# Cancer Center Support Grant (CCSG)

> **NIH NIH P30** · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · 2023 · $500,000

## Abstract

PROJECT SUMMARY
Circular extrachromosomal DNA (ecDNA) is a special type of structural variant and a common vehicle of high
oncogene amplification in cancers. Due to the lack of centromeres, ecDNAs can segregate unevenly to daughter
cells during cell division, leading to substantial cell-to-cell variability and a high copy number of ecDNAs in some
cells. ecDNAs have been found to be important prognostic markers in some cancers. Mechanistically, ecDNAs
can create many copies of proto-oncogenes and up-regulate their expression by providing a high chromatin
accessibility environment and sometimes rewiring of enhancer targeting.
 Identifying ecDNAs from sequencing data is challenging due to complex rearrangements of DNA segments
in the ecDNA, which make read alignment and inference of segment connection structures non-trivial. In addition,
other types of non-ecDNA genomic rearrangements can also confuse the inference process. To address these
issues, we have previously developed and thoroughly tested a computational pipeline that can accurately identify
ecDNA from whole-genome sequencing data. Using the pipeline, we have discovered that ecDNA is associated
with higher cancer recurrence rate and poorer patient survival in medulloblastoma.
 This project aims at facilitating the investigations of the prevalence, prognostic value, and functional
significance of ecDNA in other childhood, adolescent and young adult (AYA) cancers. We will collect sequencing
data from these cancer types for more than 3,500 tumor samples. We will apply our established computational
pipeline to identify ecDNAs from all these samples. We will then build a web portal such that all these results are
readily accessible to the public. The web portal will also provide functionalities for performing various kinds of
comparisons between groups of samples, patients, or ecDNAs and visualize the results using standard plots.
For example, users can define groups of patients with different sex or age/ethnicity and compare how their
cancer recurrence rates and survival time are affected by presence of ecDNA or specific genes contained in the
ecDNA. Such comparisons can identify groups of patients particularly susceptible to ecDNA-associated poor
prognosis and suggest ways to perform patient stratification. In our project we will also systematically perform
this type of comparisons for groups defined by all possible single- and double-variable combinations, with the
statistical significance of all comparison results carefully evaluated using rigorous procedures. All these results
will also be made accessible on our web portal. The statistically significant results can be used by anyone
studying childhood and AYA cancers to form concrete hypotheses and investigate further.
 Overall, our resource will substantially lower the barrier of studying ecDNAs in childhood and AYA cancers.
Our resource will also contribute toward the Childhood Cancer Data Initiative by supplying information about the
no...

## Key facts

- **NIH application ID:** 10880000
- **Project number:** 3P30CA030199-42S1
- **Recipient organization:** SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE
- **Principal Investigator:** Zeev A. Ronai
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $500,000
- **Award type:** 3
- **Project period:** 1997-05-01 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10880000

## Citation

> US National Institutes of Health, RePORTER application 10880000, Cancer Center Support Grant (CCSG) (3P30CA030199-42S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10880000. Licensed CC0.

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