Proteomics Shared Resource

NIH RePORTER · NIH · P30 · $258,833 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY: Proteomics Shared Resource (PSR) Proteins are the ultimate executors of biology, with nearly all cellular processes being dependent on the molecular work performed by protein products of genes. Furthermore, there is a tremendous regulatory potential that can be acutely utilized through fine-tuning of protein function through reversible chemical post-translational modifications and interactions with other protein partners. Because of these functionalities, a majority of cancer drugs act directly on protein targets or create a dependency on a protein function (e.g., DNA damage agents that overwhelm protein enzymes involved in repair). It is now an increasing realization in the cancer research field that without knowledge of the dynamics of protein networks (i.e., proteome dynamics), genomic and transcriptomic data are often insufficient for determination of targetable, or “actionable,” events and mechanisms of resistance to treatment. The goal of proteomics in cancer research is to define perturbations of complex and dynamic protein signaling networks that are associated with development and progression of cancer and to use this information for identification of novel therapeutic targets and biomarkers that can predict response or resistance to specific therapies. We have established a comprehensive Shared Resource for protein biology with a strong background in cancer biology and protein biochemistry. Since there is no single technology platform to analyze all aspects of the cellular proteome, multiple enrichment, purification, and measurement approaches have been developed to address diverse research questions studied by DLDCCC investigators. Specifically, our Shared Resource provides targeted antibody-based protein profiling with custom RPPA platform and a suite of mass spectrometry-based assays for expression profiling and determination of protein interactions. Furthermore, recognizing the challenges of “big data,” we strive for excellence in data analysis and communication. Our services are therefore provided as beginning-to-end packages to assist investigators with up-front study design and feasibility assessment, execution of experimental analysis by various technology platforms, specialized analysis and interpretation of data, troubleshooting, and decision-making in follow-up studies.

Key facts

NIH application ID
10025015
Project number
2P30CA125123-14
Recipient
BAYLOR COLLEGE OF MEDICINE
Principal Investigator
Anna Malovannaya
Activity code
P30
Funding institute
NIH
Fiscal year
2020
Award amount
$258,833
Award type
2
Project period
2007-07-01 → 2025-06-30