The proposed Genome Data Analysis Center B (GDAC B) will work cooperatively with other GDACs funded by The Cancer Genome Atlas (TCGA) project to (i) develop an innovative, integrative pipeline for systems- level analysis of TCGA's molecular profiling data on many different types of human tumors and (ii) apply that pipeline and its component modules to TCGA data to address important biological and clinical questions. An overarching goal is to 'personalize'the management of patients'cancers on the basis of new tumor biomarkers and biosignatures. For the first time, it is easier to generate millions of data points on tumors than to analyze or interpret those data, hence the bioinformatic challenge is formidable. The pipeline will be constructed using the Agile software development paradigm and semantic web query architecture. It will be based on novel algorithms and modules developed by participants in the GDAC. Included will be modules for data integration, data visualization, pathway analysis, and systems biological interpretation, all designed to be user-friendly for the bench researcher and clinician. Those modules will be interfaced with additional ones developed by other GDACs, All development will adhere to standards of TCGA and the Cancer Biomedical Informatics Grid (caBIG) and will provide controlled access to ensure confidentiality of personally identifiable data. The proposed GDAC team brings to this project expertise in bioinformatics, biostatistics, software engineering, high-throughput molecular profiling technologies, systems-oriented biology, biomarker studies, pathology, and clinical research. The three co-PIs (for bioinformatics, systems biology, and clinical research) have each participated actively in TCGA since its inception, as have other members of the team, including the lead software engineer. A major strength is the University of Texas M. D. Anderson Cancer Center (MDACC) as an institution. MDACC has been, and presumably will continue to be, the largest source of tumor specimens for TCGA. As one of the country's foremost cancer centers, with by far the largest cancer clinical research program, MDACC has unparalleled expertise for follow up on medically important leads that result from the development and application of the pipeline to TCGA data.

Public Health Relevance

The Cancer Genome Atlas project will generate multi-faceted molecular profiles on 25 different human cancer types. The result will be a treasure trove of information that can be used to personalize cancer diagnosis and treatment. Analysis of the data is a bottleneck, which the proposed Genome Data Analysis Center will alleviate by building an innovative, advanced bioinformatic analysis pipeline.

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
University of Texas MD Anderson Cancer Center
Biostatistics & Other Math Sci
Other Domestic Higher Education
United States
Zip Code
MartĂ­nez, E; Yoshihara, K; Kim, H et al. (2015) Comparison of gene expression patterns across 12 tumor types identifies a cancer supercluster characterized by TP53 mutations and cell cycle defects. Oncogene 34:2732-40
Yoshihara, K; Wang, Q; Torres-Garcia, W et al. (2015) The landscape and therapeutic relevance of cancer-associated transcript fusions. Oncogene 34:4845-54
Yuan, Yuan; Van Allen, Eliezer M; Omberg, Larsson et al. (2014) Assessing the clinical utility of cancer genomic and proteomic data across tumor types. Nat Biotechnol 32:644-52
Cancer Genome Atlas Research Network (2014) Comprehensive molecular profiling of lung adenocarcinoma. Nature 511:543-50
Akbani, Rehan; Ng, Patrick Kwok Shing; Werner, Henrica M J et al. (2014) A pan-cancer proteomic perspective on The Cancer Genome Atlas. Nat Commun 5:3887
Tucker, Susan L; Gharpure, Kshipra; Herbrich, Shelley M et al. (2014) Molecular biomarkers of residual disease after surgical debulking of high-grade serous ovarian cancer. Clin Cancer Res 20:3280-8
Purwaha, Preeti; Silva, Leslie P; Hawke, David H et al. (2014) An artifact in LC-MS/MS measurement of glutamine and glutamic acid: in-source cyclization to pyroglutamic acid. Anal Chem 86:5633-7
Lorenzi, Philip L; Claerhout, Sofie; Mills, Gordon B et al. (2014) A curated census of autophagy-modulating proteins and small molecules: candidate targets for cancer therapy. Autophagy 10:1316-26
Wang, Yong; Waters, Jill; Leung, Marco L et al. (2014) Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 512:155-60
Torres-GarcĂ­a, Wandaliz; Zheng, Siyuan; Sivachenko, Andrey et al. (2014) PRADA: pipeline for RNA sequencing data analysis. Bioinformatics 30:2224-6

Showing the most recent 10 out of 52 publications