Allelic variation and differential expression of the mSIN3A histone deacetylase complex gene Arid4b promote mammary tumor growth and metastasis.

Accumulating evidence suggests that breast cancer metastatic progression is modified by germline polymorphism, although specific modifier genes have remained largely undefined. In the current study, we employ the MMTV-PyMT transgenic mouse model and the AKXD panel of recombinant inbred mice to identify AT-rich interactive domain 4B (Arid4b; NM_194262) as a breast cancer progression modifier gene. Ectopic expression of Arid4b promoted primary tumor growth in vivo as well as increased migration and invasion in vitro, and the phenotype was associated with polymorphisms identified between the AKR/J and DBA/2J alleles as predicted by our genetic analyses. Stable shRNA-mediated knockdown of Arid4b caused a significant reduction in pulmonary metastases, validating a role for Arid4b as a metastasis modifier gene. ARID4B physically interacts with the breast cancer metastasis suppressor BRMS1, and we detected differential binding of the Arid4b alleles to histone deacetylase complex members mSIN3A and mSDS3, suggesting that the mechanism of Arid4b action likely involves interactions with chromatin modifying complexes. Downregulation of the conserved Tpx2 gene network, which is comprised of many factors regulating cell cycle and mitotic spindle biology, was observed concomitant with loss of metastatic efficiency in Arid4b knockdown cells. Consistent with our genetic analysis and in vivo experiments in our mouse model system, ARID4B expression was also an independent predictor of distant metastasis-free survival in breast cancer patients with ER+ tumors. These studies support a causative role of ARID4B in metastatic progression of breast cancer.

Integrated cross-species transcriptional network analysis of metastatic susceptibility.

Metastatic disease is the proximal cause of mortality for most cancers and remains a significant problem for the clinical management of neoplastic disease. Recent advances in global transcriptional analysis have enabled better prediction of individuals likely to progress to metastatic disease. However, minimal overlap between predictive signatures has precluded easy identification of key biological processes contributing to the prometastatic transcriptional state. To overcome this limitation, we have applied network analysis to two independent human breast cancer datasets and three different mouse populations developed for quantitative analysis of metastasis. Analysis of these datasets revealed that the gene membership of the networks is highly conserved within and between species, and that these networks predicted distant metastasis free survival. Furthermore these results suggest that susceptibility to metastatic disease is cell-autonomous in estrogen receptor-positive tumors and associated with the mitotic spindle checkpoint. In contrast, nontumor genetics and pathway activities-associated stromal biology are significant modifiers of the rate of metastatic spread of estrogen receptor-negative tumors. These results suggest that the application of network analysis across species may provide a robust method to identify key biological programs associated with human cancer progression.

Gene expression pathway analysis to predict response to neoadjuvant docetaxel and capecitabine for breast cancer.

Neoadjuvant chemotherapy has been shown to be equivalent to post-operative treatment for breast cancer, and allows for assessment of chemotherapy response. In a pilot trial of docetaxel (T) and capecitabine (X) neoadjuvant chemotherapy for Stage II/III BC, we assessed correlation between baseline gene expression and tumor response to treatment, and examined changes in gene expression associated with treatment. Patients received four cycles of TX. Tumor tissue obtained from Mammotome core biopsies pretreatment (BL) and post-cycle 1 (C1) of TX was FLash frozen and stored at -70 degrees C until processing. Gene expression analysis utilized Affymetrix HG-U133 Plus 2.0 GeneChip arrays. Statistical analysis was performed using BRB Array Tools after RMA normalization. Gene ontology (GO) pathway analysis used random variance t tests with a significance level of P\0.005. For gene categories identified byGO pathway analysis as significant, expression levels of individual genes within those pathways were compared between classes using univariate t tests; those genes with significance level of P\0.05 were reported. PAM50 analyses were performed on tumor samples to investigate biologic subtype and risk of relapse (ROR). Using GO pathway analysis, 39 gene categories discriminated between responders and non-responders,most notably genes involved in microtubule assembly and regulation. When comparing pre- and post-chemotherapy specimens, we identified 71 differentially expressed gene categories, including DNA repair and cell proliferation regulation. There were 45 GO pathways in which the change in expression after one cycle of chemotherapy was significantly different among responders and nonresponders. The majority of tumor samples fell into the basal like and luminal B categories. ROR scores decreased in response to chemotherapy; this change was more evident in samples from patients classified as responders by clinical criteria. GO pathway analysis identified a number of gene categories pertinent to therapeutic response, and may be an informative method for identifying genes important in response to chemotherapy. Larger studies using the methods described here are necessary to fully evaluate gene expression changes in response to chemotherapy.

