Tumour evolution inferred by single-cell sequencing
Open accessAbstract
Genomic analysis provides insights into the role of copy number variation in disease, but most methods are not designed to resolve mixed populations of cells. In tumours, where genetic heterogeneity is common, very important information may be lost that would be useful for reconstructing evolutionary history. Here we show that with flow-sorted nuclei, whole genome amplification and next generation sequencing we can accurately quantify genomic copy number within an individual nucleus. We apply single-nucleus sequencing to investigate tumour population structure and evolution in two human breast cancer cases. Analysis of 100 single cells from a polygenomic tumour revealed three distinct clonal subpopulations that probably represent sequential clonal expansions. Additional analysis of 100 single cells from a monogenomic primary tumour and its liver metastasis indicated that a single clonal expansion formed the primary tumour and seeded the metastasis. In both primary tumours, we also identified an unexpectedly abundant subpopulation of genetically diverse 'pseudodiploid' cells that do not travel to the metastatic site. In contrast to gradual models of tumour progression, our data indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.
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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 [11]
Multiple-omic protocols will not only allow results to be corroborated by distinct data types but also elucidate how information flows in biological circuits from DNA to RNA to protein.
“Multiple-omic protocols will not only allow results to be corroborated by distinct data types (e.g., CNV calling from DNA-seq11 and scRNA-seq data97) but also elucidate how information flows in biological circuits from DNA to RNA to protein.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [11]
Important strides have been made in single-cell DNA sequencing as well as in analysis of copy-number variations (CNVs) and point mutations from single-cell DNA data.
“While our focus has been on single-cell transcriptomics, important strides have also been made in single-cell DNA sequencing77,194 as well as in analysis of copy-number variations (CNVs)11 and point mutations15,195 from single-cell DNA data.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [11]
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 [11]
Single-cell sequencing is becoming common as a research platform but is not yet suitable for clinical use.
“More sensitive approaches of genetic characterization, like single-cell sequencing, are becoming increasingly common as research platforms but are not yet amenable to a clinical setting6, 7.”
From Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate (2016) · cites this paper as [6]
Single-cell sequencing has been used to evaluate the clonal evolution of tumors.
“Single-cell sequencing has already been used to evaluate the clonal evolution of tumors (Hou et al., 2012; Navin et al., 2011; Xu et al., 2012) and the spontaneous mutation of sperm cells (Lu et al., 2012; Wang et al., 2012).”
From Genetic Changes Shaping the Human Brain (2015) · cites this paper as Navin et al., 2011
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Cites
The neighbor-joining method: a new method for reconstructing phylogenetic trees.
Saitou, N., & Nei, M. (1987) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040454 · Cited by 59,962 · see citing works
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849 · see citing works
Nowell, P. C. (1976) · Science · doi:10.1126/science.959840 · Cited by 6,471 · see citing works
Distant metastasis occurs late during the genetic evolution of pancreatic cancer
Yachida, S., Jones, S., Bozic, I., Antal, T., Leary, R., Fu, B., Kamiyama, M., Hruban, R. H., Eshleman, J. R., Nowak, M. A., et al. (2010) · Nature · doi:10.1038/nature09515 · Cited by 2,502 · see citing works
Genome remodelling in a basal-like breast cancer metastasis and xenograft
Ding, L., Ellis, M. J., Li, S., Larson, D. E., Chen, K., Wallis, J. W., Harris, C. C., McLellan, M. D., Fulton, R. S., Fulton, L., et al. (2010) · Nature · doi:10.1038/nature08989 · Cited by 1,134 · see citing works
Punctuated equilibrium comes of age
Gould, S. J., & Eldredge, N. (1993) · Nature · doi:10.1038/366223a0 · Cited by 957 · see citing works
A systematic comparison and evaluation of biclustering methods for gene expression data
Prelić, A., Stefan Bleuler, A., Philip Zimmermann, B., Wille, A., Bühlmann, P., Gruissem, W., Hennig, L., Thiele, L., & Zitzler, E. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl060 · Cited by 916 · see citing works
Personalized copy number and segmental duplication maps using next-generation sequencing
Alkan, C., Kidd, J. M., Marques-Bonet, T., Aksay, G., Antonacci, F., Hormozdiari, F., Kitzman, J. O., Baker, C., Malig, M., Mutlu, O., et al. (2009) · Nature Genetics · doi:10.1038/ng.437 · Cited by 748 · see citing works
Copy number analysis indicates monoclonal origin of lethal metastatic prostate cancer
Liu, W., Laitinen, S., Khan, S., Vihinen, M., Kowalski, J., Yu, G., Chen, L., Ewing, C. M., Eisenberger, M. A., Carducci, M. A., et al. (2009) · Nature Medicine · doi:10.1038/nm.1944 · Cited by 655 · see citing works
Sensitive and accurate detection of copy number variants using read depth of coveragePreprint
Yoon, S. C., Xuan, Z., Makarov, V., Ye, K. Q., & Sebat, J. L. (2009) · Genome Research · doi:10.1101/gr.092981.109 · Cited by 619 · see citing works
Errors in DNA replication as a basis of malignant changes.
