The Outcome Of Tgf Beta Antagonism In Metastatic Breast Cancer Models In Vivo Reflects A Complex Balance Between Tumor-Suppressive And Proprogression Activities Of Tgf Beta

Purpose: TGF beta s are overexpressed in many advanced cancers and promote cancer progression through mechanisms that include suppression of immunosurveillance. Multiple strategies to antagonize the TGF beta pathway are in early-phase oncology trials. However, TGF beta s also have tumor-suppressive activities early in tumorigenesis, and the extent to which these might be retained in advanced disease has not been fully explored.Experimental Design: A panel of 12 immunocompetent mouse allograft models of metastatic breast cancer was tested for the effect of neutralizing anti-TGF beta antibodies on lung metastatic burden. Extensive correlative biology analyses were performed to assess potential predictive biomarkers and probe underlying mechanisms.Results: Heterogeneous responses to anti-TGF beta treatment were observed, with 5 of 12 models (42%) showing suppression of metastasis, 4 of 12 (33%) showing no response, and 3 of 12 (25%) showing an undesirable stimulation (up to 9-fold) of metastasis. Inhibition of metastasis was immune-dependent, whereas stimulation of metastasis was immune-independent and targeted the tumor cell compartment, potentially affecting the cancer stem cell. Thus, the integrated outcome of TGF beta antagonism-depends on a complex balance between enhancing effective antitumor immunity and disrupting persistent tumor-suppressive effects of TGF beta on the tumor cell. Applying transcriptomic signatures derived from treatment-naive mouse primary tumors to human breast cancer datasets suggested that patients with breast cancer with high-grade, estrogen receptor-negative disease are most likely to benefit from anti-TGF beta therapy.Conclusions: Contrary to dogma, tumor-suppressive responses to TGF beta are retained in some advanced metastatic tumors. Safe deployment of TGF beta antagonists in the clinic will require good predictive biomarkers.