Genetic Modifiers of Initiation and Progression of Mammary Cancer

乳腺癌发生和进展的基因修饰因素

• 批准号: 10486799
• 负责人: KENT William HUNTER
• 金额: $ 274.59万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10486799
• 关键词: 1-Phosphatidylinositol 3-Kinase; Adjuvant Chemotherapy; Age; Allografting; American; Amino Acid Substitution; Animals; Antigens; Bioinformatics; Biology; Breast Cancer gene; Breast cancer metastasis; Cancer Etiology; Candidate Disease Gene; Cell physiology; Cessation of life; Chromosome 19; Chromosome Mapping; Clinical; Critical Pathways; Development; Diagnosis; Discipline; Disease; Distant; Enhancers; Epidemiology; Etiology; Experimental Genetics; Female; Future; Gene Expression Profiling; Generations; Genes; Genetic; Genetic Polymorphism; Genetic Predisposition to Disease; Genetic Screening; Genetic Transcription; Genetic Variation; Genetically Engineered Mouse; Genome; Genomics; Goals; Growth; Haplotypes; Histopathology; Human; Human Genetics; Inbred Strain; Inbred Strains Mice; Inherited; Intervention; Laboratories; Localized Disease; Malignant Neoplasms; Mammary Neoplasms; Mammary Tumorigenesis; Manuscripts; Measures; Meiosis; Metastatic Neoplasm to the Lung; Metastatic breast cancer; Metastatic to; Methods; MicroRNAs; Modeling; Molecular; Morbidity - disease rate; Mouse Mammary Tumor Virus; Mus; Mutate; Mutation; Neoplasm Metastasis; Nulliparity; Oncogenic; Palpable; Pathway interactions; Patients; Penetrance; Phenotype; Phylogenetic Analysis; Polyomavirus; Population; Preparation; Primary Lesion; Proteomics; Public Health; Publishing; Recurrence; Relapse; Resolution; Resources; Role; Series; Survival Rate; Susceptibility Gene; System; Technology; Therapeutic; Transcript; Transgenes; Trees; Tumor Antigens; United States; Validation; Variant; Woman; advanced breast cancer; base; burden of illness; clinically relevant; design; driver mutation; epidemiology study; epigenomics; experimental study; genetic analysis; genetic signature; genetic variant; genome-wide; improved; insight; knock-down; lung metastatic; male; malignant breast neoplasm; metastatic process; molecular subtypes; mortality; mouse genetics; multidisciplinary; overexpression; population based; precision medicine; prevent; prognostic; promoter; small hairpin RNA; transcriptome sequencing; transgene expression; tumor; tumor growth; tumor progression

Breast cancer remains the most commonly diagnosed malignancy and is the second leading cause of cancer-related death in American women. It is estimated that there were more than 266,000 new cases of breast cancer in the United States in 2018, with 41,000 patients succumbing to the disease. Although the 5-year survival approaches 100% for those patients diagnosed with localized disease, the 5-year survival rate for patients diagnosed with distant metastatic disease in only 27%, highlighting the critical importance of the metastatic process in patient mortality. For those patients diagnosed with localized disease, the widespread application of adjuvant chemotherapy has reduced late relapse and long-term mortality by an estimated 19%. However, despite these efforts, 25% of patients receiving adjuvant chemotherapy still progress to metastatic disease. Despite changes in therapeutic strategies little improvement in the survival of these patients has been observed . At present it is estimated that 155,000 women are currently living with metastatic disease in the United States, highlighting the significant public health burden of this disease. It is therefore critically important to obtain a comprehensive understanding of the etiology and biology of metastases to develop more effective clinical interventions to further reduce the morbidity and mortality of advanced breast cancer. My laboratory pioneered the use of mouse meiotic genetic screens to gain additional insights into the etiology of metastatic progression in breast cancer. To implement this strategy my laboratory has exploited the highly metastatic FVB/N-Tg(MMTV-PyMT)634Mul genetically engineered mouse model of mammary carcinogenesis. This model expresses the mouse polyoma middle-T antigen (PyMT), expressed using mouse mammary tumor virus (MMTV) enhancer and promoter. This results in the activation of the PI-3-Kinase pathway, modeling one of the most frequently mutated pathways in human breast cancer. As a result, nulliparous female PyMT mice develop synchronous palpable, multifocal mammary tumors by 60 days of age. Detailed histopathology analysis suggests that this model has a high degree of similarity with human breast cancer and gene expression profiling suggest that it most closely resembles the luminal subtype of human breast cancer. By 100 days of age, in our