39 research outputs found
Breast Cancer Subtypes, Mouse Models, and Microarrays
Breast cancer can no longer be viewed as a single disease. Molecular profiling studies have altered the way we consider breast cancer, showing us that there are several subtypes, each with their own unique biology. There are many model systems available in which to study breast cancer, however, each of these comes with advantages and disadvantages. We chose the mouse as a model to investigate breast cancer biology because it gives us the ability to study tumor progression and response to therapy in vivo. Numerous mouse models of breast carcinomas have been developed. The extent to which any faithfully represent clinically significant human phenotypes was unknown. Analogous to our human studies, we characterized mammary tumor gene expression profiles from a large number of murine models using DNA microarrays and compared the resulting data to our human breast tumor dataset. Two major applications of across-species tumor comparisons surfaced from these studies. First, we were able to determine that mouse models contain many of the global characteristics of particular classes or subtypes of human tumors. This included basal versus luminal distinctions, a proliferation/cell cycle signature, and a fibroblast signature. Second, the mouse models were able to inform the human disease; for example, we identified an amplicon that included the K-ras gene present in both mouse and human basal tumors. The high proliferation seen in common between mouse models of Rb loss and human basal-like breast tumors hinted that there is an Rb defect in this human subtype. And finally the mouse spindloid tumors shared significant gene overlap with a new molecular subtype of breast cancer. Although no single murine model recapitulated all the expression features of a given human subtype, these shared expression features have provided us a common framework so that we can now integrate these murine mammary tumor models into our studies of human breast cancer
The functional loss of the retinoblastoma tumor suppressor is a common event in basal-like and Luminal B breast carcinomas
Abstract Introduction Breast cancers can be classified using whole genome expression into distinct subtypes that show differences in prognosis. One of these groups, the basal-like subtype, is poorly differentiated, highly metastatic, genomically unstable, and contains specific genetic alterations such as the loss of tumour protein 53 (TP53). The loss of the retinoblastoma tumour suppressor encoded by the RB1 locus is a well-characterised occurrence in many tumour types; however, its role in breast cancer is less clear with many reports demonstrating a loss of heterozygosity that does not correlate with a loss of RB1 protein expression. Methods We used gene expression analysis for tumour subtyping and polymorphic markers located at the RB1 locus to assess the frequency of loss of heterozygosity in 88 primary human breast carcinomas and their normal tissue genomic DNA samples. Results RB1 loss of heterozygosity was observed at an overall frequency of 39%, with a high frequency in basal-like (72%) and luminal B (62%) tumours. These tumours also concurrently showed low expression of RB1 mRNA. p16INK4a was highly expressed in basal-like tumours, presumably due to a previously reported feedback loop caused by RB1 loss. An RB1 loss of heterozygosity signature was developed and shown to be highly prognostic, and was potentially a predictive marker of response to neoadjuvant chemotherapy. Conclusions These results suggest that the functional loss of RB1 is common in basal-like tumours, which may play a key role in dictating their aggressive biology and unique therapeutic responses
Molecular analysis reveals heterogeneity of mouse mammary tumors conditionally mutant for Brca1
<p>Abstract</p> <p>Background</p> <p>Development of therapies for patients with BRCA1 mutations has been hampered by lack of readily available <it>in vitro </it>and <it>in vivo </it>models. We recently showed that transplantation of transgenic mammary tumors as cell suspensions into naïve recipients generates reproducible tumors with remarkable stability of gene expression profile. We examined the expression profiles of original and serially transplanted mammary tumors from <it>Brca1 </it>deficient mice, and tumor derived cell lines to validate their use for preclinical testing and studies of tumor biology.</p> <p>Methods</p> <p>Original tumors, serially transplanted and multiple cell lines derived from <it>Brca1 </it>mammary tumors were characterized by morphology, gene and protein expression, and cell surface markers.