The origins of breast cancer prognostic gene expression profiles.

Recent high profile clinical trials show that microarray-based gene expression profiling has the potential to become an important tool for predicting prognosis in breast cancer. Earlier work in our laboratory using mouse models and human breast cancer populations has enabled us to show that metastasis susceptibility is an inherited trait. This same combined approach facilitated the identification of a number of candidate genes that, when dysregulated, have the potential to induce prognostic gene expression profiles in human data sets. To investigate if these gene expression signatures were of somatic or germline origin and to assess the contribution of different cell types to the induction of these signatures, we have performed a series of expression profiling experiments in a mouse model of metastatic breast cancer. These results show that both the tumor epithelium and invading stromal tissues contribute to the development of prognostic gene signatures. Furthermore, analysis of normal tissues and tumor transplants suggests that prognostic signatures result from both somatic and inherited components, with the inherited components being more consistently predictive.

Bromodomain 4 activation predicts breast cancer survival.

Previous work identified the Rap1 GTPase-activating protein Sipa1 as a germ-line-encoded metastasis modifier. The bromodomain protein Brd4 physically interacts with and modulates the enzymatic activity of Sipa1. In vitro analysis of a highly metastatic mouse mammary tumor cell line ectopically expressing Brd4 demonstrates significant reduction of invasiveness without altering intrinsic growth rate. However, a dramatic reduction of tumor growth and pulmonary metastasis was observed after s.c. implantation into mice, implying that activation of Brd4 may somehow be manipulating response to tumor microenvironment in the in vivo setting. Further in vitro analysis shows that Brd4 modulates extracellular matrix gene expression, a class of genes frequently present in metastasis-predictive gene signatures. Microarray analysis of the mammary tumor cell lines identified a Brd4 activation signature that robustly predicted progression and/or survival in multiple human breast cancer datasets analyzed on different microarray platforms. Intriguingly, the Brd4 signature also almost perfectly matches a molecular classifier of low-grade tumors. Taken together, these data suggest that dysregulation of Brd4-associated pathways may play an important role in breast cancer progression and underlies multiple common prognostic signatures.

The Diasporin Pathway: a tumor progression-related transcriptional network that predicts breast cancer survival.

Microarray expression signature analyses have suggested that extracellular matrix (ECM) gene dysregulation is predictive of metastasis in both mouse mammary tumorigenesis and human breast cancer. We have previously demonstrated that such ECM dysregulation is influenced by hereditary germline-encoded variation. To identify novel metastasis efficiency modifiers, we performed expression QTL (eQTL) mapping in recombinant inbred mice by characterizing genetic loci modulating metastasis-predictive ECM gene expression. Three reproducible eQTLs were observed on chromosomes 7, 17 and 18. Candidate genes were identified by correlation analyses and known associations with metastasis. Seven candidates were identified (Ndn, Pi16, Luc7l, Rrp1b, Brd4, Centd3 and Csf1r). Stable transfection of the highly metastatic Mvt-1 mouse mammary tumor cell line with expression vectors encoding each candidate modulated metastasis-predictive ECM gene expression. Implantation of these cells into mice demonstrated that candidate gene ectopic expression impacts tumor progression. Gene expression analyses facilitated the construction of a transcriptional network that we have termed the 'Diasporin Pathway'. This pathway contains the seven candidates, as well as metastasis-predictive ECM genes and metastasis suppressors. Brd4 and Rrp1b appear to form a central node within this network, which likely is a consequence of their physical interaction with the metastasis efficiency modifier Sipa1. Furthermore, we demonstrate that the microarray gene expression signatures induced by activation of ECM eQTL genes in the Mvt-1 cell line can be used to accurately predict survival in a human breast cancer cohort. These data imply that the Diasporin Pathway may be an important nexus in tumor progression in both mice and humans.