Loeb, L. A., Springgate, C. F., & Battula, N. (1974) · PubMed · Cited by 521 · see citing works
Inferring tumor progression from genomic heterogeneityPreprint
Navin, N. E., Krasnitz, A., Rodgers, L., Cook, K., Meth, J. L., Kendall, J., Riggs, M. G., Eberling, Y., Troge, J. E., Grubor, V. D., et al. (2009) · Genome Research · doi:10.1101/gr.099622.109 · Cited by 515 · see citing works
Self-citationHigh-resolution mapping of copy-number alterations with massively parallel sequencing
Chiang, D. Y., Getz, G. A., Jaffe, D. B., O'Kelly, M., Zhao, X., Carter, S. L., Russ, C., Nusbaum, C., Meyerson, M. M., & Lander, E. S. (2008) · Nature Methods · doi:10.1038/nmeth.1276 · Cited by 510 · see citing works
Human cancers express a mutator phenotype
Bielas, J. H., Loeb, K. R., Rubin, B. P., True, L. D., & Loeb, L. A. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0607057103 · Cited by 354 · see citing works
Park, S. Y., Gönen, M., Kim, H. J., Franziska Michor, A., & Polyák, K. (2010) · Journal of Clinical Investigation · doi:10.1172/jci40724 · Cited by 324 · see citing works
Novel patterns of genome rearrangement and their association with survival in breast cancerPreprint
Hicks, J. B., Krasnitz, A., Lakshmi, B. V., Navin, N. E., Riggs, M. G., Leibu, E., Esposito, D., Alexander, J., Troge, J. E., Grubor, V. D., et al. (2006) · Genome Research · doi:10.1101/gr.5460106 · Cited by 320 · see citing works
Self-citationTorres, L., Ribeiro, F. R., Pandis, N., Andersen, J. A., Heim, S., & Teixeira, M. R. (2006) · Breast Cancer Research and Treatment · doi:10.1007/s10549-006-9317-6 · Cited by 187 · see citing works
Stochastic cancer progression driven by non‐clonal chromosome aberrations
Heng, H. H., Stevens, J. B., Liu, G., Bremer, S. W., Ye, K. J., Reddy, P.-V., Wu, G. S., Wang, Y., Tainsky, M. A., & Ye, C. J. (2006) · Journal of Cellular Physiology · doi:10.1002/jcp.20685 · Cited by 162 · see citing works
Geigl, J. B., Obenauf, A. C., Waldispuehl‐Geigl, J., et al. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp526 · Cited by 106 · see citing works
Impact of whole genome amplification on analysis of copy number variants
Pugh, T. J., Delaney, A. D., Farnoud, N. R., Flibotte, S., Griffith, M., Li, H. I., Qian, H., Farinha, P., Gascoyne, R. D., & Marra, M. A. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn378 · Cited by 89 · see citing works
Bueno, C., Almeida, J., Alguero, M. C., S�nchez, M. L., Vaquero, J. M., Laso, F. J., Miguel, J. F. S., Escribano, L., & Orfao, A. (2001) · Cytometry · doi:10.1002/1097-0320(20010215)46:1 · Cited by 60 · see citing works
High-resolution array comparative genomic hybridization of single micrometastatic tumor cells
Fuhrmann, C., Schmidt‐Kittler, O., Stoecklein, N. H., Petat‐Dutter, K., Vay, C., Bockler, K., Reinhardt, R., Ragg, T., & Klein, C. A. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn101 · Cited by 58 · see citing works
Hughes, S., Lim, G., Beheshti, B., et al. (2004) · Cytogenetic and Genome Research · doi:10.1159/000078004 · Cited by 27 · see citing works
Whole genome amplification and its impact on CGH array profiles
Talseth‐Palmer, B. A., Bowden, N. A., Hill, A., et al. (2008) · BMC Research Notes · doi:10.1186/1756-0500-1-56 · Cited by 24 · see citing works
Huang, J., Pang, J. C. S., Watanabe, T., Ng, H., & Ohgaki, H. (2009) · Journal of Molecular Diagnostics · doi:10.2353/jmoldx.2009.080143 · Cited by 20 · see citing works
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Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453 · see citing works
Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
