Abstract LE03-01: Functional and computational approaches to uncover selection advantages of cancer aneuploidy

Abstract

Abstract Aneuploidy, including the gain or loss of whole chromosomes or chromosome arms, is a near-universal feature of cancer. We previously applied methods that define chromosome arm aneuploidy to over 10,000 tumors in the Cancer Genome Atlas (TCGA). Cancer subtypes are often characterized by tumor specific patterns of chromosome arm copy number alterations and breakpoints; for example, squamous cell carcinomas (SCCs) from different tissues of origin are characterized by chromosome 3p (chr3p) loss and chromosome 3q (chr3q) gain. From the TCGA aneuploidy data, we developed an algorithm called BISCUT to distinguish peak regions of aneuploidy breakpoints on each chromosome arm. BISCUT identified loci affected by broad copy number alterations that provide fitness advantages or disadvantages both within individual cancer types and across cancers. Our analyses are consistent with selection being the primary driver of aneuploidy events in cancer. Recent advances in genome engineering allow generation of large chromosomal alterations and validation of findings from patient genomic data. We used the CRISPR-Cas9 system to delete one copy of chr3p in a human immortalized lung epithelial cell line similar to the putative cell-of-origin in lung SCC. Consistent with patient data, expression of chr3p genes was decreased upon deletion, as well as increased expression of interferon response genes. Cells with chr3p deletion initially proliferated more slowly than their siblings. Interestingly, after several passages in culture, this proliferation defect was rescued in chr3p deleted cells. Genome sequencing and karyotype analyses suggested that this was partially the result of chr3 duplication, with cells transitioning to a state of chr3q gain. Isolated cells with chr3q gain show deficiencies in squamous differentiation in organoid culture. Our genome engineering approach to model chromosome arm aneuploidies provides a robust model that will address a gap in our understanding of aneuploidy in cancer. Citation Format: Alison Marie Taylor. Functional and computational approaches to uncover selection advantages of cancer aneuploidy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LE03-01.