TY - JOUR
T1 - Reconstructing mutational lineages in breast cancer by multi-patient-targeted single-cell DNA sequencing
AU - Leighton, Jake
AU - Hu, Min
AU - Sei, Emi
AU - Meric-Bernstam, Funda
AU - Navin, Nicholas E.
N1 - Funding Information:
This study was supported by grants to N.E.N. from the American Cancer Society (129098-RSG-16-092-01-TBG), the NIH National Cancer Institute (RO1CA240526 and RO1CA236864), the Emerson Collective Cancer Research Fund, and the CPRIT Single Cell Genomics Center (RP180684). N.E.N. is an AAAS Wachtel Scholar, Andrew Sabin Family Fellow, Jack & Beverly Randall Innovator, and AAAS Fellow. This study was supported by the MD Anderson Sequencing Core Facility Grant (CA016672) and MD Anderson T32 Translational Genomics and Precision Medicine Fellowship (CA217789). We thank Hongli Tang, Louis Ramagli, and Erika Thompson for their help with next-generation sequencing. We are grateful to Alexander Davis for providing guidance on the mutation trees and Darlan Minussi, Naveen Ramesh, Tapsi Kumar, and Aislyn Schlack for data analysis support. Finally, we thank Robert Durruthy, Kelly Kaihara, and Anjali Pradhan from Mission Bio for their computational and technical support for this project. J.L. performed experiments and data analysis and prepared the manuscript. E.S. performed FACS and exome experiments. M.H. performed data analysis. F.M.-B. obtained clinical tissues and clinical data. N.E.N. managed the project and wrote the manuscript. N.E.N. is a member of the Scientific Advisory Board (SAB) for Mission Bio
Funding Information:
This study was supported by grants to N.E.N. from the American Cancer Society ( 129098-RSG-16-092-01-TBG ), the NIH National Cancer Institute ( RO1CA240526 and RO1CA236864 ), the Emerson Collective Cancer Research Fund, and the CPRIT Single Cell Genomics Center ( RP180684 ). N.E.N. is an AAAS Wachtel Scholar, Andrew Sabin Family Fellow, Jack & Beverly Randall Innovator, and AAAS Fellow. This study was supported by the MD Anderson Sequencing Core Facility Grant ( CA016672 ) and MD Anderson T32 Translational Genomics and Precision Medicine Fellowship ( CA217789 ). We thank Hongli Tang, Louis Ramagli, and Erika Thompson for their help with next-generation sequencing. We are grateful to Alexander Davis for providing guidance on the mutation trees and Darlan Minussi, Naveen Ramesh, Tapsi Kumar, and Aislyn Schlack for data analysis support. Finally, we thank Robert Durruthy, Kelly Kaihara, and Anjali Pradhan from Mission Bio for their computational and technical support for this project.
Publisher Copyright:
© 2022 The Author(s)
PY - 2023/1/11
Y1 - 2023/1/11
N2 - Single-cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells; however, most genomic regions sequenced in single cells are non-informative. To overcome this issue, we developed a multi-patient-targeted (MPT) scDNA-seq method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 patients with triple negative-breast cancer (TNBC), which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From these data, we reconstructed mutational lineages and identified early mutational and copy-number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggest that MPT can overcome a major technical obstacle for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.
AB - Single-cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells; however, most genomic regions sequenced in single cells are non-informative. To overcome this issue, we developed a multi-patient-targeted (MPT) scDNA-seq method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 patients with triple negative-breast cancer (TNBC), which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From these data, we reconstructed mutational lineages and identified early mutational and copy-number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggest that MPT can overcome a major technical obstacle for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.
KW - breast cancer
KW - intratumor heterogeneity
KW - mutational evolution
KW - single-cell genomics
KW - triple-negative breast cancer
UR - http://www.scopus.com/inward/record.url?scp=85146135915&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146135915&partnerID=8YFLogxK
U2 - 10.1016/j.xgen.2022.100215
DO - 10.1016/j.xgen.2022.100215
M3 - Article
C2 - 36777188
AN - SCOPUS:85146135915
SN - 2666-979X
VL - 3
JO - Cell Genomics
JF - Cell Genomics
IS - 1
M1 - 100215
ER -