Literature DB >> 10713698

Genetic determinants of response to chemotherapy in transgenic mouse mammary and salivary tumors.

D J Bearss1, M A Subler, J E Hundley, D A Troyer, R A Salinas, J J Windle.   

Abstract

Several transgenic mouse tumor models were utilized to explore how specific genetic alterations affect the tumor cell response to chemotherapeutic agents in vivo. Specifically, MMTV-ras transgenic mice were interbred to p53 knock-out mice to create a model for assessing the role of p53 in chemotherapeutic responses. In addition, MMTV-ras tumors were compared to MMTV-myc and MMTV-ras/myc tumors. Mice of each genotype reproducibly develop mammary and/or salivary tumors, but tumor growth dynamics vary considerably between genotypes. MMTV-ras/p53-/- tumors exhibit higher S phase fractions than MMTV-ras/p53+/+ tumors, although both tumor types display very low apoptosis levels. In contrast, MMTV-myc tumors exhibit both high S phase fractions and spontaneous apoptosis levels. Tumor-bearing mice of each genotype were treated with either doxorubicin or paclitaxel, and effects on overall tumor growth, cell cycle distribution and apoptosis were evaluated. Surprisingly, neither agent efficiently induced apoptosis in any of the tumor models, including those with wildtype p53. Rather, tumor responses were mediated primarily by changes in cell cycle distribution. However, the spontaneous apoptosis levels did serve as a predictor of tumor growth response, in that only those tumors with high pretreatment apoptosis levels underwent significant regression following treatment with either agent.

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Year:  2000        PMID: 10713698     DOI: 10.1038/sj.onc.1203275

Source DB:  PubMed          Journal:  Oncogene        ISSN: 0950-9232            Impact factor:   9.867


  16 in total

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Authors:  Xi-Shan Wang; Kuan Wang; Xue Li; Song-Bin Fu
Journal:  World J Gastroenterol       Date:  2004-12-01       Impact factor: 5.742

Review 2.  Murine models to evaluate novel and conventional therapeutic strategies for cancer.

Authors:  James E Talmadge; Rakesh K Singh; Isaiah J Fidler; Avraham Raz
Journal:  Am J Pathol       Date:  2007-03       Impact factor: 4.307

3.  A bioinformatics-based strategy identifies c-Myc and Cdc25A as candidates for the Apmt mammary tumor latency modifiers.

Authors:  Diana Cozma; Luanne Lukes; Jessica Rouse; Ting Hu Qiu; Edison T Liu; Kent W Hunter
Journal:  Genome Res       Date:  2002-06       Impact factor: 9.043

4.  p53-mediated senescence impairs the apoptotic response to chemotherapy and clinical outcome in breast cancer.

Authors:  James G Jackson; Vinod Pant; Qin Li; Leslie L Chang; Alfonso Quintás-Cardama; Daniel Garza; Omid Tavana; Peirong Yang; Taghi Manshouri; Yi Li; Adel K El-Naggar; Guillermina Lozano
Journal:  Cancer Cell       Date:  2012-06-12       Impact factor: 31.743

5.  Therapeutic efficacy of p53 restoration in Mdm2-overexpressing tumors.

Authors:  Qin Li; Yun Zhang; Adel K El-Naggar; Shunbin Xiong; Peirong Yang; James G Jackson; Gilda Chau; Guillermina Lozano
Journal:  Mol Cancer Res       Date:  2014-03-05       Impact factor: 5.852

Review 6.  Animal models of breast cancer for the study of pathogenesis and therapeutic insights.

Authors:  Angels Sierra
Journal:  Clin Transl Oncol       Date:  2009-11       Impact factor: 3.405

Review 7.  A critical review of lipid-based nanoparticles for taxane delivery.

Authors:  Lan Feng; Russell J Mumper
Journal:  Cancer Lett       Date:  2012-07-13       Impact factor: 8.679

8.  Apoptosis and survival.

Authors:  Manjul Tiwari
Journal:  Indian J Hum Genet       Date:  2011-09

9.  Paclitaxel-induced apoptosis is BAK-dependent, but BAX and BIM-independent in breast tumor.

Authors:  Anna V Miller; Mark A Hicks; Wataru Nakajima; Amanda C Richardson; Jolene J Windle; Hisashi Harada
Journal:  PLoS One       Date:  2013-04-05       Impact factor: 3.240

Review 10.  Knockout and transgenic mice of Trp53: what have we learned about p53 in breast cancer?

Authors:  Anneke C Blackburn; D Joseph Jerry
Journal:  Breast Cancer Res       Date:  2002-04-18       Impact factor: 6.466

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