Inhalation of panaxadiol alleviates lung inflammation via inhibiting TNFA/TNFAR and IL7/IL7R signalling [Human]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE226900 | GEO | 2024/02/02
REPOSITORIES: GEO
Similar Datasets
Project description:Background: There are no highly effective medications for treating pneumonia. Ginseng and its derivatives have anti-inflammatory properties, but their unstable physicochemical and metabolic properties prevent them from being used to treat pneumonia. The aforementioned issues may be resolved by inhalation, but the precise mechanism of action must be investigated. Methods: In order to study the effects and mechanisms of PD inhalation drug delivery, models of LPS-induced murine holistic pneumonia, isolated macrophage inflammation, and epithelial cell co-culture are utilized. For the evaluation of efficacy, pathology and molecular assays have been utilized. Mechanisms of action and targets were screened and validated by molecular means using transcriptome sequencing. Efficacy and mechanism of action were ultimately validated using human BALF cell models. Also studied were pharmacokinetic parameters of inhaled PD. Results: Inhalation of PD dose-dependently reduced LPS-induced lung inflammation in mice, including inflammatory cell infiltration, lung histopathology, and inflammatory factor expression. Oral PD had the same anti-inflammatory effect as inhalation, but inhalation was more effective at the same dose. It could be a result of its increased bioavailability and improved pharmacokinetic parameters. Using transcriptome analysis and validation of macrophage and epithelial cell experiments, we discovered that PD may inhibit TNFA/TFNAR and IL7/IL7R signaling to inhibit macrophage inflammatory factor-induced epithelial cell apoptosis and promote value-added initiation. Human alveolar lavage cell experimentation confirmed this result. Conclusion: PD inhalation alleviates lung inflammation and pathology by inhibiting TNFA/TFNAR and IL7/IL7R signaling. PD may be a novel drug for the clinical treatment of lung inflammation.
2024-02-02 | GSE227089 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-02-02 | GSE227090 | GEO
Project description: Not available
| S-EPMC1569185 | biostudies-literature
Project description:Bronchoalveolar lavage is commonly performed to examine inflammation and responsible pathogens in lung diseases, and its findings may be used to assess the immune profile of the lung tumor microenvironment (TME). To investigate whether analyses of bronchoalveolar lavage fluid (BALF) can help identify non-small cell lung cancer (NSCLC) patients who respond to immune checkpoint inhibitors (ICIs), BALF and blood were prospectively collected before initiating nivolumab. The secreted molecules, microbiome, and cellular profiles based on BALF and blood analysis were compared regarding therapeutic effect in 12 patients. Compared to non-responders, responders showed significantly higher CXCL9 levels and greater diversity in the lung microbiome profile in BALF, and greater frequency of CD56+ subset in blood T cells, whereas no significant difference was found in PD-L1 expression of tumor cells. Antibiotic treatment in a preclinical lung cancer model significantly decreased CXCL9 in the lung TME, resulting in reduced sensitivity to nivolumab, which was reversed by CXCL9 induction in tumor cells. Thus, CXCL9 and the microbiome in the lung TME might be associated with each other, and their balance could contribute to nivolumab sensitivity in NSCLC patients. BALF analysis can help predict the efficacy of ICIs when performed along with currently approved examinations.
2022-04-07 | GSE193049 | GEO
Project description:Zhu2015 - Combined gemcitabine and birinapant
in pancreatic cancer cells - basic PD model
Mathematical model to illustrate the
effectiveness of combination chemotherapy involving gemcitabine and
birinapant against pancreatic cancer.
This model is described in the article:
Mechanism-based mathematical
modeling of combined gemcitabine and birinapant in pancreatic
cancer cells.
Zhu X, Straubinger RM, Jusko
WJ.
J Pharmacokinet Pharmacodyn 2015 Oct;
42(5): 477-496
Abstract:
Combination chemotherapy is standard treatment for
pancreatic cancer. However, current drugs lack efficacy for
most patients, and selection and evaluation of new combination
regimens is empirical and time-consuming. The efficacy of
gemcitabine, a standard-of-care agent, combined with
birinapant, a pro-apoptotic antagonist of Inhibitor of
Apoptosis Proteins (IAPs), was investigated in pancreatic
cancer cells. PANC-1 cells were treated with vehicle,
gemcitabine (6, 10, 20 nM), birinapant (50, 200, 500 nM), and
combinations of the two drugs. Temporal changes in cell
numbers, cell cycle distribution, and apoptosis were measured.
