1
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Stonehouse OJ, Biben C, Weber TS, Garnham A, Fennell KA, Farley A, Terreaux AF, Alexander WS, Dawson MA, Naik SH, Taoudi S. Clonal analysis of fetal hematopoietic stem/progenitor cells reveals how post-transplantation capabilities are distributed. Stem Cell Reports 2024; 19:1189-1204. [PMID: 39094562 DOI: 10.1016/j.stemcr.2024.07.003] [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: 03/13/2024] [Revised: 07/02/2024] [Accepted: 07/02/2024] [Indexed: 08/04/2024] Open
Abstract
It has been proposed that adult hematopoiesis is sustained by multipotent progenitors (MPPs) specified during embryogenesis. Adult-like hematopoietic stem cell (HSC) and MPP immunophenotypes are present in the fetus, but knowledge of their functional capacity is incomplete. We found that fetal MPP populations were functionally similar to adult cells, albeit with some differences in lymphoid output. Clonal assessment revealed that lineage biases arose from differences in patterns of single-/bi-lineage differentiation. Long-term (LT)- and short-term (ST)-HSC populations were distinguished from MPPs according to capacity for clonal multilineage differentiation. We discovered that a large cohort of long-term repopulating units (LT-RUs) resides within the ST-HSC population; a significant portion of these were labeled using Flt3-cre. This finding has two implications: (1) use of the CD150+ LT-HSC immunophenotype alone will significantly underestimate the size and diversity of the LT-RU pool and (2) LT-RUs in the ST-HSC population have the attributes required to persist into adulthood.
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Affiliation(s)
- Olivia J Stonehouse
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia; Lowy Cancer Research Centre, UNSW, Sydney, New South Wales, Australia
| | - Christine Biben
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia
| | - Tom S Weber
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia
| | - Alexandra Garnham
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia
| | - Katie A Fennell
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alison Farley
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia
| | - Antoine F Terreaux
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia
| | - Warren S Alexander
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia
| | - Mark A Dawson
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia; The University of Melbourne Centre for Cancer Research, The University of Melbourne, Melbourne, Victoria, Australia
| | - Shalin H Naik
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia
| | - Samir Taoudi
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; The University of Melbourne, Melbourne, Victoria, Australia; School of Cellular and Molecular Medicine, University of Bristol, Bristol, England, UK.
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2
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Gao Y, Feder AF. Detecting branching rate heterogeneity in multifurcating trees with applications in lineage tracing data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.27.601073. [PMID: 39005367 PMCID: PMC11244928 DOI: 10.1101/2024.06.27.601073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Understanding cellular birth rate differences is crucial for predicting cancer progression and interpreting tumor-derived genetic data. Lineage tracing experiments enable detailed reconstruction of cellular genealogies, offering new opportunities to measure branching rate heterogeneity. However, the lineage tracing process can introduce complex tree features that complicate this effort. Here, we examine tree characteristics in lineage tracing-derived genealogies and find that editing window placement leads to multifurcations at a tree's root or tips. We propose several ways in which existing tree topology-based metrics can be extended to test for rate heterogeneity on trees even in the presence of lineage-tracing associated distortions. Although these methods vary in power and robustness, a test based on the J 1 statistic effectively detects branching rate heterogeneity in simulated lineage tracing data. Tests based on other common statistics ( ŝ and the Sackin index) show interior performance to J 1 . We apply our validated methods to xenograft experimental data and find widespread rate heterogeneity across multiple study systems. Our results demonstrate the potential of tree topology statistics in analyzing lineage tracing data, and highlight the challenges associated with adapting phylogenetic methods to these systems.
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3
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Cristalli C, Scotlandi K. Targeting DNA Methylation Machinery in Pediatric Solid Tumors. Cells 2024; 13:1209. [PMID: 39056791 PMCID: PMC11275080 DOI: 10.3390/cells13141209] [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: 05/20/2024] [Revised: 07/08/2024] [Accepted: 07/16/2024] [Indexed: 07/28/2024] Open
Abstract
DNA methylation is a key epigenetic regulatory mechanism that plays a critical role in a variety of cellular processes, including the regulation of cell fate during development, maintenance of cell identity, and genome stability. DNA methylation is tightly regulated by enzymatic reactions and its deregulation plays an important role in the development of cancer. Specific DNA methylation alterations have been found in pediatric solid tumors, providing new insights into the development of these tumors. In addition, DNA methylation profiles have greatly contributed to tune the diagnosis of pediatric solid tumors and to define subgroups of patients with different risks of progression, leading to the reduction in unwanted toxicity and the improvement of treatment efficacy. This review highlights the dysregulated DNA methylome in pediatric solid tumors and how this information provides promising targets for epigenetic therapies, particularly inhibitors of DNMT enzymes (DNMTis). Opportunities and limitations are considered, including the ability of DNMTis to induce viral mimicry and immune signaling by tumors. Besides intrinsic action against cancer cells, DNMTis have the potential to sensitize immune-cold tumors to immunotherapies and may represent a remarkable option to improve the treatment of challenging pediatric solid tumors.
