Literature DB >> 31227983

How to Choose a Mouse Model of Breast Cancer, a Genomic Perspective.

Matthew R Swiatnicki1, Eran R Andrechek2.   

Abstract

Human breast cancer is a heterogeneous disease with numerous subtypes that have been defined through immunohistological, histological, and gene expression patterns. The diversity of breast cancer has made the study of its various underlying causes complex. To facilitate the examination of particular facets of breast cancer, mouse models have been generated, ranging from carcinogen induced models to genetically engineered mice. While mouse models have been generated to mimic the initiating event, including p53 loss, BRCA loss, or overexpression of HER2 / Neu / erbB2, other genomic events are often not well characterized. However, these secondary genetic events are often critical to the mouse tumor evolution, subtype, and outcome, just as they are in human breast cancer. As such, these other genomic events are a critical component of what models are chosen to study specific subtypes of human breast cancer. Here we review the genomic analyses that have been completed for various genetically engineered mouse models, how they compare to human breast cancer, and detail how this information can be used in choosing a mouse model for analysis.

Entities:  

Keywords:  Breast cancer; Genomics; Mouse models

Year:  2019        PMID: 31227983     DOI: 10.1007/s10911-019-09433-3

Source DB:  PubMed          Journal:  J Mammary Gland Biol Neoplasia        ISSN: 1083-3021            Impact factor:   2.673


  124 in total

1.  Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes.

Authors:  Yoko S DeRose; Guoying Wang; Yi-Chun Lin; Philip S Bernard; Saundra S Buys; Mark T W Ebbert; Rachel Factor; Cindy Matsen; Brett A Milash; Edward Nelson; Leigh Neumayer; R Lor Randall; Inge J Stijleman; Bryan E Welm; Alana L Welm
Journal:  Nat Med       Date:  2011-10-23       Impact factor: 53.440

2.  Concordance among gene-expression-based predictors for breast cancer.

Authors:  Cheng Fan; Daniel S Oh; Lodewyk Wessels; Britta Weigelt; Dimitry S A Nuyten; Andrew B Nobel; Laura J van't Veer; Charles M Perou
Journal:  N Engl J Med       Date:  2006-08-10       Impact factor: 91.245

3.  Genomic landscape of non-small cell lung cancer in smokers and never-smokers.

Authors:  Ramaswamy Govindan; Li Ding; Malachi Griffith; Janakiraman Subramanian; Nathan D Dees; Krishna L Kanchi; Christopher A Maher; Robert Fulton; Lucinda Fulton; John Wallis; Ken Chen; Jason Walker; Sandra McDonald; Ron Bose; David Ornitz; Donghai Xiong; Ming You; David J Dooling; Mark Watson; Elaine R Mardis; Richard K Wilson
Journal:  Cell       Date:  2012-09-14       Impact factor: 41.582

4.  Conditional mutation of Brca1 in mammary epithelial cells results in blunted ductal morphogenesis and tumour formation.

Authors:  X Xu; K U Wagner; D Larson; Z Weaver; C Li; T Ried; L Hennighausen; A Wynshaw-Boris; C X Deng
Journal:  Nat Genet       Date:  1999-05       Impact factor: 38.330

5.  The origins of breast cancer prognostic gene expression profiles.

Authors:  Luanne Lukes; Nigel P S Crawford; Renard Walker; Kent W Hunter
Journal:  Cancer Res       Date:  2009-01-01       Impact factor: 12.701

6.  Genetic heterogeneity of Myc-induced mammary tumors reflecting diverse phenotypes including metastatic potential.

Authors:  Eran R Andrechek; Robert D Cardiff; Jeffrey T Chang; Michael L Gatza; Chaitanya R Acharya; Anil Potti; Joseph R Nevins
Journal:  Proc Natl Acad Sci U S A       Date:  2009-09-04       Impact factor: 11.205

7.  Conditional activation of Pik3ca(H1047R) in a knock-in mouse model promotes mammary tumorigenesis and emergence of mutations.

Authors:  W Yuan; E Stawiski; V Janakiraman; E Chan; S Durinck; K A Edgar; N M Kljavin; C S Rivers; F Gnad; M Roose-Girma; P M Haverty; G Fedorowicz; S Heldens; R H Soriano; Z Zhang; J J Wallin; L Johnson; M Merchant; Z Modrusan; H M Stern; S Seshagiri
Journal:  Oncogene       Date:  2012-02-27       Impact factor: 9.867

8.  Identification of early molecular markers for breast cancer.

Authors:  Céline Kretschmer; Anja Sterner-Kock; Friederike Siedentopf; Winfried Schoenegg; Peter M Schlag; Wolfgang Kemmner
Journal:  Mol Cancer       Date:  2011-02-11       Impact factor: 27.401

9.  An intraductal human-in-mouse transplantation model mimics the subtypes of ductal carcinoma in situ.

Authors:  Fariba Behbod; Frances S Kittrell; Heather LaMarca; David Edwards; Sofia Kerbawy; Jessica C Heestand; Evelin Young; Purna Mukhopadhyay; Hung-Wen Yeh; D Craig Allred; Min Hu; Kornelia Polyak; Jeffrey M Rosen; Daniel Medina
Journal:  Breast Cancer Res       Date:  2009       Impact factor: 6.466

10.  HER2+ Cancer Cell Dependence on PI3K vs. MAPK Signaling Axes Is Determined by Expression of EGFR, ERBB3 and CDKN1B.

Authors:  Daniel C Kirouac; Jinyan Du; Johanna Lahdenranta; Matthew D Onsum; Ulrik B Nielsen; Birgit Schoeberl; Charlotte F McDonagh
Journal:  PLoS Comput Biol       Date:  2016-04-01       Impact factor: 4.475

View more
  4 in total

1.  Hippo-TAZ signaling is the master regulator of the onset of triple-negative basal-like breast cancers.

Authors:  Hirotoshi Soyama; Miki Nishio; Junji Otani; Toshiko Sakuma; Shintaro Takao; Shigeo Hara; Takaaki Masuda; Koshi Mimori; Shinya Toyokuni; John P Lydon; Kazuwa Nakao; Hiroshi Nishina; Takumi Fukumoto; Tomohiko Maehama; Akira Suzuki
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-11       Impact factor: 12.779

2.  Pathological and genetic aspects of spontaneous mammary gland tumor in Tupaia belangeri (tree shrew).

Authors:  Chi Hai-Ying; Yuki Tanaka; Tatsuro Hifumi; Koichiro Shoji; Mohammad Enamul Hoque Kayesh; Md Abul Hashem; Bouchra Kitab; Takahiro Sanada; Tomoko Fujiyuki; Misako Yoneda; Hitoshi Hatai; Akira Yabuki; Noriaki Miyoshi; Chieko Kai; Michinori Kohara; Kyoko Tsukiyama-Kohara
Journal:  PLoS One       Date:  2020-05-18       Impact factor: 3.240

3.  ppGalNAc-T4-catalyzed O-Glycosylation of TGF-β type Ⅱ receptor regulates breast cancer cells metastasis potential.

Authors:  Qiong Wu; Cheng Zhang; Keren Zhang; Qiushi Chen; Sijin Wu; Huang Huang; Tianmiao Huang; Nana Zhang; Xue Wang; Wenli Li; Yubo Liu; Jianing Zhang
Journal:  J Biol Chem       Date:  2020-12-03       Impact factor: 5.157

4.  Drug efficacy and toxicity prediction: an innovative application of transcriptomic data.

Authors:  Xuhua Xia
Journal:  Cell Biol Toxicol       Date:  2020-08-11       Impact factor: 6.691

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.