1
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Wang J, Ye F, Chai H, Jiang Y, Wang T, Ran X, Xia Q, Xu Z, Fu Y, Zhang G, Wu H, Guo G, Guo H, Ruan Y, Wang Y, Xing D, Xu X, Zhang Z. Advances and applications in single-cell and spatial genomics. SCIENCE CHINA. LIFE SCIENCES 2025; 68:1226-1282. [PMID: 39792333 DOI: 10.1007/s11427-024-2770-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Accepted: 10/10/2024] [Indexed: 01/12/2025]
Abstract
The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.
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Affiliation(s)
- Jingjing Wang
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Fang Ye
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Haoxi Chai
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China
| | - Yujia Jiang
- BGI Research, Shenzhen, 518083, China
- BGI Research, Hangzhou, 310030, China
| | - Teng Wang
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Xia Ran
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China
| | - Qimin Xia
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China
| | - Ziye Xu
- Department of Laboratory Medicine of The First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Yuting Fu
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Guodong Zhang
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Hanyu Wu
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Guoji Guo
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Zhejiang Provincial Key Lab for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, 310058, China.
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China.
| | - Hongshan Guo
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China.
| | - Yijun Ruan
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China.
| | - Yongcheng Wang
- Department of Laboratory Medicine of The First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
| | - Dong Xing
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China.
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, 100871, China.
| | - Xun Xu
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Hangzhou, 310030, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China.
| | - Zemin Zhang
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China.
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2
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Salcedo A, Tarabichi M, Buchanan A, Espiritu SMG, Zhang H, Zhu K, Ou Yang TH, Leshchiner I, Anastassiou D, Guan Y, Jang GH, Mootor MFE, Haase K, Deshwar AG, Zou W, Umar I, Dentro S, Wintersinger JA, Chiotti K, Demeulemeester J, Jolly C, Sycza L, Ko M, Wedge DC, Morris QD, Ellrott K, Van Loo P, Boutros PC. Crowd-sourced benchmarking of single-sample tumor subclonal reconstruction. Nat Biotechnol 2025; 43:581-592. [PMID: 38862616 PMCID: PMC11994449 DOI: 10.1038/s41587-024-02250-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 04/17/2024] [Indexed: 06/13/2024]
Abstract
Subclonal reconstruction algorithms use bulk DNA sequencing data to quantify parameters of tumor evolution, allowing an assessment of how cancers initiate, progress and respond to selective pressures. We launched the ICGC-TCGA (International Cancer Genome Consortium-The Cancer Genome Atlas) DREAM Somatic Mutation Calling Tumor Heterogeneity and Evolution Challenge to benchmark existing subclonal reconstruction algorithms. This 7-year community effort used cloud computing to benchmark 31 subclonal reconstruction algorithms on 51 simulated tumors. Algorithms were scored on seven independent tasks, leading to 12,061 total runs. Algorithm choice influenced performance substantially more than tumor features but purity-adjusted read depth, copy-number state and read mappability were associated with the performance of most algorithms on most tasks. No single algorithm was a top performer for all seven tasks and existing ensemble strategies were unable to outperform the best individual methods, highlighting a key research need. All containerized methods, evaluation code and datasets are available to support further assessment of the determinants of subclonal reconstruction accuracy and development of improved methods to understand tumor evolution.
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Affiliation(s)
- Adriana Salcedo
- Department of Human Genetics, University of California, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA.
- Institute for Precision Health, University of California, Los Angeles, CA, USA.
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
| | - Maxime Tarabichi
- The Francis Crick Institute, London, UK.
- Wellcome Sanger Institute, Hinxton, UK.
- Institute for Interdisciplinary Research, Université Libre de Bruxelles, Brussels, Belgium.
| | - Alex Buchanan
- Oregon Health and Sciences University, Portland, OR, USA
| | | | - Hongjiu Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Kaiyi Zhu
- Department of Systems Biology, Columbia University, New York, NY, USA
- Center for Cancer Systems Therapeutics, Columbia University, New York, NY, USA
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Tai-Hsien Ou Yang
- Department of Systems Biology, Columbia University, New York, NY, USA
- Center for Cancer Systems Therapeutics, Columbia University, New York, NY, USA
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | | | - Dimitris Anastassiou
- Department of Systems Biology, Columbia University, New York, NY, USA
- Center for Cancer Systems Therapeutics, Columbia University, New York, NY, USA
- Department of Electrical Engineering, Columbia University, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Yuanfang Guan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Electronic Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
| | - Gun Ho Jang
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Mohammed F E Mootor
- Department of Human Genetics, University of California, Los Angeles, CA, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA
- Institute for Precision Health, University of California, Los Angeles, CA, USA
| | | | - Amit G Deshwar
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - William Zou
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Imaad Umar
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Stefan Dentro
- The Francis Crick Institute, London, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Jeff A Wintersinger
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Kami Chiotti
- Oregon Health and Sciences University, Portland, OR, USA
| | - Jonas Demeulemeester
- The Francis Crick Institute, London, UK
- VIB Center for Cancer Biology, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
| | | | - Lesia Sycza
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Minjeong Ko
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - David C Wedge
- Big Data Institute, University of Oxford, Oxford, UK
- Manchester Cancer Research Center, University of Manchester, Manchester, UK
| | - Quaid D Morris
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Vector Institute, Toronto, Ontario, Canada
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kyle Ellrott
- Oregon Health and Sciences University, Portland, OR, USA.
| | - Peter Van Loo
- The Francis Crick Institute, London, UK.
