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Torres-Arzayus, Maria I

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Torres-Arzayus

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Maria I

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Torres-Arzayus, Maria I

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20132

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Author's Publications: search.filters.isAuthorOfPublication.00b9dd45-49cf-4b2b-8a4a-3836a1246f12

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    Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts
    (BioMed Central, 2013) Pfefferle, Adam D; Herschkowitz, Jason I; Usary, Jerry; Harrell, Joshua Chuck; Spike, Benjamin T; Adams, Jessica R; Torres-Arzayus, Maria I; Brown, Myles; Egan, Sean E; Wahl, Geoffrey M; Rosen, Jeffrey M; Perou, Charles M
    Background: Human breast cancer is a heterogeneous disease consisting of multiple molecular subtypes. Genetically engineered mouse models are a useful resource for studying mammary cancers in vivo under genetically controlled and immune competent conditions. Identifying murine models with conserved human tumor features will facilitate etiology determinations, highlight the effects of mutations on pathway activation, and should improve preclinical drug testing. Results: Transcriptomic profiles of 27 murine models of mammary carcinoma and normal mammary tissue were determined using gene expression microarrays. Hierarchical clustering analysis identified 17 distinct murine subtypes. Cross-species analyses using three independent human breast cancer datasets identified eight murine classes that resemble specific human breast cancer subtypes. Multiple models were associated with human basal-like tumors including TgC3(1)-Tag, TgWAP-Myc and Trp53-/-. Interestingly, the TgWAPCre-Etv6 model mimicked the HER2-enriched subtype, a group of human tumors without a murine counterpart in previous comparative studies. Gene signature analysis identified hundreds of commonly expressed pathway signatures between linked mouse and human subtypes, highlighting potentially common genetic drivers of tumorigenesis. Conclusions: This study of murine models of breast carcinoma encompasses the largest comprehensive genomic dataset to date to identify human-to-mouse disease subtype counterparts. Our approach illustrates the value of comparisons between species to identify murine models that faithfully mimic the human condition and indicates that multiple genetically engineered mouse models are needed to represent the diversity of human breast cancers. The reported trans-species associations should guide model selection during preclinical study design to ensure appropriate representatives of human disease subtypes are used.
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    Ret inhibition decreases growth and metastatic potential of estrogen receptor positive breast cancer cells
    (Blackwell Publishing Ltd, 2013) Gattelli, Albana; Nalvarte, Ivan; Boulay, Anne; Roloff, Tim C; Schreiber, Martin; Carragher, Neil; Macleod, Kenneth K; Schlederer, Michaela; Lienhard, Susanne; Kenner, Lukas; Torres-Arzayus, Maria I; Hynes, Nancy E
    We show that elevated levels of Ret receptor are found in different sub-types of human breast cancers and that high Ret correlates with decreased metastasis-free survival. The role of Ret in ER+ breast cancer models was explored combining in vitro and in vivo approaches. Our analyses revealed that ligand-induced Ret activation: (i) stimulates migration of breast cancer cells; (ii) rescues cells from anti-proliferative effects of endocrine treatment and (iii) stimulates expression of cytokines in the presence of endocrine agents. Indeed, we uncovered a positive feed-forward loop between the inflammatory cytokine IL6 and Ret that links them at the expression and the functional level. In vivo inhibition of Ret in a metastatic breast cancer model inhibits tumour outgrowth and metastatic potential. Ret inhibition blocks the feed-forward loop by down-regulating Ret levels, as well as decreasing activity of Fak, an integrator of IL6-Ret signalling. Our results suggest that Ret kinase should be considered as a novel therapeutic target in subsets of breast cancer.