1. Stromal-Based Signatures for the Classification of Gastric Cancer
- Author
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Diane M. Bodenmiller, Jeeyun Lee, Alberto Santamaria-Pang, Shou-Ching S. Jaminet, Yunxia Sui, Aejaz Nasir, Julie Stewart, Fiona Ginty, Anthony S. Fischl, Keyur Desai, Larry E. Douglass, Yousef Al-Kofahi, Thompson N. Doman, Harold F. Dvorak, Hilal Celikkaya, Damien Gerald, Bronislaw Pytowski, Cynthia Jeffries, Seema Iyer, Sudhakar Chintharlapalli, Amit Aggarwal, Christina Lowes, Mark T. Uhlik, Jiangang Liu, Beverly L. Falcon, Marguerita O’Mahony, Christopher J. Sevinsky, Julia H. Carter, Laura E. Benjamin, Janice A. Nagy, and Qi Xue
- Subjects
Vascular Endothelial Growth Factor A ,0301 basic medicine ,Cancer Research ,Stromal cell ,Angiogenesis ,medicine.drug_class ,medicine.medical_treatment ,Biology ,Bioinformatics ,Monoclonal antibody ,Mice ,03 medical and health sciences ,Stomach Neoplasms ,Biomarkers, Tumor ,Image Processing, Computer-Assisted ,Tumor Microenvironment ,medicine ,Animals ,Humans ,Oligonucleotide Array Sequence Analysis ,Tumor microenvironment ,Neovascularization, Pathologic ,Gene Expression Profiling ,Computational Biology ,Immunotherapy ,Immunohistochemistry ,Phenotype ,Gene expression profiling ,Disease Models, Animal ,030104 developmental biology ,Oncology ,Tissue Array Analysis ,Cancer research ,Heterografts ,Transcriptome - Abstract
Treatment of metastatic gastric cancer typically involves chemotherapy and monoclonal antibodies targeting HER2 (ERBB2) and VEGFR2 (KDR). However, reliable methods to identify patients who would benefit most from a combination of treatment modalities targeting the tumor stroma, including new immunotherapy approaches, are still lacking. Therefore, we integrated a mouse model of stromal activation and gastric cancer genomic information to identify gene expression signatures that may inform treatment strategies. We generated a mouse model in which VEGF-A is expressed via adenovirus, enabling a stromal response marked by immune infiltration and angiogenesis at the injection site, and identified distinct stromal gene expression signatures. With these data, we designed multiplexed IHC assays that were applied to human primary gastric tumors and classified each tumor to a dominant stromal phenotype representative of the vascular and immune diversity found in gastric cancer. We also refined the stromal gene signatures and explored their relation to the dominant patient phenotypes identified by recent large-scale studies of gastric cancer genomics (The Cancer Genome Atlas and Asian Cancer Research Group), revealing four distinct stromal phenotypes. Collectively, these findings suggest that a genomics-based systems approach focused on the tumor stroma can be used to discover putative predictive biomarkers of treatment response, especially to antiangiogenesis agents and immunotherapy, thus offering an opportunity to improve patient stratification. Cancer Res; 76(9); 2573–86. ©2016 AACR.
- Published
- 2016
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