High tumor incidence and activation of the PI3K/AKT pathway in transgenic mice define AIB1 as an oncogene

AbstractThe gene encoding AIB1, an estrogen receptor coactivator, is amplified in a subset of human breast cancers. Here we show that overexpression of AIB1 in transgenic mice (AIB1-tg) leads to mammary hypertrophy, hyperplasia, abnormal postweaning involution, and the development of malignant mammary tumors. Tumors are also increased in other organs, including the pituitary and uterus. AIB1 overexpression increases mammary IGF-I mRNA and serum IGF-I protein levels. In addition, IGF-I receptor and downstream signaling molecules are activated in primary mammary epithelial cells and mammary tumor cells derived from AIB1-tg mice. Knockdown of AIB1 expression in cultured AIB1-tg mammary tumor cells leads to reduced IGF-I mRNA levels and increased apoptosis, suggesting that an autocrine IGF-I loop underlies the mechanism of AIB1-induced oncogenesis

Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts

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

Ret inhibition decreases growth and metastatic potential of estrogen receptor positive breast cancer cells

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

A cell-type-specific transcriptional network required for estrogen regulation of cyclin D1 and cell cycle progression in breast cancer

Estrogen stimulates the proliferation of the most common type of human breast cancer that expresses estrogen receptor α (ERα) through the activation of the cyclin D1 (CCND1) oncogene. However, our knowledge of ERα transcriptional mechanisms remains limited. Hence, it is still elusive why ERα ectopically expressed in ER-negative breast cancer cells (BCC) is functional on ectopic reporter constructs but lacks activity on many endogenous target genes, including CCND1. Here, we show that estradiol (E2) stimulation of CCND1 expression in BCC depends on a novel cell-type-specific enhancer downstream from the CCND1 coding region, which is the primary ERα recruitment site in estrogen-responsive cells. The pioneer factor FoxA1 is specifically required for the active chromatin state of this enhancer and as such is crucial for both CCND1 expression and subsequent cell cycle progression. Interestingly, even in BCC, CCND1 levels and proliferation are tightly controlled by E2 through the establishment of a negative feedforward loop involving the induction of NFIC, a putative tumor suppressor capable of directly repressing CCND1 transcription. Taken together, our results reveal an estrogen-regulated combinatorial network including cell-specific cis- and trans-regulators of CCND1 expression where ERα collaborates with other transcription factors associated with the ER-positive breast cancer phenotype, including FoxA1 and NFIC

High tumor incidence and activation of the PI3K/AKT pathway in transgenic mice define AIB1 as an oncogene

The gene encoding AIB1, an estrogen receptor coactivator, is amplified in a subset of human breast cancers. Here we show that overexpression of AIB1 in transgenic mice (AIB1-tg) leads to mammary hypertrophy, hyperplasia, abnormal postweaning involution, and the development of malignant mammary tumors. Tumors are also increased in other organs, including the pituitary and uterus. AIB1 overexpression increases mammary IGF-I mRNA and serum IGF-I protein levels. In addition, IGF-I receptor and downstream signaling molecules are activated in primary mammary epithelial cells and mammary tumor cells derived from AIB1-tg mice. Knockdown of AIB1 expression in cultured AIB1-tg mammary tumor cells leads to reduced IGF-I mRNA levels and increased apoptosis, suggesting that an autocrine IGF-I loop underlies the mechanism of AIB1-induced oncogenesis

Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts

Abstract 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