Metastasis confronts clinicians with two major challenges: estimating the patient's risk of metastasis and identifying therapeutic targets. Because they are key signal integrators connecting cellular processes to clinical outcome, we aimed to identify transcriptional nodes regulating cancer cell metastasis. Using rodent xenograft models that we previously developed, we identified the transcription factor Fos-related antigen-1 (Fra-1) as a key coordinator of metastasis. Because Fra-1 often is overexpressed in human metastatic breast cancers and has been shown to control their invasive potential in vitro, we aimed to assess the implication and prognostic significance of the Fra-1-dependent genetic program in breast cancer metastasis and to identify potential Fra-1-dependent therapeutic targets. In several in vivo assays in mice, we demonstrate that stable RNAi depletion of Fra-1 from human breast cancer cells strongly suppresses their ability to metastasize. These results support a clinically important role for Fra-1 and the genetic program it controls. We show that a Fra-1-dependent gene-expression signature accurately predicts recurrence of breast cancer. Furthermore, a synthetic lethal drug screen revealed that antagonists of the adenosine receptor A 2B (ADORA2B) are preferentially toxic to breast tumor cells expressing Fra-1. Both RNAi silencing and pharmacologic blockade of ADORA2B inhibited filopodia formation and invasive activity of breast cancer cells and correspondingly reduced tumor outgrowth in the lungs. These data show that Fra-1 activity is causally involved in and is a prognostic indicator of breast cancer metastasis. They suggest that Fra-1 activity predicts responsiveness to inhibition of pharmacologically tractable targets, such as ADORA2B, which may be used for clinical interference of metastatic breast cancer.epithelial-mesenchymal transition | invasion T he path toward improved management of metastatic tumors, the major cause of death among cancer patients, involves tackling of two major challenges: the development of therapies that combat the patient's metastatic disease and of means of reliably assessing the individual patient's risk of developing metastasis. In line with the second objective, patient stratification has received increasing attention as a way to improve the therapeutic management of cancer patients. In recent years, for example, gene-expression profiling of primary breast cancer has uncovered gene signatures that assist clinicians in classifying breast cancer subtypes more accurately (1, 2) and that provide predictions of tumor recurrence and clinical outcome (3-5). Such classifiers have proven useful for formulating prognosis and adjusting therapeutic management of breast cancer patients, complementing conventional histopathological criteria such as tumor size, nodal status, and estrogen receptor (ER) status (6-8) to predict clinical outcome better.The most important challenge posed by metastatic cancer, blocking metastatic spread, has proven more troublesome. Indeed, most ...