ABSTRACT
In the tumor microenvironment, Cancer Associated Fibroblasts (CAFs) become activated by cancer cells and increase their secretory activity to produce soluble factors that contribute to tumor cells proliferation, invasion and dissemination to distant organs. The pro-tumorigenic transcription factor STAT3 and its canonical inducer, the pro-inflammatory cytokine IL-6, act conjunctly in a positive feedback loop that maintains high levels of IL-6 secretion and STAT3 activation in both tumor and stromal cells. Here, we demonstrate that STAT3 is essential for the pro-tumorigenic functions of murine breast cancer CAFs both in vitro and in vivo, and identify a STAT3 signature significantly enriched for genes encoding for secreted proteins. Among these, ANGPTL4, MMP13 and STC-1 were functionally validated as STAT3-dependent mediators of CAF pro-tumorigenic functions by different approaches. Both in vitro and in vivo CAFs activities were moreover impaired by MMP13 inhibition, supporting the feasibility of a therapeutic approach based on inhibiting STAT3-induced CAF-secreted proteins. The clinical potential of such an approach is supported by the observation that an equivalent CAF-STAT3 signature in humans is expressed at high levels in breast cancer stromal cells and characterizes patients with a shorter disease specific survival, including those with basal-like disease.
Subject(s)
Breast Neoplasms , Cancer-Associated Fibroblasts , Angiopoietin-Like Protein 4/genetics , Animals , Breast Neoplasms/pathology , Cancer-Associated Fibroblasts/metabolism , Cell Line, Tumor , Female , Fibroblasts/metabolism , Glycoproteins , Humans , Interleukin-6/genetics , Interleukin-6/metabolism , Matrix Metalloproteinase 13/genetics , Matrix Metalloproteinase 13/metabolism , Mice , STAT3 Transcription Factor/genetics , STAT3 Transcription Factor/metabolism , Signal Transduction/physiology , Tumor Microenvironment/geneticsABSTRACT
Transcriptome data provide a valuable resource for the study of cancer molecular mechanisms, but technical biases, sample heterogeneity, and small sample sizes result in poorly reproducible lists of regulated genes. Additionally, the presence of multiple cellular components contributing to cancer development complicates the interpretation of bulk transcriptomic profiles. To address these issues, we collected 48 microarray datasets derived from laser capture microdissected stroma or epithelium in breast tumors and performed a meta-analysis identifying robust lists of differentially expressed genes. This was used to create a database with carefully harmonized metadata that we make freely available to the research community. As predicted, combining the results of multiple datasets improved statistical power. Moreover, the separate analysis of stroma and epithelium allowed the identification of genes with different contributions in each compartment, which would not be detected by bulk analysis due to their distinct regulation in the two compartments. Our method can be profitably used to help in the discovery of biomarkers and the identification of functionally relevant genes in both the stroma and the epithelium. This database was made to be readily accessible through a user-friendly web interface.
