Validation of six genetic determinants of susceptibility to estrogen-induced mammary cancer in the rat and assessment of their relevance to breast cancer risk in humans

Rat Models of Hormone Receptor-Positive Breast Cancer

Hormone receptor-positive (HR+) breast cancer (BC) is the most common type of breast cancer among women worldwide, accounting for 70-80% of all invasive cases. Patients with HR+ BC are commonly treated with endocrine therapy, but intrinsic or acquired resistance is a frequent problem, making HR+ BC a focal point of intense research. Despite this, the malignancy still lacks adequate in vitro and in vivo models for the study of its initiation and progression as well as response and resistance to endocrine therapy. No mouse models that fully mimic the human disease are available, however rat mammary tumor models pose a promising alternative to overcome this limitation. Compared to mice, rats are more similar to humans in terms of mammary gland architecture, ductal origin of neoplastic lesions and hormone dependency status. Moreover, rats can develop spontaneous or induced mammary tumors that resemble human HR+ BC. To date, six different types of rat models of HR+ BC have been established. These include the spontaneous, carcinogen-induced, transplantation, hormone-induced, radiation-induced and genetically engineered rat mammary tumor models. Each model has distinct advantages, disadvantages and utility for studying HR+ BC. This review provides a comprehensive overview of all published models to date.

SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions

BACKGROUND

Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. The EI detection problem is dependent on epistasis models and corresponding optimization methods. Although various models and methods have been proposed to detect EIs, identifying EIs efficiently and accurately is still a challenge.

RESULTS

Here, we propose a linear mixed statistical epistasis model (LMSE) and a spherical evolution approach with a feedback mechanism (named SEEI). The LMSE model expands the existing single epistasis models such as LR-Score, K2-Score, Mutual information, and Gini index. The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. We analyzed the performances of 8 random disease models, 12 disease models with marginal effects, 30 disease models without marginal effects, and 10 high-order disease models. The 60 simulated disease models and a real breast cancer dataset were used to evaluate eight algorithms (SEEI, EACO, EpiACO, FDHEIW, MP-HS-DHSI, NHSA-DHSC, SNPHarvester, CSE). Three evaluation criteria (pow1, pow2, pow3), a T-test, and a Friedman test were used to compare the performances of these algorithms. The results show that the SEEI algorithm (order 1, averages ranks = 13.125) outperformed the other algorithms in detecting EIs.

CONCLUSIONS

Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. The proposed method performed better than the other seven algorithms tested in its ability to identify EIs in genome-wide association datasets. We identified new SNP-SNP combinations in the real breast cancer dataset and verified the results. Our findings provide new insights for the diagnosis and treatment of breast cancer.

AVAILABILITY AND IMPLEMENTATION

https://github.com/scutdy/SSO/blob/master/SEEI.zip .

Rat Mammary carcinoma susceptibility 3 (Mcs3) pleiotropy, socioenvironmental interaction, and comparative genomics with orthologous human 15q25.1-25.2

Genome-wide association studies of breast cancer susceptibility have revealed risk-associated genetic variants and nominated candidate genes; however, the identification of causal variants and genes is often undetermined by genome-wide association studies. Comparative genomics, utilizing Rattus norvegicus strains differing in susceptibility to mammary tumor development, is a complimentary approach to identify breast cancer susceptibility genes. Mammary carcinoma susceptibility 3 (Mcs3) is a Copenhagen (COP/NHsd) allele that confers resistance to mammary carcinomas when introgressed into a mammary carcinoma susceptible Wistar Furth (WF/NHsd) genome. Here, Mcs3 was positionally mapped to a 7.2-Mb region of RNO1 spanning rs8149408 to rs107402736 (chr1:143700228-150929594, build 6.0/rn6) using WF.COP congenic strains and 7,12-dimethylbenz(a)anthracene-induced mammary carcinogenesis. Male and female WF.COP-Mcs3 rats had significantly lower body mass compared to the Wistar Furth strain. The effect on female body mass was observed only when females were raised in the absence of males indicating a socioenvironmental interaction. Furthermore, female WF.COP-Mcs3 rats, raised in the absence of males, did not develop enhanced lobuloalveolar morphologies compared to those observed in the Wistar Furth strain. Human 15q25.1-25.2 was determined to be orthologous to rat Mcs3 (chr15:80005820-82285404 and chr15:83134545-84130720, build GRCh38/hg38). A public database search of 15q25.1-25.2 revealed genome-wide significant and nominally significant associations for body mass traits and breast cancer risk. These results support the existence of a breast cancer risk-associated allele at human 15q25.1-25.2 and warrant ultrafine mapping of rat Mcs3 and human 15q25.1-25.2 to discover novel causal genes and variants.

