FIP Seminar: Multiphoton Intravital imaging at single cell resolution reveals mechanisms of cancer dissemination and markers for prognosis and treatment of breast cancer patients
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Wed, 01/25/2017 - 12:00 to 13:00
John S. Condeelis - Professor, Albert Einstein College of Medicine
Multiphoton microscopy of live animals in real time, used in combination with imaging windows and photo-conversion fate mapping, led to the discovery of cause and effect relationships between cells, not possible to define in fixed tissue, that cause tumor metastasis This has revolutionized our understanding of cancer metastasis. Multiphoton imaging at single cell resolution in vivo demonstrates that tumor cells form migratory streams with macrophages and move with high persistence to blood vessels under control of HGF gradients (1). Once at the blood vessel a cell complex involving the direct contact between a tumor cell, endothelial cell and macrophage forms the Tumor MicroEnvironment of Metastasis (TMEM) (2, 3). High resolution imaging at single cell resolution in live mice in real time has defined the mechanisms responsible for the function of TMEM as the only site in breast tumors of tumor cell transendothelial migration and intravasation leading to metastasis (3). The TMEM structure itself, as well as the gene expression patent of tumor cells interacting with TMEM, have been validated as prognostic markers for predicting metastasis in breast cancer patients (4). These are the first markers of metastasis in clinical use derived from multiphoton intravital imaging. Clinical trials using these markers to assess treatment strategies directed at inhibiting TMEM function are now underway in breast cancer patients at several sites in North American.
1. Leung E, Xue A, Wang Y, Rougerie P, Sharma V, Eddy R, Cox D, Condeelis J. (2016). Blood vessel endothelium -directed tumor cell streaming in breast tumors requires the HGF/CMet signaling pathway. In Press. 2. Rohan TE, Xue X, Lin HM, D'Alfonso TM, Ginter PS, Oktay MH, Robinson BD, Ginsberg M, Gertler FB, Glass AG, Sparano JA, Condeelis JS, Jones JG. (2014). Tumor microenvironment of metastasis and risk of distant metastasis of breast cancer. Journal of the National Cancer Institute. 106(8). PMID: 24895374 /PMCID: PMC4133559. 3. Harney AS, Arwert EN, Entenberg D, Wang Y, Guo P, Qian BZ, Oktay MH, Pollard JW, Jones JG, Condeelis JS. (2015). Real-Time Imaging Reveals Local, Transient Vascular Permeability, and Tumor Cell Intravasation Stimulated by TIE2hi Macrophage-Derived VEGFA. Cancer Discovery. 5(9):932-43. PMID: 26269515 / PMCID: PMC4560669. 4. Karagiannis GS, Goswami S, Jones JG, Oktay MH, Condeelis JS. (2016). Signatures of breast cancer metastasis at a glance. Journal of Cell Science. 129(9):1751-8. PMID: 27084578 / PMCID: PMC4893654.
John Condeelis’ expertise is in optical physics, cell biophysics, cancer biology and mouse models. He and his collaborators developed the custom built multiphoton imaging technology and animal models used to identify the invasion and intravasation microenvironments in mammary tumors. This led to the discovery of the paracrine interaction between tumor cells and macrophages in vivo, and the role of macrophages in the migration of tumor cells and intravasation in primary mammary tumors. Based on these results, cell collection techniques, including the in vivo invasion assay, were developed for the collection of migrating and disseminating macrophages and tumor cells. This led to the discovery of the mouse and human invasion signatures which have supplied markers for the prediction of breast tumor metastasis in humans. Three of these markers, TMEM, MenaCalc and cofilin x p-cofilin, have been used in retrospective studies of cohorts of breast cancer patients to successfully predict metastatic risk and are now in clinical validation trials. Condeelis brings a multidisciplinary set of imaging and cell biophysics tools to this program to support molecular level analysis of mechanisms involved in invasion, transendothelial migration and signaling and methods to inhibit these phenotypes.