Rrp1b, a new candidate susceptibility gene for breast cancer progression and metastasis.

A novel candidate metastasis modifier, ribosomal RNA processing 1 homolog B (Rrp1b), was identified through two independent approaches. First, yeast two-hybrid, immunoprecipitation, and functional assays demonstrated a physical and functional interaction between Rrp1b and the previous identified metastasis modifier Sipa1. In parallel, using mouse and human metastasis gene expression data it was observed that extracellular matrix (ECM) genes are common components of metastasis predictive signatures, suggesting that ECM genes are either important markers or causal factors in metastasis. To investigate the relationship between ECM genes and poor prognosis in breast cancer, expression quantitative trait locus analysis of polyoma middle-T transgene-induced mammary tumor was performed. ECM gene expression was found to be consistently associated with Rrp1b expression. In vitro expression of Rrp1b significantly altered ECM gene expression, tumor growth, and dissemination in metastasis assays. Furthermore, a gene signature induced by ectopic expression of Rrp1b in tumor cells predicted survival in a human breast cancer gene expression dataset. Finally, constitutional polymorphism within RRP1B was found to be significantly associated with tumor progression in two independent breast cancer cohorts. These data suggest that RRP1B may be a novel susceptibility gene for breast cancer progression and metastasis.

Accelerated preclinical testing using transplanted tumors from genetically engineered mouse breast cancer models.

PURPOSE: The use of genetically engineered mouse (GEM) models for preclinical testing of anticancer therapies is hampered by variable tumor latency, incomplete penetrance, and complicated breeding schemes. Here, we describe and validate a transplantation strategy that circumvents some of these difficulties. EXPERIMENTAL DESIGN: Tumor fragments from tumor-bearing MMTV-PyMT or cell suspensions from MMTV-PyMT, -Her2/neu, -wnt1, -wnt1/p53(+/-), BRCA1/p53(+/-), and C3(1)T-Ag mice were transplanted into the mammary fat pad or s.c. into naïve syngeneic or immunosuppressed mice. Tumor development was monitored and tissues were processed for histopathology and gene expression profiling. Metastasis was scored 60 days after the removal of transplanted tumors. RESULTS: PyMT tumor fragments and cell suspensions from anterior glands grew faster than posterior tumors in serial passages regardless of the site of implantation. Microarray analysis revealed genetic differences between these tumors. The transplantation was reproducible using anterior tumors from multiple GEM, and tumor growth rate correlated with the number of transplanted cells. Similar morphologic appearances were observed in original and transplanted tumors. Metastasis developed in >90% of mice transplanted with PyMT, 40% with BRCA1/p53(+/-) and wnt1/p53(+/-), and 15% with Her2/neu tumors. Expansion of PyMT and wnt1 tumors by serial transplantation for two passages did not lead to significant changes in gene expression. PyMT-transplanted tumors and anterior tumors of transgenic mice showed similar sensitivities to cyclophosphamide and paclitaxel. CONCLUSIONS: Transplantation of GEM tumors can provide a large cohort of mice bearing mammary tumors at the same stage of tumor development and with defined frequency of metastasis in a well-characterized molecular and genetic background.

Parallel analysis of transcript and translation profiles: identification of metastasis-related signal pathways differentially regulated by drug and genetic modifications.