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Affiliation(s)
- Camilla Cristalli
- Laboratory of Experimental Oncology, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano, 1/10, 40136 Bologna, Italy
| | - Katia Scotlandi
- Laboratory of Experimental Oncology, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano, 1/10, 40136 Bologna, Italy
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4
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Zhang Z, Melzer ME, Arun KM, Sun H, Eriksson CJ, Fabian I, Shaashua S, Kiani K, Oren Y, Goyal Y. Synthetic DNA barcodes identify singlets in scRNA-seq datasets and evaluate doublet algorithms. CELL GENOMICS 2024; 4:100592. [PMID: 38925122 PMCID: PMC11293576 DOI: 10.1016/j.xgen.2024.100592] [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: 08/08/2023] [Revised: 03/26/2024] [Accepted: 06/05/2024] [Indexed: 06/28/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) datasets contain true single cells, or singlets, in addition to cells that coalesce during the protocol, or doublets. Identifying singlets with high fidelity in scRNA-seq is necessary to avoid false negative and false positive discoveries. Although several methodologies have been proposed, they are typically tested on highly heterogeneous datasets and lack a priori knowledge of true singlets. Here, we leveraged datasets with synthetically introduced DNA barcodes for a hitherto unexplored application: to extract ground-truth singlets. We demonstrated the feasibility of our framework, "singletCode," to evaluate existing doublet detection methods across a range of contexts. We also leveraged our ground-truth singlets to train a proof-of-concept machine learning classifier, which outperformed other doublet detection algorithms. Our integrative framework can identify ground-truth singlets and enable robust doublet detection in non-barcoded datasets.
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Affiliation(s)
- Ziyang Zhang
- 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, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Madeline E Melzer
- 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, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Keerthana M Arun
- 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, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Hanxiao Sun
- 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, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Carl-Johan Eriksson
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Itai Fabian
- Department of Human Molecular Genetics & Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Sagi Shaashua
- Department of Human Molecular Genetics & Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Karun Kiani
- Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yaara Oren
- Department of Human Molecular Genetics & Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - 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, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; CZ Biohub Chicago, Chicago, IL, USA.
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5
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Winter PS, Ramseier ML, Navia AW, Saksena S, Strouf H, Senhaji N, DenAdel A, Mirza M, An HH, Bilal L, Dennis P, Leahy CS, Shigemori K, Galves-Reyes J, Zhang Y, Powers F, Mulugeta N, Gupta AJ, Calistri N, Van Scoyk A, Jones K, Liu H, Stevenson KE, Ren S, Luskin MR, Couturier CP, Amini AP, Raghavan S, Kimmerling RJ, Stevens MM, Crawford L, Weinstock DM, Manalis SR, Shalek AK, Murakami MA. Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597767. [PMID: 38915726 PMCID: PMC11195125 DOI: 10.1101/2024.06.06.597767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.
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Affiliation(s)
- Peter S. Winter
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Michelle L. Ramseier
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Andrew W. Navia
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Sachit Saksena
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
- Computational and Systems Biology Program, MIT, Cambridge, MA, USA
| | - Haley Strouf
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Nezha Senhaji
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Alan DenAdel
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
- Department of Biostatistics, Brown University, Providence, RI, USA
| | - Mahnoor Mirza
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Hyun Hwan An
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Laura Bilal
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Peter Dennis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Catharine S. Leahy
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kay Shigemori
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jennyfer Galves-Reyes
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Ye Zhang
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
| | - Foster Powers
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Nolawit Mulugeta
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | | | - Nicholas Calistri
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Alex Van Scoyk
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kristen Jones
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Huiyun Liu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Siyang Ren
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA USA
| | - Marlise R. Luskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Charles P. Couturier
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | | | - Srivatsan Raghavan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | - Mark M. Stevens
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Lorin Crawford
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
- Department of Biostatistics, Brown University, Providence, RI, USA
- Microsoft Research, Cambridge, MA, USA
| | - David M. Weinstock
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Current Address: Merck and Co., Rahway, NJ, USA
| | - Scott R. Manalis
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
| | - Alex K. Shalek
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Mark A. Murakami
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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6
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Whiting FJH, Househam J, Baker AM, Sottoriva A, Graham TA. Phenotypic noise and plasticity in cancer evolution. Trends Cell Biol 2024; 34:451-464. [PMID: 37968225 DOI: 10.1016/j.tcb.2023.10.002] [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: 07/13/2023] [Revised: 09/29/2023] [Accepted: 10/04/2023] [Indexed: 11/17/2023]
Abstract
Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these phenomena can influence a cell's fitness by conferring access to heritable, beneficial phenotypes. Herein, we argue that current discussions of 'phenotypic plasticity' in cancer evolution ignore a salient feature of the original definition: namely, that it occurs in response to an environmental change. We suggest 'phenotypic noise' be used to distinguish non-genetic changes in phenotype that occur independently from the environment. We discuss the conceptual and methodological techniques used to identify these phenomena during cancer evolution. We propose that the distinction will guide efforts to define mechanisms of phenotype change, accelerate translational work to manipulate phenotypes through treatment, and, ultimately, improve patient outcomes.
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Affiliation(s)
| | - Jacob Househam
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Ann-Marie Baker
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Andrea Sottoriva
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK; Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Trevor A Graham
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
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7
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Aalam SMM, Nguyen LV, Ritting ML, Kannan N. Clonal tracking in cancer and metastasis. Cancer Metastasis Rev 2024; 43:639-656. [PMID: 37910295 DOI: 10.1007/s10555-023-10149-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 10/16/2023] [Indexed: 11/03/2023]
Abstract
The eradication of many cancers has proven challenging due to the presence of functionally and genetically heterogeneous clones maintained by rare cancer stem cells (CSCs), which contribute to disease progression, treatment refractoriness, and late relapse. The characterization of functional CSC activity has necessitated the development of modern clonal tracking strategies. This review describes viral-based and CRISPR-Cas9-based cellular barcoding, lineage tracing, and imaging-based approaches. DNA-based cellular barcoding technology is emerging as a powerful and robust strategy that has been widely applied to in vitro and in vivo model systems, including patient-derived xenograft models. This review also highlights the potential of these methods for use in the clinical and drug discovery contexts and discusses the important insights gained from such approaches.
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Affiliation(s)
| | - Long Viet Nguyen
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Megan L Ritting
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Nagarajan Kannan
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
- Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, MN, USA.
- Center for Regenerative Biotherapeutics, Mayo Clinic, Rochester, MN, USA.
