Ovarian cancer evolution through stochastic genome alterations: defining the genomic role in ovarian cancer. (February 2014)

• Record Type: Journal Article
• Authors: Abdallah, Batoul Y.; Horne, Steven D.; Kurkinen, Markku; Stevens, Joshua B.; Liu, Guo; Ye, Christine J.; Barbat, Justin; Bremer, Steven W.; Heng, Henry H.Q.
• Is Part Of: Systems biology in reproductive medicine. Volume 60:Number 1(2014:Feb.)
• Page Start: 2
• Page End: 13
• Publication Date: 2014-02
• Subjects: Systems biology -- Periodicals; Andrology -- Periodicals; Generative organs, Male -- Diseases -- Periodicals; Biological systems -- Periodicals; Reproductive health -- Periodicals; Human reproduction -- Periodicals; 612.61
• DOI: 10.3109/19396368.2013.837989
• Languages: English
• ISSNs: 1939-6368

Abstract

<abstract> <title>Abstract</title> <p>Ovarian cancer is the fifth leading cause of death among women worldwide. Characterized by complex etiology and multi-level heterogeneity, its origins are not well understood. Intense research efforts over the last decade have furthered our knowledge by identifying multiple risk factors that are associated with the disease. However, it is still unclear how genetic heterogeneity contributes to tumor formation, and more specifically, how genome-level heterogeneity acts as the key driving force of cancer evolution. Most current genomic approaches are based on 'average molecular profiling.' While effective for data generation, they often fail to effectively address the issue of high level heterogeneity because they mask variation that exists in a cell population. In this synthesis, we hypothesize that genome-mediated cancer evolution can effectively explain diverse factors that contribute to ovarian cancer. In particular, the key contribution of genome replacement can be observed during major transitions of ovarian cancer evolution including cellular immortalization, transformation, and malignancy. First, we briefly review major updates in the literature, and illustrate how current gene-mediated research will offer limited insight into cellular heterogeneity and ovarian cancer evolution. We next explain a holistic framework for genome-based ovarian cancer evolution and apply it to understand the genomic dynamics of a syngeneic ovarian cancer mouse model. Finally, we employ single cell assays to further test our hypothesis, discuss some predictions, and report some recent findings.</p> </abstract>