A basic pharmacodynamic (PD) model based on cell numbers, and a
mechanism-based PD model integrating all measurements, were
developed. The basic PD model indicated that synergistic
effects occurred in both cell proliferation and death
processes. The mechanism-based model captured key features of
drug action: temporary cell cycle arrest in S phase induced by
gemcitabine alone, apoptosis induced by birinapant alone, and
prolonged cell cycle arrest and enhanced apoptosis induced by
the combination. A drug interaction term Ψ was employed in
the models to signify interactions of the combination when data
were limited. When more experimental information was utilized,
Ψ values approaching 1 indicated that specific mechanisms
of interactions were captured better. PD modeling identified
the potential benefit of combining gemcitabine and birinapant,
and characterized the key interaction pathways. An optimal
treatment schedule of pretreatment with gemcitabine for 24-48 h
was suggested based on model predictions and was verified
experimentally. This approach provides a generalizable modeling
platform for exploring combinations of cytostatic and cytotoxic
agents in cancer cell culture studies.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000668.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2018-02-05 | BIOMD0000000668 | BioModels
Project description:Zhu2015 - combined gemcitabine and birinapant
in pancreatic cancer cells - mechanistic PD model
Mechanistic mathematical model to
illustrate the effectiveness of combination chemotherapy involving
gemcitabine and birinapant against pancreatic cancer.
This model is described in the article:
Mechanism-based mathematical
modeling of combined gemcitabine and birinapant in pancreatic
cancer cells.
Zhu X, Straubinger RM, Jusko
WJ.
J Pharmacokinet Pharmacodyn 2015 Oct;
42(5): 477-496
Abstract:
Combination chemotherapy is standard treatment for
pancreatic cancer. However, current drugs lack efficacy for
most patients, and selection and evaluation of new combination
regimens is empirical and time-consuming. The efficacy of
gemcitabine, a standard-of-care agent, combined with
birinapant, a pro-apoptotic antagonist of Inhibitor of
Apoptosis Proteins (IAPs), was investigated in pancreatic
cancer cells. PANC-1 cells were treated with vehicle,
gemcitabine (6, 10, 20 nM), birinapant (50, 200, 500 nM), and
combinations of the two drugs. Temporal changes in cell
numbers, cell cycle distribution, and apoptosis were measured.
A basic pharmacodynamic (PD) model based on cell numbers, and a
mechanism-based PD model integrating all measurements, were
developed. The basic PD model indicated that synergistic
effects occurred in both cell proliferation and death
processes. The mechanism-based model captured key features of
drug action: temporary cell cycle arrest in S phase induced by
gemcitabine alone, apoptosis induced by birinapant alone, and
prolonged cell cycle arrest and enhanced apoptosis induced by
the combination. A drug interaction term Ψ was employed in
the models to signify interactions of the combination when data
were limited. When more experimental information was utilized,
Ψ values approaching 1 indicated that specific mechanisms
of interactions were captured better. PD modeling identified
the potential benefit of combining gemcitabine and birinapant,
and characterized the key interaction pathways. An optimal
treatment schedule of pretreatment with gemcitabine for 24-48 h
was suggested based on model predictions and was verified
experimentally. This approach provides a generalizable modeling
platform for exploring combinations of cytostatic and cytotoxic
agents in cancer cell culture studies.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000669.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2018-02-06 | BIOMD0000000669 | BioModels
Project description:CSF from unique groups of Parkinson's disease (PD) patients was biochemically profiled to identify previously unreported metabolic pathways linked to PD pathogenesis, and novel biochemical biomarkers of the disease were characterized. Utilizing both 1H NMR and DI-LC-MS/MS we quantitatively profiled CSF from patients with sporadic PD (n = 20) and those who are genetically predisposed (LRRK2) to the disease (n = 20), and compared those results with age and gender-matched controls (n = 20). Further, we systematically evaluated the utility of several machine learning techniques for the diagnosis of PD. 1H NMR and mass spectrometry-based metabolomics, in combination with bioinformatic analyses, provided useful information highlighting previously unreported biochemical pathways and CSF-based biomarkers associated with both sporadic PD (sPD) and LRRK2 PD. Results of this metabolomics study further support our group's previous findings identifying bile acid metabolism as one of the major aberrant biochemical pathways in PD patients. This study demonstrates that a combination of two complimentary techniques can provide a much more holistic view of the CSF metabolome, and by association, the brain metabolome. Future studies for the prediction of those at risk of developing PD should investigate the clinical utility of these CSF-based biomarkers in more accessible biomatrices. Further, it is essential that we determine whether the biochemical pathways highlighted here are recapitulated in the brains of PD patients with the aim of identifying potential therapeutic targets.
