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Title:
Clonal evolution in breast cancer revealed by single nucleus genome sequencing | Nature
Description:
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. To investigate genomic diversity within tumours, a new type of whole-genome and exome single cell sequencing has been developed using G2/M nuclei; the technique was used to sequence single nuclei from an oestrogen-positive breast cancer and a triple-negative ductal carcinoma—aneuploidy rearrangements emerged as early events in tumour formation and then point mutations evolved gradually over time. Human breast cancers often display intratumour genomic heterogeneity, making clinical diagnosis difficult and complicating the interpretation of research results. This study tackles the problem using a newly developed whole-genome single-cell sequencing technique called nuc-seq that makes use of the natural genome duplication that occurs in the S phase of the cell cycle to achieve 91% mean coverage breadth. The method is applied to sequence single normal and tumour nuclei from an oestrogen-receptor-positive breast cancer and a triple-negative ductal carcinoma. Aneuploid rearrangements emerge as early events, and they remain stable during clonal expansion. In contrast, point mutations appear to evolve gradually, generating extensive clonal diversity. The data also show that no two single tumour cells are genetically identical, raising interesting questions as to the strict definition of a clone.
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headline:Clonal evolution in breast cancer revealed by single nucleus genome sequencing
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type:Organization
name:Hong Zhang
affiliation:
name:The University of Texas MD Anderson Cancer Center
address:
name:Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, USA
type:PostalAddress
type:Organization
name:Rui Zhao
affiliation:
name:Dana-Farber Cancer Institute, Harvard School of Public Health
address:
name:Department of Biostatistics and Computational Biology, and Department of Biostatistics, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
type:PostalAddress
type:Organization
name:Franziska Michor
affiliation:
name:Dana-Farber Cancer Institute, Harvard School of Public Health
address:
name:Department of Biostatistics and Computational Biology, and Department of Biostatistics, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
type:PostalAddress
type:Organization
name:Funda Meric-Bernstam
affiliation:
name:The University of Texas MD Anderson Cancer Center Department of Investigational Cancer Therapeutics
address:
name:The University of Texas MD Anderson Cancer Center Department of Investigational Cancer Therapeutics, Houston, USA
type:PostalAddress
type:Organization
name:Nicholas E. Navin
affiliation:
name:The University of Texas MD Anderson Cancer Center
address:
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
type:PostalAddress
type:Organization
name:The University of Texas Graduate School of Biomedical Sciences
address:
name:The University of Texas Graduate School of Biomedical Sciences, Houston, USA
type:PostalAddress
type:Organization
name:The University of Texas MD Anderson Cancer Center
address:
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
type:PostalAddress
type:Organization
email:[email protected]
PostalAddress:
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:The University of Texas Graduate School of Biomedical Sciences, Houston, USA
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
name:The University of Texas Graduate School of Biomedical Sciences, Houston, USA
name:Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, USA
name:The University of Texas Graduate School of Biomedical Sciences, Houston, USA
name:Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, USA
name:Department of Biostatistics and Computational Biology, and Department of Biostatistics, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
name:Department of Biostatistics and Computational Biology, and Department of Biostatistics, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, USA
name:The University of Texas MD Anderson Cancer Center Department of Investigational Cancer Therapeutics, Houston, USA
name:Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA
name:The University of Texas Graduate School of Biomedical Sciences, Houston, USA
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
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