# Precancer Atlas of Familial Adenomatous Polyposis

> **NIH NIH U2C** · STANFORD UNIVERSITY · 2023 · $970,941

## Abstract

Colorectal cancer (CRC) is the third highest cause of cancer death in the United States. Almost 80% of 
sporadic colorectal cancers have an APC gene mutation. Familial adenomatous polyposis (FAP), a hereditary 
colon cancer syndrome, is also caused by mutations in APC and affects children as young as 7 years of age. 
FAP causes hundreds of colonic polyps in affected individuals and a 100% lifetime risk of CRC. In preliminary 
efforts we have successfully collected hundreds of pre-cancerous colon polyps from individual FAP patients, 
applied genomic, epigenomic and other multi-omic analyses and begun to elucidate the impact of multiple 
types of “omic” alterations on precancerous colon polyp evolution toward CRC. We propose to use an 
integrated and collaborative approach to develop a PreCancer Atlas for colorectal adenocarcinoma using FAP 
as the disease model. We will: 
1) Establish a biospecimen collection pipeline for procurement of longitudinal tissue samples during 
surveillance colonoscopy and during prophylactic surgical colectomy, including whole blood, serum, normal 
colonic tissue, colon microbiome, benign pre-cancerous polyps, dysplastic precancerous polyps and colon 
adenocarcinomas. The material will be used for our own center and will also be available to the Human Tumor 
Atlas Network (HTAN). Medical records, longitudinal samples and all relevant metadata will also be collected. 
2) Establish a center to characterize the tissue samples with state-of-the-art omics and imaging technologies. 
These include but are not limited to whole genome sequencing, methylation, transcriptome, proteome, 
cytokine, metabolome, microbiome, and molecular imaging. 
3) Establish an analysis core that analyzes and integrates results from -omics, imaging and medical 
information, builds a spatiotemporal, multidimensional, integrative multi-omics cancer atlas, and develops 
longitudinal and predictive models for PreCancer biology and progression, as well as data portal and 
visualization framework. 
4) Establish multi-omics technologies on smaller number of samples. 
5) Perform a “multiscale deep data analysis” on a large number of samples (57) from a few people and a fewer 
number of samples (6) from many people. Use this information to guide additional data collection. 
6) Identify factors (e.g. germline genetics, microbiome, immune dysfunction) contributing to polyp 
heterogeneity between and across individuals. Build disease progression models based on these data. 
7) Make all biospecimens, information, protocols and software available to the PCA, HTAN and the general 
scientific community. 
We expect our efforts will greatly facilitate understanding CRC at its earliest stages and serve as a model for 
understanding precancerous lesions of other solid tumor malignancies.

## Key facts

- **NIH application ID:** 10900834
- **Project number:** 3U2CCA233311-01S1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** MICHAEL P. SNYDER
- **Activity code:** U2C (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $970,941
- **Award type:** 3
- **Project period:** 2023-04-04 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10900834

## Citation

> US National Institutes of Health, RePORTER application 10900834, Precancer Atlas of Familial Adenomatous Polyposis (3U2CCA233311-01S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10900834. Licensed CC0.

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