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8
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Jindal K, Adil MT, Yamaguchi N, Yang X, Wang HC, Kamimoto K, Rivera-Gonzalez GC, Morris SA. Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes. Nat Biotechnol 2024; 42:946-959. [PMID: 37749269 PMCID: PMC11180607 DOI: 10.1038/s41587-023-01931-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 07/31/2023] [Indexed: 09/27/2023]
Abstract
Complex gene regulatory mechanisms underlie differentiation and reprogramming. Contemporary single-cell lineage-tracing (scLT) methods use expressed, heritable DNA barcodes to combine cell lineage readout with single-cell transcriptomics. However, reliance on transcriptional profiling limits adaptation to other single-cell assays. With CellTag-multi, we present an approach that enables direct capture of heritable random barcodes expressed as polyadenylated transcripts, in both single-cell RNA sequencing and single-cell Assay for Transposase Accessible Chromatin using sequencing assays, allowing for independent clonal tracking of transcriptional and epigenomic cell states. We validate CellTag-multi to characterize progenitor cell lineage priming during mouse hematopoiesis. Additionally, in direct reprogramming of fibroblasts to endoderm progenitors, we identify core regulatory programs underlying on-target and off-target fates. Furthermore, we reveal the transcription factor Zfp281 as a regulator of reprogramming outcome, biasing cells toward an off-target mesenchymal fate. Our results establish CellTag-multi as a lineage-tracing method compatible with multiple single-cell modalities and demonstrate its utility in revealing fate-specifying gene regulatory changes across diverse paradigms of differentiation and reprogramming.
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Affiliation(s)
- Kunal Jindal
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Mohd Tayyab Adil
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Naoto Yamaguchi
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Xue Yang
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Helen C Wang
- Department of Pediatrics, Division of Hematology and Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Kenji Kamimoto
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Guillermo C Rivera-Gonzalez
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Samantha A Morris
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA.
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA.
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9
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Lenz G. Heterogeneity generating capacity in tumorigenesis and cancer therapeutics. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167226. [PMID: 38734320 DOI: 10.1016/j.bbadis.2024.167226] [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: 12/08/2023] [Revised: 04/26/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024]
Abstract
Cells of multicellular organisms generate heterogeneity in a controlled and transient fashion during embryogenesis, which can be reactivated in pathologies such as cancer. Although genomic heterogeneity is an important part of tumorigenesis, continuous generation of phenotypic heterogeneity is central for the adaptation of cancer cells to the challenges of tumorigenesis and response to therapy. Here I discuss the capacity of generating heterogeneity, hereafter called cell hetness, in cancer cells both as the activation of hetness oncogenes and inactivation of hetness tumor suppressor genes, which increase the generation of heterogeneity, ultimately producing an increase in adaptability and cell fitness. Transcriptomic high hetness states in therapy-tolerant cell states denote its importance in cancer resistance to therapy. The definition of the concept of hetness will allow the understanding of its origins, its control during embryogenesis, its loss of control in tumorigenesis and cancer therapeutics and its active targeting.
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Affiliation(s)
- Guido Lenz
- Departamento de Biofísica, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Centro de Biotecnologia, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil.
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10
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Schiroli G, Kartha V, Duarte FM, Kristiansen TA, Mayerhofer C, Shrestha R, Earl A, Hu Y, Tay T, Rhee C, Buenrostro JD, Scadden DT. Cell of origin epigenetic priming determines susceptibility to Tet2 mutation. Nat Commun 2024; 15:4325. [PMID: 38773071 PMCID: PMC11109152 DOI: 10.1038/s41467-024-48508-6] [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: 06/17/2023] [Accepted: 04/30/2024] [Indexed: 05/23/2024] Open
Abstract
Hematopoietic stem cell (HSC) mutations can result in clonal hematopoiesis (CH) with heterogeneous clinical outcomes. Here, we investigate how the cell state preceding Tet2 mutation impacts the pre-malignant phenotype. Using an inducible system for clonal analysis of myeloid progenitors, we find that the epigenetic features of clones at similar differentiation status are highly heterogeneous and functionally respond differently to Tet2 mutation. Cell differentiation stage also influences Tet2 mutation response indicating that the cell of origin's epigenome modulates clone-specific behaviors in CH. Molecular features associated with higher risk outcomes include Sox4 that sensitizes cells to Tet2 inactivation, inducing dedifferentiation, altered metabolism and increasing the in vivo clonal output of mutant cells, as confirmed in primary GMP and HSC models. Our findings validate the hypothesis that epigenetic features can predispose specific clones for dominance, explaining why identical genetic mutations can result in different phenotypes.
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Affiliation(s)
- Giulia Schiroli
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Vinay Kartha
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Fabiana M Duarte
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Trine A Kristiansen
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Christina Mayerhofer
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Rojesh Shrestha
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Andrew Earl
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Yan Hu
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Tristan Tay
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Catherine Rhee
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Jason D Buenrostro
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA.
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA.
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
| | - David T Scadden
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA.
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA.
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11
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Holze H, Talarmain L, Fennell KA, Lam EY, Dawson MA, Vassiliadis D. Analysis of synthetic cellular barcodes in the genome and transcriptome with BARtab and bartools. CELL REPORTS METHODS 2024; 4:100763. [PMID: 38670101 PMCID: PMC11133760 DOI: 10.1016/j.crmeth.2024.100763] [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: 12/20/2023] [Revised: 02/25/2024] [Accepted: 04/03/2024] [Indexed: 04/28/2024]
Abstract
Cellular barcoding is a lineage-tracing methodology that couples heritable synthetic barcodes to high-throughput sequencing, enabling the accurate tracing of cell lineages across a range of biological contexts. Recent studies have extended these methods by incorporating lineage information into single-cell or spatial transcriptomics readouts. Leveraging the rich biological information within these datasets requires dedicated computational tools for dataset pre-processing and analysis. Here, we present BARtab, a portable and scalable Nextflow pipeline, and bartools, an open-source R package, designed to provide an integrated end-to-end cellular barcoding analysis toolkit. BARtab and bartools contain methods to simplify the extraction, quality control, analysis, and visualization of lineage barcodes from population-level, single-cell, and spatial transcriptomics experiments. We showcase the utility of our integrated BARtab and bartools workflow via the analysis of exemplar bulk, single-cell, and spatial transcriptomics experiments containing cellular barcoding information.