</p> <p>Results</p> <p>Gene expression among <it>Brca1 </it>tumors showed more heterogeneity than among previously characterized tumors from MMTV-<it>PyMT </it>and -<it>Wnt1 </it>models. Gene expression data segregated <it>Brca1 </it>tumors into 3 distinct types: basal, mixed luminal, and tumors with epithelial-to-mesenchymal transition (EMT). Serial transplantation of individual tumors and multiple cell lines derived from the original tumors recapitulated the molecular characteristics of each tumor of origin. One tumor had distinct features of EMT and gave rise to cell lines that contained a distinct CD44<sup>+</sup>/CD24<sup>-/low </sup>population that may correlate with human breast cancer stem cells.</p> <p>Conclusion</p> <p>Although individual tumors expanded by transplantation maintain the genomic profile of the original tumors, the heterogeneity among <it>Brca1 </it>tumors limits the extent of their use for preclinical testing. However, cell lines offer a robust material for understanding tumor biology and response to therapies driven by BRCA1 deficiency.</p
Overexpression of miR-146a in basal-like breast cancer cells confers enhanced tumorigenic potential in association with altered p53 status
The tumor suppressor p53 is the most frequently mutated gene in human cancers, mutated in 25–30% of breast cancers. However, mutation rates differ according to breast cancer subtype, being more prevalent in aggressive estrogen receptor-negative tumors and basal-like and HER2-amplified subtypes. This heterogeneity suggests that p53 may function differently across breast cancer subtypes. We used RNAi-mediated p53 knockdown (KD) and antagomir-mediated KD of microRNAs to study how gene expression and cellular response to p53 loss differ in luminal versus basal-like breast cancer. As expected, p53 loss caused downregulation of established p53 targets (e.g. p21 and miR-34 family) and increased proliferation in both luminal and basal-like cell lines. However, some p53-dependent changes were subtype specific, including expression of miR-134, miR-146a and miR-181b. To study the cellular response to miR-146a upregulation in p53-impaired basal-like lines, antagomir KD of miR-146a was performed. KD of miR-146a caused decreased proliferation and increased apoptosis, effectively ablating the effects of p53 loss. Furthermore, we found that miR-146a upregulation decreased NF-κB expression and downregulated the NF-κB-dependent extrinsic apoptotic pathway (including tumor necrosis factor, FADD and TRADD) and antagomir-mediated miR-146a KD restored expression of these components, suggesting a plausible mechanism for miR-146a-dependent cellular responses. These findings are relevant to human basal-like tumor progression in vivo, since miR-146a is highly expressed in p53 mutant basal-like breast cancers. These findings suggest that targeting miR-146a expression may have value for altering the aggressiveness of p53 mutant basal-like tumors
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
Department of Pathology, Thomas Jefferson University, Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors.
BACKGROUND: Although numerous mouse models of breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human phenotypes. To address this need, we characterized mammary tumor gene expression profiles from 13 different murine models using DNA microarrays and compared the resulting data to those from human breast tumors. RESULTS: Unsupervised hierarchical clustering analysis showed that six models (TgWAP-Myc, TgMMTV-Neu, TgMMTV-PyMT, TgWAP-Int3, TgWAP-Tag, and TgC3(1)-Tag) yielded tumors with distinctive and homogeneous expression patterns within each strain. However, in each of four other models (TgWAP-T121, TgMMTV-Wnt1, Brca1Co/Co;TgMMTV-Cre;p53+/- and DMBA-induced), tumors with a variety of histologies and expression profiles developed. In many models, similarities to human breast tumors were recognized, including proliferation and human breast tumor subtype signatures. Significantly, tumors of several models displayed characteristics of human basal-like breast tumors, including two models with induced Brca1 deficiencies. Tumors of other murine models shared features and trended towards significance of gene enrichment with human luminal tumors; however, these murine tumors lacked expression of estrogen receptor (ER) and ER-regulated genes. TgMMTV-Neu tumors did not have a significant gene overlap with the human HER2+/ER- subtype and were more similar to human luminal tumors. CONCLUSION: Many of the defining characteristics of human subtypes were conserved among the mouse models. Although no single mouse model recapitulated all the expression features of a given human subtype, these shared expression features provide a common framework for an improved integration of murine mammary tumor models with human breast tumors
Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors
Comparison of mammary tumor gene-expression profiles from thirteen murine models using microarrays and with that of human breast tumors showed that many of the defining characteristics of human subtypes were conserved among mouse models
Fibroblast Growth Factor Receptor Signaling Dramatically Accelerates Tumorigenesis and Enhances Oncoprotein Translation in the Mouse Mammary Tumor Virus-Wnt-1 Mouse Model of Breast Cancer
Fibroblast growth factor (FGF) cooperates with the Wnt/β-catenin pathway to promote mammary tumorigenesis. To investigate the mechanisms involved in FGF/Wnt cooperation, we genetically engineered a model of inducible FGF receptor (iFGFR) signaling in the context of the well-established mouse mammary tumor virus–Wnt-1 transgenic mouse. In the bigenic mice, iFGFR1 activation dramatically enhanced mammary tumorigenesis. Expression microarray analysis did not show transcriptional enhancement of Wnt/β-catenin target genes but instead showed a translational gene signature that also correlated with elevated FGFR1 and FGFR2 in human breast cancer data sets. Additionally, iFGFR1 activation enhanced recruitment of RNA to polysomes, resulting in a marked increase in protein expression of several different Wnt/β-catenin target genes. FGF pathway activation stimulated extracellular signal-regulated kinase and the phosphorylation of key translation regulators both in vivo in the mouse model and in vitro in a human breast cancer cell line. Our results suggest that cooperation of the FGF and Wnt pathways in mammary tumorigenesis is based on the activation of protein translational pathways that result in, but are not limited to, increased expression of Wnt/β-catenin target genes (at the level of protein translation). Further, they reveal protein translation initiation factors as potential therapeutic targets for human breast cancers with alterations in FGF signaling
Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer
Abstract Introduction In breast cancer, gene expression analyses have defined five tumor subtypes (luminal A, luminal B, HER2-enriched, basal-like and claudin-low), each of which has unique biologic and prognostic features. Here, we comprehensively characterize the recently identified claudin-low tumor subtype. Methods The clinical, pathological and biological features of claudin-low tumors were compared to the other tumor subtypes using an updated human tumor database and multiple independent data sets. These main features of claudin-low tumors were also evaluated in a panel of breast cancer cell lines and genetically engineered mouse models. Results Claudin-low tumors are characterized by the low to absent expression of luminal differentiation markers, high enrichment for epithelial-to-mesenchymal transition markers, immune response genes and cancer stem cell-like features. Clinically, the majority of claudin-low tumors are poor prognosis estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and epidermal growth factor receptor 2 (HER2)-negative (triple negative) invasive ductal carcinomas with a high frequency of metaplastic and medullary differentiation. They also have a response rate to standard preoperative chemotherapy that is intermediate between that of basal-like and luminal tumors. Interestingly, we show that a group of highly utilized breast cancer cell lines, and several genetically engineered mouse models, express the claudin-low phenotype. Finally, we confirm that a prognostically relevant differentiation hierarchy exists across all breast cancers in which the claudin-low subtype most closely resembles the mammary epithelial stem cell. Conclusions These results should help to improve our understanding of the biologic heterogeneity of breast cancer and provide tools for the further evaluation of the unique biology of claudin-low tumors and cell lines
Predicting Drug Responsiveness in Human Cancers Using Genetically Engineered Mice
To use genetically engineered mouse models (GEMMs) and orthotopic syngeneic murine transplants (OSTs) to develop gene-expression based predictors of response to anti-cancer drugs in human tumors. These mouse models offer advantages including precise genetics and an intact microenvironment/immune system