colonies, greater than 85% of the animals develop macroscopic pulmonary metastases on the FVB/NJ background. To demonstrate that inherited allelic variants significantly contribute to metastatic progression, as a proof-of-principle experiment, we bred male PyMT mice to female mice from more than 25 different inbred mouse strains, representing different branches of the mouse phylogenetic tree. The oncogenic transgene was therefore on different genetic backgrounds in the resulting F1 progeny due to the contributions of the dams from each inbred strain. The F1 females were permitted to age for tumor and potential metastasis development, then euthanized and different tumor phenotypes measured. Significant variation in tumor latency, growth and pulmonary metastatic colonization were observed. Analysis of the metastatic capacity of the tumors across the different genetic backgrounds revealed a continuum rather than discrete classes of low or high metastatic burden, indicative of the presence of multiple polymorphic genes contributing to the phenotype rather than one or two dominant loci. No alterations in transgene expression were found, consistent with a role for polymorphic effects on these tumor phenotypes. Strains were identified that suppressed the metastatic capacity of the PyMT tumors, without altering tumor growth rate or latency. Chromosomal substitution strains and genetic experimental crosses were then generated to identify regions of the genome harboring metastasis susceptibility genes. Haplotype mapping across multiple experimental crosses restricted a candidate region on mouse chromosome 19 to a 110 kb interval containing only 5 genes. Sequencing analysis of the genes in the interval across high- and low-metastatic genetic backgrounds revealed a single amino acid substitution in Sipa1 that segregated with metastatic capacity. Functional analysis revealed that this substitution reduced the RAP-GAP activity of SIPA1 in the low metastatic strains. Subsequent modeling of this reduction by shRNA knockdown or overexpression of Sipa1 in a highly metastatic mammary tumor mouse allograft model demonstrated that Sipa1 transcript levels correlated with pulmonary metastatic burden. Epidemiological investigations by our lab and others found associations between SIPA1 polymorphisms and metastatic progression in human patients, consistent with SIPA1 as a metastasis susceptibility gene in both mice and humans. Population-based epidemiology further demonstrated the presence of inherited metastasis predisposition genes in breast cancer as well as other human cancers. These studies therefore validated our original hypothesis that inherited susceptibility is a significant component of cancer progression. In addition, these results suggest that our mouse-based genetic mapping strategy is a viable approach to identify human-relevant genes for further characterization of the metastatic cascade. Subsequently, my laboratory has increasingly incorporated genomic technologies to investigate how inherited polymorphisms influence metastatic disease. Incorporation of expression technologies, first Affymetrix chip-based expression analysis and more recently RNA-sequencing methods, with the genetic analysis have helped accelerate candidate gene identification for validation and analysis. In addition, we have also incorporated more sophisticated genetic mapping resources, primarily the Diversity Outbred mouse mapping panel, to improve the genetic mapping resolution and to generate experimental crosses that more closely resemble the genetic diversity observed across human populations. Moreover, we have utilized the resources generated from these projects to demonstrate the contribution of genetic background to clinically relevant factors such as the generation of breast cancer molecular subtype classifiers like the PAM50 and prognostic gene signatures such as MammaPrint. To date, my laboratory has published an additional 16 metastasis-associated genes and six microRNAs since the identification of Sipa1. In addition, we have validated an additional 11 genes as metastasis modifiers; these genes are in varying stages of characterization or manuscript preparation and submission. in addition, we have initiated a series of experiments to identify metastasis driver mutations by performing genomic landscape analysis of matched primary and metastatic lesions from the PyMT model. This has led to the identification of three genes that are recurrently mutated in secondary tumors, and thus are likely to be metatasis activating mutations. Current efforts are underway to validate and characterize how these genes and their downstream pathways contribute to metastatic breast cancer.