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Affiliation(s)
- Henrietta Holze
- Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC 3000, Australia
| | - Laure Talarmain
- Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC 3000, Australia
| | - Katie A Fennell
- Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC 3000, Australia
| | - Enid Y Lam
- Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC 3000, Australia
| | - Mark A Dawson
- Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC 3000, Australia; The University of Melbourne Centre for Cancer Research, The University of Melbourne, Melbourne, VIC 3000, Australia.
| | - Dane Vassiliadis
- Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC 3000, Australia.
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12
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Karras P, Black JRM, McGranahan N, Marine JC. Decoding the interplay between genetic and non-genetic drivers of metastasis. Nature 2024; 629:543-554. [PMID: 38750233 DOI: 10.1038/s41586-024-07302-6] [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: 06/24/2022] [Accepted: 03/12/2024] [Indexed: 05/18/2024]
Abstract
Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.
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Affiliation(s)
- Panagiotis Karras
- Laboratory for Molecular Cancer Biology, VIB Center for Cancer Biology, KU Leuven, Leuven, Belgium
- Department of Oncology, KU Leuven, Leuven, Belgium
| | - James R M Black
- Cancer Genome Evolution Research Group, UCL Cancer Institute, London, UK
| | | | - Jean-Christophe Marine
- Laboratory for Molecular Cancer Biology, VIB Center for Cancer Biology, KU Leuven, Leuven, Belgium.
- Department of Oncology, KU Leuven, Leuven, Belgium.
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13
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Decollogny M, Rottenberg S. Persisting cancer cells are different from bacterial persisters. Trends Cancer 2024; 10:393-406. [PMID: 38429144 DOI: 10.1016/j.trecan.2024.02.002] [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: 10/20/2023] [Revised: 01/22/2024] [Accepted: 02/02/2024] [Indexed: 03/03/2024]
Abstract
The persistence of drug-sensitive tumors poses a significant challenge in cancer treatment. The concept of bacterial persisters, which are a subpopulation of bacteria that survive lethal antibiotic doses, is frequently used to compare to residual disease in cancer. Here, we explore drug tolerance of cancer cells and bacteria. We highlight the fact that bacteria, in contrast to cancer cells, have been selected for survival at the population level and may therefore possess contingency mechanisms that cancer cells lack. The precise mechanisms of drug-tolerant cancer cells and bacterial persisters are still being investigated. Undoubtedly, by understanding common features as well as differences, we, in the cancer field, can learn from microbiology to find strategies to eradicate persisting cancer cells.
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Affiliation(s)
- Morgane Decollogny
- Institute of Animal Pathology, Vetsuisse Faculty, University of Bern, Bern, Switzerland; Bern Center for Precision Medicine and Department for BioMedical Research, University of Bern, Bern, Switzerland
| | - Sven Rottenberg
- Institute of Animal Pathology, Vetsuisse Faculty, University of Bern, Bern, Switzerland; Bern Center for Precision Medicine and Department for BioMedical Research, University of Bern, Bern, Switzerland.
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14
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Parreno V, Loubiere V, Schuettengruber B, Fritsch L, Rawal CC, Erokhin M, Győrffy B, Normanno D, Di Stefano M, Moreaux J, Butova NL, Chiolo I, Chetverina D, Martinez AM, Cavalli G. Transient loss of Polycomb components induces an epigenetic cancer fate. Nature 2024; 629:688-696. [PMID: 38658752 PMCID: PMC11096130 DOI: 10.1038/s41586-024-07328-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/15/2024] [Indexed: 04/26/2024]
Abstract
Although cancer initiation and progression are generally associated with the accumulation of somatic mutations1,2, substantial epigenomic alterations underlie many aspects of tumorigenesis and cancer susceptibility3-6, suggesting that genetic mechanisms might not be the only drivers of malignant transformation7. However, whether purely non-genetic mechanisms are sufficient to initiate tumorigenesis irrespective of mutations has been unknown. Here, we show that a transient perturbation of transcriptional silencing mediated by Polycomb group proteins is sufficient to induce an irreversible switch to a cancer cell fate in Drosophila. This is linked to the irreversible derepression of genes that can drive tumorigenesis, including members of the JAK-STAT signalling pathway and zfh1, the fly homologue of the ZEB1 oncogene, whose aberrant activation is required for Polycomb perturbation-induced tumorigenesis. These data show that a reversible depletion of Polycomb proteins can induce cancer in the absence of driver mutations, suggesting that tumours can emerge through epigenetic dysregulation leading to inheritance of altered cell fates.
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Affiliation(s)
- V Parreno
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France
| | - V Loubiere
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France
- Research Institute of Molecular Pathology, Vienna BioCenter, Vienna, Austria
| | - B Schuettengruber
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France
| | - L Fritsch
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France
| | - C C Rawal
- University of Southern California, Los Angeles, CA, USA
| | - M Erokhin
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russia
| | - B Győrffy
- Semmelweis University Department of Bioinformatics, Budapest, Hungary
- Department of Biophysics, Medical School, University of Pécs, Pécs, Hungary
| | - D Normanno
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France
| | - M Di Stefano
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France
| | - J Moreaux
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France
- Department of Biological Hematology, CHU Montpellier, Montpellier, France
- UFR Medicine, University of Montpellier, Montpellier, France
| | - N L Butova
- University of Southern California, Los Angeles, CA, USA
| | - I Chiolo
- University of Southern California, Los Angeles, CA, USA
| | - D Chetverina
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russia
| | - A-M Martinez
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France.
| | - G Cavalli
- Institute of Human Genetics, CNRS, University of Montpellier, Montpellier, France.
