# Proteomics Shared Resource

> **NIH NIH P30** · BAYLOR COLLEGE OF MEDICINE · 2021 · $251,422

## 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:** 10239125
- **Project number:** 5P30CA125123-15
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Anna Malovannaya
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $251,422
- **Award type:** 5
- **Project period:** 2007-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10239125

## Citation

> US National Institutes of Health, RePORTER application 10239125, Proteomics Shared Resource (5P30CA125123-15). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10239125. Licensed CC0.

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