# Predicting actionable cancer vulnerabilities enabled by mutant-directed protein-protein interactions

> **NIH NIH R21** · EMORY UNIVERSITY · 2022 · $182,909

## Abstract

Cancer is the second leading cause of death worldwide, causing more than 10 million deaths every year. In
response, tremendous efforts have been made over the past decades to understand the molecular mechanisms
of tumorigenesis and inform new therapeutic strategies in cancer. Unraveling the cancer genome and proteome
landscapes revealed that genomic alterations, such as missense mutations, promote tumorigenesis by rewiring
networks of protein-protein interactions (PPI). However, the understanding of how mutant-directed neomorph
PPIs (neoPPI) lead to the acquisition of cancer hallmarks and the discovery of neoPPI-enabled cancer
vulnerabilities remain major challenges. We propose to address this challenge by developing novel
computational methods termed Averon Notebook to discover actionable vulnerabilities enabled by rewired
oncogenic networks. To achieve this goal, we will leverage our expertise in both cancer bioinformatics and
experimental cancer biology demonstrated in numerous publications and long-time participation in the Cancer
Target Discovery and Development (CTD^2) Network of the National Cancer Institute. Over the past decade, we
have established comprehensive bioinformatics workflows and novel analytical tools to collect, process,
integrate, and analyze different types of cancer-related data. To integrate cancer genomics data with protein-
protein interaction networks and clinical compounds, we have developed the OncoPPi Portal, which has already
enabled the discovery of multiple new molecular mechanisms of tumorigenesis. In this project, we will capitalize
on our expertise in computational science and cancer biology to develop i) a new algorithm to determine the
neoPPI-regulated biological programs, and ii) methods to determine actionable vulnerabilities in neoPPI-
regulated pathways. Ultimately, this project will provide the first computational environment specially designed
to rapidly identify actionable targets and pathways enabled by mutant-directed protein-protein interactions to
inform target discovery in cancer.

## Key facts

- **NIH application ID:** 10528836
- **Project number:** 1R21CA274620-01
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** ANDREY IVANOV
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $182,909
- **Award type:** 1
- **Project period:** 2022-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10528836

## Citation

> US National Institutes of Health, RePORTER application 10528836, Predicting actionable cancer vulnerabilities enabled by mutant-directed protein-protein interactions (1R21CA274620-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10528836. Licensed CC0.

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