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15
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Olesinski EA, Bhatia KS, Wang C, Pioso MS, Lin XX, Mamdouh AM, Ng SX, Sandhu V, Jasdanwala SS, Yilma B, Bohl S, Ryan JA, Malani D, Luskin MR, Kallioniemi O, Porkka K, Adamia S, Chng WJ, Osato M, Weinstock DM, Garcia JS, Letai A, Bhatt S. Acquired Multidrug Resistance in AML Is Caused by Low Apoptotic Priming in Relapsed Myeloblasts. Blood Cancer Discov 2024; 5:180-201. [PMID: 38442309 PMCID: PMC11061585 DOI: 10.1158/2643-3230.bcd-24-0001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/05/2023] [Accepted: 12/19/2023] [Indexed: 03/07/2024] Open
Abstract
In many cancers, mortality is associated with the emergence of relapse with multidrug resistance (MDR). Thus far, the investigation of cancer relapse mechanisms has largely focused on acquired genetic mutations. Using acute myeloid leukemia (AML) patient-derived xenografts (PDX), we systematically elucidated a basis of MDR and identified drug sensitivity in relapsed AML. We derived pharmacologic sensitivity for 22 AML PDX models using dynamic BH3 profiling (DBP), together with genomics and transcriptomics. Using in vivo acquired resistant PDXs, we found that resistance to unrelated, narrowly targeted agents in distinct PDXs was accompanied by broad resistance to drugs with disparate mechanisms. Moreover, baseline mitochondrial apoptotic priming was consistently reduced regardless of the class of drug-inducing selection. By applying DBP, we identified drugs showing effective in vivo activity in resistant models. This study implies evasion of apoptosis drives drug resistance and demonstrates the feasibility of the DBP approach to identify active drugs for patients with relapsed AML. SIGNIFICANCE Acquired resistance to targeted therapy remains challenging in AML. We found that reduction in mitochondrial priming and common transcriptomic signatures was a conserved mechanism of acquired resistance across different drug classes in vivo. Drugs active in vivo can be identified even in the multidrug resistant state by DBP.
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MESH Headings
- Leukemia, Myeloid, Acute/drug therapy
- Leukemia, Myeloid, Acute/pathology
- Leukemia, Myeloid, Acute/genetics
- Humans
- Apoptosis/drug effects
- Animals
- Mice
- Drug Resistance, Neoplasm/drug effects
- Drug Resistance, Neoplasm/genetics
- Drug Resistance, Multiple/genetics
- Drug Resistance, Multiple/drug effects
- Xenograft Model Antitumor Assays
- Granulocyte Precursor Cells/drug effects
- Granulocyte Precursor Cells/pathology
- Antineoplastic Agents/pharmacology
- Antineoplastic Agents/therapeutic use
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Affiliation(s)
- Elyse A. Olesinski
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | | | - Chuqi Wang
- Department of Pharmacy, National University of Singapore, Singapore
| | - Marissa S. Pioso
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Xiao Xian Lin
- Department of Pharmacy, National University of Singapore, Singapore
| | - Ahmed M. Mamdouh
- Department of Pharmacy, National University of Singapore, Singapore
| | - Shu Xuan Ng
- Department of Pharmacy, National University of Singapore, Singapore
| | - Vedant Sandhu
- Department of Pharmacy, National University of Singapore, Singapore
| | | | - Binyam Yilma
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Stephan Bohl
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jeremy A. Ryan
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Disha Malani
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Marlise R. Luskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Olli Kallioniemi
- Institute for Molecular Medicine Finland FIMM, Hi-Life, University of Helsinki, Helsinki, Finland
- Science for Life Laboratory, Department of Oncology and Pathology, Karolinska Institute, Solna, Sweden
| | - Kimmo Porkka
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Department of Hematology, HUS, Helsinki, Finland
| | - Sophia Adamia
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Wee Joo Chng
- Cancer Science Institute of Singapore, National University of Singapore, Centre for Translational Medicine, Singapore
| | - Motomi Osato
- Cancer Science Institute of Singapore, National University of Singapore, Centre for Translational Medicine, Singapore
| | - David M. Weinstock
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jacqueline S. Garcia
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Anthony Letai
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Shruti Bhatt
- Department of Pharmacy, National University of Singapore, Singapore
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16
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Hollands CG, Boyd AL, Zhao X, Reid JC, Henly C, ElRafie A, Boylan D, Broder E, Kalau O, Johnson P, Mark A, McNicol J, Xenocostas A, Berg T, Foley R, Trus M, Leber B, Garcia-Horton A, Campbell C, Bhatia M. Identification of cells of leukemic stem cell origin with non-canonical regenerative properties. Cell Rep Med 2024; 5:101485. [PMID: 38582086 PMCID: PMC11031376 DOI: 10.1016/j.xcrm.2024.101485] [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: 05/19/2023] [Revised: 10/19/2023] [Accepted: 03/04/2024] [Indexed: 04/08/2024]
Abstract
Despite most acute myeloid leukemia (AML) patients entering remission following chemotherapy, outcomes remain poor due to surviving leukemic cells that contribute to relapse. The nature of these enduring cells is poorly understood. Here, through temporal single-cell transcriptomic characterization of AML hierarchical regeneration in response to chemotherapy, we reveal a cell population: AML regeneration enriched cells (RECs). RECs are defined by CD74/CD68 expression, and although derived from leukemic stem cells (LSCs), are devoid of stem/progenitor capacity. Based on REC in situ proximity to CD34-expressing cells identified using spatial transcriptomics on AML patient bone marrow samples, RECs demonstrate the ability to augment or reduce leukemic regeneration in vivo based on transfusion or depletion, respectively. Furthermore, RECs are prognostic for patient survival as well as predictive of treatment failure in AML cohorts. Our study reveals RECs as a previously unknown functional catalyst of LSC-driven regeneration contributing to the non-canonical framework of AML regeneration.
