Literature DB >> 21331759

Studying therapy response and resistance in mouse models for BRCA1-deficient breast cancer.

Ewa Malgorzata Michalak1, Jos Jonkers.   

Abstract

Worldwide, more than one million women are diagnosed with breast cancer every year, making it the most common malignancy of females in the developed world. Germline mutations in the breast cancer susceptibility genes BRCA1 and BRCA2 account for 4-6% of all breast cancer cases, and mutation carriers have a lifetime risk of 80% for developing breast cancer and 40% for developing ovarian cancer. Current treatment options are limited and often do not lead to cure. In the 17 years since the discovery of BRCA1, the generation of mouse models for BRCA1 deficiency has greatly aided our understanding of it's role in tumorigenesis. In contrast to human BRCA1 mutation carriers, mice carrying heterozygous mutations in Brca1 did not develop spontaneous tumors. This led to the generation of conditional mouse models in which tissue-specific Brca1 deletion induces formation of mammary tumors that closely resemble human BRCA1-mutated breast tumors. These models have proven useful for studying BRCA1-related tumor development, drug response and resistance. BRCA1-deficient cancer cells are defective in DNA repair mediated by homologous recombination (HR) and therefore highly sensitive to DNA-damaging agents such as platinum drugs and poly(ADP-ribose) polymerase (PARP) inhibitors. However, BRCA1-mutated tumors can develop resistance to these drugs; hence improved treatment strategies are critical. Existing mouse models have already proven useful for preclinical testing of (combinations of) therapeutic agents that may be beneficial for the treatment of patients with BRCA1-mutated tumors. In this review, we discuss the progress made towards modeling BRCA1-deficient breast cancer in mice and what we have learned from preclinical studies using these models.

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Year:  2011        PMID: 21331759     DOI: 10.1007/s10911-011-9199-z

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


  93 in total

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Authors:  Ursula Kortmann; Jessica N McAlpine; Hui Xue; Jun Guan; Gavin Ha; Sophie Tully; Sharaz Shafait; Alan Lau; Aaron N Cranston; Mark J O'Connor; David G Huntsman; Yuzhuo Wang; C Blake Gilks
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  12 in total

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2.  Impact of intertumoral heterogeneity on predicting chemotherapy response of BRCA1-deficient mammary tumors.

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Journal:  Cancer Res       Date:  2012-03-06       Impact factor: 12.701

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4.  Evaluation of candidate biomarkers to predict cancer cell sensitivity or resistance to PARP-1 inhibitor treatment.

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5.  Noise-induced bistability in the fate of cancer phenotypic quasispecies: a bit-strings approach.

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Review 9.  The unpluggable in pursuit of the undruggable: tackling the dark matter of the cancer therapeutics universe.

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Journal:  Breast Cancer Res       Date:  2013-10-01       Impact factor: 6.466

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