Expression data from endothelial cell
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE105437 | GEO | 2017/10/21
SECONDARY ACCESSION(S): PRJNA415176
REPOSITORIES: GEO
Similar Datasets
Project description:The vascular endothelial growth factor A (VEGF) is involved in various physiological processes such as angiogenesis or wound healing but is also crucial in pathological events such as tumor growth. Thus, clinical anti-VEGF treatments have been developed which could already prove to have enormous beneficial effects for cancer patients. In this article we describe the first VEGF-derived CD8+ T-cell epitope. The natural HLA ligand SRFGGAVVR was identified by differential mass spectrometry in two primary renal cell carcinomas (RCC) and was significantly over-presented on both tumor tissues. SRFGGAVVR is derived from a cryptic translated region of VEGF presumably by initiation of translation at the non-classical start codon CUG499. SRFGGAVVR specific T-cells were generated in vitro using peptide loaded dendritic cells or artificial antigen presenting cells. They were identified by HLA tetramer analysis after in vitro stimulation. SRFGGAVVR specific CD8+ T-cells were fully functional T-effector cells, which were able to secrete IFN-gamma upon stimulation and killed tumor cells in vitro. Additionally, we have quantitatively analyzed VEGF mRNA and protein levels in RCC tumor and normal tissue samples by gene chip analysis, qRT-PCR, in situ hybridization, and bead based immuno assay. In the future, T-cells directed against VEGF as a tumor associated antigen may represent a possible way of combining peptide-based anti-VEGF immunotherapy with already existent anti-VEGF cancer therapies. Experiment Overall Design: Two clear cell renal cell carcinomas including autologous normal tissue were analyzed.
2008-06-15 | E-GEOD-8050 | biostudies-arrayexpress
Project description:Angiogenesis, the formation of new blood vessels from pre-existing ones, is a complex and demanding biological process that plays an important role in physiological as well as pathological settings such as cancer and ischemia. Given its critical role, the regulation of endothelial growth factor receptor (e.g. VEGFR2, FGFR1) represents important mechanisms for the control of angiogenesis. Recent evidences support cell metabolism as a critical regulator of angiogenesis. However, it is unknown how glutamine metabolism regulates growth factor receptor expression. Here, by using genetic and pharmacological approaches, we show that glutaminolysis and glutamate-dependent transaminases (TAs) support alpha-ketoglutarate (αKG) levels and are critical regulators of angiogenic response during pathological conditions. Indeed, the endothelial specific blockage of GLS1 impairs ischemic and tumor angiogenesis by suppressing VEGFR2 translation via mTORC1-dependent pathway. Lastly, we discover that ECs catabolized the glutamine-derived glutamate via phosphoserine aminotransferase 1 (PSAT1) as crucial to support VEGFR2 translation. These findings identify glutamine anaplerosis and TA activity as a critical regulator of growth factor receptor translation in normal and pathological angiogenesis. We anticipate our studies to be a starting point for novel anti-angiogenesis approaches based on GLS1/PSAT1 inhibitor treatments to overcome anti-VEGF therapies resistance.
2022-04-22 | PXD022379 | Pride
Project description:This a model from the article:
Modeling the effects of treating diabetic wounds with engineered skin
substitutes.
Waugh HV, Sherratt JA. Wound Repair Regen
2007 Jul-Aug;15(4):556-65 17650100
,
Abstract:
In this paper, a novel mathematical model of wound healing in both normal and
diabetic cases is presented, focusing upon the effects of adding two currently
available commercial engineered skin substitute therapies to the wound
(Apligraf) and Dermagraft). Our work extends a previously developed model, which
considers inflammatory and repair macrophage dynamics in normal and diabetic
wound healing. Here, we extend the model to include equations for
platelet-derived growth factor concentration, fibroblast density, collagen
density, and hyaluronan concentration. This enables us to examine the variation
of these components in both normal and diabetic wound healing cases, and to
model the treatment protocols of these therapies. Within the context of our
model, we find that the key component to successful healing in diabetic wounds
is hyaluronan and that the therapies work by increasing the amount of hyaluronan
available in the wound environment. The time-to-healing results correlate with
those observed in clinical trials and the model goes some way to establishing an
understanding of why diabetic wounds do not heal, and how these treatments
affect the diabetic wound environment to promote wound closure.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Waugh HV, Sherratt JA. (2007) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1006230102 | BioModels
Project description:This a model from the article:
Modeling the effects of treating diabetic wounds with engineered skin
substitutes.
