Data from The Outcome of TGFβ Antagonism in Metastatic Breast Cancer Models <i>In Vivo</i> Reflects a Complex Balance between Tumor-Suppressive and Proprogression Activities of TGFβ

Abstract

<div>AbstractPurpose:<p>TGFβs are overexpressed in many advanced cancers and promote cancer progression through mechanisms that include suppression of immunosurveillance. Multiple strategies to antagonize the TGFβ pathway are in early-phase oncology trials. However, TGFβs 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.</p>Experimental Design:<p>A panel of 12 immunocompetent mouse allograft models of metastatic breast cancer was tested for the effect of neutralizing anti-TGFβ antibodies on lung metastatic burden. Extensive correlative biology analyses were performed to assess potential predictive biomarkers and probe underlying mechanisms.</p>Results:<p>Heterogeneous responses to anti-TGFβ 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 TGFβ antagonism depends on a complex balance between enhancing effective antitumor immunity and disrupting persistent tumor-suppressive effects of TGFβ on the tumor cell. Applying transcriptomic signatures derived from treatment-naïve 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-TGFβ therapy.</p>Conclusions:<p>Contrary to dogma, tumor-suppressive responses to TGFβ are retained in some advanced metastatic tumors. Safe deployment of TGFβ antagonists in the clinic will require good predictive biomarkers.</p></div>