Genetic mechanisms underlying sexual dimorphism in cancer and response to therapy

项目总结/摘要 癌症包括具有显著发病率和死亡率的多种疾病。几乎所有常见的 癌症在例如发病率、预后或对治疗的反应方面表现出某种形式的两性异形。 这种二态性被假设来自于雄性和雌性之间激素的差异， 性染色体和环境暴露;然而，这些差异的分子基础仍然存在 大部分未知。理解这种二态性是癌症精确医学的基础， 可能导致发现新的生物标志物，治疗靶点和改善的结果。我们建议 通过以下目的发现癌症中两性异形的分子基础：目的1将 描述基因表达的性别二态性及其在肿瘤类型内和肿瘤类型之间的调节 癌症基因组图谱（TCGA）利用TCGA，我们将描述性二态性， 转录组水平及其在癌症内和跨癌症的潜在基因组和表观遗传原因。目标2将 描述癌症易感性的遗传遗传成分中的性二态性， 常见的癌症利用最大的癌症全基因组关联研究的数据，我们将寻找 男性和女性之间遗传结构的差异。我们决定了 每种癌症的遗传成分在性别之间共享，并估计性别特异性共享的程度 跨癌症。使用多种遗传模型，我们将进行性别意识关联研究，以确定 影响男性和女性不同的基因变异。我们将测试一个遗传风险模型， 相同的等位基因影响两性，但风险较低的性别将需要更多或更强的遗传风险因素， 发展疾病。我们将测试性染色体上编码的特定风险或保护因素， 性别差异。我们将测试基因-性别相互作用，即常染色体基因座在性别依赖性中起作用。 方式，有或没有生殖介导的或其他两性异形作用于基因表达 水平目的3将描述性二态性对治疗的反应，并定义其分子机制。 特征和机制促成了这种二态性。利用分子和表型药物 从癌症基因组计划（CGP）的1000多个癌细胞系的反应数据，我们将建立性别- 然后，我们将应用于来自全套基因表达数据的药物反应的特定预测模型。 TCGA肿瘤样本，以插补每个TCGA样本的性别特异性药物应答。我们将相互关联 针对TCGA肿瘤分子特征的药物应答，重点关注目标1和2中确定的药物应答， 候选人建议我们的初步数据和文献。我们将从功能上验证预测的性行为 使用细胞模型，包括淋巴母细胞样细胞系组，人 肝细胞和癌细胞系。这项研究的结果将定义遗传和基因组特征， 在癌症生物学、易感性和对治疗的反应中的性别二态性。

PROJECT SUMMARY/ABSTRACT Cancer comprises a diverse group of diseases with significant morbidity and mortality. Nearly all common cancers exhibit some form of sexual dimorphism, for example in incidence, prognosis, or response to therapy. This dimorphism has been hypothesized to derive from differences between males and females in hormones, sex chromosomes, and environmental exposures; however the molecular basis of these disparities remains largely unknown. An understanding of this dimorphism is fundamental to precision medicine in cancer, and may lead to discovery of novel biomarkers, therapeutic targets, and improved outcomes. We propose to discover the molecular basis of sexual dimorphism in cancer though the following Aims: Aim 1 will characterize sexual dimorphism in gene expression and its regulation within and between tumor types of NCI's The Cancer Genome Atlas (TCGA). Leveraging TCGA, we will characterize sexual dimorphism at the transcriptome level and its potential genomic and epigenetic causes within and across cancers. Aim 2 will characterize sexual dimorphism in the heritable genetic component of cancer susceptibility across common cancers. Utilizing data from the largest genome-wide association studies of cancer we will search for differences in the genetic architecture between males and females. We determine what proportion of the heritable component of each cancer is shared across sexes, and also estimate how much sex-specific sharing across cancers. Using multiple genetic models, we will perform sex-aware association studies to identify genetic variants that affect males and females differently. We will test a model for genetic risk, whereby the same alleles affect both sexes, but the lower-risk sex would require more or stronger genetic risk factors to develop disease. We will test for specific risk or protective factors encoded on the sex chromosomes that affect the sexes differentially. We will test for gene-sex interactions whereby autosomal loci act in a sex-dependent manner, with or without hormonally-mediated or other sexual dimorphism acting at the gene expression level. Aim 3 will characterize sexual dimorphism in response to therapeutics and define the molecular features and mechanisms contributing to that dimorphism. Utilizing molecular and phenotypic drug response data from over 1000 cancer cell lines from the Cancer Genome Project (CGP), we will build sex- specific predictive models of drug response that we will then apply to gene expression data from the full set of TCGA tumor samples to impute a sex-specific drug response for each TCGA sample. We will correlate imputed drug responses to TCGA tumor molecular features, with focus on those identified in Aims 1 and 2 and candidates suggested by our preliminary data and the literature. We will functionally validate predicted sexually dimorphic response to therapy using cell models, including panels of lymphoblastoid cell lines, human hepatocytes, and cancer cell lines. The results of this study will define genetic and genomic features that underlie sexual dimorphism in cancer biology, susceptibility, and response to therapeutics.