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Stromal-Based Signatures for the Classification of Gastric Cancer [part I]

ABSTRACT: 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.

ORGANISM(S): Mus musculus

PROVIDER: GSE76588 | GEO | 2016/01/07

SECONDARY ACCESSION(S): PRJNA308105

REPOSITORIES: GEO

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Stromal-Based Signatures for the Classification of Gastric Cancer [RRT2]

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

Stromal-Based Signatures for the Classification of Gastric Cancer [PRT1]

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 GeneChipÂ® 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

Stromal-Based Signatures for the Classification of Gastric Cancer [part II]

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Gene expression data of MKN45 xenograft tumors treated with anti-VEGFR2 and anti-VEGF-A antibodies

Project description:The vascular endothelial growth factor (VEGF) /VEGF receptor (VEGFR) axis is an essential regulator of angiogenesis and important therapeutic target in cancer. However, the efficacy of combination treatment with an anti-VEGFR2 antibody and anti-VEGFR-A antibody on tumor progression is not clear. In this study, we examined the anti-tumor effect of the combination treatment using BALB/c-nu/nu mouse xenograft model subcutaneously injected with human gastric cancer MKN45 cells. In this model, we evaluated intra-tumor molecular changes after the combination treatment by cDNA microarray analysis.

2021-07-28 | GSE160613 | GEO

Transcription profiling of human VEGF-derived CD8+ T-cell epitope

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

Regulation of Angiogenesis by EZH2

Project description:While VEGF-targeted therapies are showing promise in clinical studies, new angiogenesis targets are needed to make additional gains. Here, we show that increased Zeste homologue 2 (EZH2) expression in either tumor cells or in tumor vasculature is predictive of poor clinical outcome. The increase in endothelial EZH2 is a direct result of VEGF stimulation and indicates the presence of a paracrine circuit that promotes angiogenesis by methylating and silencing vasohibin 1 (VASH1). EZH2 silencing in the tumor-associated endothelial cells resulted in inhibition of angiogenesis mediated by reactivation of VASH1, and reduced ovarian cancer growth. Combined, these data provide a new understanding of the regulation of tumor angiogenesis and support the potential for targeting EZH2 as a novel therapeutic approach. Pre-clinical study, DNA microarray (Illumina HumanHT-12)

2010-10-12 | E-GEOD-20381 | biostudies-arrayexpress

Interleukin-17 mediated paracrine network promote tumor resistance to anti-angiogenic therapy

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