# Copy Number Alterations in Low Mutation Cancer

> **NIH NIH R00** · MEDICAL UNIVERSITY OF SOUTH CAROLINA · 2020 · $246,525

## Abstract

Abstract
Two general types of genetic alterations drive cancer progression; mutations and copy number alterations
(CNAs). Research into mutations such ABL fusions and BRAF have yielded powerful targeted therapeutics.
However, not all cancers are mutated in targetable genes; 48% of serous ovarian cancers (OV) have no
oncogenic mutation other than in p53. For these low-mutation tumors and cancer types, the most likely culprit
for tumorigenesis and drug resistance lies in CNAs. The OV genome is remarkably unstable; in the average
tumor, 2/3 of genes display a copy number change: roughly 1/3 are deleted and 1/3 are increased in gene
dosage. One known CNA driver in ovarian cancer is a homozygous loss in BRCA1/2 genes in ~10% of
patients; however 99% of deletions in SOC are heterozygous, not homozygous deletions. This remaining 99%
of deletions must contain tumor suppressors which contribute to cancer progression with only heterozygous
losses, which accumulate along individual pathways. We developed novel "HAPTRIG" pathway analysis of
loss events in whole genome datasets with the ability to work in highly altered backgrounds like OV and can
perform calculations of multiple pathways at once. We discovered that the cellular recycling pathway of
autophagy is universally (98% of tumors), redundantly (at least 4 genes are deleted in the average tumor), and
uniquely (more than any other tumor type) suppressed by deletions in serous ovarian cancer. The most
impactful lost autophagy genes are BECN1 and LC3B. We found BECN1 and LC3B loss is to contribute to OV
aneuploidy and monoallelic BECN1 loss to accelerate OV tumorigenesis in a mouse model. We propose to
develop our understanding of tumor CNAs by [1] analyzing every tumor for pathway disruptions in >3,000
known molecular pathways using an automated HAPTRIG bioinformatics tool, [2] scoring the most impactful
genes in each pathway/tumor pair to identify novel CNA drivers of cancer, and [3] release the tool in a user-
friendly portal for any oncologist to perform CNA pathway analysis on any cohort of tumors. Since our top
predictions from the CNA networks were validated to impact genomic copy number variability, oncogenesis,
and therapy targeting in OV, we propose to provide further mechanistic understanding of CNA losses by [1]
analyzing the types and heterogeneity of CNAs caused by BECN1 and LC3B depletion, [2] the metabolic,
CNA, and stem cell changes present in BECN1+/- murine OV tumors, and [3] assaying autophagic flux and
metabolic alterations for chloroquine therapy, which selectively kills BECN1 and LC3B depleted OV cells.

## Key facts

- **NIH application ID:** 9841919
- **Project number:** 5R00CA207729-04
- **Recipient organization:** MEDICAL UNIVERSITY OF SOUTH CAROLINA
- **Principal Investigator:** Joe R Delaney
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $246,525
- **Award type:** 5
- **Project period:** 2018-12-01 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9841919

## Citation

> US National Institutes of Health, RePORTER application 9841919, Copy Number Alterations in Low Mutation Cancer (5R00CA207729-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9841919. Licensed CC0.

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