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Affiliation(s)
- Cameron G Hollands
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Allison L Boyd
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Xueli Zhao
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Jennifer C Reid
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Charisa Henly
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Amro ElRafie
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - David Boylan
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Emily Broder
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Olivia Kalau
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Paige Johnson
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Alyssa Mark
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Jamie McNicol
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - Anargyros Xenocostas
- Department of Medicine, Division of Hematology, Schulich School of Medicine, University of Western Ontario, London, Ontario N6A 3K7, Canada; Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada
| | - Tobias Berg
- Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada; Department of Oncology, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Ronan Foley
- Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada; Department of Oncology, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Michael Trus
- Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Brian Leber
- Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Alejandro Garcia-Horton
- Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada; Department of Oncology, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Clinton Campbell
- Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Mickie Bhatia
- Michael G. DeGroote School of Medicine, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada; Hematology Exploration and Applications in Leukemia (HEAL) Program, Hamilton, ON, Canada.
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17
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Scherer M, Singh I, Braun M, Szu-Tu C, Kardorff M, Rühle J, Frömel R, Beneyto-Calabuig S, Raffel S, Rodriguez-Fraticelli A, Velten L. Somatic epimutations enable single-cell lineage tracing in native hematopoiesis across the murine and human lifespan. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.01.587514. [PMID: 38617287 PMCID: PMC11014487 DOI: 10.1101/2024.04.01.587514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Current approaches to lineage tracing of stem cell clones require genetic engineering or rely on sparse somatic DNA variants, which are difficult to capture at single-cell resolution. Here, we show that targeted single-cell measurements of DNA methylation at single-CpG resolution deliver joint information about cellular differentiation state and clonal identities. We develop EPI-clone, a droplet-based method for transgene-free lineage tracing, and apply it to study hematopoiesis, capturing hundreds of clonal trajectories across almost 100,000 single-cells. Using ground-truth genetic barcodes, we demonstrate that EPI-clone accurately identifies clonal lineages throughout hematopoietic differentiation. Applied to unperturbed hematopoiesis, we describe an overall decline of clonal complexity during murine ageing and the expansion of rare low-output stem cell clones. In aged human donors, we identified expanded hematopoietic clones with and without genetic lesions, and various degrees of clonal complexity. Taken together, EPI-clone enables accurate and transgene-free single-cell lineage tracing at scale.
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Affiliation(s)
- Michael Scherer
- Computational Biology and Health Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Indranil Singh
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Martina Braun
- Computational Biology and Health Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Chelsea Szu-Tu
- Computational Biology and Health Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Michael Kardorff
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Julia Rühle
- Computational Biology and Health Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Robert Frömel
- Computational Biology and Health Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Sergi Beneyto-Calabuig
- Computational Biology and Health Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Simon Raffel
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Alejo Rodriguez-Fraticelli
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Lars Velten
- Computational Biology and Health Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
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18
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Eisele AS, Tarbier M, Dormann AA, Pelechano V, Suter DM. Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets. Nat Commun 2024; 15:2744. [PMID: 38553478 PMCID: PMC10980719 DOI: 10.1038/s41467-024-47158-y] [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: 01/29/2024] [Accepted: 03/20/2024] [Indexed: 04/02/2024] Open
Abstract
Assigning single cell transcriptomes to cellular lineage trees by lineage tracing has transformed our understanding of differentiation during development, regeneration, and disease. However, lineage tracing is technically demanding, often restricted in time-resolution, and most scRNA-seq datasets are devoid of lineage information. Here we introduce Gene Expression Memory-based Lineage Inference (GEMLI), a computational tool allowing to robustly identify small to medium-sized cell lineages solely from scRNA-seq datasets. GEMLI allows to study heritable gene expression, to discriminate symmetric and asymmetric cell fate decisions and to reconstruct individual multicellular structures from pooled scRNA-seq datasets. In human breast cancer biopsies, GEMLI reveals previously unknown gene expression changes at the onset of cancer invasiveness. The universal applicability of GEMLI allows studying the role of small cell lineages in a wide range of physiological and pathological contexts, notably in vivo. GEMLI is available as an R package on GitHub ( https://github.com/UPSUTER/GEMLI ).
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Affiliation(s)
- A S Eisele
- Ecole Polytechnique Fédérale de Lausanne, School of Life Sciences, Institute of Bioengineering, Lausanne, Switzerland.
| | - M Tarbier
- Science for Life Laboratory, Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Solna, Sweden
| | - A A Dormann
- Ecole Polytechnique Fédérale de Lausanne, School of Life Sciences, Institute of Bioengineering, Lausanne, Switzerland
| | - V Pelechano
- Science for Life Laboratory, Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Solna, Sweden
| | - D M Suter
- Ecole Polytechnique Fédérale de Lausanne, School of Life Sciences, Institute of Bioengineering, Lausanne, Switzerland.
