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

Maja Starostecka1,2, Hyobin Jeong1,3, Patrick Hasenfeld1

  • 1European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg 69117, Germany.

Insights

Doxorubicin chemotherapy increases structural variants (SVs) and genomic instability in HER2+ breast cancer cells. This study reveals uniform susceptibility across cell types and highlights persistent genomic stress post-treatment.

Area of Science:

  • Genomics
  • Cancer Biology
  • Molecular Oncology

Background:

  • Chemotherapeutics like doxorubicin induce DNA damage to eliminate cancer cells.
  • Defective DNA repair can lead to mutations, therapy resistance, and secondary cancers.
  • Structural variants (SVs) drive tumor evolution but are understudied post-chemotherapy.

Purpose of the Study:

  • To investigate doxorubicin-induced de novo structural variants (SVs) in a HER2+ breast cancer model.
  • To simultaneously detect SVs and classify cell types using single-cell multiomics.

Main Methods:

  • Adaptation of single-cell template-strand sequencing (Strand-seq) for SV detection.
  • Coupling Strand-seq with nucleosome occupancy (NO) measurements in the same single cell.
  • Utilizing a HER2+ breast cancer organoid model (TetO-CMYC/TetO-Neu/MMTV-rtTA mice) and generating 459 Strand-seq libraries.

Main Results:

  • A 7.4-fold increase in large chromosomal alterations was observed post-doxorubicin treatment.
  • Complex DNA rearrangements, deletions, and duplications were prevalent across basal, luminal progenitor (LP), and mature luminal (ML) cells.
  • Doxorubicin elevated sister chromatid exchanges (SCEs) and altered nucleosome occupancy on cancer-related genes, indicating persistent genomic stress.

Conclusions:

  • HER2+ breast cancer cell types exhibit uniform susceptibility to doxorubicin-induced SV formation.
  • The developed single-cell multiomics system enables comprehensive analysis of therapy-associated SV mutational signatures.
  • This approach facilitates systematic studies on the impact of therapy on cancer evolution.