Gerlinger, M., Rowan, A. J., Horswell, S., Larkin, J., Endesfelder, D., Gronroos, E., Martinez, P., Matthews, N., Stewart, A., Tarpey, P., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1113205 · Cited by 7,774 · see citing works
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
Patel, A. P., Tirosh, I., Trombetta, J. J., Shalek, A. K., Gillespie, S. M., Wakimoto, H., Cahill, D. P., Nahed, B. V., Curry, W. T., Martuza, R. L., et al. (2014) · Science · doi:10.1126/science.1254257 · Cited by 5,063 · see citing works
Tumor Metastasis: Molecular Insights and Evolving Paradigms
Valastyan, S., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.09.024 · Cited by 4,011 · see citing works
Tumour heterogeneity and resistance to cancer therapies
Dagogo-Jack, I., & Shaw, A. T. (2018) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.166 · Cited by 3,846 · see citing works
Greaves, M., & Maley, C. C. (2012) · Nature · doi:10.1038/nature10762 · Cited by 3,162 · see citing works
Triple-negative breast cancer: challenges and opportunities of a heterogeneous disease
Bianchini, G., Balko, J. M., Mayer, I. A., Sanders, M. E., & Gianni, L. (2016) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.66 · Cited by 3,079 · see citing works
Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing
Ding, L., Ley, T. J., Larson, D. E., Miller, C. A., Koboldt, D. C., Welch, J. S., Ritchey, J. K., Young, M. A., Lamprecht, T., McLellan, M. D., et al. (2012) · Nature · doi:10.1038/nature10738 · Cited by 1,993 · see citing works
Mapping the Mouse Cell Atlas by Microwell-Seq
Han, X., Wang, R., Zhou, Y., Fei, L., Sun, H., Lai, S., Saadatpour, A., Zhou, Z., Chen, H., Ye, F., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.001 · Cited by 1,597 · see citing works
The Life History of 21 Breast Cancers
Nik-Zainal, S., Van Loo, P., Wedge, D. C., Alexandrov, L. B., Greenman, C. D., Lau, K. W., Raine, K., Jones, D., Marshall, J., Ramakrishna, M., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.023 · Cited by 1,443 · see citing works
Eleven grand challenges in single-cell data science
Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-1926-6 · Cited by 1,327 · see citing works
Single-cell genome sequencing: current state of the science
Gawad, C., Koh, W., & Quake, S. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.16 · Cited by 1,334 · see citing works
Integrative single-cell analysis
Stuart, T., & Satija, R. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0093-7 · Cited by 1,460 · see citing works
Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing
Cusanovich, D. A., Daza, R., Adey, A., Pliner, H. A., Christiansen, L., Gunderson, K. L., Steemers, F. J., Trapnell, C., & Shendure, J. (2015) · Science · doi:10.1126/science.aab1601 · Cited by 1,248 · see citing works
Evolution and impact of subclonal mutations in chronic lymphocytic leukemia
Landau, D. A., Carter, S. L., Stojanov, P., McKenna, A., Stevenson, K., Lawrence, M. S., Sougnez, C., Stewart, C., Sivachenko, A., Wang, L., et al. (2013) · Cell · doi:10.1016/j.cell.2013.01.019 · Cited by 1,379 · see citing works
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177 · see citing works
Genome-Wide Detection of Single-Nucleotide and Copy-Number Variations of a Single Human Cell
Zong, C., Lu, S., Chapman, A. R., & Xie, X. S. (2012) · Science · doi:10.1126/science.1229164 · Cited by 1,154 · see citing works
Biological and therapeutic impact of intratumor heterogeneity in cancer evolution
McGranahan, N., & Swanton, C. (2015) · Cancer Cell · doi:10.1016/j.ccell.2014.12.001 · Cited by 1,077 · see citing works
Clonal evolution in breast cancer revealed by single nucleus genome sequencing
