 476,000 cases per year. While historically, the long-term impact of Lyme disease on patients has been controversial, mounting evidence supports the idea that a substantial number of patients experience persistent symptoms following treatment. The research community has largely lacked the necessary funding to properly advance the scientific and clinical understanding of the disease, or to develop and evaluate innovative approaches for prevention, diagnosis, and treatment. Given the many outstanding questions raised into the diagnosis, clinical presentation and treatment of Lyme disease, and the underlying molecular mechanisms that trigger persistent disease, there is an urgent need for more support. This review article summarizes progress over the past 5 years in our understanding of Lyme and tick-borne diseases in the United States and highlights remaining challenges.

5.
Proc Natl Acad Sci U S A ; 118(23)2021 06 08.
Artigo em Inglês | MEDLINE | ID: mdl-34074766

RESUMO

Altered cellular metabolism in kidney proximal tubule (PT) cells plays a critical role in acute kidney injury (AKI). The transcription factor Krüppel-like factor 6 (KLF6) is rapidly and robustly induced early in the PT after AKI. We found that PT-specific Klf6 knockdown (Klf6 PTKD) is protective against AKI and kidney fibrosis in mice. Combined RNA and chromatin immunoprecipitation sequencing analysis demonstrated that expression of genes encoding branched-chain amino acid (BCAA) catabolic enzymes was preserved in Klf6 PTKD mice, with KLF6 occupying the promoter region of these genes. Conversely, inducible KLF6 overexpression suppressed expression of BCAA genes and exacerbated kidney injury and fibrosis in mice. In vitro, injured cells overexpressing KLF6 had similar decreases in BCAA catabolic gene expression and were less able to utilize BCAA. Furthermore, knockdown of BCKDHB, which encodes one subunit of the rate-limiting enzyme in BCAA catabolism, resulted in reduced ATP production, while treatment with BCAA catabolism enhancer BT2 increased metabolism. Analysis of kidney function, KLF6, and BCAA gene expression in human chronic kidney disease patients showed significant inverse correlations between KLF6 and both kidney function and BCAA expression. Thus, targeting KLF6-mediated suppression of BCAA catabolism may serve as a key therapeutic target in AKI and kidney fibrosis.

6.
Nucleic Acids Res ; 49(W1): W304-W316, 2021 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-34019655

RESUMO

Phosphoproteomics and proteomics experiments capture a global snapshot of the cellular signaling network, but these methods do not directly measure kinase state. Kinase Enrichment Analysis 3 (KEA3) is a webserver application that infers overrepresentation of upstream kinases whose putative substrates are in a user-inputted list of proteins. KEA3 can be applied to analyze data from phosphoproteomics and proteomics studies to predict the upstream kinases responsible for observed differential phosphorylations. The KEA3 background database contains measured and predicted kinase-substrate interactions (KSI), kinase-protein interactions (KPI), and interactions supported by co-expression and co-occurrence data. To benchmark the performance of KEA3, we examined whether KEA3 can predict the perturbed kinase from single-kinase perturbation followed by gene expression experiments, and phosphoproteomics data collected from kinase-targeting small molecules. We show that integrating KSIs and KPIs across data sources to produce a composite ranking improves the recovery of the expected kinase. The KEA3 webserver is available at https://maayanlab.cloud/kea3.


Assuntos
Proteínas Quinases/metabolismo , Software , Expressão Gênica , Humanos , Fosforilação , Inibidores de Proteínas Quinases , Proteômica , SARS-CoV-2/enzimologia
7.
Sci Rep ; 11(1): 7315, 2021 04 01.
Artigo em Inglês | MEDLINE | ID: mdl-33795767