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Paul C Boutros
- Department of Human Genetics, University of California, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA.
- Institute for Precision Health, University of California, Los Angeles, CA, USA.
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada.
- Department of Urology, University of California, Los Angeles, CA, USA.
- Broad Stem Cell Research Center, University of California, Los Angeles, CA, USA.
- California NanoSystems Institute, University of California, Los Angeles, CA, USA.
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3
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Maulding ND, Zou J, Zhou W, Metcalfe C, Stuart JM, Ye X, Hafner M. Transformer-based modeling of Clonal Selection and Expression Dynamics reveals resistance mechanisms in breast cancer. NPJ Syst Biol Appl 2025; 11:5. [PMID: 39794360 PMCID: PMC11723929 DOI: 10.1038/s41540-024-00485-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 12/25/2024] [Indexed: 01/13/2025] Open
Abstract
Understanding transcriptional heterogeneity in cancer cells and its implication for treatment response is critical to identify how resistance occurs and may be targeted. Such heterogeneity can be captured by in vitro studies through clonal barcoding methods. We present TraCSED (Transformer-based modeling of Clonal Selection and Expression Dynamics), a dynamic deep learning approach for modeling clonal selection. Using single-cell gene expression and the fitness of barcoded clones, TraCSED identifies interpretable gene programs and the time points at which they are associated with clonal selection. When applied to cells treated with either giredestrant, a selective estrogen receptor (ER) antagonist and degrader, or palbociclib, a CDK4/6 inhibitor, pathways dynamically associated with resistance are revealed. For example, ER activity is associated with positive selection around day four under palbociclib treatment and this adaptive response can be suppressed by combining the drugs. Yet, in the combination treatment, one clone still emerged. Clustering based on partial least squares regression found that high baseline expression of both SNHG25 and SNCG genes was the primary marker of positive selection to co-treatment and thus potentially associated with innate resistance - an aspect that traditional differential analysis methods missed. In conclusion, TraCSED enables associating features with phenotypes in a time-dependent manner from scRNA-seq data.
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Affiliation(s)
- Nathan D Maulding
- gRED Computational Sciences, Genentech Inc, South San Francisco, CA, USA
- Department of Biomolecular Engineering and Bioinformatics, UC Santa Cruz, Santa Cruz, CA, USA
| | - Jun Zou
- Discovery Oncology, Genentech Inc, South San Francisco, CA, USA
| | - Wei Zhou
- Discovery Oncology, Genentech Inc, South San Francisco, CA, USA
| | - Ciara Metcalfe
- Discovery Oncology, Genentech Inc, South San Francisco, CA, USA
| | - Joshua M Stuart
- Department of Biomolecular Engineering and Bioinformatics, UC Santa Cruz, Santa Cruz, CA, USA
| | - Xin Ye
- Discovery Oncology, Genentech Inc, South San Francisco, CA, USA
| | - Marc Hafner
- gRED Computational Sciences, Genentech Inc, South San Francisco, CA, USA.
- Discovery Oncology, Genentech Inc, South San Francisco, CA, USA.
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4
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Lin Y, Wang J, Wang K, Bai S, Thennavan A, Wei R, Yan Y, Li J, Elgamal H, Sei E, Casasent A, Rao M, Tang C, Multani AS, Ma J, Montalvan J, Nagi C, Winocour S, Lim B, Thompson A, Navin N. Normal breast tissues harbour rare populations of aneuploid epithelial cells. Nature 2024; 636:663-670. [PMID: 39567687 DOI: 10.1038/s41586-024-08129-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 09/27/2024] [Indexed: 11/22/2024]
Abstract
Aneuploid epithelial cells are common in breast cancer1,2; however, their presence in normal breast tissues is not well understood. To address this question, we applied single-cell DNA sequencing to profile copy number alterations in 83,206 epithelial cells from the breast tissues of 49 healthy women, and we applied single-cell DNA and assay for transposase-accessible chromatin sequencing co-assays to the samples of 19 women. Our data show that all women harboured rare aneuploid epithelial cells (median 3.19%) that increased with age. Many aneuploid epithelial cells (median 82.22%) in normal breast tissues underwent clonal expansions and harboured copy number alterations reminiscent of invasive breast cancers (gains of 1q; losses of 10q, 16q and 22q). Co-assay profiling showed that the aneuploid cells were mainly associated with the two luminal epithelial lineages, and spatial mapping showed that they localized in ductal and lobular structures with normal histopathology. Collectively, these data show that even healthy women have clonal expansions of rare aneuploid epithelial cells in their breast tissues.
