Model driven optimization of antiangiogenics + cytotoxics combination: application to breast cancer mice treated with bevacizumab + paclitaxel doublet leads to reduced tumor growth and fewer metastasis.

Bevacizumab is the first-in-class antiangiogenic drug and is almost always administrated in combination with cytotoxics. Reports have shown that bevacizumab could induce a transient phase of vascular normalization, thus ensuring a better drug delivery when cytotoxics administration is adjuvant. However, determining the best sequence remains challenging. We have developed a mathematical model describing the impact of antiangiogenics on tumor vasculature. A 3.4 days gap between bevacizumab and paclitaxel was first proposed by our model. To test its relevance, 84 mice were orthotopically xenografted with human MDA-231Luc+ refractory breast cancer cells. Two sets of experiments were performed, based upon different bevacizumab dosing (10 or 20 mg/kg) and inter-cycle intervals (7 or 10 days), comprising several combinations with paclitaxel. Results showed that scheduling bevacizumab 3 days before paclitaxel improved antitumor efficacy (48% reduction in tumor size compared with concomitant dosing, p < 0.05) and reduced metastatic spreading. Additionally, bevacizumab alone could lead to more aggressive metastatic disease with shorter survival in animals. Our model was able to fit the experimental data and provided insights on the underlying dynamics of the vasculature's ability to deliver the cytotoxic agent. Final simulations suggested a new, data-informed optimal gap of 2.2 days. Our experimental data suggest that current concomitant dosing between bevacizumab and paclitaxel could be a sub-optimal strategy at bedside. In addition, this proof of concept study suggests that mathematical modelling could help to identify the optimal interval among a variety of possible alternate treatment modalities, thus refining the way experimental or clinical studies are conducted.

In Vivo Bioluminescence Tomography for Monitoring Breast Tumor Growth and Metastatic Spreading: Comparative Study and Mathematical Modeling.

This study aimed at evaluating the reliability and precision of Diffuse Luminescent Imaging Tomography (DLIT) for monitoring primary tumor and metastatic spreading in breast cancer mice, and to develop a biomathematical model to describe the collected data. Using orthotopic mammary fat pad model of breast cancer (MDAMB231-Luc) in mice, we monitored tumor and metastatic spreading by three-dimensional (3D) bioluminescence and cross-validated it with standard bioluminescence imaging, caliper measurement and necropsy examination. DLIT imaging proved to be reproducible and reliable throughout time. It was possible to discriminate secondary lesions from the main breast cancer, without removing the primary tumor. Preferential metastatic sites were lungs, peritoneum and lymph nodes. Necropsy examinations confirmed DLIT measurements. Marked differences in growth profiles were observed, with an overestimation of the exponential phase when using a caliper as compared with bioluminescence. Our mathematical model taking into account the balance between living and necrotic cells proved to be able to reproduce the experimental data obtained with a caliper or DLIT imaging, because it could discriminate proliferative living cells from a more composite mass consisting of tumor cells, necrotic cell, or inflammatory tissues. DLIT imaging combined with mathematical modeling could be a powerful and informative tool in experimental oncology.

Combenefit: an interactive platform for the analysis and visualization of drug combinations.

MOTIVATION: Many drug combinations are routinely assessed to identify synergistic interactions in the attempt to develop novel treatment strategies. Appropriate software is required to analyze the results of these studies. RESULTS: We present Combenefit, new free software tool that enables the visualization, analysis and quantification of drug combination effects in terms of synergy and/or antagonism. Data from combinations assays can be processed using classical Synergy models (Loewe, Bliss, HSA), as single experiments or in batch for High Throughput Screens. This user-friendly tool provides laboratory scientists with an easy and systematic way to analyze their data. The companion package provides bioinformaticians with critical implementations of routines enabling the processing of combination data. AVAILABILITY AND IMPLEMENTATION: Combenefit is provided as a Matlab package but also as standalone software for Windows (http://sourceforge.net/projects/combenefit/). CONTACT: Giovanni.DiVeroli@cruk.cam.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mathematical modeling of tumor growth and metastatic spreading: validation in tumor-bearing mice.