Wang, Y., Waters, J., Leung, M. L., Unruh, A., Roh, W., Shi, X., Chen, K., Scheet, P., Vattathil, S., Liang, H., et al. (2014) · Nature · doi:10.1038/nature13600 · Cited by 1,029 · see citing works
Self-citationCombinatorial drug therapy for cancer in the post-genomic era
Al-Lazikani, B., Banerji, U., & Workman, P. (2012) · Nature Biotechnology · doi:10.1038/nbt.2284 · Cited by 1,070 · see citing works
Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing
Zhang, J., Fujimoto, J., Zhang, J., Wedge, D. C., Song, X., Zhang, J., Seth, S., Chow, C.-W., Cao, Y., Gumbs, C., et al. (2014) · Science · doi:10.1126/science.1256930 · Cited by 965 · see citing works
Intratumor Heterogeneity: Evolution through Space and Time
Swanton, C. (2012) · Cancer Research · doi:10.1158/0008-5472.can-12-2217 · Cited by 931 · see citing works
Cancer Epigenetics: Tumor Heterogeneity, Plasticity of Stem-like States, and Drug Resistance
Easwaran, H., Tsai, H.-C., & Baylin, S. B. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.05.015 · Cited by 915 · see citing works
In situ sequencing for RNA analysis in preserved tissue and cells
Ke, R., Mignardi, M., Pacureanu, A., Svedlund, J., Botling, J., Wählby, C., & Nilsson, M. (2013) · Nature Methods · doi:10.1038/nmeth.2563 · Cited by 934 · see citing works
The role of cellular reactive oxygen species in cancer chemotherapy
Yang, H., Villani, R. M., Wang, H., Simpson, M. J., Roberts, M. S., Tang, M., & Liang, X. (2018) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-018-0909-x · Cited by 794 · see citing works
Scaling single-cell genomics from phenomenology to mechanism
Tanay, A., & Regev, A. (2017) · Nature · doi:10.1038/nature21350 · Cited by 792 · see citing works
Revealing the vectors of cellular identity with single-cell genomics
Wagner, A., Regev, A., & Yosef, N. (2016) · Nature Biotechnology · doi:10.1038/nbt.3711 · Cited by 632 · see citing works
Single-Cell Exome Sequencing Reveals Single-Nucleotide Mutation Characteristics of a Kidney Tumor
Xu, X., Hou, Y., Yin, X., Bao, L., Tang, A., Song, L., Li, F., Tsang, S., Wu, K., Wu, H., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.025 · Cited by 667 · see citing works
Hou, Y., Guo, H., Cao, C., Li, X., Hu, B., Zhu, P., Wu, X., Wen, L., Tang, F., Huang, Y., et al. (2016) · Cell Research · doi:10.1038/cr.2016.23 · Cited by 647 · see citing works
Telomeres: history, health, and hallmarks of aging
Chakravarti, D., LaBella, K. A., & DePinho, R. A. (2021) · Cell · doi:10.1016/j.cell.2020.12.028 · Cited by 637 · see citing works
Tumour heterogeneity and metastasis at single-cell resolution
Lawson, D. A., Kessenbrock, K., Davis, R. T., Pervolarakis, N., & Werb, Z. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0236-7 · Cited by 606 · see citing works
Vanharanta, S., & Massagué, J. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.09.007 · Cited by 563 · see citing works
Single-Cell Exome Sequencing and Monoclonal Evolution of a JAK2-Negative Myeloproliferative Neoplasm
Hou, Y., Song, L., Zhu, P., Zhang, B., Tao, Y., Xu, X., Li, F., Wu, K., Liang, J., Shao, D., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.028 · Cited by 541 · see citing works
Design and Analysis of Single-Cell Sequencing Experiments
Grün, D., & van Oudenaarden, A. (2015) · Cell · doi:10.1016/j.cell.2015.10.039 · Cited by 536 · see citing works
Somatic mutation, genomic variation, and neurological disease
Poduri, A., Evrony, G. D., Cai, X., & Walsh, C. A. (2013) · Science · doi:10.1126/science.1237758 · Cited by 584 · see citing works
Mosaic Copy Number Variation in Human Neurons