Tumor metastasis is a complex multistep process normally involving dysregulation of multiple signal transduction pathways. In this study, we developed a novel approach to efficiently define dysreguated pathways associated with metastasis by comparing global gene and protein expressions of two distinct metastasis-suppressed models. Consequently, we identified common features shared by the two models which are potentially associated with metastasis. The efficiency of metastasis from the highly aggressive polyoma middle T-induced mouse mammary tumors was suppressed by either prolonged caffeine exposure or by breeding the animal to a low metastatic mouse strain. Molecular profiles of the primary tumors from both metastasis-suppressed classes were then derived to identify molecules and pathways that might underlie a common mechanism of metastasis. A number of differentially regulated genes and proteins were identified, including genes encoding basement membrane components, which were inversely related to metastatic efficiency. In addition, the analysis revealed that the Stat signal transduction pathways were potentially associated with metastasis inhibition, as demonstrated by enhanced Stat1 activation, and decreased Stat5 phosphorylation in both genetic and pharmacological modification models. Tumor cells of low-metastatic genotypes also demonstrated anti-apoptotic properties. The common changes of these pathways in all of the metastasis-suppressed systems suggest that they may be critical components in the metastatic cascade, at least in this model system. Our data demonstrate that analysis of common changes in genes and proteins in a metastatic-related context greatly decrease the complexity of data analysis, and may serve as a screening tool to identify biological important factors from large scale data.

Inherited metastasis susceptibility and the implications for clinical prognosis.

Extract: Metastasis, the spread of cancer throughout the body, remains the leading cause of cancer-related death despite decades of investigation and the efforts of thousands of doctors and scientists. Over the past thirty to forty years tremendous strides have been made in understanding the origins of cancer. Advances in new therapeutic agents and strategies have resulted in improved survival and cure rates in many cancers, particularly pediatric cancers. However, the presentation of a cancer patient with symptomatic metastatic disease continues to be a harbinger of poor outcome, given that secondary tumors are frequently both surgically untreatable and are frequently resistant to currently available anti-tumor drugs. To better battle this proximal cause of cancer mortality, a clearer understanding of the origins and mechanisms of the metastatic process are critical for the design of new clinical interventions. Metastasis is an extraordinarily complex process, and to successfully colonize a secondary site a cancer cell must complete a sequential series of steps before it becomes a clinically detectable tumor. These steps include separation from the primary tumor, invasion through surrounding tissues, entry into and survival in blood or lymph vessels, arresting in a distant site, usually followed by penetration into the surrounding tissue, survival in the distant organ site, proliferation, and creation of new blood vessels, all the while evading the immune response and intrinsic apoptosis mechanisms.

Metastasis predictive signature profiles pre-exist in normal tissues.

Previous studies from our laboratory have demonstrated that metastatic propensity is significantly influenced by the genetic background upon which tumors arise. We have also established that human gene expression profiles predictive of metastasis are not only present in mouse tumors with both high and low metastatic capacity, but also correlate with genetic background. These results suggest that human metastasis-predictive gene expression signatures may be significantly driven by genetic background, rather than acquired somatic mutations. To test this hypothesis, gene expression profiling was performed on inbred mouse strains with significantly different metastatic efficiencies. Analysis of previously described human metastasis signature gene expression patterns in normal tissues permitted accurate categorization of high or low metastatic mouse genotypes. Furthermore, prospective identification of animals at high risk of metastasis was achieved by using mass spectrometry to characterize salivary peptide polymorphisms in a genetically heterogeneous population. These results strongly support the role of constitutional genetic variation in modulation of metastatic efficiency and suggest that predictive signature profiles could be developed from normal tissues in humans. The ability to identify those individuals at high risk of disseminated disease at the time of clinical manifestation of a primary cancer could have a significant impact on cancer management.

Caffeine suppresses metastasis in a transgenic mouse model: a prototype molecule for prophylaxis of metastasis.