Induced mammary cancer in rat models: pathogenesis, genetics, and relevance to female breast cancer

Mammary cancer, or breast cancer in women, is a polygenic disease with a complex etiopathogenesis. While much remains elusive regarding its origin, it is well established that chemical carcinogens and endogenous estrogens contribute significantly to the initiation and progression of this disease. Rats have been useful models to study induced mammary cancer. They develop mammary tumors with comparable histopathology to humans and exhibit differences in resistance or susceptibility to mammary cancer depending on strain. While some rat strains (e.g., Sprague-Dawley) readily form mammary tumors following treatment with the chemical carcinogen, 7,12-dimethylbenz[a]-anthracene (DMBA), other strains (e.g., Copenhagen) are resistant to DMBA-induced mammary carcinogenesis. Genetic linkage in inbred strains has identified strain-specific quantitative trait loci (QTLs) affecting mammary tumors, via mechanisms that act together to promote or attenuate, and include 24 QTLs controlling the outcome of chemical induction, 10 QTLs controlling the outcome of estrogen induction, and 4 QTLs controlling the outcome of irradiation induction. Moreover, and based on shared factors affecting mammary cancer etiopathogenesis between rats and humans, including orthologous risk regions between both species, rats have served as useful models for identifying methods for breast cancer prediction and treatment. These studies in rats, combined with alternative animal models that more closely mimic advanced stages of breast cancer and/or human lifestyles, will further improve our understanding of this complex disease.

Uncovering Evidence for Endocrine-Disrupting Chemicals That Elicit Differential Susceptibility through Gene-Environment Interactions

Exposure to endocrine-disrupting chemicals (EDCs) is linked to myriad disorders, characterized by the disruption of the complex endocrine signaling pathways that govern development, physiology, and even behavior across the entire body. The mechanisms of endocrine disruption involve a complex system of pathways that communicate across the body to stimulate specific receptors that bind DNA and regulate the expression of a suite of genes. These mechanisms, including gene regulation, DNA binding, and protein binding, can be tied to differences in individual susceptibility across a genetically diverse population. In this review, we posit that EDCs causing such differential responses may be identified by looking for a signal of population variability after exposure. We begin by summarizing how the biology of EDCs has implications for genetically diverse populations. We then describe how gene-environment interactions (GxE) across the complex pathways of endocrine signaling could lead to differences in susceptibility. We survey examples in the literature of individual susceptibility differences to EDCs, pointing to a need for research in this area, especially regarding the exceedingly complex thyroid pathway. Following a discussion of experimental designs to better identify and study GxE across EDCs, we present a case study of a high-throughput screening signal of putative GxE within known endocrine disruptors. We conclude with a call for further, deeper analysis of the EDCs, particularly the thyroid disruptors, to identify if these chemicals participate in GxE leading to differences in susceptibility.

Evidence for immortality and autonomy in animal cancer models is often not provided, which causes confusion on key issues of cancer biology

