Structural variant and nucleosome occupancy dynamics postchemotherapy in a HER2+ breast cancer organoid model

生物 癌症研究 癌变 乳腺癌 基因组不稳定性 癌症 类有机物 DNA损伤 DNA 遗传学
作者
Maja Starostecka,Hyobin Jeong,Patrick Hasenfeld,Eva Benito,Tania Christiansen,Catherine Brasseur,Maise Gomes Queiroz,Marta G. Montero,Martin Jechlinger,Jan O. Korbel
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [National Academy of Sciences]
卷期号:122 (9)
标识
DOI:10.1073/pnas.2415475122
摘要

The most common chemotherapeutics induce DNA damage to eradicate cancer cells, yet defective DNA repair can propagate mutations, instigating therapy resistance and secondary malignancies. Structural variants (SVs), arising from copy-number-imbalanced and -balanced DNA rearrangements, are a major driver of tumor evolution, yet understudied posttherapy. Here, we adapted single-cell template-strand sequencing (Strand-seq) to a HER2+ breast cancer model to investigate the formation of doxorubicin-induced de novo SVs. We coupled this approach with nucleosome occupancy (NO) measurements obtained from the same single cell to enable simultaneous SV detection and cell-type classification. Using organoids from TetO-CMYC/TetO-Neu/MMTV-rtTA mice modeling HER2+ breast cancer, we generated 459 Strand-seq libraries spanning various tumorigenesis stages, identifying a 7.4-fold increase in large chromosomal alterations post-doxorubicin. Complex DNA rearrangements, deletions, and duplications were prevalent across basal, luminal progenitor (LP), and mature luminal (ML) cells, indicating uniform susceptibility of these cell types to SV formation. Doxorubicin further elevated sister chromatid exchanges (SCEs), indicative of genomic stress persisting posttreatment. Altered nucleosome occupancy levels on distinct cancer-related genes further underscore the broad genomic impact of doxorubicin. The organoid-based system for single-cell multiomics established in this study paves the way for unraveling the most important therapy-associated SV mutational signatures, enabling systematic studies of the effect of therapy on cancer evolution.

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