Modeling the impact of mutations in ubiquitin ligase genes on transcriptional programs in endometrial cancer

模拟泛素连接酶基因突变对子宫内膜癌转录程序的影响

• 批准号: 9246450
• 负责人: Christina S Leslie
• 金额: $ 18.64万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9246450
• 关键词: ATAC-seq; Binding; Cancer cell line; Carboplatin; Carcinoma; Catalogs; Cell Line; Cell division; ChIP-seq; Characteristics; Clinical; Complex; Computer Simulation; Data; Data Sources; Encyclopedias; Endometrial; Endometrial Carcinoma; Endometrial Neoplasms; Enhancers; Event; FBXW7 gene; Frequencies; Gene Expression; Genes; Genetic; Genetic Transcription; Genomics; Growth; Histologic; Histones; Link; Malignant Female Reproductive System Neoplasm; Malignant Neoplasms; Measures; Methodology; Modeling; Mutate; Mutation; Ovarian; Ovarian Serous Adenocarcinoma; PTEN gene; Paclitaxel; Pathway interactions; Pattern; Pharmaceutical Preparations; Phase; Phosphoproteins; Platinum; Promoter Regions; Protein Array; Proteins; Proteomics; Publishing; Reporting; Resistance; Role; Serous; Signal Pathway; Signal Transduction; Somatic Mutation; TP53 gene; The Cancer Genome Atlas; Tumor Suppressor Proteins; Ubiquitin; United States; Uterine Cancer; Uterine Corpus Carcinosarcoma; Uterine Neoplasms; Uterus; Validation; Woman; Work; base; cancer genomics; cancer subtypes; chemotherapy; comparative; computer framework; epigenomics; experimental study; follow-up; genomic profiles; mRNA Expression; mutant; novel; ovarian neoplasm; phosphoproteomics; programs; public health relevance; response; tool; transcription factor; transcriptome sequencing; transcriptomics; tumor; ubiquitin ligase; ubiquitin-protein ligase

 DESCRIPTION (provided by applicant): Modeling the impact of mutations in ubiquitin ligase genes on transcriptional programs in endometrial cancer Abstract: Endometrial cancer is the most common gynecological cancer in the United States and has been the subject of two TCGA studies, a recently published characterization of uterine corpus endometrial carcinomas (ECs) and an ongoing study of uterine carcinosarcomas (UCs), a rare and aggressive subtype. A pan-cancer analysis reveals a strikingly high frequency of mutations of specific ubiquitin pathway genes in uterine cancers: FBXW7, SPOP, and RNF43, all encoding substrate recognition proteins in distinct E3 ubiquitin ligase complexes, and altered by somatic mutations in ~44% of UCs and ~25% of ECs based on TCGA analysis. While these genes have known or proposed tumor suppressor functions in other cancers, they are little studied in endometrial cancer. We have recently developed a novel computational approach for exploiting parallel phosphoproteomics (reverse-phase protein array) and mRNA expression (microarray or RNA-seq) data available for large tumor sets through TCGA to link dysregulation of upstream signaling pathways with altered transcriptional response through the transcriptional circuitry. Importantly, our approach provides a statistically principled framework for interpreting the impact of mutations and copy number events in terms of altered transcription factor and signaling activity. We propose to develop and apply our integrative modeling approach to interpret the role of frequently mutated ubiquitin ligase genes in endometrial cancer. We will pursue a major methodological advance in the computational model by incorporating detailed epigenomic information from appropriate cell line models in order to represent transcription factor binding signals in enhancers. We will also use comparative modeling of two genomically similar tumor types, serous ovarian and serous endometrial carcinomas, to potentially link the higher frequency of FBXW7 mutations in endometrial tumors to chemotherapeutic resistance. More broadly, this work will provide general methodological tools to enable the study of other classes of somatically altered genes across tumor types.

 描述（由申请人提供）：模拟泛素连接酶基因突变对子宫内膜癌转录程序的影响 摘要：子宫内膜癌是美国最常见的妇科癌症，并且一直是两项 TCGA 研究的主题，这是最近发表的一项表征子宫体子宫内膜癌 (EC) 和正在进行的子宫癌肉瘤 (UC)（一种罕见且侵袭性的 A 亚型）的研究。泛癌分析揭示了子宫癌中特定泛素通路基因的突变频率惊人地高：FBXW7、SPOP 和 RNF43，所有这些都编码不同 E3 泛素连接酶复合物中的底物识别蛋白，并在约 44% 的 UC 中因体细胞突变而改变约 25% 的 EC 基于 TCGA 分析，虽然这些基因在其他癌症中具有已知或提议的肿瘤抑制功能，但在子宫内膜癌中的研究却很少。我们最近开发了一种新的计算方法，通过 TCGA 利用可用于大型肿瘤集的并行磷酸蛋白质组学（反相蛋白阵列）和 mRNA 表达（微阵列或 RNA-seq）数据，通过转录将上游信号通路的失调与转录反应联系起来。重要的是，我们的方法提供了一个技术原理框架来解释影响。 我们建议开发并应用我们的综合建模方法来解释频繁突变的泛素连接酶基因在子宫内膜癌中的作用。我们还将使用两种基因组相似的肿瘤类型（浆液性卵巢癌和浆液性子宫内膜癌）的比较模型，通过整合来自适当细胞系模型的详细表观基因组信息来表示增强子中的转录因子结合信号。将子宫内膜肿瘤中较高频率的 FBXW7 突变与化疗耐药联系起来，更广泛地说，这项工作将为研究跨肿瘤类型的其他类别的体细胞改变基因提供通用的方法学工具。