RESUMO

Fibrosis occurs when collagen deposition and fibroblast proliferation replace healthy tissue. Red light (RL) may improve skin fibrosis via photobiomodulation, the process by which photosensitive chromophores in cells absorb visible or near-infrared light and undergo photophysical reactions. Our previous research demonstrated that high fluence RL reduces fibroblast proliferation, collagen deposition, and migration. Despite the identification of several cellular mechanisms underpinning RL phototherapy, little is known about the transcriptional changes that lead to anti-fibrotic cellular responses. Herein, RNA sequencing was performed on human dermal fibroblasts treated with RL phototherapy. Pathway enrichment and transcription factor analysis revealed regulation of extracellular matrices, proliferation, and cellular responses to oxygen-containing compounds following RL phototherapy. Specifically, RL phototherapy increased the expression of MMP1, which codes for matrix metalloproteinase-1 (MMP-1) and is responsible for remodeling extracellular collagen. Differential regulation of MMP1 was confirmed with RT-qPCR and ELISA. Additionally, RL upregulated PRSS35, which has not been previously associated with skin activity, but has known anti-fibrotic functions. Our results suggest that RL may benefit patients by altering fibrotic gene expression.


Assuntos
Fibroblastos/metabolismo , Fibroblastos/efeitos da radiação , Fototerapia/métodos , Pele/metabolismo , Pele/efeitos da radiação , Transcriptoma , Adulto , Movimento Celular , Proliferação de Células , Colágeno/metabolismo , Feminino , Fibrose , Perfilação da Expressão Gênica , Humanos , Masculino , Metaloproteinase 1 da Matriz/biossíntese , Pessoa de Meia-Idade , Estresse Oxidativo , Oxigênio/metabolismo , RNA-Seq , Espécies Reativas de Oxigênio , Dermatopatias/metabolismo , Fatores de Tempo , Fatores de Transcrição
8.
Front Cell Dev Biol ; 9: 630067, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33816475

RESUMO

Cell fate decisions during development are governed by multi-factorial regulatory mechanisms including chromatin remodeling, DNA methylation, binding of transcription factors to specific loci, RNA transcription and protein synthesis. However, the mechanisms by which such regulatory "dimensions" coordinate cell fate decisions are currently poorly understood. Here we quantified the multi-dimensional molecular changes that occur in mouse embryonic stem cells (mESCs) upon depletion of Estrogen related receptor beta (Esrrb), a key pluripotency regulator. Comparative analyses of expression changes subsequent to depletion of Esrrb or Nanog, indicated that a system of interlocked feed-forward loops involving both factors, plays a central part in regulating the timing of mESC fate decisions. Taken together, our meta-analyses support a hierarchical model in which pluripotency is maintained by an Oct4-Sox2 regulatory module, while the timing of differentiation is regulated by a Nanog-Esrrb module.

9.
Patterns (N Y) ; 2(3): 100213, 2021 Mar 12.
Artigo em Inglês | MEDLINE | ID: mdl-33748796

RESUMO

Jupyter Notebooks have transformed the communication of data analysis pipelines by facilitating a modular structure that brings together code, markdown text, and interactive visualizations. Here, we extended Jupyter Notebooks to broaden their accessibility with Appyters. Appyters turn Jupyter Notebooks into fully functional standalone web-based bioinformatics applications. Appyters present to users an entry form enabling them to upload their data and set various parameters for a multitude of data analysis workflows. Once the form is filled, the Appyter executes the corresponding notebook in the cloud, producing the output without requiring the user to interact directly with the code. Appyters were used to create many bioinformatics web-based reusable workflows, including applications to build customized machine learning pipelines, analyze omics data, and produce publishable figures. These Appyters are served in the Appyters Catalog at https://appyters.maayanlab.cloud. In summary, Appyters enable the rapid development of interactive web-based bioinformatics applications.

