Browse
Submit Data
Databases
API
Help

Dataset Information

14 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Serum Cytokines Predict Neurological Damage in Genetically Diverse Mouse Models.

ABSTRACT: Viral infections contribute to neurological and immunological dysfunction driven by complex genetic networks. Theiler's murine encephalomyelitis virus (TMEV) causes neurological dysfunction in mice and can model human outcomes to viral infections. Here, we used genetically distinct mice from five Collaborative Cross mouse strains and C57BL/6J to demonstrate how TMEV-induced immune responses in serum may predict neurological outcomes in acute infection. To test the hypothesis that serum cytokine levels can provide biomarkers for phenotypic outcomes of acute disease, we compared cytokine levels at pre-injection, 4 days post-injection (d.p.i.), and 14 d.p.i. Each strain produced unique baseline cytokine levels and had distinct immune responses to the injection procedure itself. Thus, we eliminated the baseline responses to the injection procedure itself and identified cytokines and chemokines induced specifically by TMEV infection. Then, we identified strain-specific longitudinal cytokine profiles in serum during acute disease. Using stepwise regression analysis, we identified serum immune markers predictive for TMEV-induced neurological phenotypes of the acute phase, e.g., IL-9 for limb paralysis; and TNF-α, IL-1β, and MIP-1β for limb weakness. These findings indicate how temporal differences in immune responses are influenced by host genetic background and demonstrate the potential of serum biomarkers to track the neurological effects of viral infection.

SUBMITTER: Perez Gomez AA

PROVIDER: S-EPMC9265636 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Genetically engineered mouse models of prostate cancer.

Project description:Despite major improvement in treatment of early stage localised prostate cancer, the distinction between indolent tumors and those that will become aggressive, as well as the lack of efficient therapies of advanced prostate cancer, remain major health problems. Genetically engineered mice (GEM) have been extensively used to investigate the molecular and cellular mechanisms underlying prostate tumor initiation and progression, and to evaluate new therapies. Moreover, the recent development of conditional somatic mutagenesis in the mouse prostate offers the possibility to generate new models that more faithfully reproduce the human disease, and thus should contribute to improve diagnosis and treatments. The strengths and weaknesses of various models will be discussed, as well as future opportunities.

| S-EPMC5528413 | biostudies-other

Regulation of protein abundance in genetically diverse mouse populations.

Project description:Genetically diverse mouse populations are powerful tools for characterizing the regulation of the proteome and its relationship to whole-organism phenotypes. We used mass spectrometry to profile and quantify the abundance of 6,798 proteins in liver tissue from mice of both sexes across 58 Collaborative Cross (CC) inbred strains. We previously collected liver proteomics data from the related Diversity Outbred (DO) mice and their founder strains. We show concordance across the proteomics datasets despite being generated from separate experiments, allowing comparative analysis. We map protein abundance quantitative trait loci (pQTLs), identifying 1,087 local and 285 distal in the CC mice and 1,706 local and 414 distal in the DO mice. We find that regulatory effects on individual proteins are conserved across the mouse populations, in particular for local genetic variation and sex differences. In comparison, proteins that form complexes are often co-regulated, displaying varying genetic architectures, and overall show lower heritability and map fewer pQTLs. We have made this resource publicly available to enable quantitative analyses of the regulation of the proteome.

| S-EPMC9536773 | biostudies-literature

Genetically engineered mouse models of pancreatic adenocarcinoma.

Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal types of human cancer for which there are no effective therapies. Deep sequencing of PDAC tumors has revealed the presence of a high number of mutations (>50) that affect at least a dozen key signaling pathways. This scenario highlights the urgent need to develop experimental models that faithfully reproduce the natural history of these human tumors in order to understand their biology and to design therapeutic approaches that might effectively interfere with their multiple mutated pathways. Over the last decade, several models, primarily based on the genetic activation of resident KRas oncogenes knocked-in within the endogenous KRas locus have been generated. These models faithfully reproduce the histological lesions that characterize human pancreatic tumors. Decoration of these models with additional mutations, primarily involving tumor suppressor loci known to be also mutated in human PDAC tumors, results in accelerated tumor progression and in the induction of invasive and metastatic malignancies. Mouse PDACs also display a desmoplastic stroma and inflammatory responses that closely resemble those observed in human patients. Interestingly, adult mice appear to be resistant to PDAC development unless the animals undergo pancreatic damage, mainly in the form of acute, chronic or even temporary pancreatitis. In this review, we describe the most representative models available to date and how their detailed characterization is allowing us to understand their cellular origin as well as the events involved in tumor progression. Moreover, their molecular dissection is starting to unveil novel therapeutic strategies that could be translated to the clinic in the very near future.

| S-EPMC5528418 | biostudies-literature

Genetically engineered mouse models for studying radiation biology.