Defining tumor stage at diagnosis is a pivotal point for clinical decisions about patient treatment strategies. In this respect, early detection of occult metastasis invisible to current imaging methods would have a major impact on best care and long-term survival. Mathematical models that describe metastatic spreading might estimate the risk of metastasis when no clinical evidence is available. In this study, we adapted a top-down model to make such estimates. The model was constituted by a transport equation describing metastatic growth and endowed with a boundary condition for metastatic emission. Model predictions were compared with experimental results from orthotopic breast tumor xenograft experiments conducted in Nod/Scidγ mice. Primary tumor growth, metastatic spread and growth were monitored by 3D bioluminescence tomography. A tailored computational approach allowed the use of Monolix software for mixed-effects modeling with a partial differential equation model. Primary tumor growth was described best by Bertalanffy, West, and Gompertz models, which involve an initial exponential growth phase. All other tested models were rejected. The best metastatic model involved two parameters describing metastatic spreading and growth, respectively. Visual predictive check, analysis of residuals, and a bootstrap study validated the model. Coefficients of determination were [Formula: see text] for primary tumor growth and [Formula: see text] for metastatic growth. The data-based model development revealed several biologically significant findings. First, information on both growth and spreading can be obtained from measures of total metastatic burden. Second, the postulated link between primary tumor size and emission rate is validated. Finally, fast growing peritoneal metastases can only be described by such a complex partial differential equation model and not by ordinary differential equation models. This work advances efforts to predict metastatic spreading during the earliest stages of cancer.

Biodistribution, tumor uptake and efficacy of 5-FU-loaded liposomes: why size matters.

PURPOSE: We have investigated the impact of particle size on the biodistribution, tumor uptake and antiproliferative efficacy of 5-FU-loaded liposomes. METHODS: Three different batches of pegylated liposomes varying in size (i.e., 70, 120 and 250 nm respectively) were tested. The active compounds encapsulated were an equimolar mix of 5-FU, 2'-deoxyinosine and folinic acid. Liposomes were subsequently tested on the human breast cancer model MDA231 cells, a model previously found to be resistant to 5-FU. In vitro, antiproliferative efficacy and microscopy studies of liposomes uptake were carried out. In vivo, comparative biodistribution and efficacy studies were performed in tumor-bearing mice. RESULTS: Difference in size did not change in vitro antiproliferative activity. Fluorescence-Microscopy studies showed that liposomes were mainly uptaken by tumor cells through a direct internalization process, regardless of their size. Biodistribution profiles in tumor-bearing mice revealed higher accumulation of small liposomes in tumors throughout time as compared with normal and large liposomes (p < 0.05). Additionally, we observed that the bigger were the tumors, the more vascularised they were and the greater was the difference in accumulation between small and large liposomes. Consequently, in vivo efficacy studies showed at study conclusion that a 68% reduction in tumor size was achieved with small liposomes (p < 0.05), whereas larger liposomes failed to reduce significantly tumor growth. Similarly, at study conclusion a trend towards higher survival-rate in animals treated with smaller liposomes was observed. CONCLUSION: This study suggests that particle size is critical to achieve higher selectivity and efficacy in experimental oncology, including in resistant tumors.

In vitro 3D angiogenesis assay in egg white matrix: comparison to Matrigel, compatibility to various species, and suitability for drug testing.

