Systems Bioinformatics Core

系统生物信息学核心（核心B）总结 H-CARR旨在询问获得性顺铂的基因组、转录组和代谢组驱动因素 HNSCC中的耐药性。项目1、2和3旨在协同实现以下双重最终目标： 鉴定顺铂耐药性的可靠生物标志物和2）开发预防其发展的策略 或收购。项目1将生成稳态和通量代谢组学数据，这些数据将与 项目2中生成的基因组和转录组数据。这些数据集将一起根据 使用非侵入性代谢成像和人类的基因组和转录组学分析获得的人类数据 HNSCC循环肿瘤细胞（CTC）。 核心B被设想为系统生物信息学核心，它将合并来自所有3个系统的数据流。 将项目纳入对顺铂反应和耐药性发展的一个连贯的多组学理解。核心 由Coarfa博士领导的B负责执行每个项目中提出的复杂数据分析， 开发用于数据采集、分析和解释的管道，这些管道可以在H- 卡尔和更广泛的ARTNet科学界。核心B将与核心A（行政）合作， 为模型（PDX、细胞系）生成、分析管道和 与其他研究者共享原始数据和处理后的数据。核心小组将利用现有的机构专门知识 通过大数据分析，沿着Coarfa博士与其他研究人员建立的科学关系， 开发一个最先进的分析平台，可用于表征和了解所获得的 对多种实体瘤和全身性药物的耐药性。

Systems Bioinformatics Core (Core B) SUMMARY H-CARR is designed to interrogate the genomic, transcriptomic and metabolomic drivers of acquired cisplatin resistance in HNSCC. Projects 1, 2 and 3 are designed to synergize with the ultimate dual objective of: 1) identifying reliable biomarkers of cisplatin resistance and 2) developing strategies for preventing its development or acquisition. Project 1 will generate steady state and flux metabolomic data which will be integrated with the genomic and transcriptomic data generated in Project 2. Together, the datasets will then be validated against human data acquired using non-invasive metabolic imaging and genomic and transcriptomic analysis of human HNSCC circulating tumor cells (CTCs). Core B is envisioned as a Systems Bioinformatics Core which will coalesce the datastreams from all 3 Projects into one coherent multi ‘omics understanding of cisplatin response and development of resistance. Core B, led by Dr. Coarfa is tasked with performing the complex data analysis proposed in each individual Project and developing pipelines for data acquisition, analysis and interpretation which can be rapidly deployed within H- CARR and the broader ARTNet scientific community. Core B, in collaboration with Core A (Administrative) will develop a near real time reporting system for both model (PDX, cell line) generation, analytical pipelines and raw and processed data sharing with other investigators. The Core will leverage existing institutional expertise with big data analysis, along with Dr. Coarfa’s established scientific relationships with the other investigators, to develop a state of the art analytical platform that can be deployed to characterize and understanding acquired resistance across multiple solid tumors and systemic agents.