Clonal evolution in breast cancer revealed by single nucleus genome sequencing
Open accessAbstract
Sequencing studies of breast tumour cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumours. Here we developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumour nuclei from an oestrogen-receptor-positive (ER(+)) breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Using targeted single-molecule sequencing, many of the diverse mutations were shown to occur at low frequencies (<10%) in the tumour mass. Using mathematical modelling we found that the triple-negative tumour cells had an increased mutation rate (13.3×), whereas the ER(+) tumour cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.
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Rapid technological advances have enabled genome-wide profiling of RNA, DNA, protein, epigenetic modifications, chromatin accessibility, and other molecular events in single cells.
“rapid technological advances have enabled genome-wide profiling of RNA7–10, DNA11–17, protein18–21, epigenetic modifications22–26, chromatin accessibility27,28, and other molecular events29 in single cells.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [15]
These methods have been used to decipher pathological evolution in tumors and somatic mosaicism in healthy tissues and in non-cancerous disease.
“These methods have been used to decipher pathological evolution in tumors11,15,195–197 and somatic mosaicism198 in healthy tissues and in non-cancerous disease199–203.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [15]
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- Authors
- Wang, Y., Waters, J., Leung, M. L., Unruh, A., Roh, W., Shi, X., Chen, K., Scheet, P., Vattathil, S., Liang, H., Multani, A., Zhang, H., Zhao, R., Michor, F., Meric-Bernstam, F., & Navin, N. E.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- Harvard University (US)
- Corresponding author
- Navin, Nicholas E.
- ORCID
- Venue
- Nature
- Published
- 2014-07-30
- Volume
- 512
- Issue
- 7513
- Pages
- 155-160
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4158312
- OpenAlex
- W2129288227
- Cited by
- 1,029
- References
- 52
- Citations by year
- 2026: 30 · 2025: 36 · 2024: 51 · 2023: 51 · 2022: 83 · 2021: 98 · 2020: 99 · 2019: 88 · 2018: 102 · 2017: 136 · 2016: 124 · 2015: 106 · 2014: 23 · 2013: 1
- FWCI
- 41.53
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health (UL1TR000371)
- National Cancer Institute (CA 016672, R01CA172652, R01CA169244, U24CA143883, R21CA174397, U54CA143798, P30CA016672)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Keywords
- breast cancer, clonal evolution, intratumoral heterogeneity, single-nucleus sequencing, aneuploidy, copy number profiling, point mutations, mutation rate, triple-negative breast cancer, estrogen receptor-positive breast cancer, ductal carcinoma, clonal diversity, tumor evolution
- MeSH terms
- Breast Neoplasms, Female, Humans, Models, Theoretical, Mutation, Genetic Variation, DNA Fingerprinting, Genome, Sequence Analysis, DNA, Cell Line, Tumor, Single-Cell Analysis, Clonal Evolution, Triple Negative Breast Neoplasms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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