In vitro angiogenesis assays are commonly used to assess pro- or anti-angiogenic drug properties. Extracellular matrix (ECM) substitutes such as Matrigel and collagen gel became very popular in in vitro 3D angiogenesis assays as they enable tubule formation by endothelial cells from culture or aortic rings. However, these assays are usually used with a single cell type, lacking the complex cellular interactions occurring during angiogenesis. Here, we report a novel angiogenesis assay using egg white as ECM substitute. We found that, similar to Matrigel, egg white elicited prevascular network formation by endothelial and/or smooth muscle cell coculture. This matrix was suitable for various cells from human, mouse, and rat origin. It is compatible with aortic ring assay and also enables vascular and tumor cell coculture. Through simple labeling (DAPI, Hoechst 33258), cell location and resulting prevascular network formation can easily be quantified. Cell transfection with green fluorescent protein improved whole cell visualization and 3D structure characterization. Finally, egg-based assay dedicated to angiogenesis studies represents a reliable and cost-effective way to produce and analyze data regarding drug effects on vascular cells.

In vitro and in vivo evaluation of lipofufol, a new triple stealth liposomal formulation of modulated 5-fu: impact on efficacy and toxicity.

PURPOSE: Drug resistance and severe toxicities are limitations when handling 5-FU. We have developed a triple liposomal formulation of 5-FU combined to 2'-deoxyinosine and folinic acid to improve its efficacy-toxicity balance. METHODS: Stealth liposomes were obtained using the thin-film method. Antiproliferative activity was tested on human colorectal and breast cancer models using sensitive (HT29) and resistant (SW620, LS174t, MDA231) cell lines. In vivo, pharmacokinetics, biodistribution and safety studies were performed in rodents. Finally, efficacy was evaluated using two tumor-bearing mice models (LS174 and MDA231) with response and survival as main endpoints. RESULTS: LipoFufol is a 120-nm pegylated liposome, displaying 20-30% encapsulation rates. In vitro, antiproliferative activities were higher than 5-FU, and matched that of FolFox combination in colorectal models, but not in breast. Drug monitoring showed an optimized pharmacokinetics profile with reduced clearance and prolonged half-life. Liposome accumulation in tumors was shown by fluorescence-based biodistribution studies. Beside, milder neutropenia was observed when giving LipoFufol to animals with transient partial DPD-deficiency, as compared with standard 5-FU. In LS174t-bearing mice, higher response and 55% longer survival were achieved with Lipofufol, as compared with 5-FU. CONCLUSION: The issues of drug-resistance and drug-related toxicity can be both addressed using a stealth liposomal formulation of modulated 5-FU.

Fingolimod inhibits PDGF-B-induced migration of vascular smooth muscle cell by down-regulating the S1PR1/S1PR3 pathway.

Platelet Derived Growth Factor (PDGF) and sphingosine-1-phosphate (S1P) pathways play a key role in mural cell recruitment during tumor growth and angiogenesis. Fingolimod, a S1P analogue, has been shown to exert antitumor and antiangiogenic properties. However, molecular targets and modes of action of fingolimod remain unclear. In this study, we confirmed the antagonizing action of S1P and PDGF-B on rat vascular smooth muscle cell (VSMCs) growth and migration. We then compared siRNA and/or fingolimod (100 nM) treatments on PDGFR-ß, S1PR1 S1PR2 and S1PR3 expression. Fingolimod induced a 50% reduction in S1PR3 protein expression which was cumulative with that obtained with anti-S1PR3 siRNA. We found that siRNA-induced inhibition of both PDGFR-ß and S1PR3 was the most effective means to block VSMC migration induced by PDGF-B. Finally, we observed that fingolimod treatment associated with anti-S1PR1 siRNA principally inhibited VSMC growth while in combination with anti-S1PR3 siRNA it strongly inhibited VSMC migration. These results suggest that for rat VSMCs, the PDGFR-S1PR1 pathway is predominantly dedicated to cell growth while PDGFR-S1PR3 stimulates cell migration. As an S1P analogue, fingolimod is considered a potent activator of S1PR1 and S1PR3. However, its action on the PDGFR-S1PR platform appears to be dependent on S1PR1 and S1PR3 specific downregulation. Considering that the S1P pathway has already been shown to exert various crosstalks with tyrosine kinase pathways, it seems of great interest to evaluate fingolimod potential in combination with the numerous tyrosine kinase inhibitors used in oncology.