Modern research into carcinogenesis has undergone three phases. Surgeons and pathologists started the first phase roughly 250 years ago, establishing morphological traits of tumors for pathologic diagnosis, and setting immortality and autonomy as indispensable criteria for neoplasms. A century ago, medical doctors, biologists and chemists started to enhance "experimental cancer research" by establishing many animal models of chemical-induced carcinogenesis for studies of cellular mechanisms. In this second phase, the two-hit theory and stepwise carcinogenesis of "initiation-promotion" or "initiation-promotion-progression" were established, with an illustrious finding that outgrowths induced in animals depend on the inducers, and thus are not authentically neoplastic, until late stages. The last 40 years are the third incarnation, molecular biologists have gradually dominated the carcinogenesis research fraternity and have established numerous genetically-modified animal models of carcinogenesis. However, evidence has not been provided for immortality and autonomy of the lesions from most of these models. Probably, many lesions had already been collected from animals for analyses of molecular mechanisms of "cancer" before the lesions became autonomous. We herein review the monumental work of many predecessors to reinforce that evidence for immortality and autonomy is essential for confirming a neoplastic nature. We extrapolate that immortality and autonomy are established early during sporadic human carcinogenesis, unlike the late establishment in most animal models. It is imperative to resume many forerunners' work by determining the genetic bases for initiation, promotion and progression, the genetic bases for immortality and autonomy, and which animal models are, in fact, good for identifying such genetic bases.

Recursive Feature Elimination by Sensitivity Testing

There is great interest in methods to improve human insight into trained non-linear models. Leading approaches include producing a ranking of the most relevant features, a non-trivial task for non-linear models. We show theoretically and empirically the benefit of a novel version of recursive feature elimination (RFE) as often used with SVMs; the key idea is a simple twist on the kinds of sensitivity testing employed in computational learning theory with membership queries (e.g., [1]). With membership queries, one can check whether changing the value of a feature in an example changes the label. In the real-world, we usually cannot get answers to such queries, so our approach instead makes these queries to a trained (imperfect) non-linear model. Because SVMs are widely used in bioinformatics, our empirical results use a real-world cancer genomics problem; because ground truth is not known for this task, we discuss the potential insights provided. We also evaluate on synthetic data where ground truth is known.

Mapping Mammary Tumor Traits in the Rat

For nearly a century, the rat has served as a key model for studying the pathophysiology and genetic risk modifiers of breast cancer. Rat mammary tumors that initiate after exposure to carcinogens or estrogens closely resemble the etiological, histopathological, and genomic features of human breast cancer. Recent developments in genome-editing techniques in the rat have also enabled the development of sophisticated models for identifying the genetic modifiers of the nonmalignant tumor microenvironment that contribute to the formation, progression, and outcome of breast cancer. In this protocol review, we discuss the current methodologies for the three genetic mapping techniques in the rat that are widely used for identifying and testing the heritable genetic modifiers of breast cancer.

Ept7, a quantitative trait locus that controls estrogen-induced pituitary lactotroph hyperplasia in rat, is orthologous to a locus in humans that has been associated with numerous cancer types and common diseases

Pituitary adenoma is a common intracranial neoplasm that is observed in approximately 10% of unselected individuals at autopsy. Prolactin-producing adenomas, i.e., prolactinomas, comprise approximately 50% of all pituitary adenomas and represent the most common class of pituitary tumor. Multiple observations suggest that estrogens may contribute to development of prolactinoma; however, direct evidence for a causal role of estrogens in prolactinoma etiology is lacking. Rat models of estrogen-induced prolactinoma have been utilized extensively to identify the factors, pathways and processes that are involved in pituitary tumor development. The objective of this study was to localize to high resolution Ept7 (Estrogen-induced pituitary tumor), a quantitative trait locus (QTL) that controls lactotroph responsiveness to estrogens and was mapped to rat chromosome 7 (RNO7) in an intercross between BN and ACI rats. Data presented and discussed herein localize the Ept7 causal variant(s) to a 1.91 Mb interval of RNO7 that contains two protein coding genes, A1bg and Myc, and Pvt1, which yields multiple non-protein coding transcripts of unknown function. The Ept7 orthologous region in humans is located at 8q24.21 and has been linked in genome wide association studies to risk of 8 distinct epithelial cancers, including breast, ovarian, and endometrial cancers; 3 distinct types of B cell lymphoma; multiple inflammatory and autoimmune diseases; and orofacial cleft defects. In addition, the Ept7 locus in humans has been associated with variation in normal hematologic and development phenotypes, including height. Functional characterization of Ept7 should ultimately enhance our understanding of the genetic etiology of prolactinoma and these other diseases.

