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Tumor Angiogenesis Assays

Overview of attention for book
Attention for Chapter 13: Orthotopic Model of Ovarian Cancer
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Chapter title
Orthotopic Model of Ovarian Cancer
Chapter number 13
Book title
Tumor Angiogenesis Assays
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3999-2_13
Pubmed ID
Book ISBNs
978-1-4939-3997-8, 978-1-4939-3999-2
Authors

Alessandra Decio, Raffaella Giavazzi

Abstract

Epithelial ovarian cancer (EOC) is the fifth commonest cancer-related cause of female death in the developed world. In spite of current surgical and chemotherapeutic options the vast majority of patients have widely metastatic disease and the survival rate has not much changed over the last years. The anti-angiogenic drugs are driving the field of agents targeting the tumor microenvironment in ovarian cancer. Preclinical models that accurately reproduce the molecular and biological features of ovarian cancer patients are a valuable means of producing reliable data on personalized medicine and predicting the therapeutic response in clinical trials.In this methodological chapter we describe the orthotopic model of ovarian cancer implanted under the ovarian bursa of mice. In spite of anatomical differences between the rodent and human bursa-fallopian tube, the appropriate primary tumor microenvironment at the site of the implant allows investigation of tumor-stroma interactions (e.g., angiogenesis), and is well suited for studying the tumor dissemination and metastasis typical of this disease.This model-although fairly labor intensive-may be useful for assessing novel, more selective therapeutic interventions and for biomarker discovery, reflecting the behavior of this disease.

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Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 17%
Student > Ph. D. Student 2 17%
Researcher 2 17%
Student > Doctoral Student 1 8%
Professor > Associate Professor 1 8%
Other 0 0%
Unknown 4 33%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Biochemistry, Genetics and Molecular Biology 1 8%
Immunology and Microbiology 1 8%
Social Sciences 1 8%
Medicine and Dentistry 1 8%
Other 0 0%
Unknown 7 58%