Literature DB >> 15185337

Polygenic control of hepatocarcinogenesis in Copenhagen x F344 rats.

Maria R De Miglio1, Rosa M Pascale, Maria M Simile, Maria R Muroni, Patrizia Virdis, Kelvin M-T Kwong, Leslie K L Wong, Giovanni M Bosinco, Franca R Pulina, Diego F Calvisi, Maddalena Frau, Geoffrey A Wood, Michael C Archer, Francesco Feo.   

Abstract

Cop and CFF1 rats exhibit resistance to hepatocarcinogenesis, associated with high rates of remodeling of neoplastic lesions. We have mapped hepatocarcinogenesis susceptibility, resistance and remodeling loci affecting the number, volume and volume fraction of neoplastic nodules induced by the "resistant hepatocyte" model in male CFF2 rats. Three loci in significant linkage with the number or volume of nonremodeling lesions were identified on chromosomes 1, 4 and 18. Suggestive linkage with number or volume fraction of total, nonremodeling or remodeling lesions was found for 7 loci on chromosomes 1, 2, 13, 14 and 15. All of these loci showed significant allele-specific effects on the phenotypic traits. We also detected by analysis of variance 19 2-way interactions inducing phenotypic effects not predictable on the basis of the sum of separate effects. These novel epistatic loci were in significant linkage with the number and/or volume of total, nonremodeling or remodeling nodules. These data indicate that susceptibility to hepatocarcinogenesis in Cop rats is controlled by a complex array of genes with several gene-gene interactions and that different genetic mechanisms control remodeling and nonremodeling liver nodules. Frequent deregulation in human liver cancer of genes positioned in chromosomal segments syntenic to rat susceptibility/resistance loci suggests some similarities between the genetic mechanisms involved in hepatocarcinogenesis in rats and humans. Copyright 2004 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2004        PMID: 15185337     DOI: 10.1002/ijc.20225

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  8 in total

1.  An ensemble learning approach jointly modeling main and interaction effects in genetic association studies.

Authors:  Zhaogong Zhang; Shuanglin Zhang; Man-Yu Wong; Nicholas J Wareham; Qiuying Sha
Journal:  Genet Epidemiol       Date:  2008-05       Impact factor: 2.135

Review 2.  Metabolic genes in cancer: their roles in tumor progression and clinical implications.

Authors:  Eiji Furuta; Hiroshi Okuda; Aya Kobayashi; Kounosuke Watabe
Journal:  Biochim Biophys Acta       Date:  2010-02-01

3.  Powerful tests for detecting a gene effect in the presence of possible gene-gene interactions using garrote kernel machines.

Authors:  Arnab Maity; Xihong Lin
Journal:  Biometrics       Date:  2011-04-19       Impact factor: 2.571

4.  A testing framework for identifying susceptibility genes in the presence of epistasis.

Authors:  Joshua Millstein; David V Conti; Frank D Gilliland; W James Gauderman
Journal:  Am J Hum Genet       Date:  2005-11-11       Impact factor: 11.025

5.  Interaction of major genes predisposing to hepatocellular carcinoma with genes encoding signal transduction pathways influences tumor phenotype and prognosis.

Authors:  Francesco Feo; Maddalena Frau; Rosa-Maria Pascale
Journal:  World J Gastroenterol       Date:  2008-11-21       Impact factor: 5.742

6.  Two-stage two-locus models in genome-wide association.

Authors:  David M Evans; Jonathan Marchini; Andrew P Morris; Lon R Cardon
Journal:  PLoS Genet       Date:  2006-09-22       Impact factor: 5.917

Review 7.  Experimental Models to Define the Genetic Predisposition to Liver Cancer.

Authors:  Rosa M Pascale; Maria M Simile; Graziella Peitta; Maria A Seddaiu; Francesco Feo; Diego F Calvisi
Journal:  Cancers (Basel)       Date:  2019-09-27       Impact factor: 6.639

8.  Genome-wide association reveals three SNPs associated with sporadic amyotrophic lateral sclerosis through a two-locus analysis.

Authors:  Qiuying Sha; Zhaogong Zhang; Jennifer C Schymick; Bryan J Traynor; Shuanglin Zhang
Journal:  BMC Med Genet       Date:  2009-09-09       Impact factor: 2.103

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.