The prognostic ease and difficulty of invasive breast carcinoma.

Breast carcinoma (BC) has been extensively profiled by high-throughput technologies for over a decade, and broadly speaking, these studies can be grouped into those that seek to identify patient subtypes (studies of heterogeneity) or those that seek to identify gene signatures with prognostic or predictive capacity. The sheer number of reported signatures has led to speculation that everything is prognostic in BC. Here, we show that this ubiquity is an apparition caused by a poor understanding of the interrelatedness between subtype and the molecular determinants of prognosis. Our approach constructively shows how to avoid confounding due to a patient's subtype, clinicopathological profile, or treatment profile. The approach identifies patients who are predicted to have good outcome at time of diagnosis by all available clinical and molecular markers but who experience a distant metastasis within 5 years. These inherently difficult patients (~7% of BC) are prioritized for investigations of intratumoral heterogeneity.

Identification of a Stat3-dependent transcription regulatory network involved in metastatic progression.

High levels of activated Stat3 are often found in human breast cancers and can correlate with poor patient outcome. We employed an activated ErbB2 mouse model of breast cancer to investigate the in vivo role of Stat3 in mammary tumor progression and found that Stat3 does not alter mammary tumor initiation but dramatically affects metastatic progression. Four-fold fewer animals exhibited lung metastases in the absence of Stat3 and a 12-fold reduction in the number of lung lesions was observed in animals bearing Stat3-null tumors when compared with the wild-type cohort. The decreased malignancy in Stat3-deficient tumors is attributed to a reduction in both angiogenic and inflammatory responses associated with a Stat3-dependent transcriptional cascade involving CCAAT/enhancer binding protein delta.