Fingolimod potentiates the effects of sunitinib malate in a rat breast cancer model.

Most of the antiangiogenic strategies used in oncology principally target endothelial cells through the vascular endothelial growth factor (VEGF) pathway. Multiple kinase inhibitors can secondarily reduce mural cell stabilization of the vessels by blocking platelet-derived growth factor receptor (PDGFR) activity. However, sphingosine-1-phosphate (S1P), which is also implicated in mural cell recruitment, has yet to be targeted in clinical practice. We therefore investigated the potential of a simultaneous blockade of the PDGF and S1P pathways on the chemotactic responses of vascular smooth muscle cells (VSMCs) and the resulting effects of this blockade on breast tumor growth. Due to crosstalk between the S1P and PDGF pathways, we used AG1296 and/or VPC-23019 to inhibit PDGFR-ß and S1PR1/S1PR3 receptors, respectively. We showed that S1PR1 and S1PR3 are the principal receptors that mediate the S1P chemotactic signal on rat VSMCs and that they act synergistically with PDGFR-ß during PDGF-B signaling. We also showed that simultaneous blockade of the PDGFR-ß and S1PR1/S1PR3 signals had a synergistic effect, decreasing VSMC migration velocity toward endothelial cell and breast carcinoma cell-secreted cytokines by 65-90%. This blockade also strongly decreased the ability of VSMCs to form a three-dimensional cell network. Similar results were obtained with the combination of sunitinib malate (a VEGFR/PDGFR kinase inhibitor) and fingolimod (an S1P analog). Sunitinib malate is a clinically approved cancer treatment, whereas fingolimod is currently indicated only for treatment of multiple sclerosis. Orally administered, the combination of these drugs greatly decreased rat breast tumor growth in a syngeneic cancer model (Walker 256). This bi-therapy did not exert cumulative toxicity and histological analysis of the tumors revealed normalization of the tumor vasculature. The simultaneous blockade of these signaling pathways with sunitinib malate and fingolimod may provide an effective means of reducing tumor angiogenesis, and may improve the delivery of other chemotherapies.

How can grafted breast cancer models be optimized?

Breast cancer is the most frequent spontaneous malignancy diagnosed in women and is characterized by a broad histological diversity. Progression of the disease has a metastasizing trend and can be resistant to hormonal and chemotherapy. Animal models have provided some understanding of these features and have allowed new treatments to be proposed. However, these models need to be revised because they have some limitations in predicting the clinical efficacy of new therapies. In this review, we discuss the biological criteria to be taken into account for a realistic animal model of breast cancer graft (tumor implantation site, animal immune status, histological diversity, modern imaging). We emphasize the need for more stringent monitoring criteria, and suggest adopting the human RECIST (Response Evaluation Criteria in Solid Tumors) criteria to evaluate treatments in animal models.

Amine-guanidine switch: a promising approach to improve DNA binding and antiproliferative activities.

A series of polyaromatic guanidino derivatives was synthesized and evaluated for growth inhibitory properties in several human carcinoma cell lines. The properties of these guanidino compounds were compared to those of their corresponding synthetic amino precursors. The size of the polyaromatic ring system as well as the length of the tether attached to the ring had a direct impact on the observed antiproliferative profiles, compound 14 having the broadest spectrum of activity. As both series intercalate DNA, guanidine derivatives showed a remarkable affinity for DNA and the guanidinium group appeared to be essential, yet not sufficient for caspase-3/7 activation. Compound 14 also showed significant in vivo activity against breast cancer cell xenografts in NOG/SCID mice. These results suggest that the electronic nature of chain tethering an intercalator not only influences the DNA-binding process but also controls the antitumoral activity of the whole compound.