Genetic variation in sensitivity to estrogens and breast cancer risk

Breast cancer risk is intimately intertwined with exposure to estrogens. While more than 160 breast cancer risk loci have been identified in humans, genetic interactions with estrogen exposure remain to be established. Strains of rodents exhibit striking differences in their responses to endogenous ovarian estrogens (primarily 17β-estradiol). Similar genetic variation has been observed for synthetic estrogen agonists (ethinyl estradiol) and environmental chemicals that mimic the actions of estrogens (xenoestrogens). This review of literature highlights the extent of variation in responses to estrogens among strains of rodents and compiles the genetic loci underlying pathogenic effects of excessive estrogen signaling. Genetic linkage studies have identified a total of the 35 quantitative trait loci (QTL) affecting responses to 17β-estradiol or diethylstilbestrol in five different tissues. However, the QTL appear to act in a tissue-specific manner with 9 QTL affecting the incidence or latency of mammary tumors induced by 17β-estradiol or diethylstilbestrol. Mammary gland development during puberty is also exquisitely sensitive to the actions of endogenous estrogens. Analysis of mammary ductal growth and branching in 43 strains of inbred mice identified 20 QTL. Regions in the human genome orthologous to the mammary development QTL harbor loci associated with breast cancer risk or mammographic density. The data demonstrate extensive genetic variation in regulation of estrogen signaling in rodent mammary tissues that alters susceptibility to tumors. Genetic variants in these pathways may identify a subset of women who are especially sensitive to either endogenous estrogens or environmental xenoestrogens and render them at increased risk of breast cancer.

Rat models of 17β-estradiol-induced mammary cancer reveal novel insights into breast cancer etiology and prevention

Numerous laboratory and epidemiologic studies strongly implicate endogenous and exogenous estrogens in the etiology of breast cancer. Data summarized herein suggest that the ACI rat model of 17β-estradiol (E2)-induced mammary cancer is unique among rodent models in the extent to which it faithfully reflects the etiology and biology of luminal types of breast cancer, which together constitute ~70% of all breast cancers. E2 drives cancer development in this model through mechanisms that are largely dependent upon estrogen receptors and require progesterone and its receptors. Moreover, mammary cancer development appears to be associated with generation of oxidative stress and can be modified by multiple dietary factors, several of which may attenuate the actions of reactive oxygen species. Studies of susceptible ACI rats and resistant COP or BN rats provide novel insights into the genetic bases of susceptibility and the biological processes regulated by genetic determinants of susceptibility. This review summarizes research progress resulting from use of these physiologically relevant rat models to advance understanding of breast cancer etiology and prevention.

Genome-Wide Analysis Identifies Germ-Line Risk Factors Associated with Canine Mammary Tumours

Canine mammary tumours (CMT) are the most common neoplasia in unspayed female dogs. CMTs are suitable naturally occurring models for human breast cancer and share many characteristics, indicating that the genetic causes could also be shared. We have performed a genome-wide association study (GWAS) in English Springer Spaniel dogs and identified a genome-wide significant locus on chromosome 11 (p_raw = 5.6x10^-7, p_perm = 0.019). The most associated haplotype spans a 446 kb region overlapping the CDK5RAP2 gene. The CDK5RAP2 protein has a function in cell cycle regulation and could potentially have an impact on response to chemotherapy treatment. Two additional loci, both on chromosome 27, were nominally associated (p_raw = 1.97x10^-5 and p_raw = 8.30x10^-6). The three loci explain 28.1±10.0% of the phenotypic variation seen in the cohort, whereas the top ten associated regions account for 38.2±10.8% of the risk. Furthermore, the ten GWAS loci and regions with reduced genetic variability are significantly enriched for snoRNAs and tumour-associated antigen genes, suggesting a role for these genes in CMT development. We have identified several candidate genes associated with canine mammary tumours, including CDK5RAP2. Our findings enable further comparative studies to investigate the genes and pathways in human breast cancer patients.

