Abstract Ovarian cancer (OV) remains one of the most lethal malignancies, and target discovery is hindered by limited oncogenic somatic single-nucleotide mutations and extensive chromosomal instability. Conventional strategies prioritize targeting of amplified genes based on frequency and amplitude of copy number amplification. However, these metrics are confounded by regional genomic architecture and abundant passenger events, rendering it difficult to identify the amplifications that truly increase cell proliferation and survival during tumor evolution. To address this problem, we developed an evolutionary model that quantifies the cancer effect size (CES) of amplifications, directly estimating the selective advantage conferred by each event, mirroring methodologies developed for single-nucleotide variants. By integrating observed amplification patterns with regional background copy number alteration (CNA) rates to quantify fitness contributions, we distinguished amplifications that genuinely drive tumor evolution from passengers elevated by genomic instability. Using segmented copy number profiles from a cohort of 554 ovarian cancer tumor sequences, we quantified cancer effects of amplifications across the genome. Known oncogenes like MYC and CCNE1 exhibit high CES. Some oft-reported recurrent amplifications exhibited low CES, consistent with a passenger status, whereas several moderately high-frequency focal amplifications exhibited strong selective advantage, representing key CNA drivers that are obscured by conventional copy-number metrics. This stratification is critical for therapeutic development because high-CES amplifications mark loci where tumors are both dosage-increased and selectively dependent. Dosage-increased, selectively dependent loci have direct translational relevance for triplex-forming oligonucleotide (TFO) therapies, which trigger DNA damage at triplex-forming motifs, with amplified loci providing increased target dosage. High-CES loci simultaneously provide abundant TFO-binding sites and represent core cancer dependencies, embodying a mechanism for durable therapeutic impact. Quantification of selection for amplifications provides a rigorous, evolutionarily grounded basis for cancer effect, identifying true amplification drivers of oncogenesis and precisely positioning therapeutically actionable targets in cancers dominated by chromosomal instability. Citation Format: Meng Liu, Jeff Mandell, Jeffrey Peter Townsend. Quantifying the selective advantage of copy number amplifications to reveal therapeutic targets in ovarian cancer abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 52.
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