# Development of a cancer driver mutation screening panel to predict carcinogenesis using error corrected duplex sequencing technology

> **NIH NIH N01** · BATTELLE MEMORIAL INSTITU · 2024 · $544,131

## Abstract

The main premise for the current project is that cancer is a chronic disease and the earliest molecular diagnostic time point in a rodent model for any reliable indicator of carcinogenicity may be in the order of 3-6 months (the time likely needed for mutations to occur and drive clonal expansion that may or may not be detectable histologically). Examination of cancer driver genes, mutation signatures, and other transcripts at these subchronic timepoints will likely probe the preneoplastic or carcinogenic processes that have the greater predictive potential for a carcinogenic hazard. The hypothesis is that there will be additional clonally expanded pathogenic mutations and cancer driver genes in the treated animals compared to the age-matched controls in the study. And the abundance and size of those clones will be greatest in the most cancer-prone tissues and/or in samples collected at later time points. This study will also establish a database on mutation endpoints that accumulate naturally due to normal aging and this information can be used as a reference in future studies. Examination of the cancer driver genes, mutation signatures, and transcriptomic alterations from subchronic (~3-6 months) animal studies or long-term (~3 months) in vitro exposures for predicting carcinogenicity is a novel approach.

## Key facts

- **NIH application ID:** 11219541
- **Project number:** 273201700005C-P00022-9999-22
- **Recipient organization:** BATTELLE MEMORIAL INSTITU
- **Principal Investigator:** BARNEY SPARROW
- **Activity code:** N01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $544,131
- **Award type:** —
- **Project period:** 2017-09-26 → 2025-09-25

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11219541

## Citation

> US National Institutes of Health, RePORTER application 11219541, Development of a cancer driver mutation screening panel to predict carcinogenesis using error corrected duplex sequencing technology (273201700005C-P00022-9999-22). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11219541. Licensed CC0.

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