ABSTRACT: We have recently proposed a new model for understanding tumor metabolism, termed: "The Autophagic Tumor Stroma Model of Cancer Metabolism". In this new paradigm, catabolism (autophagy) in the tumor stroma fuels the anabolic growth of aggressive cancer cells. Mechanistically, tumor cells induce autophagy in adjacent cancer-associated fibroblasts via the loss of caveolin-1 (Cav-1), which is sufficient to promote oxidative stress in stromal fibroblasts. To further test this hypothesis, here we created human Cav-1 deficient immortalized fibroblasts using a targeted sh-RNA knock-down approach. Relative to control fibroblasts, Cav-1 deficient fibroblasts dramatically promoted tumor growth in xenograft assays employing an aggressive human breast cancer cell line, namely MDA-MB-231 cells. Co-injection of Cav-1 deficient fibroblasts, with MDA-MB-231 cells, increased both tumor mass and tumor volume by ~4-fold. Immuno-staining with CD31 indicated that this paracrine tumor promoting effect was clearly independent of angiogenesis. Mechanistically, proteomic analysis of these human Cav-1 deficient fibroblasts identified > 40 protein biomarkers that were upregulated, most of which were associated with i) myofibroblast differentiation, or ii) oxidative stress/hypoxia. In direct support of these findings, the tumor promoting effects of Cav-1 deficient fibroblasts could be functionally suppressed (nearly 2-fold) by the recombinant over-expression of SOD2 (superoxide dismutase 2), a known mitochondrial enzyme that de-activates superoxide, thereby reducing mitochondrial oxidative stress. In contrast, cytoplasmic soluble SOD1 had no effect, further highlighting a specific role for mitochondrial oxidative stress in this process. In summary, here we provide new evidence directly supporting a key role for a loss of stromal Cav-1 expression and oxidative stress in cancer-associated fibroblasts, in promoting tumor growth, which is consistent with "The Autophagic Tumor Stroma Model of Cancer". The human Cav-1 deficient fibroblasts that we have generated are a new genetically tractable model system for identifying other suppressors of the cancer-associated fibroblast phenotype, via a genetic "complementation" approach. This has important implications for understanding the pathogenesis of triple negative and basal breasts cancers, as well as tamoxifen-resistance in ER+ breast cancers, which are all associated with a Cav-1 deficient "lethal" tumor micro-environment, driving poor clinical outcome.