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19
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Lee E, Zhang Z, Chen CC, Choi D, Rivera ACA, Linton E, Ho YJ, Love J, LaClair J, Wongvipat J, Sawyers CL. Timing of treatment shapes the path to androgen receptor signaling inhibitor resistance in prostate cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585532. [PMID: 38562884 PMCID: PMC10983989 DOI: 10.1101/2024.03.18.585532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
There is optimism that cancer drug resistance can be addressed through appropriate combination therapy, but success requires understanding the growing complexity of resistance mechanisms, including the evolution and population dynamics of drug-sensitive and drug-resistant clones over time. Using DNA barcoding to trace individual prostate tumor cells in vivo , we find that the evolutionary path to acquired resistance to androgen receptor signaling inhibition (ARSI) is dependent on the timing of treatment. In established tumors, resistance occurs through polyclonal adaptation of drug-sensitive clones, despite the presence of rare subclones with known, pre-existing ARSI resistance. Conversely, in an experimental setting designed to mimic minimal residual disease, resistance occurs through outgrowth of pre-existing resistant clones and not by adaptation. Despite these different evolutionary paths, the underlying mechanisms responsible for resistance are shared across the two evolutionary paths. Furthermore, mixing experiments reveal that the evolutionary path to adaptive resistance requires cooperativity between subclones. Thus, despite the presence of pre-existing ARSI-resistant subclones, acquired resistance in established tumors occurs primarily through cooperative, polyclonal adaptation of drug-sensitive cells. This tumor ecosystem model of resistance has new implications for developing effective combination therapy.
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20
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Kapadia CD, Goodell MA. Tissue mosaicism following stem cell aging: blood as an exemplar. NATURE AGING 2024; 4:295-308. [PMID: 38438628 DOI: 10.1038/s43587-024-00589-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 02/07/2024] [Indexed: 03/06/2024]
Abstract
Loss of stem cell regenerative potential underlies aging of all tissues. Somatic mosaicism, the emergence of cellular patchworks within tissues, increases with age and has been observed in every organ yet examined. In the hematopoietic system, as in most tissues, stem cell aging through a variety of mechanisms occurs in lockstep with the emergence of somatic mosaicism. Here, we draw on insights from aging hematopoiesis to illustrate fundamental principles of stem cell aging and somatic mosaicism. We describe the generalizable changes intrinsic to aged stem cells and their milieu that provide the backdrop for somatic mosaicism to emerge. We discuss genetic and nongenetic mechanisms that can result in tissue somatic mosaicism and existing methodologies to detect such clonal outgrowths. Finally, we propose potential avenues to modify mosaicism during aging, with the ultimate aim of increasing tissue resiliency.
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Affiliation(s)
- Chiraag D Kapadia
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
- Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX, USA
| | - Margaret A Goodell
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA.
- Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX, USA.
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21
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Achinger-Kawecka J, Stirzaker C, Portman N, Campbell E, Chia KM, Du Q, Laven-Law G, Nair SS, Yong A, Wilkinson A, Clifton S, Milioli HH, Alexandrou S, Caldon CE, Song J, Khoury A, Meyer B, Chen W, Pidsley R, Qu W, Gee JMW, Schmitt A, Wong ES, Hickey TE, Lim E, Clark SJ. The potential of epigenetic therapy to target the 3D epigenome in endocrine-resistant breast cancer. Nat Struct Mol Biol 2024; 31:498-512. [PMID: 38182927 PMCID: PMC10948365 DOI: 10.1038/s41594-023-01181-7] [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: 12/13/2022] [Accepted: 11/15/2023] [Indexed: 01/07/2024]
Abstract
Three-dimensional (3D) epigenome remodeling is an important mechanism of gene deregulation in cancer. However, its potential as a target to counteract therapy resistance remains largely unaddressed. Here, we show that epigenetic therapy with decitabine (5-Aza-mC) suppresses tumor growth in xenograft models of pre-clinical metastatic estrogen receptor positive (ER+) breast tumor. Decitabine-induced genome-wide DNA hypomethylation results in large-scale 3D epigenome deregulation, including de-compaction of higher-order chromatin structure and loss of boundary insulation of topologically associated domains. Significant DNA hypomethylation associates with ectopic activation of ER-enhancers, gain in ER binding, creation of new 3D enhancer-promoter interactions and concordant up-regulation of ER-mediated transcription pathways. Importantly, long-term withdrawal of epigenetic therapy partially restores methylation at ER-enhancer elements, resulting in a loss of ectopic 3D enhancer-promoter interactions and associated gene repression. Our study illustrates the potential of epigenetic therapy to target ER+ endocrine-resistant breast cancer by DNA methylation-dependent rewiring of 3D chromatin interactions, which are associated with the suppression of tumor growth.
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Affiliation(s)
- Joanna Achinger-Kawecka
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia.
| | - Clare Stirzaker
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Neil Portman
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Elyssa Campbell
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Kee-Ming Chia
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Qian Du
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Geraldine Laven-Law
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
| | - Shalima S Nair
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Aliza Yong
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Ashleigh Wilkinson
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Samuel Clifton
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Heloisa H Milioli
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Sarah Alexandrou
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - C Elizabeth Caldon
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Jenny Song
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Amanda Khoury
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Braydon Meyer
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Wenhan Chen
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Ruth Pidsley
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Wenjia Qu
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Julia M W Gee
- Breast Cancer Molecular Pharmacology Group, School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, Wales, UK
| | | | - Emily S Wong
- Victor Chang Cardiac Institute, Sydney, New South Wales, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - Theresa E Hickey
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
| | - Elgene Lim
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Susan J Clark
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia.
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22
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Mold JE, Weissman MH, Ratz M, Hagemann-Jensen M, Hård J, Eriksson CJ, Toosi H, Berghenstråhle J, Ziegenhain C, von Berlin L, Martin M, Blom K, Lagergren J, Lundeberg J, Sandberg R, Michaëlsson J, Frisén J. Clonally heritable gene expression imparts a layer of diversity within cell types. Cell Syst 2024; 15:149-165.e10. [PMID: 38340731 DOI: 10.1016/j.cels.2024.01.004] [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: 08/24/2022] [Revised: 05/25/2023] [Accepted: 01/18/2024] [Indexed: 02/12/2024]
Abstract
Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high-coverage single-cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying clonal human lymphocytes and mouse brain cells, we uncovered a vast diversity of heritable gene expression patterns among different clones of cells of the same type in vivo. We combined chromatin accessibility and RNA profiling on different lymphocyte clones to reveal thousands of regulatory regions exhibiting interclonal variation, which could be directly linked to interclonal variation in gene expression. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging, and disease. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Jeff E Mold
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Martin H Weissman
- Mathematics Department, University of California, Santa Cruz, CA, USA.
