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Updated: Jan 16, 2026

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Tracking clonal evolution during treatment in ovarian cancer using cell-free DNA
Marc J Williams1,2, Ignacio Vázquez-García3,4,5,6,7, Grittney Tam8
1Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. william1@mskcc.org.
Abstract:
Emergence of drug resistance is the main cause of therapeutic failure in patients with high-grade serous ovarian cancer (HGSOC)1. To study drug resistance in patients, we developed CloneSeq-SV, which combines single-cell whole-genome sequencing2 with targeted deep sequencing of clone-specific genomic structural variants in time-series cell-free DNA. CloneSeq-SV exploits tumour clone-specific structural variants as highly sensitive endogenous cell-free DNA markers, enabling the relative abundance measurements and evolutionary analysis of co-existing clonal populations over the therapeutic time course. Here, using this approach, we studied 18 patients with HGSOC over a multi-year period from diagnosis to recurrence and showed that drug resistance typically arose from selective expansion of a single or small subset of clones present at diagnosis. Drug-resistant clones frequently showed interpretable and distinctive genomic features, including chromothripsis, whole-genome doubling, and high-level amplifications of oncogenes such as CCNE1, RAB25, MYC and NOTCH3. Phenotypic analysis of matched single-cell RNA sequencing data3 indicated pre-existing and clone-specific transcriptional states such as upregulation of epithelial-to-mesenchymal transition and VEGF pathways, linked to drug resistance. In one notable case, clone-specific ERBB2 amplification affected the efficacy of a secondary targeted therapy with a positive patient outcome. Together, our findings indicate that drug-resistant states in HGSOC pre-exist at diagnosis, leading to positive selection and reduced clonal complexity at relapse. We suggest these findings motivate investigation of evolution-informed adaptive treatment regimens to ablate drug resistance in future HGSOC studies.
Insights
Drug resistance in high-grade serous ovarian cancer (HGSOC) often stems from pre-existing clones. CloneSeq-SV reveals that resistant clones expand during therapy, offering insights for adaptive treatment strategies.
Area of Science:
- Genomics
- Cancer Biology
- Molecular Oncology
Background:
- Drug resistance is a primary cause of therapeutic failure in high-grade serous ovarian cancer (HGSOC).
- Understanding the clonal evolution of HGSOC is crucial for developing effective treatments.
Purpose of the Study:
- To develop and apply a novel method, CloneSeq-SV, for analyzing clonal evolution and drug resistance in HGSOC.
- To investigate the origins and genomic features of drug-resistant clones in HGSOC patients over time.
Main Methods:
- Developed CloneSeq-SV, combining single-cell whole-genome sequencing with targeted deep sequencing of structural variants in cell-free DNA.
- Applied CloneSeq-SV to analyze samples from 18 HGSOC patients over multiple years, from diagnosis to recurrence.
- Integrated phenotypic analysis using matched single-cell RNA sequencing data.
Main Results:
- Drug resistance in HGSOC typically arises from the selective expansion of pre-existing clones present at diagnosis.
- Drug-resistant clones exhibit distinct genomic features like chromothripsis, whole-genome doubling, and oncogene amplifications (e.g., CCNE1, MYC).
- Pre-existing, clone-specific transcriptional states, including epithelial-to-mesenchymal transition and VEGF pathways, are linked to drug resistance.
Conclusions:
- Drug-resistant states in HGSOC are pre-existing at diagnosis, leading to positive selection and reduced clonal complexity at relapse.
- Clone-specific genomic alterations, such as ERBB2 amplification, can impact targeted therapy efficacy.
- Findings support the investigation of evolution-informed adaptive treatment regimens to overcome drug resistance in HGSOC.