乳腺癌仍然是最常见的恶性肿瘤，也是美国妇女癌症相关死亡的第二大原因。据估计，2018年美国有超过26.6万例新发乳腺癌病例，其中4.1万名患者死于这种疾病。虽然那些被诊断为局部疾病的患者的5年生存率接近100%，但被诊断为远处转移性疾病的患者的5年生存率仅为27%，这突出了转移过程在患者死亡率中的关键重要性。对于那些诊断为局限性疾病的患者，广泛应用辅助化疗可使晚期复发和长期死亡率降低约19%。然而，尽管做出了这些努力，25%接受辅助化疗的患者仍然进展为转移性疾病。尽管治疗策略发生了变化，但观察到这些患者的生存率几乎没有改善。目前，美国估计有15.5万名妇女患有转移性疾病，这凸显了这种疾病的重大公共卫生负担。因此，全面了解转移的病因和生物学，以制定更有效的临床干预措施，进一步降低晚期乳腺癌的发病率和死亡率，是至关重要的。我的实验室率先使用小鼠减数分裂基因筛选来获得乳腺癌转移进展的病因学的更多见解。为了实施这一策略，我的实验室利用了高转移性FVB/N-Tg(MMTV-PyMT)634Mul基因工程小鼠乳腺癌模型。该模型表达用小鼠乳腺肿瘤病毒（MMTV）增强子和启动子表达的小鼠多瘤中间t抗原（PyMT）。这导致pi -3激酶途径的激活，模拟了人类乳腺癌中最常见的突变途径之一。因此，未生育的雌性PyMT小鼠在60日龄时出现同步可触及的多灶性乳腺肿瘤。详细的组织病理学分析表明，该模型与人类乳腺癌具有高度的相似性，基因表达谱表明它与人类乳腺癌的腔内亚型最相似。到100日龄时，在我们的菌落中，超过85%的动物在FVB/NJ背景下发生宏观肺转移。为了证明遗传等位基因变异显著地促进了转移进展，作为一项原理验证实验，我们将雄性PyMT小鼠与来自25种不同近交小鼠品系的雌性小鼠杂交，这些品系代表了小鼠系统发育树的不同分支。因此，由于每个近交系的基因坝的贡献，致癌转基因在产生的F1后代中具有不同的遗传背景。允许F1雌性随着肿瘤和潜在转移的发展而衰老，然后安乐死并测量不同的肿瘤表型。观察到肿瘤潜伏期、生长和肺转移定植的显著变化。对不同遗传背景的肿瘤转移能力的分析揭示了一个连续的而不是离散的低或高转移负担类别，这表明存在多个多态性基因而不是一个或两个显性基因位点。没有发现转基因表达的改变，这与多态效应在这些肿瘤表型中的作用一致。鉴定出的菌株抑制了PyMT肿瘤的转移能力，而不改变肿瘤的生长速度或潜伏期。然后生成染色体替代菌株和遗传实验杂交，以鉴定基因组中含有转移易感基因的区域。多个实验杂交的单倍型定位将小鼠19号染色体上的候选区域限制在仅包含5个基因的110 kb区间内。在高转移性和低转移性遗传背景之间的基因测序分析显示，Sipa1中存在单个氨基酸替代，其分离具有转移能力。功能分析表明，这种取代降低了低转移菌株SIPA1的RAP-GAP活性。随后，在高转移性乳腺肿瘤小鼠同种异体移植模型中，通过shRNA敲低或Sipa1过表达来模拟这种减少，结果表明Sipa1转录物水平与肺转移负荷相关。我们实验室和其他实验室的流行病学调查发现SIPA1多态性与人类患者转移进展之间存在关联，这与SIPA1在小鼠和人类中作为转移易感基因的观点一致。基于人群的流行病学进一步证明了乳腺癌和其他人类癌症中存在遗传转移易感基因。因此，这些研究证实了我们最初的假设，即遗传易感性是癌症进展的重要组成部分。此外，这些结果表明，我们基于小鼠的遗传作图策略是一种可行的方法来鉴定人类相关基因，以进一步表征转移级联。随后，我的实验室越来越多地结合基因组技术来研究遗传多态性如何影响转移性疾病。结合表达技术，首先基于Affymetrix芯片的表达分析和最近的rna测序方法，与遗传分析有助于加速候选基因的验证和分析鉴定。此外，我们还整合了更复杂的遗传作图资源，主要是多样性近交系小鼠作图面板，以提高遗传作图的分辨率，并产生更接近于在人类群体中观察到的遗传多样性的实验杂交。此外，我们利用这些项目产生的资源来证明遗传背景对临床相关因素的贡献，例如乳腺癌分子亚型分类器（如PAM50）和预后基因标记（如MammaPrint）的产生。迄今为止，我的实验室已经发表了自Sipa1鉴定以来的另外16个转移相关基因和6个microrna。此外，我们还验证了另外11个基因作为转移修饰因子；这些基因处于不同的鉴定阶段或手稿准备和提交阶段。此外，我们已经启动了一系列实验，通过对PyMT模型中匹配的原发和转移性病变进行基因组景观分析，来确定转移驱动突变。这导致鉴定出三个基因在继发性肿瘤中反复突变，因此可能是转移激活突变。目前正在努力验证和描述这些基因及其下游途径如何导致转移性乳腺癌。