Il1b signaling in mouse gastric stromal cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE302280 | GEO | 2026/08/06
REPOSITORIES: GEO
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Project description:Il1b signaling in mouse gastric stromal cells
| PRJNA1289787 | ENA
Project description:Helicobacter pylori infection leads to influx of immune cells in the gastric mucosa, causing chronic inflammation. Since the mesenchymal niche is known to play a crucial role in the development of infection-associated gastric pathology, we investigate how stromal cells respond to inflammatory triggers, founding that they respond to Il1b and promote epithelial regeneration. To characterize the function of Il1 signaling in stromal cells, we exploit a conditional mouse model that allows the knockout of Il1r1 receptor in the gastric mesenchyme via Col1a2CreErt2:Il1r1 fl/fl.
2026-08-06 | GSE283927 | GEO
Project description:Mesenchymal stromal cells (MSCs) have been introduced as promising cell source for regenerative medicine. Besides their multilineage differentiation capacity, MSCs release a wide spectrum of bioactive factors. This secretome holds immunomodulatory and regenerative capacities. In intervertebral disc (IVD) cells, application of MSC secretome has been shown to decrease the apoptosis rate, induce proliferation and promote production of extracellular matrix (ECM). For clinical translation of secretome-based treatment, characterization of the secretome composition is needed to better understand the induced biological processes and identify potentially effective secretomes. Methods: This study aimed to investigate the proteome released by bone marrow derived MSCs following exposure to a healthy, traumatic, or degenerative human IVD environment by mass spectroscopy and quantitative immunoassay analyses. Exposure of MSCs to the proinflammatory stimulus interleukin 1β (IL-1b) was used as control.
2021-09-09 | PXD021281 | Pride
Project description:Increasing success is being achieved in the treatment of malignancies with stromal-targeted therapies, predominantly in anti-angiogenesis and immunotherapy, predominantly checkpoint inhibitors. Despite 15 years of clinical trials with anti-VEGF pathway inhibitors for cancer, we still find ourselves lacking reliable predictive biomarkers to select patients for anti-angiogenesis therapy. For the more recent immunotherapy agents, there are many approaches for patient selection under investigation. Notably, the predictive power of an Ad-VEGF-A164 mouse model to drive a stromal response with similarities to a wound healing response shows relevance for human cancer and was used to generate stromal signatures. We have developed gene signatures for 3 stromal states and leveraged the data from multiple large cohort bioinformatics studies of gastric cancer (TCGA, ACRG) to further understand how these relate to the dominant patient phenotypes identified by previous bioinformatics efforts. We have also designed multiplexed IHC assays that robustly represent the vascular and immune diversity in gastric cancer. Finally, we have used this methodology to arrive at a hypothesis of how angiogenesis and immunotherapy may fit into the experimental approaches for gastric cancer treatments.
2016-01-08 | GSE76628 | GEO
Project description:Increasing success is being achieved in the treatment of malignancies with stromal-targeted therapies, predominantly in anti-angiogenesis and immunotherapy, predominantly checkpoint inhibitors. Despite 15 years of clinical trials with anti-VEGF pathway inhibitors for cancer, we still find ourselves lacking reliable predictive biomarkers to select patients for anti-angiogenesis therapy. For the more recent immunotherapy agents, there are many approaches for patient selection under investigation. Notably, the predictive power of an Ad-VEGF-A164 mouse model to drive a stromal response with similarities to a wound healing response shows relevance for human cancer and was used to generate stromal signatures. We have developed gene signatures for 3 stromal states and leveraged the data from multiple large cohort bioinformatics studies of gastric cancer (TCGA, ACRG) to further understand how these relate to the dominant patient phenotypes identified by previous bioinformatics efforts. We have also designed multiplexed IHC assays that robustly represent the vascular and immune diversity in gastric cancer. Finally, we have used this methodology to arrive at a hypothesis of how angiogenesis and immunotherapy may fit into the experimental approaches for gastric cancer treatments.