10.
Database (Oxford) ; 20212021 03 31.
Artigo em Inglês | MEDLINE | ID: mdl-33787872

RESUMO

Understanding the underlying molecular and structural similarities between seemingly heterogeneous sets of drugs can aid in identifying drug repurposing opportunities and assist in the discovery of novel properties of preclinical small molecules. A wealth of information about drug and small molecule structure, targets, indications and side effects; induced gene expression signatures; and other attributes are publicly available through web-based tools, databases and repositories. By processing, abstracting and aggregating information from these resources into drug set libraries, knowledge about novel properties of drugs and small molecules can be systematically imputed with machine learning. In addition, drug set libraries can be used as the underlying database for drug set enrichment analysis. Here, we present Drugmonizome, a database with a search engine for querying annotated sets of drugs and small molecules for performing drug set enrichment analysis. Utilizing the data within Drugmonizome, we also developed Drugmonizome-ML. Drugmonizome-ML enables users to construct customized machine learning pipelines using the drug set libraries from Drugmonizome. To demonstrate the utility of Drugmonizome, drug sets from 12 independent SARS-CoV-2 in vitro screens were subjected to consensus enrichment analysis. Despite the low overlap among these 12 independent in vitro screens, we identified common biological processes critical for blocking viral replication. To demonstrate Drugmonizome-ML, we constructed a machine learning pipeline to predict whether approved and preclinical drugs may induce peripheral neuropathy as a potential side effect. Overall, the Drugmonizome and Drugmonizome-ML resources provide rich and diverse knowledge about drugs and small molecules for direct systems pharmacology applications. Database URL: https://maayanlab.cloud/drugmonizome/.


Assuntos
COVID-19/tratamento farmacológico , Bases de Dados de Produtos Farmacêuticos , SARS-CoV-2/efeitos dos fármacos , Antivirais/química , Antivirais/farmacologia , COVID-19/virologia , Descoberta de Drogas , Avaliação Pré-Clínica de Medicamentos , Reposicionamento de Medicamentos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Humanos , Técnicas In Vitro , Aprendizado de Máquina , Doenças do Sistema Nervoso Periférico/induzido quimicamente , SARS-CoV-2/fisiologia , Bibliotecas de Moléculas Pequenas , Interface Usuário-Computador , Replicação Viral/efeitos dos fármacos
11.
Front Immunol ; 12: 636289, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33763080

RESUMO

Although widely prevalent, Lyme disease is still under-diagnosed and misunderstood. Here we followed 73 acute Lyme disease patients and uninfected controls over a period of a year. At each visit, RNA-sequencing was applied to profile patients' peripheral blood mononuclear cells in addition to extensive clinical phenotyping. Based on the projection of the RNA-seq data into lower dimensions, we observe that the cases are separated from controls, and almost all cases never return to cluster with the controls over time. Enrichment analysis of the differentially expressed genes between clusters identifies up-regulation of immune response genes. This observation is also supported by deconvolution analysis to identify the changes in cell type composition due to Lyme disease infection. Importantly, we developed several machine learning classifiers that attempt to perform various Lyme disease classifications. We show that Lyme patients can be distinguished from the controls as well as from COVID-19 patients, but classification was not successful in distinguishing those patients with early Lyme disease cases that would advance to develop post-treatment persistent symptoms.


Assuntos
Leucócitos Mononucleares/imunologia , Doença de Lyme/genética , Adulto , COVID-19/genética , COVID-19/imunologia , Citocinas/genética , Citocinas/imunologia , Feminino , Seguimentos , Humanos , Leucócitos Mononucleares/química , Doença de Lyme/sangue , Doença de Lyme/imunologia , Aprendizado de Máquina , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , RNA-Seq
12.
Curr Protoc ; 1(3): e90, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33780170

RESUMO

Profiling samples from patients, tissues, and cells with genomics, transcriptomics, epigenomics, proteomics, and metabolomics ultimately produces lists of genes and proteins that need to be further analyzed and integrated in the context of known biology. Enrichr (Chen et al., 2013; Kuleshov et al., 2016) is a gene set search engine that enables the querying of hundreds of thousands of annotated gene sets. Enrichr uniquely integrates knowledge from many high-profile projects to provide synthesized information about mammalian genes and gene sets. The platform provides various methods to compute gene set enrichment, and the results are visualized in several interactive ways. This protocol provides a summary of the key features of Enrichr, which include using Enrichr programmatically and embedding an Enrichr button on any website. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Analyzing lists of differentially expressed genes from transcriptomics, proteomics and phosphoproteomics, GWAS studies, or other experimental studies Basic Protocol 2: Searching Enrichr by a single gene or key search term Basic Protocol 3: Preparing raw or processed RNA-seq data through BioJupies in preparation for Enrichr analysis Basic Protocol 4: Analyzing gene sets for model organisms using modEnrichr Basic Protocol 5: Using Enrichr in Geneshot Basic Protocol 6: Using Enrichr in ARCHS4 Basic Protocol 7: Using the enrichment analysis visualization Appyter to visualize Enrichr results Basic Protocol 8: Using the Enrichr API Basic Protocol 9: Adding an Enrichr button to a website.


