Sylvia E. Le Dévédec

Annexin A1 regulates TGF-β signaling and promotes metastasis formation of basal-like breast cancer cells

Annexin A1 (AnxA1) is a candidate regulator of the epithelial- to mesenchymal (EMT)-like phenotypic switch, a pivotal event in breast cancer progression. We show here that AnxA1 expression is associated with a highly invasive basal-like breast cancer subtype both in a panel of human breast cancer cell lines as in breast cancer patients and that AnxA1 is functionally related to breast cancer progression. AnxA1 knockdown in invasive basal-like breast cancer cells reduced the number of spontaneous lung metastasis, whereas additional expression of AnxA1 enhanced metastatic spread. AnxA1 promotes metastasis formation by enhancing TGFβ/Smad signaling and actin reorganization, which facilitates an EMT-like switch, thereby allowing efficient cell migration and invasion of metastatic breast cancer cells.

A computational study of the Warburg effect identifies metabolic targets inhibiting cancer migration

Over the last decade, the field of cancer metabolism has mainly focused on studying the role of tumorigenic metabolic rewiring in supporting cancer proliferation. Here, we perform the first genome‐scale computational study of the metabolic underpinnings of cancer migration. We build genome‐scale metabolic models of the NCI‐60 cell lines that capture the Warburg effect (aerobic glycolysis) typically occurring in cancer cells. The extent of the Warburg effect in each of these cell line models is quantified by the ratio of glycolytic to oxidative ATP flux (AFR), which is found to be highly positively associated with cancer cell migration. We hence predicted that targeting genes that mitigate the Warburg effect by reducing the AFR may specifically inhibit cancer migration. By testing the anti‐migratory effects of silencing such 17 top predicted genes in four breast and lung cancer cell lines, we find that up to 13 of these novel predictions significantly attenuate cell migration either in all or one cell line only, while having almost no effect on cell proliferation. Furthermore, in accordance with the predictions, a significant reduction is observed in the ratio between experimentally measured ECAR and OCR levels following these perturbations. Inhibiting anti‐migratory targets is a promising future avenue in treating cancer since it may decrease cytotoxic‐related side effects that plague current anti‐proliferative treatments. Furthermore, it may reduce cytotoxic‐related clonal selection of more aggressive cancer cells and the likelihood of emerging resistance.

Phenotype-based cell-specific metabolic modeling reveals metabolic liabilities of cancer

Utilizing molecular data to derive functional physiological models tailored for specific cancer cells can facilitate the use of individually tailored therapies. To this end we present an approach termed PRIME for generating cell-specific genome-scale metabolic models (GSMMs) based on molecular and phenotypic data. We build >280 models of normal and cancer cell-lines that successfully predict metabolic phenotypes in an individual manner. We utilize this set of cell-specific models to predict drug targets that selectively inhibit cancerous but not normal cell proliferation. The top predicted target, MLYCD, is experimentally validated and the metabolic effects of MLYCD depletion investigated. Furthermore, we tested cell-specific predicted responses to the inhibition of metabolic enzymes, and successfully inferred the prognosis of cancer patients based on their PRIME-derived individual GSMMs. These results lay a computational basis and a counterpart experimental proof of concept for future personalized metabolic modeling applications, enhancing the search for novel selective anticancer therapies. DOI: http://dx.doi.org/10.7554/eLife.03641.001

Tumor cell migration screen identifies SRPK1 as breast cancer metastasis determinant

Tumor cell migration is a key process for cancer cell dissemination and metastasis that is controlled by signal-mediated cytoskeletal and cell matrix adhesion remodeling. Using a phagokinetic track assay with migratory H1299 cells, we performed an siRNA screen of almost 1,500 genes encoding kinases/phosphatases and adhesome- and migration-related proteins to identify genes that affect tumor cell migration speed and persistence. Thirty candidate genes that altered cell migration were validated in live tumor cell migration assays. Eight were associated with metastasis-free survival in breast cancer patients, with integrin β3-binding protein (ITGB3BP), MAP3K8, NIMA-related kinase (NEK2), and SHC-transforming protein 1 (SHC1) being the most predictive. Examination of genes that modulate migration indicated that SRPK1, encoding the splicing factor kinase SRSF protein kinase 1, is relevant to breast cancer outcomes, as it was highly expressed in basal breast cancer. Furthermore, high SRPK1 expression correlated with poor breast cancer disease outcome and preferential metastasis to the lungs and brain. In 2 independent murine models of breast tumor metastasis, stable shRNA-based SRPK1 knockdown suppressed metastasis to distant organs, including lung, liver, and spleen, and inhibited focal adhesion reorganization. Our study provides comprehensive information on the molecular determinants of tumor cell migration and suggests that SRPK1 has potential as a drug target for limiting breast cancer metastasis.