2016-01-07 | GSE76588 | GEO
Project description:Increasing success is being achieved in the treatment of malignancies with stromal-targeted therapies, predominantly in anti-angiogenesis and immunotherapy, predominantly checkpoint inhibitors. Despite 15 years of clinical trials with anti-VEGF pathway inhibitors for cancer, we still find ourselves lacking reliable predictive biomarkers to select patients for anti-angiogenesis therapy. For the more recent immunotherapy agents, there are many approaches for patient selection under investigation. Notably, the predictive power of an Ad-VEGF-A164 mouse model to drive a stromal response with similarities to a wound healing response shows relevance for human cancer and was used to generate stromal signatures. We have developed gene signatures for 3 stromal states and leveraged the data from multiple large cohort bioinformatics studies of gastric cancer (TCGA, ACRG) to further understand how these relate to the dominant patient phenotypes identified by previous bioinformatics efforts. We have also designed multiplexed IHC assays that robustly represent the vascular and immune diversity in gastric cancer. Finally, we have used this methodology to arrive at a hypothesis of how angiogenesis and immunotherapy may fit into the experimental approaches for gastric cancer treatments. The Ad-VEGF-A164 flank model was performed as described in Flank tissue from harvest day 0, day 5, day 20, and day 60 was taken for RNA generation. Samples for messenger RNA (mRNA) profiling studies were processed by Asuragen, Inc. (Austin, TX, USA) using GeneChip® Mouse Genome 430 2.0 Array (Affymetrix, Santa Clara, CA) according to the company's standard operating procedures as described previously in detail [45]. A summary of the image signal data, detection calls and gene annotations for every gene interrogated on the arrays was generated using the Affymetrix Statistical Algorithm MAS 5.0 (GCOS v1.3) algorithm (scaling factor = 1500).
2016-01-07 | E-GEOD-76588 | biostudies-arrayexpress
Project description:Increasing success is being achieved in the treatment of malignancies with stromal-targeted therapies, predominantly in anti-angiogenesis and immunotherapy, predominantly checkpoint inhibitors. Despite 15 years of clinical trials with anti-VEGF pathway inhibitors for cancer, we still find ourselves lacking reliable predictive biomarkers to select patients for anti-angiogenesis therapy. For the more recent immunotherapy agents, there are many approaches for patient selection under investigation. Notably, the predictive power of an Ad-VEGF-A164 mouse model to drive a stromal response with similarities to a wound healing response shows relevance for human cancer and was used to generate stromal signatures. We have developed gene signatures for 3 stromal states and leveraged the data from multiple large cohort bioinformatics studies of gastric cancer (TCGA, ACRG) to further understand how these relate to the dominant patient phenotypes identified by previous bioinformatics efforts. We have also designed multiplexed IHC assays that robustly represent the vascular and immune diversity in gastric cancer. Finally, we have used this methodology to arrive at a hypothesis of how angiogenesis and immunotherapy may fit into the experimental approaches for gastric cancer treatments. The Ad-VEGF-A164 angiogenesis model was performed as previously described. Animals were treated with various anti-VEGF Receptor antibodies via intraperitoneal injection at the doses (DC101 20 mpk or G6 10 mpk) and time points (day 0, day 5, day 20, day 60) to target all of the different populations of tumor-surrogate blood vessels, as they each develop at different time points. At least 5 animals, equally matched, were used per group. At the end of the experiment, angiogenic sites in flanks were photographed and tissues were taken for histology and RNA preparation.
2016-01-08 | E-GEOD-76628 | biostudies-arrayexpress
Project description:Gastric epithelial stem cells are responsible for constant epithelial self-renewal, which is accelerated by infection with the gastric pathogen Helicobacter pylori. However, the mechanism that regulates stem cell turnover in the stomach remains unknown. Here we show that signaling by R-spondin 3 and Wnt hierarchically organizes the stem cell compartment in the antrum, producing two Wnt-responsive populations, which are either Lgr5+ve or Axin2 +ve. The positional identity of the Axin2+ve population relies on R-spondin 3 produced by stromal myofibroblasts. Increased availability of R-spondin induces hyperproliferation through specific expansion of Axin2+ve but not Lgr5+ve cells. Similarly, infection with H. pylori induces an increase in stromal R-spondin 3 expression, resulting in hyperplasia as well as shedding of bacteria that have entered the gland. This identifies a role for stromal cells in environmental sensing to orchestrate epithelial homeostasis via Wnt signaling.
2017-06-30 | GSE79494 | GEO
Project description:Stromal-Based Signatures for the Classification of Gastric Cancer
| PRJNA308196 | ENA
Project description:The canonical role IL-4 is to induce M2 macrophage polarization. Herein we report that in addition to its canonical role, IL-4 also induces non-canonical pro-inflammatory response via epigenetic memory. Although IL-4 stimulated macrophages do not produce classic proinflammatory cytokines such as IL-6 and IL-1b, they produce heightened proinflammatory cytokine upon LPS stimulation.
2022-12-31 | GSE184811 | GEO