McConnell, M. J., Lindberg, M. R., Brennand, K. J., Piper, J. C., Voet, T., Cowing-Zitron, C., Shumilina, S., Lasken, R. S., Vermeesch, J. R., Hall, I. M., et al. (2013) · Science · doi:10.1126/science.1243472 · Cited by 551 · see citing works
Single-Neuron Sequencing Analysis of L1 Retrotransposition and Somatic Mutation in the Human Brain
Evrony, G. D., Cai, X., Lee, E., Hills, L. B., Elhosary, P. C., Lehmann, H. S., Parker, J. J., Atabay, K. D., Gilmore, E. C., Poduri, A., et al. (2012) · Cell · doi:10.1016/j.cell.2012.09.035 · Cited by 548 · see citing works
Guo, H., Zhu, P., Wu, X., Li, X., Wen, L., & Tang, F. (2013) · Genome Research · doi:10.1101/gr.161679.113 · Cited by 518 · see citing works
Spatially resolved transcriptomics and beyond
Crosetto, N., Bienko, M., & van Oudenaarden, A. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3832 · Cited by 509 · see citing works
Integrated genome and transcriptome sequencing of the same cell
Dey, S. S., Kester, L., Spanjaard, B., Bienko, M., & van Oudenaarden, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3129 · Cited by 502 · see citing works
Single-cell analysis tools for drug discovery and development
Heath, J. R., Ribas, A., & Mischel, P. S. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2015.16 · Cited by 473 · see citing works
Ni, X., Zhuo, M., Su, Z., Duan, J., Gao, Y., Wang, Z., Zong, C., Bai, H., Chapman, A. R., Zhao, J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320659110 · Cited by 454 · see citing works
Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing
Casasent, A. K., Schalck, A., Gao, R., Sei, E., Long, A., Pangburn, W., Casasent, T., Meric-Bernstam, F., Edgerton, M. E., & Navin, N. E. (2018) · Cell · doi:10.1016/j.cell.2017.12.007 · Cited by 411 · see citing works
Self-citationHigh-throughput mapping of single-neuron projections by sequencing of barcoded RNA
Kebschull, J. M., Garcia da Silva, P., Reid, A. P., Peikon, I. D., Albeanu, D. F., & Zador, A. M. (2016) · Neuron · doi:10.1016/j.neuron.2016.07.036 · Cited by 376 · see citing works
Single Cell Genomics: Advances and Future Perspectives
Macaulay, I. C., & Voet, T. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004126 · Cited by 384 · see citing works
Kim, H., Zheng, S., Amini, S. S., Virk, S. M., Mikkelsen, T., Brat, D. J., Grimsby, J., Sougnez, C., Muller, F., Hu, J., et al. (2015) · Genome Research · doi:10.1101/gr.180612.114 · Cited by 411 · see citing works
Makohon-Moore, A. P., Zhang, M., Reiter, J. G., Bozic, I., Allen, B., Kundu, D., Chatterjee, K., Wong, F., Jiao, Y., Kohutek, Z. A., et al. (2017) · Nature Genetics · doi:10.1038/ng.3764 · Cited by 403 · see citing works
Single-Cell Transcriptomics Meets Lineage Tracing
Kester, L., & van Oudenaarden, A. (2018) · Cell Stem Cell · doi:10.1016/j.stem.2018.04.014 · Cited by 375 · see citing works
Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells
Guo, F., Li, L., Li, J., Wu, X., Hu, B., Zhu, P., Wen, L., & Tang, F. (2017) · Cell Research · doi:10.1038/cr.2017.82 · Cited by 374 · see citing works
Ubiquitous L1 Mosaicism in Hippocampal Neurons
Upton, K. R., Gerhardt, D. J., Jesuadian, J. S., Richardson, S. R., Sánchez-Luque, F. J., Bodea, G. O., Ewing, A. D., Salvador-Palomeque, C., van der Knaap, M. S., Brennan, P. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.03.026 · Cited by 320 · see citing works
Role of integrated cancer nanomedicine in overcoming drug resistance
Iyer, A. K., Singh, A., Ganta, S., & Amiji, M. M. (2013) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2013.07.012 · Cited by 343 · see citing works
Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
Ding, J., Condon, A., & Shah, S. P. (2018) · Nature Communications · doi:10.1038/s41467-018-04368-5 · Cited by 337 · see citing works
