A Signature Predicting Poor Prognosis in Gastric and Ovarian Cancer Represents a Coordinated Macrophage and Stromal Response

Abstract

Purpose: Gene-expression profiling has revolutionized the way we think about cancer and confers the ability to observe the synchronous expression of thousands of genes. The use of putative genome-level expression profiles has allowed biologists to observe the complex interactions of genes that constitute recognized biologic pathways. We used gastric and ovarian datasets to identify gene-expression signatures and determine any functional significance.Experimental Design: Microarray data of 94-tumor and 45-benign samples derived from patients with gastric cancer were interrogated using Hierarchical Ordered Partitioning and Collapsing Hybrid analysis identifying clusters of coexpressed genes. Clusters were further characterized with respect to biologic significance, gene ontology, and ability to discriminate between normal and tumor tissue. Tumor tissues were separated into epithelial and stromal compartments and immunohistochemical analysis performed to further elucidate specific cell lineages expressing genes contained in the signature.Results: We identified a "stromal-response" expression signature, highly enriched for inflammatory, extracellular matrix, cytokine, and growth factor proteins. The majority of genes in the signature are expressed in the tumor-associated stroma but were absent in associated premalignant conditions. In gastric cancer, this module almost perfectly differentiates tumor from nonmalignant gastric tissue and hence can be regarded as a highly tumor-specific gene-expression signature.Conclusions: We show that these genes are consistently coexpressed across a range of independent gastric datasets as well as other cancer types suggesting a conserved functional role in cancer. In addition, we show that this signature can be a surrogate marker for M2 macrophage activity and has significant prognostic implications in gastric and ovarian high-grade serous cancer. Clin Cancer Res; 20(10); 2761-72. Ó2014 AACR.

Genetics and Molecular Pathogenesis of Gastric Adenocarcinoma

“…Several studies have now confirmed that GCs with a high stromal content, determined either by gene expression analysis or histopathological evaluation, are associated with poor prognosis. 129,130 Similar findings have also been reported in other tumor types, such as breast, lung and esophageal cancers. 131,132 The mechanisms underlying the role of the tumor stroma in supporting GC growth are likely multi-factorial, ranging from providing a suitable extracellular matrix to maintain cancer cell growth, active cell-cell interactions via cancer-associated fibroblasts which can secrete growth-stimulatory molecules such as IL-6, and providing a physical barrier inhibiting chemotherapy from reaching target malignant cells.…”

The transcriptional signature of human ovarian carcinoma macrophages is associated with extracellular matrix reorganization

“…Busuttil and colleagues [71] identified a “stromal-response” signature in ovarian cancer that is associated with poor survival and enriched for genes encoding inflammatory and extracellular matrix proteins expressed by the tumor-associated stroma. Furthermore, the mesenchymal subtype of ovarian HGSC, characterized by the upregulation of ECM remodeling genes, has the worst clinical outcome of all subtypes [72, 73].…”

Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients

“…We assembled a gastric cancer database using samples measured in three different sources including previously partly published data at the Max Delbrück Center for Molecular Medicine, Berlin, Germany (“Berlin dataset”, published in GEO as GSE22377) [36]; at the Transgenic Oncogenesis and Genomics Section, Laboratory of Cancer Biology and Genetics, National Cancer Institute, Bethesda, Maryland, USA (“Bethesda dataset”, published in GEO as GSE14210) [37]; and at the Peter MacCallum Cancer Centre, Melbourne, Australia (“Melbourne dataset”, published in GEO as GSE51105) [38]. Sample collection, hybridization, and gene expression measurements were described previously.…”