Cancer onset and progression involves disruptions of complex networks of biomolecular interactions in cells, as a result of genomic and epigenomic aberrations. To achieve a deeper understanding of the genetic basis of cancer and to identify novel translational directions requires moving beyond detecting simple associations between genomic aberrations and clinical endpoints. However, little is known about how the states of disease-perturbed regulatory networks are altered by such aberrations, or how aberrations ultimately lead to cellular dysfunction. The goal of the Center for Systems Analysis of the Cancer Regulome is to address this challenge by developing and applying advanced algorithms and model-based approaches to enable the interpretation of TCGA data at the level of regulatory mechanisms;and to use such knowledge for enabling principled and systematic approaches for drug target discovery and therapeutic intervention in a clinically relevant manner. The Center will build three computational pipelines that will carry out integrated analyses of TCGA-derived high-throughput experimental data sets. These pipelines will: 1) identify potential mechanisms of genomic-transcriptomic regulation associated with specific cancers and clinical parameters;2) infer networks that explain cancer type-specific transcriptional profiles, and identify molecules that may be important control nodes in these networks as a means to prioritize drug targets for therapeutic intervention;and 3) compare cancer-associated features across all cancer types within TCGA to gain insight into the regulatory basis for cancer progression in different cancer types. The results of these pipelines will be rapidly disseminated through TCGA, together with visualization tools that facilitate the exploration and evaluation of each derived regulatory mechanism.

Public Health Relevance

Cancer is a major cause of mortality and morbidity in the United States. Developing new therapies requires a deep understanding of the molecular basis of this complex genetic disease. Our integrated systems-level analysis of cancer onset and progression will map the molecular processes undertying cancer and identify potential novel drug targets for therapeutic intervention.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1-SRLB-U (O1))
Program Officer
Yang, Liming
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Institute for Systems Biology
United States
Zip Code
Sun, Yan; Hu, Limei; Zheng, Hong et al. (2015) MiR-506 inhibits multiple targets in the epithelial-to-mesenchymal transition network and is associated with good prognosis in epithelial ovarian cancer. J Pathol 235:25-36
Li, X; Liu, Y; Granberg, K J et al. (2015) Two mature products of MIR-491 coordinate to suppress key cancer hallmarks in glioblastoma. Oncogene 34:1619-28
Annala, Matti; Kivinummi, Kati; Leinonen, Katri et al. (2014) DOT1L-HES6 fusion drives androgen independent growth in prostate cancer. EMBO Mol Med 6:1121-3
Kemp, Christopher J; Moore, James M; Moser, Russell et al. (2014) CTCF haploinsufficiency destabilizes DNA methylation and predisposes to cancer. Cell Rep 7:1020-9
Hoadley, Katherine A; Yau, Christina; Wolf, Denise M et al. (2014) Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 158:929-44
Cancer Genome Atlas Research Network (2014) Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 507:315-22
Rupaimoole, Rajesha; Wu, Sherry Y; Pradeep, Sunila et al. (2014) Hypoxia-mediated downregulation of miRNA biogenesis promotes tumour progression. Nat Commun 5:5202
Cancer Genome Atlas Research Network (2014) Comprehensive molecular characterization of gastric adenocarcinoma. Nature 513:202-9
Liu, Guoyan; Sun, Yan; Ji, Ping et al. (2014) MiR-506 suppresses proliferation and induces senescence by directly targeting the CDK4/6-FOXM1 axis in ovarian cancer. J Pathol 233:308-18
Liu, Yuexin; Patel, Lalit; Mills, Gordon B et al. (2014) Clinical significance of CTNNB1 mutation and Wnt pathway activation in endometrioid endometrial carcinoma. J Natl Cancer Inst 106:

Showing the most recent 10 out of 26 publications