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Hi-C identifies structural variation associated with resistance in paired patient-derived ovarian cancer models

GSE135242 Homo sapiens Genome binding/occupancy profiling by high throughput sequencing 8 samples Submitted 2025/07/22 Platform GPL20301
Summary
Purpose: To establish a bioinformatics pipeline for identifying structural variation in cancer cell lines using Hi-C. Results: We were able to identify translocations as the primary genomic aberration in the PEO1 and PEO4 cell lines, while copy number alterations were the primary mutational process in the PEO14 and PEO23 cell lines. Conclusions: The strategy we present can be widely applied to the analysis of structural variation in cancer, and the data we have generated provides valuable insight into the processes that occur upon treatment of ovarian cancer with cisplatin.
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Also filed as BioProject PRJNA558137 and SRA study SRP217207. Searching any of these in the dataset finder brings you back here.

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