The Galaxy bioinformatics framework is used by thousands of cancer researchers, primarily for genomics-based studies. It's open and flexible environment enables interoperation of diverse bioinformatics software via a user-friendly web-based interface. Despite its proven value for genomic bioinformatics, Galaxy's potential for enabling cancer research has not been fully realized. One area of emerging potential for Galaxy is multi- omic informatics. Multi-omics integrates high throughput genomic, transcriptomic, proteomic and metabolomics data to reveal new molecular discoveries in cancer. For example, integrating metabolomics information with genomic and/or proteomic data reveals biochemical consequences of gene and protein variations underlying carcinogenesis. Integration of genomic or transcriptomic data with mass spectrometry (MS)-based proteomic data (proteogenomics) identifies novel protein variants linked to genome mutations. Integration of metagenomic data with MS-based proteomic data (metaproteomics) identifies proteins expressed by microbial communities giving insights into biochemical contributions from the microbiome to carcinogenesis. Despite their potential pay-off, these multi-omic approaches require use of diverse informatics tools out of the reach of most bench researchers. Fortunately, Galaxy offers a solution. We propose to extend Galaxy and create a powerful, unified hub for multi-omic informatics. We will focus on enhancing Galaxy with a stand-alone Multi-omics Visualization Platform (MVP) for results visualization and interpretation. We will build novel Galaxy extensions enabling metabolite profiling, results interpretation and targeted clinical validation studies. We will extend current Galaxy-based tools to create a complete solution for proteogenomic and metaproteomic informatics, making easy-to-build workflows that ensure accurate results. Finally, we will empower cancer researchers to use Galaxy for multi-omics in their work via a variety of dissemination and training activities. We will achieve these outcomes via these Specific Aims: 1) Extend a Galaxy-compatible Multi-omics Visualization Platform (MVP) for enhanced results interpretation and data exchange utilizing cancer knowledge bases and informatics resources; 2) Extend Galaxy and the MVP tool for metabolite profiling in cancer research; 3) Extend Galaxy and the MVP tool for integrative genomic-proteomic informatics and workflows.; 4) Catalyze the use of multi-omic workflows and associated tools by cancer researchers via dissemination, promotion and training activities. Our work will be guided via driving cancer projects with a network of collaborators. We will partner with developers of established software and methods in different 'omic domains, and utilize world-class infrastructure at the Minnesota Supercomputing Institute. Our deliverables will directly complement other projects currently funded through the NIH ITCR program. The upshot of our work will be a large network of cancer researchers empowered to utilize high impact, multi-omic approaches, ultimately catalyzing new discoveries that will help decrease the suffering and death from cancer.

Public Health Relevance

The proposed work seeks to extend the Galaxy bioinformatics software to create a unified, publically available resource enabling integrated analysis of data that will reveal molecular connections between genes, proteins and metabolites in cancer-relevant samples. Results from these analyses will provide new information into the molecular mechanisms of cancer, leading to better diagnosis and treatment.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
5U24CA199347-02
Application #
9275443
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Li, Jerry
Project Start
2016-05-18
Project End
2020-04-30
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Biochemistry
Type
Schools of Medicine
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
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