Dogs provide an excellent model system for several human diseases, including cancer. Heavy breeding for certain behavioural or phenotypic traits has created genetic isolates–breeds–characterised by low levels of genetic variation and a limited number of genetic disease variants within each breed. Cancer is the most common cause of death in dogs today, and canine mammary tumours (CMT) are the most prevalent tumour type in unspayed female dogs. These tumours are very similar to human breast cancer and could therefore be used as a naturally occurring model for the human disease. We have investigated genetic variants associated with CMT in English Springer Spaniels pointing to a gene involved in cell cycle regulation (CDK5RAP2). The CDK5RAP2 could therefore have a key role in the development of mammary tumours and we suggest that further studies should be performed in both dogs and women to investigate CDK5RAP2 and its possible effect on disease and treatment response.

Development and characterization of a novel rat model of estrogen-induced mammary cancer

The ACI rat model of 17β-estradiol (E2)-induced mammary cancer is highly relevant for use in establishing the endocrine, genetic, and environmental bases of breast cancer etiology and identifying novel agents and strategies for preventing breast cancer. E2 treatment rapidly induces mammary cancer in female ACI rats and simultaneously induces pituitary lactotroph hyperplasia and adenoma. The pituitary tumors can result in undesired morbidity, which compromises long-term studies focused on mammary cancer etiology and prevention. We have defined the genetic bases of susceptibility to E2-induced mammary cancers and pituitary tumors and have utilized the knowledge gained in these studies to develop a novel inbred rat strain, designated ACWi, that retains the high degree of susceptibility to E2-induced mammary cancer exhibited by ACI rats, but lacks the treatment-related morbidity associated with pituitary lactotroph hyperplasia/adenoma. When treated with E2, female ACWi rats developed palpable mammary cancer at a median latency of 116 days, an incidence of 100% by 161 days and exhibited an average of 15.6 mammary tumors per rat following 196 days of treatment. These parameters did not differ from those observed for contemporaneously treated ACI rats. None of the E2-treated ACWi rats were killed before the intended experimental end point due to any treatment-related morbidity other than mammary cancer burden, whereas 20% of contemporaneously treated ACI rats exhibited treatment-related morbidity that necessitated premature killing. The ACWi rat strain is well suited for use by those in the research community, focusing on breast cancer etiology and prevention.

Genetic etiology of renal agenesis: fine mapping of Renag1 and identification of Kit as the candidate functional gene

Congenital anomalies of the kidney and urogenital tract (CAKUT) occur in approximately 0.5% of live births and represent the most frequent cause of end-stage renal disease in neonates and children. The genetic basis of CAKUT is not well defined. To understand more fully the genetic basis of one type of CAKUT, unilateral renal agenesis (URA), we are studying inbred ACI rats, which spontaneously exhibit URA and associated urogenital anomalies at an incidence of approximately 10%. URA is inherited as an incompletely dominant trait with incomplete penetrance in crosses between ACI and Brown Norway (BN) rats and a single responsible genetic locus, designated Renag1, was previously mapped to rat chromosome 14 (RNO14). The goals of this study were to fine map Renag1, identify the causal genetic variant responsible for URA, confirm that the Renag1 variant is the sole determinant of URA in the ACI rat, and define the embryologic basis of URA in this rat model. Data presented herein localize Renag1 to a 379 kilobase (kb) interval that contains a single protein coding gene, Kit (v-kit Hardy-Zukerman 4 feline sarcoma viral oncogene homolog); identify an endogenous retrovirus-derived long terminal repeat located within Kit intron 1 as the probable causal variant; demonstrate aberrant development of the nephric duct in the anticipated number of ACI rat embryos; and demonstrate expression of Kit and Kit ligand (Kitlg) in the nephric duct. Congenic rats that harbor ACI alleles at Renag1 on the BN genetic background exhibit the same spectrum of urogenital anomalies as ACI rats, indicating that Renag1 is necessary and sufficient to elicit URA and associated urogenital anomalies. These data reveal the first genetic link between Kit and URA and illustrate the value of the ACI rat as a model for defining the mechanisms and cell types in which Kit functions during urogenital development.