# TCPA: an Integrated Bioinformatics Resource for Functional Cancer Proteomic Data

> **NIH NIH U24** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2020 · $689,191

## Abstract

SUMMARY/ABSTRACT
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 resea...

## Key facts

- **NIH application ID:** 10006080
- **Project number:** 5U24CA209851-05
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Han Liang
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $689,191
- **Award type:** 5
- **Project period:** 2016-09-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10006080

## Citation

> US National Institutes of Health, RePORTER application 10006080, TCPA: an Integrated Bioinformatics Resource for Functional Cancer Proteomic Data (5U24CA209851-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10006080. Licensed CC0.

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