Abstract PS2-09-16: Optical genome mapping and multi-modal characterization of breast tumor and organoid samples reveal structural variation and gene fusion signatures

Abstract Background: Despite progress in diagnosis and treatment, the heterogeneity of breast cancer (BC) continues to challenge therapeutic strategies. To better understand the genomic and transcriptomic alterations driving BC progression, we applied an integrative approach combining optical genome mapping (OGM) and RNA-seq. OGM is a powerful tool for detecting large structural variants (SVs), genomic instability, and fusion. We independently analyzed breast tumor tissues and patient-derived organoids (PDOs) models using both platforms. By comparing genomic and transcriptomic landscapes across these models, we aim to identify key alterations and evaluate the ability of organoids to reflect critical features of BC biology. Methods: The study cohort consists of 62 samples, including 27 breast tumor tissues and 35 PDOs, categorized based upon origin (tumor vs. PDO), tissue source (primary vs. metastatic), and histological subtype (invasive lobular carcinoma, ILC, and no special type, NST). OGM was performed on all 62 samples using the Bionano Saphyr platform. Bulk RNA sequencing was conducted on a subset of 55 samples, comprising 22 tumor tissues and 33 PDOs. RNA-seq libraries were prepared and sequenced in paired-end mode using the Illumina platform. Fusion analysis was performed by the nf-core/rnafusion module, and Oncofuse tool was used to predict the oncogenic potential of fusion genes. Results: SVs analysis revealed a complex landscape of genomic alterations across PDOs and tumor samples. A total of 3,007 SVs were identified in PDOs and 2,241 SVs in tumors. In both cohorts, deletions represented the most shared type of SVs, followed by inter/intra-chromosomal translocations. Intrachromosomal SV size distributions were comparable, with tumors showing a slightly larger median size. Cytoband analysis revealed 42 regions enriched for SVs, with hotspots on chromosomes 8 and 1. However, over 95% of SVs were non-recurrent, highlighting predominant patient-specific structural alterations. To assess functional impact, SVs were mapped to BC-related genes from the OncoVar database. Recurrent top alterations were identified in ESR1, PPM1D, CCND1, and ERBB3 across both PDOs and tumors, spanning diverse SV types and gene roles. Genome instability profiling showed a wide range of homologous recombination deficiency (HRD) scores in both groups, calculated from large-scale state transitions (LST), loss of heterozygosity (LOH), and telomeric allelic imbalance (TAI) components. HRD-high samples (score >42) were present in both PDOs and tumors, independent of histology. Circos plots revealed structural complexity ranging from stable to highly rearranged genomes. A total of 216 amplicons were detected in PDOs, including 5 break fusion bridge (BFB) positive amplicons, while 131 amplicons were identified in tumor samples, with 2 BFB-positive amplicons. Chromothripsis events were observed in both PDO and tumor samples, with varying levels of confidence. The most frequently affected chromosomes included chr8, chr12, and chr17, suggesting recurrent loci of catastrophic genomic rearrangement. Fusion detection using RNA-seq and OGM identified 411 and 1,178 events, respectively, with 37 overlapping fusions. Shared fusions showed both up- and downregulated expression patterns. High-confidence driver fusions included ESR1-ARNT2, DENND5A-SORL1, TAB3-DMD, and ARHGEF7-ATP11A, implicating them as potentially functional alterations. Conclusions: This study provides a comprehensive multi-platform characterization of SVs using both tumor tissues and PDOs. Collectively, these findings highlight the genomic fidelity of PDOs in modeling primary breast tumors and underscore the value of integrating OGM and transcriptomic profiling to uncover novel structural drivers of BC. Citation Format: R. Kumar, O. Shah, B. Schlegel, J. Hooda, D. Brown, H. Chang, A. Chang, J. Chen, J. Xavier, P. Mattila, L. Fairfull, G. Tseng, R. Bhargava, S. Oesterreich, A. Lee. Optical genome mapping and multi-modal characterization of breast tumor and organoid samples reveal structural variation and gene fusion signatures [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-09-16.