Reverse-phase protein arrays (RPPAs) offer a powerful functional proteomic approach to investigate molecular mechanisms and response to therapy in cancer. MD Anderson Cancer Center has been a leader in the implementation of this antibody-based technology that can assess many protein markers across large numbers of samples in a cost-effective, sensitive and high-throughput manner. The platform currently assesses ~300 protein markers, covering all major signaling pathways and most drug targets. Its utility was demonstrated through its selection as the sole platform for characterizing >10,000 patient samples through The Cancer Genome Atlas (TCGA); and recently it has been designated as one of two NCI Genome Characterization Centers, and will characterize up to ~10,000 samples from ongoing NCI initiatives and other consortium projects. For TCGA project, the applicants built The Cancer Proteome Atlas (TCPA), a web platform for visualizing and analyzing RPPA data, which has a community of >5,000 users worldwide. The long-term goal is to promote the ability of functional proteomics to impact cancer research and the development of relevant therapeutic strategies. The current objective is to expand the scope of TCPA by adding new functionalities and datasets, and to enhance and improve its existing analytic capabilities. Working relationships have been formed to link TCPA with other widely used bioinformatic resources (e.g., cBio, UCSC Genome Browsers, Firehose and Synpase) and other ITCR projects. An experienced, multidisciplinary team has been assembled to pursue four specific aims:
Aim #1. Develop an open source, all-in-one software package for processing RPPA data. This effort will standardize each informatic step for RPPA data generation including experimental design, quality control, and data normalization. The resultant program will be exported to other RPPA facilities.
Aim #2. Expand and enhance our existing web platform for the analysis of patient-cohort RPPA data. The web platform will cover other patient cohorts, incorporate other types of molecular/clinical data, and provide pathway/network-based analytics.
Aim #3. Build a user-friendly, interactive, open web platform for the analysis of cell line RPPA data. This effort will collect and compile RPPA data of >1,500 cell lines, and develop a web platform parallel to Aim #2.
Aim #4. Promote TCPA and active interaction with the user community. This effort will provide documentation, hands-on workshops, and bug fixes, and build web APIs for interaction with other tools. The expected outcome is the first, dedicated bioinformatic resource that fully integrates RPPA data generation, analysis and user feedback, allowing for fluent exploration and analysis of high-quality proteomic data in a rich context. The project is important because it will greatly enhance the quality and reproducibility of RPPA data from important consortium projects; substantially reduce barriers biomedical researchers face in mining complex functional proteomic data; serve as a hub for integrating proteomic data into other widely used bioinformatic resources; and directly facilitate development of protein markers for precision cancer medicine.
The bioinformatics resource for generating and analyzing cancer functional proteomic data proposed in this application is relevant to public health because it will greatly help biomedical researchers understand the molecular mechanisms and treatment responses of human cancer, thereby facilitating the development and implementation of precision cancer medicine. Thus, this project is relevant to the NIH mission to develop fundamental knowledge that will reduce the burden of illness and disability.
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