Assuntos
Descoberta do Conhecimento , Software , Animais , Biologia Computacional , Genômica , Humanos , RNA-Seq
13.
Biochemistry ; 60(18): 1430-1446, 2021 05 11.
Artigo em Inglês | MEDLINE | ID: mdl-33606503

RESUMO

While hundreds of genes have been associated with pain, much of the molecular mechanisms of pain remain unknown. As a result, current analgesics are limited to few clinically validated targets. Here, we trained a machine learning (ML) ensemble model to predict new targets for 17 categories of pain. The model utilizes features from transcriptomics, proteomics, and gene ontology to prioritize targets for modulating pain. We focused on identifying novel G-protein-coupled receptors (GPCRs), ion channels, and protein kinases because these proteins represent the most successful drug target families. The performance of the model to predict novel pain targets is 0.839 on average based on AUROC, while the predictions for arthritis had the highest accuracy (AUROC = 0.929). The model predicts hundreds of novel targets for pain; for example, GPR132 and GPR109B are highly ranked GPCRs for rheumatoid arthritis. Overall, gene-pain association predictions cluster into three groups that are enriched for cytokine, calcium, and GABA-related cell signaling pathways. These predictions can serve as a foundation for future experimental exploration to advance the development of safer and more effective analgesics.


Assuntos
Analgésicos/química , Analgésicos/farmacologia , Sistemas de Liberação de Medicamentos , Aprendizado de Máquina , Dor/tratamento farmacológico , Desenho de Fármacos , Descoberta de Drogas , Humanos , Modelos Biológicos
14.
Diabetes ; 70(2): 589-602, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33067313

RESUMO

Diabetic kidney disease (DKD) remains the most common cause of kidney failure, and the treatment options are insufficient. Here, we used a connectivity mapping approach to first collect 15 gene expression signatures from 11 DKD-related published independent studies. Then, by querying the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 data set, we identified drugs and other bioactive small molecules that are predicted to reverse these gene signatures in the diabetic kidney. Among the top consensus candidates, we selected a PLK1 inhibitor (BI-2536) for further experimental validation. We found that PLK1 expression was increased in the glomeruli of both human and mouse diabetic kidneys and localized largely in mesangial cells. We also found that BI-2536 inhibited mesangial cell proliferation and extracellular matrix in vitro and ameliorated proteinuria and kidney injury in DKD mice. Further pathway analysis of the genes predicted to be reversed by the PLK1 inhibitor was of members of the TNF-α/NF-κB, JAK/STAT, and TGF-ß/Smad3 pathways. In vitro, either BI-2536 treatment or knockdown of PLK1 dampened the NF-κB and Smad3 signal transduction and transcriptional activation. Together, these results suggest that the PLK1 inhibitor BI-2536 should be further investigated as a novel therapy for DKD.


Assuntos
Diabetes Mellitus , Nefropatias Diabéticas , Preparações Farmacêuticas , Animais , Nefropatias Diabéticas/tratamento farmacológico , Rim , Camundongos , Pteridinas , Transcriptoma
15.
J Immunol ; 205(8): 2188-2206, 2020 10 15.
Artigo em Inglês | MEDLINE | ID: mdl-32948682

