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Series GSE76628 Query DataSets for GSE76628
Status Public on Jan 08, 2016
Title Stromal-Based Signatures for the Classification of Gastric Cancer [part II]
Organism Mus musculus
Experiment type Expression profiling by array
Summary 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.
Overall design 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.
Contributor(s) Uhlik MT, Liu J, Falcon BL, Iyer S, Stewart J, Celikkaya H, O’Mahony M, Sevinsky C, Lowes C, Douglass L, Jeffries C, Bodenmiller D, Chintharlapalli S, Fischl A, Gerald D, Xue Q, Lee J, Santamaria-Pang A, Al-Kofahi Y, Sui Y, Desai K, Doman T, Aggarwal A, Carter J, Pytowski B, Jaminet S, Ginty F, Nasir A, Nagy JA, Dvorak HF, Benjamin LE
Citation(s) 27197264
Submission date Jan 07, 2016
Last update date Feb 11, 2019
Contact name Jiangang Liu
Phone 317-433-0033
Organization name Eli Lilly and Company
Department Tailored Therapeutics
Street address 893 S Delaware St
City Indianapolis
State/province IN
ZIP/Postal code 46225
Country USA
Platforms (1)
GPL1261 [Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
Samples (78)
GSM2029389 can_Ad_VEGF_Normal_095
GSM2029390 can_Ad_VEGF_Normal_096
GSM2029391 can_Ad_VEGF_Normal_097
This SubSeries is part of SuperSeries:
GSE76630 Stromal-Based Signatures for the Classification of Gastric Cancer
BioProject PRJNA308202

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE76628_RAW.tar 291.7 Mb (http)(custom) TAR (of CEL)
Raw data provided as supplementary file
Processed data included within Sample table

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