# An integrated functional proteomics platform for accelerated discovery of isoform-specific determinants of cancer

> **NIH NIH R33** · UNIVERSITY OF VIRGINIA · 2024 · $412,365

## Abstract

PROJECT SUMMARY
 Aberrant splicing is a major mechanism leading to the progression of cancer, and newly emerging
experimental and computational approaches reveal a critically important, high-resolution view of the
heterogeneity of cancer to most directly pinpoint biomarkers, drug targets, and neoantigens for
immunotherapies. Current gene-targeted cancer therapies are primarily hampered by the extreme
genetic heterogeneity observed across patient populations. “One gene, one function, one disease” model
cannot reconcile with the complexity that different mutations of the same gene often lead to different
phenotypes. A recent pan-cancer characterization of aberrant splicing we conducted revealed thousands
of potential driver mutations that alter the activity of splice regulatory regions and their target protein
isoforms. In the recent past, genome and exome sequencing projects have identified thousands of
genetic mutations in cancer patients, including somatic and germline mutations. To date, most literature
has focused on studying mutations that affect the encoded protein amino acid sequence. Recent
evidence has emerged to indicate possible functions of “silent” mutations, which act to deregulate
alternative splicing, leading to production of aberrant levels or identities of distinct protein isoforms.
 Here we propose a set of innovative, broadly applicable technologies to systematically link silent
cancer mutations to splicing events and the functional impacts of their consequent protein isoforms.
Specifically we will pursue the following two aims: (1) SysMap-Splice: An integrated systems approach
coupled with long-read sequencing to discover and characterize full-length protein isoform drivers in
cancer; and (2) Can-IsoPPI: An enhanced platform to investigate full-length splice isoform-mediated PPI
rewiring in cancer, based on affinity purification-mass spectrometry. Together, our integrative approach
is both innovative and significant, because it will provide insights in prioritizing cancer-causing genotypes
that have a direct impact on protein isoform expression of a patient, a critical step towards isoform-
resolved personalized precision medicine, drug targets, and neoantigen discovery.
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## Key facts

- **NIH application ID:** 10798690
- **Project number:** 1R33CA281919-01A1
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Gloria Sheynkman
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $412,365
- **Award type:** 1
- **Project period:** 2024-03-01 → 2027-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10798690

## Citation

> US National Institutes of Health, RePORTER application 10798690, An integrated functional proteomics platform for accelerated discovery of isoform-specific determinants of cancer (1R33CA281919-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10798690. Licensed CC0.

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