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Affiliation(s)
- Yiyun Lin
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Junke Wang
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kaile Wang
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Shanshan Bai
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Aatish Thennavan
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Runmin Wei
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yun Yan
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jianzhuo Li
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Heba Elgamal
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Emi Sei
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Anna Casasent
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mitchell Rao
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Chenling Tang
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Asha S Multani
- Department of Genetics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jin Ma
- Department of Genetics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Chandandeep Nagi
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
| | | | - Bora Lim
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Nicholas Navin
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Graduate School of Biomedical Sciences, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genetics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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5
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Yuan DJ, Zinno J, Botella T, Dhingra D, Wang S, Hawkins A, Swett A, Sotelo J, Raviram R, Hughes C, Potenski C, Yokoyama A, Kakiuchi N, Ogawa S, Landau DA. Genotype-to-phenotype mapping of somatic clonal mosaicism via single-cell co-capture of DNA mutations and mRNA transcripts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.22.595241. [PMID: 38826366 PMCID: PMC11142212 DOI: 10.1101/2024.05.22.595241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Somatic mosaicism is a hallmark of malignancy that is also pervasively observed in human physiological aging, with clonal expansions of cells harboring mutations in recurrently mutated driver genes. Bulk sequencing of tissue microdissection captures mutation frequencies, but cannot distinguish which mutations co-occur in the same clones to reconstruct clonal architectures, nor phenotypically profile clonal populations to delineate how driver mutations impact cellular behavior. To address these challenges, we developed single-cell Genotype-to-Phenotype sequencing (scG2P) for high-throughput, highly-multiplexed, single-cell joint capture of recurrently mutated genomic regions and mRNA phenotypic markers in cells or nuclei isolated from solid tissues. We applied scG2P to aged esophagus samples from five individuals with high alcohol and tobacco exposure and observed a clonal landscape dominated by a large number of clones with a single driver event, but only rare clones with two driver mutations. NOTCH1 mutants dominate the clonal landscape and are linked to stunted epithelial differentiation, while TP53 mutants and double-driver mutants promote clonal expansion through both differentiation biases and increased cell cycling. Thus, joint single-cell highly multiplexed capture of somatic mutations and mRNA transcripts enables high resolution reconstruction of clonal architecture and associated phenotypes in solid tissue somatic mosaicism.
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Affiliation(s)
- Dennis J Yuan
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - John Zinno
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Theo Botella
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | | | | | - Allegra Hawkins
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Ariel Swett
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Jesus Sotelo
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Ramya Raviram
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Clayton Hughes
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Catherine Potenski
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Akira Yokoyama
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Medical Oncology, Kyoto University, Kyoto, Japan
| | - Nobuyuki Kakiuchi
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- The Hakubi Center for Advanced Research, Kyoto University, Kyoto, Japan
| | - Seishi Ogawa
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
| | - Dan A Landau
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
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6
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Liu Y, Edrisi M, Yan Z, A Ogilvie H, Nakhleh L. NestedBD: Bayesian inference of phylogenetic trees from single-cell copy number profiles under a birth-death model. Algorithms Mol Biol 2024; 19:18. [PMID: 38685065 PMCID: PMC11059640 DOI: 10.1186/s13015-024-00264-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 03/27/2024] [Indexed: 05/02/2024] Open
Abstract
Copy number aberrations (CNAs) are ubiquitous in many types of cancer. Inferring CNAs from cancer genomic data could help shed light on the initiation, progression, and potential treatment of cancer. While such data have traditionally been available via "bulk sequencing," the more recently introduced techniques for single-cell DNA sequencing (scDNAseq) provide the type of data that makes CNA inference possible at the single-cell resolution. We introduce a new birth-death evolutionary model of CNAs and a Bayesian method, NestedBD, for the inference of evolutionary trees (topologies and branch lengths with relative mutation rates) from single-cell data. We evaluated NestedBD's performance using simulated data sets, benchmarking its accuracy against traditional phylogenetic tools as well as state-of-the-art methods. The results show that NestedBD infers more accurate topologies and branch lengths, and that the birth-death model can improve the accuracy of copy number estimation. And when applied to biological data sets, NestedBD infers plausible evolutionary histories of two colorectal cancer samples. NestedBD is available at https://github.com/Androstane/NestedBD .
