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Stromal-Based Signatures for the Classification of Gastric Cancer.

Mark T Uhlik1, Jiangang Liu1, Beverly L Falcon1

  • 1Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana.

Cancer Research
|May 20, 2016
PubMed
Summary

Researchers identified distinct tumor stroma phenotypes in gastric cancer by integrating mouse models and genomic data. This approach can discover biomarkers to predict response to antiangiogenesis and immunotherapy, improving patient selection.

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Area of Science:

  • Oncology
  • Cancer Genomics
  • Tumor Microenvironment Research

Background:

  • Metastatic gastric cancer treatment relies on chemotherapy and targeted therapies like anti-HER2 and anti-VEGFR2 (KDR) antibodies.
  • Current limitations exist in identifying patients who benefit from stromal-targeting treatments, including immunotherapies.

Purpose of the Study:

  • To identify gene expression signatures and develop predictive biomarkers for gastric cancer treatment strategies.
  • To stratify patients based on tumor stroma characteristics for improved therapeutic selection.

Main Methods:

  • Integrated a mouse model of VEGF-A-induced stromal activation with gastric cancer genomic data.
  • Generated multiplexed immunohistochemistry (IHC) assays to classify human gastric tumors into dominant stromal phenotypes.
  • Correlated identified stromal gene signatures with established gastric cancer genomic classifications.

Main Results:

  • Identified distinct stromal gene expression signatures associated with immune infiltration and angiogenesis.
  • Classified human gastric tumors into four distinct stromal phenotypes based on vascular and immune diversity.
  • Revealed relationships between stromal phenotypes and major gastric cancer genomic subtypes.

Conclusions:

  • A genomics-based systems approach focusing on the tumor stroma can discover predictive biomarkers.
  • This strategy offers potential for improved patient stratification for antiangiogenesis and immunotherapy.
  • Findings pave the way for personalized treatment strategies in gastric cancer.