Project description:Genetically engineered mouse models (GEMMs) are valuable research tools that have transformed our understanding of cancer. The first GEMMs generated in the 1980s and 1990s were knock-in and knock-out models of single oncogenes or tumor suppressors. The advances that made these models possible catalyzed both technological and conceptual shifts in the way cancer research was conducted. As a result, dozens of mouse models of cancer exist today, covering nearly every tissue type. The advantages inherent to GEMMs compared to in vitro and in vivo transplant models are compounded in preclinical radiobiology research for several reasons. First, they accurately and robustly recapitulate primary cancers anatomically, histopathologically, and genetically. Reliable models are a prerequisite for predictive preclinical studies. Second, they preserve the tumor microenvironment, including the immune, vascular, and stromal compartments, which enables the study of radiobiology at a systems biology level. Third, they provide exquisite control over the genetics and kinetics of tumor initiation, which enables the study of specific gene mutations on radiation response and functional genomics in vivo. Taken together, these facets allow researchers to utilize GEMMs for rigorous and reproducible preclinical research. In the three decades since the generation of the first GEMMs of cancer, advancements in modeling approaches have rapidly progressed and expanded the mouse modeling toolbox with techniques such as in vivo short hairpin RNA (shRNA) knockdown, inducible gene expression, site-specific recombinases, and dual recombinase systems. Our lab and many others have utilized these tools to study cancer and radiobiology. Recent advances in genome engineering with CRISPR/Cas9 technology have made GEMMs even more accessible to researchers. Here, we review current and future approaches to mouse modeling with a focus on applications in preclinical radiobiology research.

| S-EPMC6363345 | biostudies-literature

Serum LDH levels may predict poor neurological outcome after aneurysmal subarachnoid hemorrhage.

Project description:IntroductionSerum lactate dehydrogenase (LDH) levels are often elevated in cardiovascular diseases. Their prognostic role after subarachnoid hemorrhage (SAH) remains poorly evaluated.MethodsThis is a retrospective single-center study of patients with non-traumatic SAH admitted to the intensive care unit (ICU) of an University Hospital from 2007 to 2022. Exclusion criteria were pregnancy and incomplete medical records or follow-up data. Baseline information, clinical data, radiologic data, the occurrence of neurological complications as well as serum LDH levels during the first 14 days of ICU stay were collected. Unfavorable neurological outcome (UO) at 3 months was defined as a Glasgow Outcome Scale of 1-3.ResultsFive hundred and forty-seven patients were included; median serum LDH values on admission and the highest LDH values during the ICU stay were 192 [160-230] IU/L and 263 [202-351] IU/L, respectively. The highest LDH value was recorded after a median of 4 [2-10] days after ICU admission. LDH levels on admission were significantly higher in patients with UO. When compared with patients with favorable outcome (FO), patients with UO had higher serum LDH values over time. In the multivariate logistic regression model, the highest LDH value over the ICU stay (OR 1.004 [95% CI 1.002 - 1.006]) was independently associated with the occurrence of UO; the area under the receiving operator (AUROC) curve for the highest LDH value over the ICU stay showed a moderate accuracy to predict UO (AUC 0.76 [95% CI 0.72-0.80]; p < 0.001), with an optimal threshold of > 272 IU/L (69% sensitivity and 74% specificity).ConclusionsThe results in this study suggest that high serum LDH levels are associated with the occurrence of UO in SAH patients. As a readily and available biomarker, serum LDH levels should be evaluated to help with the prognostication of SAH patients.

| S-EPMC10262567 | biostudies-literature

Genetically engineered mucin mouse models for inflammation and cancer.