Sequencing thousands of single-cell genomes with combinatorial indexing
Vitak, S. A., Torkenczy, K. A., Rosenkrantz, J. L., Fields, A. J., Christiansen, L., Wong, M. H., Carbone, L., Steemers, F. J., & Adey, A. (2017) · Nature Methods · doi:10.1038/nmeth.4154 · Cited by 294 · see citing works
Cai, X., Evrony, G. D., Lehmann, H. S., Elhosary, P. C., Mehta, B. K., Poduri, A., & Walsh, C. A. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.07.043 · Cited by 318 · see citing works
Cancer stem cells in osteosarcoma
Brown, H. K., Tellez-Gabriel, M., & Heymann, D. (2017) · Cancer Letters · doi:10.1016/j.canlet.2016.11.019 · Cited by 303 · see citing works
Breast tumours maintain a reservoir of subclonal diversity during expansion
Minussi, D. C., Nicholson, M. D., Ye, H., Davis, A., Wang, K., Baker, T., Tarabichi, M., Sei, E., Du, H., Rabbani, M., et al. (2021) · Nature · doi:10.1038/s41586-021-03357-x · Cited by 256 · see citing works
Self-citationDisentangling neural cell diversity using single-cell transcriptomics
Poulin, J.-F., Tasic, B., Hjerling-Leffler, J., Trimarchi, J. M., & Awatramani, R. (2016) · Nature Neuroscience · doi:10.1038/nn.4366 · Cited by 293 · see citing works
<i>EGFR</i> Variant Heterogeneity in Glioblastoma Resolved through Single-Nucleus Sequencing
Francis, J. M., Zhang, C.-Z., Maire, C. L., Jung, J., Manzo, V. E., Adalsteinsson, V. A., Homer, H., Haidar, S., Blumenstiel, B., Pedamallu, C. S., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0879 · Cited by 287 · see citing works
Single-cell sequencing techniques from individual to multiomics analyses
Kashima, Y., Sakamoto, Y., Kaneko, K., Seki, M., Suzuki, Y., & Suzuki, A. (2020) · Experimental & Molecular Medicine · doi:10.1038/s12276-020-00499-2 · Cited by 270 · see citing works
Building a lineage from single cells: genetic techniques for cell lineage tracking
Woodworth, M. B., Girskis, K. M., & Walsh, C. A. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.159 · Cited by 236 · see citing works
Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia
Gaiti, F., Chaligne, R., Gu, H., Brand, R. M., Kothen-Hill, S., Schulman, R. C., Grigorev, K., Risso, D., Kim, K.-T., Pastore, A., et al. (2019) · Nature · doi:10.1038/s41586-019-1198-z · Cited by 262 · see citing works
Gole, J., Gore, A., Richards, A., Chiu, Y.-J., Fung, H.-L., Bushman, D., Chiang, H.-I., Chun, J., Lo, Y.-H., & Zhang, K. (2013) · Nature Biotechnology · doi:10.1038/nbt.2720 · Cited by 238 · see citing works
Ordered and deterministic cancer genome evolution after p53 loss
Baslan, T., Morris, J. P., Zhao, Z., Reyes, J., Ho, Y.-J., Tsanov, K. M., Bermeo, J., Tian, S., Zhang, S., Askan, G., et al. (2022) · Nature · doi:10.1038/s41586-022-05082-5 · Cited by 221 · see citing works
Self-citationCompetition between human cells by entosis
Sun, Q., Luo, T., Ren, Y., Florey, O., Shirasawa, S., Sasazuki, T., Robinson, D. N., & Overholtzer, M. (2014) · Cell Research · doi:10.1038/cr.2014.138 · Cited by 233 · see citing works
Single-cell transcriptome sequencing: recent advances and remaining challenges
Liu, S., & Trapnell, C. (2016) · F1000Research · doi:10.12688/f1000research.7223.1 · Cited by 230 · see citing works
Hoang, M. L., Kinde, I., Tomasetti, C., McMahon, K. W., Rosenquist, T. A., Grollman, A. P., Kinzler, K. W., Vogelstein, B., & Papadopoulos, N. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1607794113 · Cited by 224 · see citing works
Tian, Q., Price, N. D., & Hood, L. (2012) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2011.02498.x · Cited by 224 · see citing works
Modules, networks and systems medicine for understanding disease and aiding diagnosis