An improved model to study tumor cell autonomous metastasis programs using MTLn3 cells and the Rag2−/− γc−/− mouse

The occurrence of metastases is a critical determinant of the prognosis for breast cancer patients. Effective treatment of breast cancer metastases is hampered by a poor understanding of the mechanisms involved in the formation of these secondary tumor deposits. To study the processes of metastasis, valid in vivo tumor metastasis models are required. Here, we show that increased expression of the EGF receptor in the MTLn3 rat mammary tumor cell-line is essential for efficient lung metastasis formation in the Rag mouse model. EGFR expression resulted in delayed orthotopic tumor growth but at the same time strongly enhanced intravasation and lung metastasis. Previously, we demonstrated the critical role of NK cells in a lung metastasis model using MTLn3 cells in syngenic F344 rats. However, this model is incompatible with human EGFR. Using the highly metastatic EGFR-overexpressing MTLn3 cell-line, we report that only Rag2−/−γc−/− mice, which lack NK cells, allow efficient lung metastasis from primary tumors in the mammary gland. In contrast, in nude and SCID mice, the remaining innate immune cells reduce MTLn3 lung metastasis formation. Furthermore, we confirm this finding with the orthotopic transplantation of the 4T1 mouse mammary tumor cell-line. Thus, we have established an improved in vivo model using a Rag2−/− γc−/− mouse strain together with MTLn3 cells that have increased levels of the EGF receptor, which enables us to study EGFR-dependent tumor cell autonomous mechanisms underlying lung metastasis formation. This improved model can be used for drug target validation and development of new therapeutic strategies against breast cancer metastasis formation.

Systems microscopy approaches to understand cancer cell migration and metastasis.

Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration.

A Red-Light-Activated Ruthenium-Caged NAMPT Inhibitor Remains Phototoxic in Hypoxic Cancer Cells

Abstract We describe two water‐soluble ruthenium complexes, [1]Cl2 and [2]Cl2, that photodissociate to release a cytotoxic nicotinamide phosphoribosyltransferase (NAMPT) inhibitor with a low dose (21 J cm−2) of red light in an oxygen‐independent manner. Using a specific NAMPT activity assay, up to an 18‐fold increase in inhibition potency was measured upon red‐light activation of [2]Cl2, while [1]Cl2 was thermally unstable. For the first time, the dark and red‐light‐induced cytotoxicity of these photocaged compounds could be tested under hypoxia (1 % O2). In skin (A431) and lung (A549) cancer cells, a 3‐ to 4‐fold increase in cytotoxicity was found upon red‐light irradiation for [2]Cl2, whether the cells were cultured and irradiated with 1 % or 21 % O2. These results demonstrate the potential of photoactivated chemotherapy for hypoxic cancer cells, in which classical photodynamic therapy, which relies on oxygen activation, is poorly efficient.

Ultra High Content Image Analysis and Phenotype Profiling of 3D Cultured Micro-Tissues

In many situations, 3D cell cultures mimic the natural organization of tissues more closely than 2D cultures. Conventional methods for phenotyping such 3D cultures use either single or multiple simple parameters based on morphology and fluorescence staining intensity. However, due to their simplicity many details are not taken into account which limits system-level study of phenotype characteristics. Here, we have developed a new image analysis platform to automatically profile 3D cell phenotypes with 598 parameters including morphology, topology, and texture parameters such as wavelet and image moments. As proof of concept, we analyzed mouse breast cancer cells (4T1 cells) in a 384-well plate format following exposure to a diverse set of compounds at different concentrations. The result showed concentration dependent phenotypic trajectories for different biologically active compounds that could be used to classify compounds based on their biological target. To demonstrate the wider applicability of our method, we analyzed the phenotypes of a collection of 44 human breast cancer cell lines cultured in 3D and showed that our method correctly distinguished basal-A, basal-B, luminal and ERBB2+ cell lines in a supervised nearest neighbor classification method.

The residence time of focal adhesion kinase (FAK) and paxillin at focal adhesions in renal epithelial cells is determined by adhesion size, strength and life cycle status.

Summary Focal adhesions (FAs) are specialized membrane-associated multi-protein complexes that link the cell to the extracellular matrix and enable cell proliferation, survival and motility. Despite the extensive description of the molecular composition of FAs, the complex regulation of FA dynamics is unclear. We have used photobleaching assays of whole cells to determine the protein dynamics in every single focal adhesion. We identified that the focal adhesion proteins FAK and paxillin exist in two different states: a diffuse cytoplasmic pool and a transiently immobile FA-bound fraction with variable residence times. Interestingly, the average residence time of both proteins increased with focal adhesion size. Moreover, increasing integrin clustering by modulating surface collagen density increased residence time of FAK but not paxillin. Finally, this approach was applied to measure FAK and paxillin dynamics using nocodazole treatment followed by washout. This revealed an opposite residence time of FAK and paxillin in maturing and disassembling FAs, which depends on the ventral and peripheral cellular position of the FAs.

Two-Photon Intravital Multicolor Imaging Combined with Inducible Gene Expression to Distinguish Metastatic Behavior of Breast Cancer Cells In Vivo

PurposeThe aim of this study is to use multicolor intravital imaging together with an inducible cell model to compare metastatic behavior of control and genetically modified breast cancer cell populations within the intact primary tumor of a mouse.ProcedureGFP-MTLn3-ErbB1 cells were generated with doxycycline-regulated conditional transgene expression using lentiviral TREAutoR3-cyan fluorescent protein (CFP). CFP expression together with tumor cell motility is monitored in vitro and in vivo.ResultsEffective and tight control of doxycycline-induced CFP expression was observed both in vitro and in vivo. Intravital multiphoton microscopy on intact orthotopic tumors allowed a clear discrimination between GFP-only and (GFP + CFP) cell populations, which enables direct comparison of the motility behavior of two different cell populations in the same microenvironment in vivo.ConclusionsThis system is robust and versatile for conditional gene expression and can be used to study the role of individual candidate metastasis genes in vitro and in vivo. This technology will allow investigations of cellular events in cancer metastasis and in particular intravasation within a primary tumor.