2022-09-02 | MTBLS863 | MetaboLights
Project description:PD-1/PD-L1 Immunoinhibitory axis has recently been demonstrated to play a key role in immune evasion of cancer cells and therapies targeting PD-1/PD-L1 axis have demonstrated high efficacy in certain cancer types. Understanding how cancer drivers regulate immune surveillance can allow for development of novel therapeutic strategies which interfere with cancer-mediated immune evasion as well as identification of new biomarkers for application of these therapies. Here we utilized genetic screening with curated library of top 500 tumor suppressor genes to identify cohesin ring, one of the most mutated complex in cancer, as the most significant suppressor of PD-L1. Additionally, we comprehensively describe the consequences of loss of STAG2 subunit of cohesin and identify induction of IFN and NFκB response. Our findings thus elucidate transcriptional changes in immune related pathways as well as upregulation of key immune regulatory molecules including PD-L1, PD-L2 and MHC in cohesin deficient cells which could have significant implications on cancer microenvironment of cohesin deficient tumors.
2022-02-07 | GSE189818 | GEO
Project description:Targeting the PD-1/PD-L1 pathway has changed the landscape of cancer immunotherapy, revolutionizing the treatment of many cancers. Somatic tumor mutational burden (TMB) and T-cell–inflamed gene expression profile (GEP) are clinically validated pan-tumor genomic biomarkers that predict responsiveness to anti-PD-1/anti-PD-L1 monotherapy in a variety of tumor types. Here we analyze the association between these biomarkers and efficacy in 11 commonly used preclinical murine syngeneic models using a rodent surrogate antibody (muDX400) of pembrolizumab, a humanized monoclonal antibody against PD-1. Response to muDX400 treatment was broadly classified in these models into 3 categories: highly responsive, partially responsive, and intrinsically resistant to therapy. Molecular and cellular profiling validated differences in immune-cell infiltration and activation in the tumor microenvironment of muDX400 responsive tumors. Baseline and post-treatment genomic analysis showed an association between murine-GEP and TMB and response to muDX400 treatment. To better understand the limitations, predictive nature and role of these models in guiding treatment options at the bedside, we extended our analysis to investigate a canonical set of cancer and immune biology-related gene expression signatures, including signatures of angiogenesis, monocytic myeloid derived suppressor cell (mMDSC) and stromal/EMT/TGF-β biology previously shown to have potential negative impact on immunotherapy efficacy in the clinic. Finally, reverse translation studies were performed to evaluate the association between murine-GEP and preclinical efficacy with standard of care and anti-angiogenic combinations with muDX400 which show promising clinical activity. These efforts begin to elucidate which biological mechanisms can and cannot be appropriately and productively tested in these preclinical models to facilitate the development of rational orthogonal combination strategies with checkpoint blockade as well as the evaluation of underlying biological mechanisms associated with response in the clinic
2022-01-07 | GSE168846 | GEO
Project description:Background: We previously reported on the role of pericyte-like cells as functional sentinel immune cells in lung injury. However, much about the biology of pericytes in lung injury remains unknown. Lung pericyte-like cells are well-positioned to sense disruption to the epithelial barrier and coordinate local inflammatory responses due to their anatomic niche within the alveoli. In this report, we characterized transcriptional responses and functional changes in pericyte-like cells following activation by alveolar components from injured and uninjured lungs. Methods: We purified pericyte-like cells from lung digests using PDGFR_ as a selection marker and expanded them in culture as previously described (1). We induced sterile acute lung injury in mice with recombinant human Fas ligand (rhFasL) instillation followed by mechanical ventilation (1). We then collected bronchoalveolar lavage fluid (BALF) from injured and uninjured mice. Purified pericyte-like cells in culture were exposed to growth media only (control), BALF from uninjured mice, and BALF from injured mice for 6 and 24 h. RNA collected from pericyte-like cells for each of these treatment conditions underwent genome-wide sequencing using RNA-seq. Targets of interest identified by bioinformatics analysis of RNA-seq data were validated using in vitro and in vivo assays. Results: We observed robust global transcriptional changes in pericyte-like cells following treatment with uninjured and injured BALF at 6 h, but this response persisted for 24 h only after exposure to injured BALF. Functional enrichment analysis of pericytes treated with injured BALF revealed activation of immuno-inflammatory, cell migration and angiogenesis-related pathways, whereas processes associated with tissue development and remodeling were down-regulated. We validated select targets in the inflammatory, angiogenesis-related, and cell migratory pathways using functional assays in vitro and in vivo. Conclusion: Lung pericyte-like cells are highly responsive to alveolar compartment content from both uninjured and injured lungs, but injured BALF elicits a more sustained response. The inflammatory, angiogenic, and migratory changes exhibited by activated pericyte-like cells underscore the phenotypic plasticity of these specialized stromal cells in the setting of acute lung injury.
2020-10-31 | GSE137363 | GEO