Gustafsson, M., Nestor, C. E., Zhang, H., Barabási, A.-L., Baranzini, S., Brunak, S., Chung, K. F., Federoff, H. J., Gavin, A.-C., Meehan, R. R., et al. (2014) · Genome Medicine · doi:10.1186/s13073-014-0082-6 · Cited by 194 · see citing works
Experimental Considerations for Single-Cell RNA Sequencing Approaches
Nguyen, Q. H., Pervolarakis, N., Nee, K., & Kessenbrock, K. (2018) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2018.00108 · Cited by 170 · see citing works
Evolution of the cancer genome
Podlaha, O., Riester, M., De, S., & Michor, F. (2012) · Trends in Genetics · doi:10.1016/j.tig.2012.01.003 · Cited by 188 · see citing works
Resolving rates of mutation in the brain using single-neuron genomics
Evrony, G. D., Lee, E., Park, P. J., & Walsh, C. A. (2016) · eLife · doi:10.7554/elife.12966 · Cited by 163 · see citing works
An approach to suppress the evolution of resistance in BRAFV600E-mutant cancer
Xue, Y., Martelotto, L., Baslan, T., Vides, A., Solomon, M., Mai, T. T., Chaudhary, N., Riely, G. J., Li, B. T., Scott, K., et al. (2017) · Nature Medicine · doi:10.1038/nm.4369 · Cited by 174 · see citing works
Positively selected enhancer elements endow osteosarcoma cells with metastatic competence
Morrow, J. J., Bayles, I., Funnell, A. P. W., Miller, T. E., Saiakhova, A., Lizardo, M. M., Bartels, C. F., Kapteijn, M. Y., Hung, S., Mendoza, A., et al. (2018) · Nature Medicine · doi:10.1038/nm.4475 · Cited by 161 · see citing works
Merino, D., Weber, T. S., Serrano, A., Vaillant, F., Liu, K., Pal, B., Di Stefano, L., Schreuder, J., Lin, D., Chen, Y., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08595-2 · Cited by 145 · see citing works
Calibrating genomic and allelic coverage bias in single-cell sequencing
Zhang, C.-Z., Adalsteinsson, V. A., Francis, J., Cornils, H., Jung, J., Maire, C., Ligon, K. L., Meyerson, M., & Love, J. C. (2015) · Nature Communications · doi:10.1038/ncomms7822 · Cited by 112 · see citing works
Genetic Changes Shaping the Human Brain
Bae, B.-I., Jayaraman, D., & Walsh, C. A. (2015) · Developmental Cell · doi:10.1016/j.devcel.2015.01.035 · Cited by 135 · see citing works
SNES: single nucleus exome sequencing
Leung, M. L., Wang, Y., Waters, J., & Navin, N. E. (2015) · Genome Biology · doi:10.1186/s13059-015-0616-2 · Cited by 112 · see citing works
Self-citationEvolution of cellular morpho-phenotypes in cancer metastasis.
Wu, P.-H., Phillip, J. M., Khatau, S. B., Chen, W.-C., Stirman, J., Rosseel, S., Tschudi, K., Van Patten, J., Wong, M., Gupta, S., et al. (2015) · Scientific Reports · doi:10.1038/srep18437 · Cited by 117 · see citing works
Ploidy Variation in Fungi: Polyploidy, Aneuploidy, and Genome Evolution
Todd, R. T., Forche, A., & Selmecki, A. (2017) · Microbiology Spectrum · doi:10.1128/microbiolspec.funk-0051-2016 · Cited by 121 · see citing works
Barriga, F. M., Tsanov, K. M., Ho, Y.-J., Sohail, N., Zhang, A., Baslan, T., Wuest, A. N., Del Priore, I., Meškauskaitė, B., Livshits, G., et al. (2022) · Nature Cancer · doi:10.1038/s43018-022-00443-5 · Cited by 125 · see citing works
Single-cell mutational profiling and clonal phylogeny in cancer
Potter, N. E., Ermini, L., Papaemmanuil, E., Cazzaniga, G., Vijayaraghavan, G., Titley, I., Ford, A., Campbell, P., Kearney, L., & Greaves, M. (2013) · Genome Research · doi:10.1101/gr.159913.113 · Cited by 107 · see citing works
From tissues to cell types and back: single-cell gene expression analysis of tissue architecture
Chen, X., Teichmann, S. A., & Meyer, K. B. (2018) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-080917-013452 · Cited by 112 · see citing works
Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate
