Literature DB >> 27613130

Defining the Influence of Germline Variation on Metastasis Using Systems Genetics Approaches.

M Lee1, N P S Crawford2.   

Abstract

Cancer is estimated to be responsible for 8 million deaths worldwide and over half a million deaths every year in the United States. The majority of cancer-related deaths in solid tumors is directly associated with the effects of metastasis. While the influence of germline factors on cancer risk and development has long been recognized, the contribution of hereditary variation to tumor progression and metastasis has only gained acceptance more recently. A variety of approaches have been used to define how hereditary variation influences tumor progression and metastasis. One approach that garnered much early attention was epidemiological studies of cohorts of cancer patients, which demonstrated that specific loci within the human genome are associated with a differential propensity for aggressive tumor development. However, a powerful, and somewhat underutilized approach has been the use of systems genetics approaches in transgenic mouse models of human cancer. Such approaches are typically multifaceted, and involve integration of multiple lines of evidence derived, for example, from genetic and transcriptomic screens of genetically diverse mouse models of cancer, coupled with bioinformatics analysis of human cancer datasets, and functional analysis of candidate genes. These methodologies have allowed for the identification of multiple hereditary metastasis susceptibility genes, with wide-ranging cellular functions including regulation of gene transcription, cell proliferation, and cell-cell adhesion. In this chapter, we review how each of these approaches have facilitated the identification of these hereditary metastasis modifiers, the molecular functions of these metastasis-associated genes, and the implications of these findings upon patient survival. 2016 Published by Elsevier Inc.

Entities:  

Keywords:  Germline polymorphism; Metastasis; Mouse model; Susceptibility loci; Systems genetics

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Year:  2016        PMID: 27613130     DOI: 10.1016/bs.acr.2016.07.003

Source DB:  PubMed          Journal:  Adv Cancer Res        ISSN: 0065-230X            Impact factor:   6.242


  2 in total

1.  Discovering Innate Driver Variants for Risk Assessment of Early Colorectal Cancer Metastasis.

Authors:  Ruo-Fan Ding; Yun Zhang; Lv-Ying Wu; Pan You; Zan-Xi Fang; Zhi-Yuan Li; Zhong-Ying Zhang; Zhi-Liang Ji
Journal:  Front Oncol       Date:  2022-06-20       Impact factor: 5.738

2.  Modifier locus mapping of a transgenic F2 mouse population identifies CCDC115 as a novel aggressive prostate cancer modifier gene in humans.

Authors:  Jean M Winter; Natasha L Curry; Derek M Gildea; Kendra A Williams; Minnkyong Lee; Ying Hu; Nigel P S Crawford
Journal:  BMC Genomics       Date:  2018-06-11       Impact factor: 3.969

  2 in total

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