Waugh HV, Sherratt JA. Wound Repair Regen
2007 Jul-Aug;15(4):556-65 17650100
,
Abstract:
In this paper, a novel mathematical model of wound healing in both normal and
diabetic cases is presented, focusing upon the effects of adding two currently
available commercial engineered skin substitute therapies to the wound
(Apligraf) and Dermagraft). Our work extends a previously developed model, which
considers inflammatory and repair macrophage dynamics in normal and diabetic
wound healing. Here, we extend the model to include equations for
platelet-derived growth factor concentration, fibroblast density, collagen
density, and hyaluronan concentration. This enables us to examine the variation
of these components in both normal and diabetic wound healing cases, and to
model the treatment protocols of these therapies. Within the context of our
model, we find that the key component to successful healing in diabetic wounds
is hyaluronan and that the therapies work by increasing the amount of hyaluronan
available in the wound environment. The time-to-healing results correlate with
those observed in clinical trials and the model goes some way to establishing an
understanding of why diabetic wounds do not heal, and how these treatments
affect the diabetic wound environment to promote wound closure.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Waugh HV, Sherratt JA. (2007) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1006230106 | BioModels
Project description:This a model from the article:
Modeling the effects of treating diabetic wounds with engineered skin
substitutes.
Waugh HV, Sherratt JA. Wound Repair Regen
2007 Jul-Aug;15(4):556-65 17650100
,
Abstract:
In this paper, a novel mathematical model of wound healing in both normal and
diabetic cases is presented, focusing upon the effects of adding two currently
available commercial engineered skin substitute therapies to the wound
(Apligraf) and Dermagraft). Our work extends a previously developed model, which
considers inflammatory and repair macrophage dynamics in normal and diabetic
wound healing. Here, we extend the model to include equations for
platelet-derived growth factor concentration, fibroblast density, collagen
density, and hyaluronan concentration. This enables us to examine the variation
of these components in both normal and diabetic wound healing cases, and to
model the treatment protocols of these therapies. Within the context of our
model, we find that the key component to successful healing in diabetic wounds
is hyaluronan and that the therapies work by increasing the amount of hyaluronan
available in the wound environment. The time-to-healing results correlate with
those observed in clinical trials and the model goes some way to establishing an
understanding of why diabetic wounds do not heal, and how these treatments
affect the diabetic wound environment to promote wound closure.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Waugh HV, Sherratt JA. (2007) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1006230099 | BioModels
Project description:This a model from the article:
Modeling the effects of treating diabetic wounds with engineered skin
substitutes.
Waugh HV, Sherratt JA. Wound Repair Regen
2007 Jul-Aug;15(4):556-65 17650100
,
Abstract:
In this paper, a novel mathematical model of wound healing in both normal and
diabetic cases is presented, focusing upon the effects of adding two currently
available commercial engineered skin substitute therapies to the wound
(Apligraf) and Dermagraft). Our work extends a previously developed model, which
considers inflammatory and repair macrophage dynamics in normal and diabetic
wound healing. Here, we extend the model to include equations for
platelet-derived growth factor concentration, fibroblast density, collagen
density, and hyaluronan concentration. This enables us to examine the variation
of these components in both normal and diabetic wound healing cases, and to
model the treatment protocols of these therapies. Within the context of our
model, we find that the key component to successful healing in diabetic wounds
is hyaluronan and that the therapies work by increasing the amount of hyaluronan
available in the wound environment. The time-to-healing results correlate with
those observed in clinical trials and the model goes some way to establishing an
understanding of why diabetic wounds do not heal, and how these treatments
affect the diabetic wound environment to promote wound closure.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Waugh HV, Sherratt JA. (2007) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1006230003 | BioModels
Project description:Severe angiopathy is a major driver for diabetes associated secondary complications. Knowledge on underlying mechanisms essential for advanced therapies to attenuate these pathologies is limited. Injection of ABCB5+ stromal precursors (SPs) at the edge of non-healing diabetic wounds in a murine db/db model, closely mirroring human type II diabetes, profoundly accelerates wound closure. Strikingly, enhanced angiogenesis was substantially enforced by the release of the ribonuclease angiogenin from ABCB5+ SPs. This compensates for the profoundly reduced angiogenin expression in non-treated murine and human chronic diabetic wounds. Silencing of angiogenin in ABCB5+ SPs prior to injection significantly reduced angiogenesis, reduced numbers of M2 macrophages and delayed wound closure in diabetic db/db mice implying an unprecedented key role for angiogenin in tissue regeneration in diabetes. These data hold significant promise for further refining SPs-based therapies of non-healing diabetic foot ulcers and other pathologies with impaired angiogenesis.
2021-08-12 | GSE181881 | GEO
Project description:We perfomed RNA-seq and wound healing analysis to identify the mechanism how SOX2 promote wound healing. We showed that induction of SOX2 in skin keratinocytes accelerates cutaneous wound healing by promoting keratinocyte migration and proliferation, and enhancement of angiogenesis via the upregulation of EGFR ligands.
2019-09-02 | GSE118859 | GEO
Project description:To identify the candidate miRNAs that might compromise wound healing and contribute to the age-associated delay in wound repair, global miRNA profiling was performed in mouse back telogen skin of young (8-week-old) and aged (2-year-old) animals.
2017-03-25 | GSE97034 | 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 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