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Affiliation(s)
- Yushu Liu
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA.
| | - Mohammadamin Edrisi
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA
| | - Zhi Yan
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA
| | - Huw A Ogilvie
- Department of Genetics, University of Texas MD Anderson Cancer Center, TX, 77030, Houston, USA
| | - Luay Nakhleh
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA
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7
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Goyal Y, Busch GT, Pillai M, Li J, Boe RH, Grody EI, Chelvanambi M, Dardani IP, Emert B, Bodkin N, Braun J, Fingerman D, Kaur A, Jain N, Ravindran PT, Mellis IA, Kiani K, Alicea GM, Fane ME, Ahmed SS, Li H, Chen Y, Chai C, Kaster J, Witt RG, Lazcano R, Ingram DR, Johnson SB, Wani K, Dunagin MC, Lazar AJ, Weeraratna AT, Wargo JA, Herlyn M, Raj A. Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells. Nature 2023; 620:651-659. [PMID: 37468627 PMCID: PMC10628994 DOI: 10.1038/s41586-023-06342-8] [Citation(s) in RCA: 81] [Impact Index Per Article: 40.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 06/19/2023] [Indexed: 07/21/2023]
Abstract
Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells1-7. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy7-9; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.
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Affiliation(s)
- Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA.
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA.
| | - Gianna T Busch
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Maalavika Pillai
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jingxin Li
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ryan H Boe
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Emanuelle I Grody
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Manoj Chelvanambi
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ian P Dardani
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin Emert
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicholas Bodkin
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jonas Braun
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Amanpreet Kaur
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Naveen Jain
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pavithran T Ravindran
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian A Mellis
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Karun Kiani
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gretchen M Alicea
- Department of Biochemistry and Molecular Biology, Johns Hopkins School of Public Health, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Mitchell E Fane
- Department of Biochemistry and Molecular Biology, Johns Hopkins School of Public Health, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Syeda Subia Ahmed
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Haiyin Li
- The Wistar Institute, Philadelphia, PA, USA
| | | | - Cedric Chai
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Reproductive Science, Northwestern University, Chicago, IL, USA
| | | | - Russell G Witt
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rossana Lazcano
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Davis R Ingram
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sarah B Johnson
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Khalida Wani
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Margaret C Dunagin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexander J Lazar
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ashani T Weeraratna
- Department of Biochemistry and Molecular Biology, Johns Hopkins School of Public Health, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Jennifer A Wargo
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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8
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Pillai M, Hojel E, Jolly MK, Goyal Y. Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools. NATURE COMPUTATIONAL SCIENCE 2023; 3:301-313. [PMID: 38177938 DOI: 10.1038/s43588-023-00427-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 03/03/2023] [Indexed: 01/06/2024]
Abstract
Individual cells within an otherwise genetically homogenous population constantly undergo fluctuations in their molecular state, giving rise to non-genetic heterogeneity. Such diversity is being increasingly implicated in cancer therapy resistance and metastasis. Identifying the origins of non-genetic heterogeneity is therefore crucial for making clinical breakthroughs. We discuss with examples how dynamical models and computational tools have provided critical multiscale insights into the nature and consequences of non-genetic heterogeneity in cancer. We demonstrate how mechanistic modeling has been pivotal in establishing key concepts underlying non-genetic diversity at various biological scales, from population dynamics to gene regulatory networks. We discuss advances in single-cell longitudinal profiling techniques to reveal patterns of non-genetic heterogeneity, highlighting the ongoing efforts and challenges in statistical frameworks to robustly interpret such multimodal datasets. Moving forward, we stress the need for data-driven statistical and mechanistically motivated dynamical frameworks to come together to develop predictive cancer models and inform therapeutic strategies.
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Affiliation(s)
- Maalavika Pillai
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Emilia Hojel
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Evanston, IL, USA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India.
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA.
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Evanston, IL, USA.
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9
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Zhang H, Karnoub ER, Umeda S, Chaligné R, Masilionis I, McIntyre CA, Sashittal P, Hayashi A, Zucker A, Mullen K, Hong J, Makohon-Moore A, Iacobuzio-Donahue CA. Application of high-throughput single-nucleus DNA sequencing in pancreatic cancer. Nat Commun 2023; 14:749. [PMID: 36765116 PMCID: PMC9918733 DOI: 10.1038/s41467-023-36344-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 01/24/2023] [Indexed: 02/12/2023] Open
Abstract
Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.
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Affiliation(s)
- Haochen Zhang
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Elias-Ramzey Karnoub
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Shigeaki Umeda
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ronan Chaligné
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ignas Masilionis
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Palash Sashittal
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Akimasa Hayashi
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Kyorin University School of Medicine, Mitaka City, Tokyo, Japan
| | - Amanda Zucker
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- School of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - Katelyn Mullen
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jungeui Hong
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alvin Makohon-Moore
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, NJ, USA
| | - Christine A Iacobuzio-Donahue
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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