# Proteogenomic Characterization of Tumor Tissues and Preclinical Models with High Precision

> **NIH NIH U24** · JOHNS HOPKINS UNIVERSITY · 2022 · $1,157,752

## Abstract

Summary
During the last 10 years of both CPTAC2 and CPTAC3, the JHU Proteome Characterization Center (JHU/PCC)
has repeatedly demonstrated superior technological innovation and robust data generation that have played
critical roles in the success of CPTAC's core mission of accelerating the understanding of the molecular basis of
cancer through the application of large-scale proteome and genome analysis technologies to different cancer
types. As one of the 3 current CPTAC3 PCCs, we established robust and standardized proteomic analysis
protocols and technologies and applied them to 7 human cancer cohorts and an additional 200 patient-derived
xenografts from the Patient-Derived Models Repository. Together with the Proteogenomic Data Analysis Centers
(PGDACs), we published articles on integrated proteogenomic studies in four cancer types. For our CPTAC4
PCC application, the overarching goal of our PCC is to generate accurate and reproducible data using
sensitive, quantitative, and standardized technologies. We will leverage our established Center's
infrastructure and capitalize on our success in clinical cancer proteogenomic discoveries to characterize
proteins, protein modifications, and protein complexes associated with genomic alterations of cancer
from additional human tumor types and pre-clinical models. We will identify unique features that are inherent
to proteins such as post-translational modifications covering acetylation and ubiquitination, as well as protein-
protein interactions in addition to glycosylation and phosphorylation that have been included in our current PCC.
We propose a three-step strategy to characterize defined sets of genomics-characterized samples using
technology platforms validated during CPTAC3: (1) Discovery of target proteins from both clinical specimens
and preclinical models using quantitative proteomics by tandem mass tags and data dependent acquisition mass
spectrometry; (2) Verification of findings using orthogonal data-independent acquisition mass spectrometry; and
(3) Confirmation of the verified targets using high-throughput, CPTAC Tier 2 analytically-validated targeted
Multiple Reaction Monitoring Mass Spectrometry (MRM-MS) assays. We further propose pilot studies for
technology improvement. While this PCC application is focused on the proteomic characterization of clinical
specimens and preclinical models, we believe that the understanding of and the expertise in proteogenomic data
analysis and translation will be critical for the success of the PCC and the overall CPTAC network. We have
assembled a team of outstanding investigators with complementary expertise and years of experience in the
CPTAC program (CPTAC2 and CPTAC3), and evidence of successful collaborations with investigators/PIs from
the CPTAC PGDACs and Proteogenomic Translational Research Centers (PTRCs). We believe that our PCC
offers the best opportunity for the successful characterization of biological and clinical specimens to discover
an...

## Key facts

- **NIH application ID:** 10440934
- **Project number:** 1U24CA271079-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** DANIEL Wanyui CHAN
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,157,752
- **Award type:** 1
- **Project period:** 2022-06-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10440934

## Citation

> US National Institutes of Health, RePORTER application 10440934, Proteogenomic Characterization of Tumor Tissues and Preclinical Models with High Precision (1U24CA271079-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10440934. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*