RESUMO

Pathogen-specific memory T cells (TM) contribute to enhanced immune protection under conditions of reinfection, and their effective recruitment into a recall response relies, in part, on cues imparted by chemokines that coordinate their spatiotemporal positioning. An integrated perspective, however, needs to consider TM as a potentially relevant chemokine source themselves. In this study, we employed a comprehensive transcriptional/translational profiling strategy to delineate the identities, expression patterns, and dynamic regulation of chemokines produced by murine pathogen-specific TM CD8+TM, and to a lesser extent CD4+TM, are a prodigious source for six select chemokines (CCL1/3/4/5, CCL9/10, and XCL1) that collectively constitute a prominent and largely invariant signature across acute and chronic infections. Notably, constitutive CCL5 expression by CD8+TM serves as a unique functional imprint of prior antigenic experience; induced CCL1 production identifies highly polyfunctional CD8+ and CD4+TM subsets; long-term CD8+TM maintenance is associated with a pronounced increase of XCL1 production capacity; chemokines dominate the earliest stages of the CD8+TM recall response because of expeditious synthesis/secretion kinetics (CCL3/4/5) and low activation thresholds (CCL1/3/4/5/XCL1); and TM chemokine profiles modulated by persisting viral Ags exhibit both discrete functional deficits and a notable surplus. Nevertheless, recall responses and partial virus control in chronic infection appear little affected by the absence of major TM chemokines. Although specific contributions of TM-derived chemokines to enhanced immune protection therefore remain to be elucidated in other experimental scenarios, the ready visualization of TM chemokine-expression patterns permits a detailed stratification of TM functionalities that may be correlated with differentiation status, protective capacities, and potential fates.


Assuntos
Linfócitos T CD4-Positivos/imunologia , Linfócitos T CD8-Positivos/imunologia , Quimiocinas/imunologia , Memória Imunológica , Infecções/imunologia , Doença Aguda , Animais , Quimiocinas/genética , Doença Crônica , Infecções/genética , Camundongos , Camundongos Endogâmicos BALB C , Camundongos Knockout
16.
J Immunol ; 205(8): 2169-2187, 2020 10 15.
Artigo em Inglês | MEDLINE | ID: mdl-32948687

RESUMO

The choreography of complex immune responses, including the priming, differentiation, and modulation of specific effector T cell populations generated in the immediate wake of an acute pathogen challenge, is in part controlled by chemokines, a large family of mostly secreted molecules involved in chemotaxis and other patho/physiological processes. T cells are both responsive to various chemokine cues and a relevant source for certain chemokines themselves; yet, the actual range, regulation, and role of effector T cell-derived chemokines remains incompletely understood. In this study, using different in vivo mouse models of viral and bacterial infection as well as protective vaccination, we have defined the entire spectrum of chemokines produced by pathogen-specific CD8+ and CD4+T effector cells and delineated several unique properties pertaining to the temporospatial organization of chemokine expression patterns, synthesis and secretion kinetics, and cooperative regulation. Collectively, our results position the "T cell chemokine response" as a notably prominent, largely invariant, yet distinctive force at the forefront of pathogen-specific effector T cell activities and establish novel practical and conceptual approaches that may serve as a foundation for future investigations into the role of T cell-produced chemokines in infectious and other diseases.


Assuntos
Linfócitos T CD4-Positivos/imunologia , Linfócitos T CD8-Positivos/imunologia , Quimiocinas/imunologia , Infecções/imunologia , Animais , Quimiocinas/genética , Infecções/genética , Camundongos , Camundongos Endogâmicos BALB C , Camundongos Knockout
17.
Patterns (N Y) ; 1(6): 100090, 2020 Sep 11.
Artigo em Inglês | MEDLINE | ID: mdl-32838343

RESUMO

In a short period, many research publications that report sets of experimentally validated drugs as potential COVID-19 therapies have emerged. To organize this accumulating knowledge, we developed the COVID-19 Drug and Gene Set Library (https://amp.pharm.mssm.edu/covid19/), a collection of drug and gene sets related to COVID-19 research from multiple sources. The platform enables users to view, download, analyze, visualize, and contribute drug and gene sets related to COVID-19 research. To evaluate the content of the library, we compared the results from six in vitro drug screens for COVID-19 repurposing candidates. Surprisingly, we observe low overlap across screens while highlighting overlapping candidates that should receive more attention as potential therapeutics for COVID-19. Overall, the COVID-19 Drug and Gene Set Library can be used to identify community consensus, make researchers and clinicians aware of new potential therapies, enable machine-learning applications, and facilitate the research community to work together toward a cure.

