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Antiangiogenic Drugs (antiangiogenic + drug)

Distribution by Scientific Domains

Medical Sciences	40%

Selected Abstracts

Antiangiogenic drugs: Current knowledge and new approaches to cancer therapy

JOURNAL OF PHARMACEUTICAL SCIENCES, Issue 10 2008
Jose L. Mauriz
Abstract Angiogenesis,process of new blood-vessel growth from existing vasculature,is an integral part of both normal developmental processes and numerous pathologies such as cancer, ischemic diseases and chronic inflammation. Angiogenesis plays a crucial role facilitating tumour growth and the metastatic process, and it is the result of a dynamic balance between proangiogenic and antiangiogenic factors. The potential to block tumour growth and metastases by angiogenesis inhibition represents an intriguing approach to the cancer treatment. Angiogenesis continues to be a topic of major scientific interest; and there are currently more antiangiogenic drugs in cancer clinical trials than those that fit into any other mechanistic category. Based on preclinical studies, researchers believe that targeting the blood vessels which support tumour growth could help treatment of a broad range of cancers. Angiogenic factors or their receptors, endothelial cell proliferation, matrix metalloproteinases or endothelial cell adhesion, are the main targets of an increasing number of clinical trials approved to test the tolerance and therapeutic efficacy of antiangiogenic agents. Unfortunately, contrary to initial expectations, it has been described that antiangiogenic treatment can cause different toxicities in cancer patients. The purpose of this article is to provide an overview of current attempts to inhibit tumour angiogenesis for cancer therapy. © 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 97:4129,4154, 2008 [source]

Combination of thalidomide and cisplatin in an head and neck squamous cell carcinomas model results in an enhanced antiangiogenic activity in vitro and in vivo

INTERNATIONAL JOURNAL OF CANCER, Issue 8 2007
Gergely P. Vasvari
Abstract Thalidomide is an immunomodulatory, antiangiogenic drug. Although there is evidence that it might be more effective in combination with chemotherapy the exact mechanism of action is unclear. Therefore, we investigated its effect in combination with metronomically applied cisplatin in a xenotransplant mouse model characteristic for advanced head and neck squamous cell carcinomas, its possible synergistic action in vitro, and which tumor-derived factors might be targeted by thalidomide. Although thalidomide alone was ineffective, a combined treatment with low-dose cisplatin inhibited significant tumor growth, proliferation and angiogenesis in vivo as well as migration and tube formation of endothelial cells in vitro. Noteworthy, the latter effect was enhanced after coapplication of cisplatin in nontoxic doses. An inhibitory effect on tumor cell migration was also observed suggesting a direct antitumor effect. Although thalidomide alone did not influence cell proliferation, it augmented antiproliferative response after cisplatin application emphasizing the idea of a potentiated effect when both drugs are combined. Furthermore, we could show that antiangiogenic effects of thalidomide are related to tumor-cell derived factors including vascular endothelial growth factor, basic fibroblast growth factor, hepatocyte growth factor and Il-8 some known and with, granulocyte colony stimulating growth factor and granulocyte macrophage colony stimulating growth factor, some new target molecules of thalidomide. Altogether, our findings reveal new insights into thalidomide-mediated antitumor and antiangiogenic effects and its interaction with cytostatic drugs. © 2007 Wiley-Liss, Inc. [source]

Antiangiogenic drugs: Current knowledge and new approaches to cancer therapy

Hemostatic complications of angiogenesis inhibitors in cancer patients,

AMERICAN JOURNAL OF HEMATOLOGY, Issue 11 2008
Francesca Elice
Tumor vasculature and tumor-associated neo-angiogenesis have recently become major targets for rational drug design of antineoplastic agents. Five such agents with angiogenesis inhibiting activity (thalidomide, lenalidomide, bevacizumab, sunitinib, sorafenib) have already obtained US Food and Drug Administration approval for clinical use and many others have entered clinical trials. Vascular complications, including venous or arterial thromboembolism and hemorrhage, have emerged as relevant toxicities in several clinical trials with angiogenesis inhibitors. Given the well-known interplay between the blood clotting system, angiogenesis, and tumor growth, a better understanding of the impact of these new drugs on overall hemostatic balance is required. In this brief overview, we discuss the incidence of hemostatic complications, the likely pathogenetic mechanisms involved, and the critical need to establish in randomized clinical trials the usefulness of thrombosis prophylaxis to prevent these complications. Careful documentation of hemostatic complications during treatment with each of the new antiangiogenic drugs is warranted. Further studies are urgently required to better define the causal association of these new agents with hemostatic complications and to establish the best prophylactic strategy. Am. J. Hematol., 2008. © 2008 Wiley-Liss, Inc. [source]

Parameter Estimation in a Gompertzian Stochastic Model for Tumor Growth

BIOMETRICS, Issue 4 2000
L. Ferrante
Summary. The problem of estimating parameters in the drift coefficient when a diffusion process is observed continuously requires some specific assumptions. In this paper, we consider a stochastic version of the Gompertzian model that describes in vivo tumor growth and its sensitivity to treatment with antiangiogenic drugs. An explicit likelihood function is obtained, and we discuss some properties of the maximum likelihood estimator for the intrinsic growth rate of the stochastic Gompertzian model. Furthermore, we show some simulation results on the behavior of the corresponding discrete estimator. Finally, an application is given to illustrate the estimate of the model parameters using real data. [source]