A significant fraction of cancer patients have occult disseminated tumors at the time of primary diagnosis, which usually progress to become clinically relevant lesions. Since the majority of cancer mortality is associated with metastatic disease, the ability to inhibit the growth of the secondary tumors would significantly reduce cancer-related morbidity and mortality. We have investigated whether caffeine, which has been shown to suppress tumor cell invasiveness and experimental metastasis, can suppress metastasis in a spontaneous transgene-induced mammary tumor model. Chronic exposure to caffeine prior to the appearance of palpable mammary tumors significantly reduced both tumor burden and metastatic colonization. However, when caffeine exposure began after the appearance of frank tumors, caffeine suppressed metastasis without changing primary tumor burden. The means by which caffeine suppressed metastatic activity may be associated with inhibition of malignant transformation of mammary epithelial cells, inhibition of conversion of dormant tumor cells to micrometastases, micrometastases to macrometastases, or inhibition of tumor cell adhesion and motility. Gene and protein expression patterns resulting from caffeine treatment showed that metastasis suppression may be associated with up-regulation the mRNA expression of multiple extracellular matrix genes, including Fbln1, Bgn, Sparc, Fbn1, Loxl1, Colla1, Col3a1, Col5a1, ColS5a2, ColSa3, Col6a1, Col6a2, and Col6a3. These data suggested that caffeine or other methyl xanthine derivatives may improve the clinical outcome in patients prior to and following the diagnosis of metastatic disease, and could potentially reduce the morbidity and mortality associated with disseminated tumors.

The Septin 9 (MSF) gene is amplified and overexpressed in mouse mammary gland adenocarcinomas and human breast cancer cell lines.

The expression of polyomavirus middle T antigen under the control of the mouse mammary tumor virus promoter in transgenic mice results in the induction of aggressive mammary gland adenocarcinomas at an early age. We screened 26 tumors for chromosomal aneuploidies using SKY and CGH. In 70% of the tumor samples we could detect high-level copy number gains, which mapped to chromosome band 11E2, a region orthologous to human 17q25.3. We then identified a bacterial artificial chromosome clone that labeled double-minute chromosomes found in the tumor metaphases. This bacterial artificial chromosome clone showed sequence homology to a member of the septin gene family. Real-time PCR analysis revealed a consistently increased expression of septin 9 (Sept9), not only in polyomavirus middle T antigen-induced, but in a wide variety of mouse models of breast cancer. Six of 9 human tumor cell lines also revealed elevated expression levels of Sept9. The family of septin genes is involved in a plethora of cellular processes, including cytokinesis in yeast and vesicle transport, and possesses GTPase activity. We identified down-regulation of Thsp1- and Bax-regulated apoptotic response in those tumors with Sept9 overexpression, an effect that could be reversed by inhibiting Sept9 expression using transfection with small interference RNA. Our results now suggest that signaling via members of the septin family plays a novel and common role in breast tumorigenesis.

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

The epistatically interacting modifier loci (Apmt1 and Apmt2) accelerate the polyoma Middle-T (PyVT)-induced mammary tumor. To identify potential candidate genes loci, a combined bioinformatics and genomics strategy was used. On the basis of the assumption that the loci were functioning in the same or intersecting pathways, a search of the literature databases was performed to identify molecular pathways containing genes from both candidate intervals. Among the genes identified by this method were the cell cycle-associated genes Cdc25A and c-Myc, both of which have been implicated in breast cancer. Genomic sequencing revealed noncoding polymorphism in both genes, in the promoter region of Cdc25A, and in the 3' UTR of c-Myc. Molecular and in vitro analysis showed that the polymorphisms were functionally significant. In vivo analysis was performed by generating compound PyVT/Myc double-transgenic animals to mimic the hypothetical model, and was found to recapitulate the age-of-onset phenotype. These data suggest that c-Myc and Cdc25A are Apmt1 and Apmt2, and suggest that, at least in certain instances, bioinformatics can be utilized to bypass congenic construction and subsequent mapping in conventional QTL studies.