18.
Glia ; 68(10): 2148-2166, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32639068

RESUMO

Glioblastoma (GBM) is the most aggressive primary brain tumor. In addition to being genetically heterogeneous, GBMs are also immunologically heterogeneous. However, whether the differences in immune microenvironment are driven by genetic driver mutation is unexplored. By leveraging the versatile RCAS/tv-a somatic gene transfer system, we establish a mouse model for Classical GBM by introducing EGFRvIII expression in Nestin-positive neural stem/progenitor cells in adult mice. Along with our previously published Nf1-silenced and PDGFB-overexpressing models, we investigate the immune microenvironments of the three models of human GBM subtypes by unbiased multiplex profiling. We demonstrate that both the quantity and composition of the microenvironmental myeloid cells are dictated by the genetic driver mutations, closely mimicking what was observed in human GBM subtypes. These myeloid cells express high levels of the immune checkpoint protein PD-L1; however, PD-L1 targeted therapies alone or in combination with irradiation are unable to increase the survival time of tumor-bearing mice regardless of the driver mutations, reflecting the outcomes of recent human trials. Together, these results highlight the critical utility of immunocompetent mouse models for preclinical studies of GBM, making these models indispensable tools for understanding the resistance mechanisms of immune checkpoint blockade in GBM and immune cell-targeting drug discovery.

19.
Stud Health Technol Inform ; 272: 334-337, 2020 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-32604670

RESUMO

Advancements in regenerative medicine have brought to the fore the need for increased standardization and sharing of stem cell product characterization to help drive these innovative interventions toward public availability. Although numerous attempts have been made to store this data, there is still a lack of a platform that incorporates heterogeneous stem cell information into a harmonized project-based framework. The aim of this project was to introduce and pilot-test an intelligent informatics solution which integrates diverse stem cell product characteristics with study subject and omics information. In the resulting platform, heterogeneous data is validated using predefined ontologies and stored in a NoSQL repository. Pilot-testing was performed on nine sponsored stem cell projects conducting preclinical and intervention evaluations. The pilot-testing demonstrated the robustness of the proposed platform, by seamlessly harmonizing diverse common data elements, and the potential of this platform for driving knowledge generation from the aggregation of this shared data.


Assuntos
Pesquisa com Células-Tronco
20.
Res Sq ; 2020 May 13.
Artigo em Inglês | MEDLINE | ID: mdl-32702729

RESUMO

The coronavirus (CoV) severe acute respiratory syndrome (SARS)-CoV-2 (COVID-19) pandemic has received rapid response by the research community to offer suggestions for repurposing of approved drugs as well as to improve our understanding of the COVID-19 viral life cycle molecular mechanisms. In a short period, tens of thousands of research preprints and other publications have emerged including those that report lists of experimentally validated drugs and compounds as potential COVID-19 therapies. In addition, gene sets from interacting COVID-19 virus-host proteins and differentially expressed genes when comparing infected to uninfected cells are being published at a fast rate. To organize this rapidly accumulating knowledge, we developed the COVID-19 Gene and Drug Set Library (https://amp.pharm.mssm.edu/covid19/), a collection of gene and drug sets related to COVID-19 research from multiple sources. The COVID-19 Gene and Drug Set Library is delivered as a web-based interface that enables users to view, download, analyze, visualize, and contribute gene and drug sets related to COVID-19 research. To evaluate the content of the library, we performed several analyses including comparing the results from 6 in-vitro drug screens for COVID-19 repurposing candidates. Surprisingly, we observe little overlap across these initial screens. The most common and unique hit across these screen is mefloquine, a malaria drug that should receive more attention as a potential therapeutic for COVID-19. Overall, the library of gene and drug sets can be used to identify community consensus, make researchers and clinicians aware of the development of new potential therapies, as well as allow the research community to work together towards a cure for COVID-19.

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