1. Comparative Genomic Profiling of Second Breast Cancers following First Ipsilateral Hormone Receptor–Positive Breast Cancers
- Author
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Elie Rassy, Ingrid Garberis, Alicia Tran-Dien, Bastien Job, Véronique Chung-Scott, Ibrahim Bouakka, Josiane Bassil, Rachel Ferkh, Magali Lacroix-Triki, Fabrizio Zanconati, Fabiola Giudici, Daniele Generali, Etienne Rouleau, Ludovic Lacroix, Fabrice Andre, and Barbara Pistilli
- Subjects
Cancer Research ,Oncology - Abstract
Purpose: We compared the mutational profile of second breast cancers (SBC) following first ipislateral hormone receptor–positive breast cancers of patient-matched tumors to distinguish new primaries from true recurrences. Experimental Design: Targeted next-generation sequencing using the Oncomine Tumor Mutation Load Assay. Variants were filtered according to their allele frequency ≥ 5%, read count ≥ 5X, and genomic effect and annotation. Whole genome comparative genomic hybridization array (CGH) was also performed to evaluate clonality. Results: Among the 131 eligible patients, 96 paired first breast cancer (FBC) and SBC were successfully sequenced and analyzed. Unshared variants specific to the FBC and SBC were identified in 71.9% and 61.5%, respectively. Paired samples exhibited similar frequency of gene variants, median number of variants per sample, and variant allele frequency of the reported variants except for GATA3. Among the 30 most frequent gene alterations, ARIDIA, NSD2, and SETD2 had statistically significant discordance rates in paired samples. Seventeen paired samples (17.7%) exhibited common variants and were considered true recurrences; these patients had a trend for less favorable survival outcomes. Among the 8 patients with available tissue for CGH analysis and considered new primaries by comparison of the mutation profiles, 4 patients had clonally related tumors. Conclusions: Patient-matched FBC and SBC analysis revealed that only a minority of patients exhibited common gene variants between the first and second tumor. Further analysis using larger cohorts, preferably using single-cell analyses to account for clonality, might better select patients with true recurrences and thereby better inform the decision-making process.
- Published
- 2023