Dissemination of tumor cells is an essential step in metastasis. Direct contact between a macrophage, Mena over-expressing tumor cell and endothelial cell [Tumor MicroEnvironment of Metastasis (TMEM)], correlates with metastasis in breast cancer patients. Here we show, using intravital high-resolution two-photon microscopy, that transient vascular permeability and tumor cell intravasation occur simultaneously and exclusively at TMEM. The hyperpermeable nature of tumor vasculature is described as spatially and temporally heterogeneous. Using real-time imaging we observed that vascular permeability is transient, restricted to TMEM, and required for tumor cell dissemination. VEGFA signaling from Tie2Hi TMEM macrophages causes local loss of vascular junctions, transient vascular permeability and tumor cell intravasation, demonstrating a role for TMEM within the primary mammary tumor. These data provide insight into the mechanism of tumor cell intravasation and vascular permeability in breast cancer, explaining the value of TMEM density as a predictor of distant metastatic recurrence in patients.

Breast cancer cells disseminate through TIE2/MENACalc/MENAINV-dependent cancer cell intravasation sites, called tumor microenvironment of metastasis (TMEM), which are clinically validated as prognostic markers of metastasis in breast cancer patients. Using fixed tissue and intravital imaging of a PyMT murine model and patient-derived xenografts, we show that chemotherapy increases the density and activity of TMEM sites and Mena expression and promotes distant metastasis. Moreover, in the residual breast cancers of patients treated with neoadjuvant paclitaxel after doxorubicin plus cyclophosphamide, TMEM score and its mechanistically connected MENAINV isoform expression pattern were both increased, suggesting that chemotherapy, despite decreasing tumor size, increases the risk of metastatic dissemination. Chemotherapy-induced TMEM activity and cancer cell dissemination were reversed by either administration of the TIE2 inhibitor rebastinib or knockdown of the MENA gene. Our results indicate that TMEM score increases and MENA isoform expression pattern changes with chemotherapy and can be used in predicting prometastatic changes in response to chemotherapy. Furthermore, inhibitors of TMEM function may improve clinical benefits of chemotherapy in the neoadjuvant setting or in metastatic disease.

Metastasis is the leading cause of cancer-related deaths; metastatic lesions develop from disseminated cancer cells (DCCs) that can remain dormant1. Metastasis-initiating cells are thought to originate from a subpopulation present in progressed, invasive tumours2. However, DCCs detected in patients before the manifestation of breast-cancer metastasis contain fewer genetic abnormalities than primary tumours or than DCCs from patients with metastases3–5. These findings, and those in pancreatic cancer6 and melanoma7 models, indicate that dissemination might occur during the early stages of tumour evolution3,8,9. However, the mechanisms that might allow early disseminated cancer cells (eDCCs) to complete all steps of metastasis are unknown8. Here we show that, in early lesions in mice and before any apparent primary tumour masses are detected, there is a sub-population of Her2+p-p38lop-Atf2loTwist1hiE-cadlo early cancer cells that is invasive and can spread to target organs. Intra-vital imaging and organoid studies of early lesions showed that Her2+ eDCC precursors invaded locally, intravasated and lodged in target organs. Her2+ eDCCs activated a Wnt-dependent epithelial–mesenchymal transition (EMT)-like dissemination program but without complete loss of the epithelial phenotype, which was reversed by Her2 or Wnt inhibition. Notably, although the majority of eDCCs were Twist1hiE-cadlo and dormant, they eventually initiated metastasis. Our work identifies a mechanism for early dissemination in which Her2 aberrantly activates a program similar to mammary ductal branching that generates eDCCs that are capable of forming metastasis after a dormancy phase.

Circulating tumor cells (CTCs) seed cancer metastases; however, the underlying cellular and molecular mechanisms remain unclear. CTC clusters were less frequently detected but more metastatic than single CTCs of triple negative breast cancer patients and representative patient-derived-xenograft (PDX) models. Using intravital multiphoton microscopic imaging, we found that clustered tumor cells in migration and circulation resulted from aggregation of individual tumor cells rather than collective migration and cohesive shedding. Aggregated tumor cells exhibited enriched expression of the breast cancer stem cell marker CD44 and promoted tumorigenesis and polyclonal metastasis. Depletion of CD44 effectively prevented tumor cell aggregation and decreased PAK2 levels. The intercellular CD44-CD44 homophilic interactions directed multicellular aggregation, requiring its N-terminal domain, and initiated CD44-PAK2 interactions for further activation of FAK signaling. Our studies highlight that CD44+ CTC clusters, whose presence is correlated with a poor prognosis of breast cancer patients, can serve as novel therapeutic targets of polyclonal metastasis.

Human serum contains a complex array of proteolytically derived peptides (serum peptidome) that may provide a correlate of biological events occurring in the entire organism; for instance, as a diagnostic for solid tumors (Petricoin, E. F.; Ardekani, A. M.; Hitt, B. A.; Levine, P. J.; Fusaro, V. A.; Steinberg, S. M.; Mills, G. B.; Simone, C.; Fishman, D. A.; Kohn, E. C.; Liotta, L. Lancet 2002, 359, 572-577). Here, we describe a novel, automated technology platform for the simultaneous measurement of serum peptides that is simple, scalable, and generates highly reproducible patterns. Peptides are captured and concentrated using reversed-phase (RP) batch processing in a magnetic particle-based format, automated on a liquid handling robot, and followed by a MALDI TOF mass spectrometric readout. The protocol is based on a detailed investigation of serum handling, RP ligand and eluant selection, small-volume robotics design, an optimized spectral acquisition program, and consistent peak extraction plus binning across a study set. The improved sensitivity and resolution allowed detection of 400 polypeptides (0.8-15-kDa range) in a single droplet (approximately 50 microL) of serum, and almost 2000 unique peptides in larger sample sets, which can then be analyzed using common microarray data analysis software. A pilot study indicated that sera from brain tumor patients can be distinguished from controls based on a pattern of 274 peptide masses. This, in turn, served to create a learning algorithm that correctly predicted 96.4% of the samples as either normal or diseased.