Pathway, Network and Spatiotemporal Integration of Cancer Genomics Data

项目总结 癌症测序项目已经证明，肿瘤具有极大的异质性， 反映了促进肿瘤生长的细胞机制中的各种扰动 和转移。来自同一类型癌症的不同患者的肿瘤有不同的 基因组、表观基因组和转录异常的集合。此外，肿瘤来自于 单个患者是多种细胞类型的混合体，包括正常细胞、间质细胞和多个亚群 癌细胞的数量。我们提出了一个基因组数据分析中心(GDAC)，它将开发和 应用新的计算方法解决肿瘤间和肿瘤内的挑战 异质性。这个GDAC将整合来自多个基因组表征平台的数据， 多种测序技术--包括整体测序、单细胞测序和空间测序 技术-并利用路径和交互网络的先验知识来解释 临床表型和告知治疗策略。GDAC将执行路径和网络 整合基因组特征数据，肿瘤微环境的空间分析，以及 肿瘤内异质性、肿瘤演变和网络重新布线的时间分析。这些 分析将使癌症基因组表征工作能够更准确地转化为 对更大比例的癌症患者的临床效用。GDAC将继续进行 PI对当前基因组数据分析网络(GDAN)和以前的贡献 癌症基因组图谱(TCGA)和国际癌症基因组联盟的努力 (ICGC)项目。

PROJECT SUMMARY Cancer sequencing projects have demonstrated that tumors are tremendously heterogeneous, reflecting the large diversity of perturbations in the cellular machinery that promote tumor growth and metastasis. Tumors from different patients with the same type of cancer have a diverse collection of genomic, epigenomic, and transcriptomic aberrations. Moreover, a tumor from a single patient is a mixture of cell types including normal cells, stroma, and multiple subpopulations of cancerous cells. We propose a Genome Data Analysis Center (GDAC) that will develop and apply novel computational approaches to address the challenges of inter-tumor and intra-tumor heterogeneity. This GDAC will integrate data from multiple genome characterization platforms, multiple sequencing technologies -- including bulk, single-cell, and spatial sequencing technologies – and leverage prior knowledge of pathways and interaction networks to explain clinical phenotypes and inform treatment strategies. The GDAC will perform pathway and network integration of genome characterization data, spatial analysis of tumor microenvironment, and temporal analysis of intra-tumor heterogeneity, tumor evolution, and network rewiring. These analyses will enable more precise translation of cancer genome characterization efforts into clinical utility for a larger fraction of cancer patients. The GDAC will continue the ongoing contributions of the PIs to the current Genome Data Analysis Network (GDAN) and previous efforts in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) projects.