Project description:Mucins are heavily O-glycosylated proteins primarily produced by glandular and ductal epithelial cells, either in membrane-tethered or secretory forms, for providing lubrication and protection from various exogenous and endogenous insults. However, recent studies have linked their aberrant overexpression with infection, inflammation, and cancer that underscores their importance in tissue homeostasis. In this review, we present current status of the existing mouse models that have been developed to gain insights into the functional role(s) of mucins under physiological and pathological conditions. Knockout mouse models for membrane-associated (Muc1 and Muc16) and secretory mucins (Muc2) have helped us to elucidate the role of mucins in providing effective and protective barrier functions against pathological threats, participation in disease progression, and improved our understanding of mucin interaction with biotic and abiotic environmental components. Emphasis is also given to available transgenic mouse models (MUC1 and MUC7), which has been exploited to understand the context-dependent regulation and therapeutic potential of human mucins during inflammation and cancer.

| S-EPMC4520780 | biostudies-literature

Genetically modified mouse models to help fight COVID-19.

Project description:The research community is in a race to understand the molecular mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, to repurpose currently available antiviral drugs and to develop new therapies and vaccines against coronavirus disease 2019 (COVID-19). One major challenge in achieving these goals is the paucity of suitable preclinical animal models. Mice constitute ~70% of all the laboratory animal species used in biomedical research. Unfortunately, SARS-CoV-2 infects mice only if they have been genetically modified to express human ACE2. The inherent resistance of wild-type mice to SARS-CoV-2, combined with a wealth of genetic tools that are available only for modifying mice, offers a unique opportunity to create a versatile set of genetically engineered mouse models useful for COVID-19 research. We propose three broad categories of these models and more than two dozen designs that may be useful for SARS-CoV-2 research and for fighting COVID-19.

| S-EPMC7704938 | biostudies-literature

Generation of genetically engineered non-human primate models of brain function and neurological disorders.

Project description:Research with non-human primates (NHP) has been essential and effective in increasing our ability to find cures for a large number of diseases that cause human suffering and death. Extending the availability and use of genetic engineering techniques to NHP will allow the creation and study of NHP models of human disease, as well as broaden our understanding of neural circuits in the primate brain. With the recent development of efficient genetic engineering techniques that can be used for NHP, there's increased hope that NHP will significantly accelerate our understanding of the etiology of human neurological and neuropsychiatric disorders. In this article, we review the present state of genetic engineering tools used in NHP, from the early efforts to induce exogeneous gene expression in macaques and marmosets, to the latest results in producing germline transmission of different transgenes and the establishment of knockout lines of specific genes. We conclude with future perspectives on the further development and employment of these tools to generate genetically engineered NHP.

| S-EPMC6463491 | biostudies-literature

Mouse models of genetically heterogeneous multiple myeloma reveal mechanisms of immune evasion that predict clinical immunotherapy responses

Project description:Data from engineered fifteen mouse strains fully encompassing MM genetic heterogeneity that recapitulate the key pathogenic elements in human MM development and multiple myeloma patients.

2023-03-17 | GSE205447 | GEO

Genetically engineered mouse models of PI3K signaling in breast cancer.

Project description:Breast cancer is the most common type of cancer in women. A substantial fraction of breast cancers have acquired mutations that lead to activation of the phosphoinositide 3-kinase (PI3K) signaling pathway, which plays a central role in cellular processes that are essential in cancer, such as cell survival, growth, division and motility. Oncogenic mutations in the PI3K pathway generally involve either activating mutation of the gene encoding PI3K (PIK3CA) or AKT (AKT1), or loss or reduced expression of PTEN. Several kinases involved in PI3K signaling are being explored as a therapeutic targets for pharmacological inhibition. Despite the availability of a range of inhibitors, acquired resistance may limit the efficacy of single-agent therapy. In this review we discuss the role of PI3K pathway mutations in human breast cancer and relevant genetically engineered mouse models (GEMMs), with special attention to the role of PI3K signaling in oncogenesis, in therapeutic response, and in resistance to therapy. Several sophisticated GEMMs have revealed the cause-and-effect relationships between PI3K pathway mutations and mammary oncogenesis. These GEMMs enable us to study the biology of tumors induced by activated PI3K signaling, as well as preclinical response and resistance to PI3K pathway inhibitors.

| S-EPMC5528412 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data