Stevens, M. M., Maire, C. L., Chou, N., Murakami, M. A., Knoff, D. S., Kikuchi, Y., Kimmerling, R. J., Liu, H., Haidar, S., Calistri, N. L., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3697 · Cited by 106 · see citing works
Using single‐cell multiple omics approaches to resolve tumor heterogeneity
Ortega, M. A., Poirion, O., Zhu, X., Huang, S., Wolfgruber, T. K., Sebra, R., & Garmire, L. X. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0177-y · Cited by 81 · see citing works
Zhou, J. X., Taramelli, R., Pedrini, E., Knijnenburg, T., & Huang, S. (2017) · Scientific Reports · doi:10.1038/s41598-017-09307-w · Cited by 85 · see citing works
Neutralization of terminal differentiation in gliomagenesis
Hu, J., Ho, A. L., Yuan, L., Hu, B., Hua, S., Hwang, S. S., Zhang, J., Hu, T., Zheng, H., Gan, B., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1308610110 · Cited by 76 · see citing works
Nanodelivery Systems for Nucleic Acid Therapeutics in Drug Resistant Tumors
Iyer, A. K., Duan, Z., & Amiji, M. M. (2014) · Molecular Pharmaceutics · doi:10.1021/mp500024p · Cited by 55 · see citing works
Analyzing Circulating Tumor Cells One at a Time
Ortiz, V., & Yu, M. (2018) · Trends in Cell Biology · doi:10.1016/j.tcb.2018.05.004 · Cited by 48 · see citing works
Peng, G., Cui, G., Ke, J., & Jing, N. (2020) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-120219-083220 · Cited by 42 · see citing works
Low-grade chromosomal mosaicism in human somatic and embryonic stem cell populations
Jacobs, K., Mertzanidou, A., Geens, M., Thi Nguyen, H., Staessen, C., & Spits, C. (2014) · Nature Communications · doi:10.1038/ncomms5227 · Cited by 41 · see citing works
Single-Cell Semiconductor Sequencing
Kohn, A. B., Moroz, T. P., Barnes, J. P., Netherton, M., & Moroz, L. L. (2013) · Methods in Molecular Biology · doi:10.1007/978-1-62703-556-9_18 · Cited by 22 · see citing works
Zhu, Q., Niu, Y., Gundry, M., & Zong, C. (2021) · Science Advances · doi:10.1126/sciadv.abf3329 · Cited by 18 · see citing works
Rajan, S., Zaccaria, S., Cannon, M. V., Cam, M., Gross, A. C., Raphael, B. J., & Roberts, R. D. (2021) · doi:10.1101/2021.08.30.458268 · Cited by 33 · see citing works
- Authors
- Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., Muthuswamy, L., Krasnitz, A., McCombie, W. R., Hicks, J., & Wigler, M.
- Affiliations
- Cold Spring Harbor Laboratory (US)
- Ontario Institute for Cancer Research (CA)
- Corresponding author
- Wigler, Michael
- ORCID
- Venue
- Nature
- Published
- 2011-03-13
- Volume
- 472
- Issue
- 7341
- Pages
- 90-94
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4504184
- OpenAlex
- W2032518018
- Cited by
- 2,598
- References
- 25
- Citations by year
- 2026: 74 · 2025: 113 · 2024: 125 · 2023: 140 · 2022: 185 · 2021: 190 · 2020: 159 · 2019: 144 · 2018: 171 · 2017: 191 · 2016: 208 · 2015: 223 · 2014: 232 · 2013: 214 · 2012: 167
- FWCI
- 73.10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- American Cancer Society
- National Cancer Institute (T32CA009176)
- 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
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Keywords
- tumor evolution, tumor heterogeneity, breast cancer, clonal expansion, single-nucleus sequencing, copy number variation, liver metastasis, whole genome amplification
- MeSH terms
- Breast Neoplasms, Clone Cells, Diploidy, Female, Flow Cytometry, Humans, Liver Neoplasms, Genome, Human, Sequence Analysis, DNA, Carcinoma, Ductal, Breast, Disease Progression, Genetic Heterogeneity, Evolution, Molecular, Loss of Heterozygosity, Genomics, Chromosome Breakpoints, Single-Cell Analysis
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