| | - Michael Ratz
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden; SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | - Joanna Hård
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Carl-Johan Eriksson
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Hosein Toosi
- SciLifeLab, Computational Science and Technology Department, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Joseph Berghenstråhle
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Christoph Ziegenhain
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Leonie von Berlin
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Marcel Martin
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, SciLifeLab, Stockholm University, Stockholm, Sweden
| | - Kim Blom
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden
| | - Jens Lagergren
- SciLifeLab, Computational Science and Technology Department, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Joakim Lundeberg
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Rickard Sandberg
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Jakob Michaëlsson
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden.
| | - Jonas Frisén
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
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23
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Fabre MA, Vassiliou GS. The lifelong natural history of clonal hematopoiesis and its links to myeloid neoplasia. Blood 2024; 143:573-581. [PMID: 37992214 DOI: 10.1182/blood.2023019964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 10/26/2023] [Accepted: 11/13/2023] [Indexed: 11/24/2023] Open
Abstract
ABSTRACT The study of somatic mutations and the associated clonal mosaicism across the human body has transformed our understanding of aging and its links to cancer. In proliferative human tissues, stem cells compete for dominance, and those with an advantage expand clonally to outgrow their peers. In the hematopoietic system, such expansion is termed clonal hematopoiesis (CH). The forces driving competition, namely heterogeneity of the hematopoietic stem cell (HSC) pool and attrition of their environment, become increasingly prominent with age. As a result, CH becomes progressively more common through life to the point of becoming essentially ubiquitous. We are beginning to unravel the specific intracellular and extracellular factors underpinning clonal behavior, with somatic mutations in specific driver genes, inflammation, telomere maintenance, extraneous exposures, and inherited genetic variation among the important players. The inevitability of CH with age combined with its unequivocal links to myeloid cancers poses a scientific and clinical challenge. Specifically, we need to decipher the factors determining clonal behavior and develop prognostic tools to identify those at high risk of malignant progression, for whom preventive interventions may be warranted. Here, we discuss how recent advances in our understanding of the natural history of CH have provided important insights into these processes and helped define future avenues of investigation.
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Affiliation(s)
- Margarete A Fabre
- Department of Haematology, Cambridge University Hospitals National Health Service Trust, Cambridge, United Kingdom
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals Research & Development, AstraZeneca, Cambridge, United Kingdom
| | - George S Vassiliou
- Department of Haematology, Cambridge University Hospitals National Health Service Trust, Cambridge, United Kingdom
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
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24
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Calderon A, Han C, Karma S, Wang E. Non-genetic mechanisms of drug resistance in acute leukemias. Trends Cancer 2024; 10:38-51. [PMID: 37839973 DOI: 10.1016/j.trecan.2023.09.003] [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: 06/20/2023] [Revised: 09/13/2023] [Accepted: 09/14/2023] [Indexed: 10/17/2023]
Abstract
Acute leukemia is characterized by clonal heterogeneity that contributes to poor drug responses in patients. Despite treatment advances, the occurrence of relapse remains a major barrier to achieving cures as current therapeutic approaches are inadequate to effectively prevent or overcome resistance. Given that only a few genetic mutations are associated with relapse in acute leukemia patients, there is a growing focus on 'non-genetic' mechanisms that affect the hallmarks of cancer to allow leukemic cells to survive post therapy. In this review, we provide an overview of the therapeutic landscape in acute leukemias. Importantly, we discuss non-genetic mechanisms exploited by leukemic cells to promote their survival after treatment. Last, we present current strategies to prevent or overcome drug resistance in this disease.
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Affiliation(s)
| | - Cuijuan Han
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Sadik Karma
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; Graduate Program in Genetics and Development, UConn Health, Farmington, CT, USA
| | - Eric Wang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA; Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, USA.
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25
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Guirguis AA, Ofir-Rosenfeld Y, Knezevic K, Blackaby W, Hardick D, Chan YC, Motazedian A, Gillespie A, Vassiliadis D, Lam EYN, Tran K, Andrews B, Harbour ME, Vasiliauskaite L, Saunders CJ, Tsagkogeorga G, Azevedo A, Obacz J, Pilka ES, Carkill M, MacPherson L, Wainwright EN, Liddicoat B, Blyth BJ, Albertella MR, Rausch O, Dawson MA. Inhibition of METTL3 Results in a Cell-Intrinsic Interferon Response That Enhances Antitumor Immunity. Cancer Discov 2023; 13:2228-2247. [PMID: 37548590 DOI: 10.1158/2159-8290.cd-23-0007] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 06/06/2023] [Accepted: 08/02/2023] [Indexed: 08/08/2023]
Abstract
Therapies that enhance antitumor immunity have altered the natural history of many cancers. Consequently, leveraging nonoverlapping mechanisms to increase immunogenicity of cancer cells remains a priority. Using a novel enzymatic inhibitor of the RNA methyl-transferase METTL3, we demonstrate a global decrease in N6-methyladenosine (m6A) results in double-stranded RNA (dsRNA) formation and a profound cell-intrinsic interferon response. Through unbiased CRISPR screens, we establish dsRNA-sensing and interferon signaling are primary mediators that potentiate T-cell killing of cancer cells following METTL3 inhibition. We show in a range of immunocompetent mouse models that although METTL3 inhibition is equally efficacious to anti-PD-1 therapy, the combination has far greater preclinical activity. Using SPLINTR barcoding, we demonstrate that anti-PD-1 therapy and METTL3 inhibition target distinct malignant clones, and the combination of these therapies overcomes clones insensitive to the single agents. These data provide the mole-cular and preclinical rationale for employing METTL3 inhibitors to promote antitumor immunity in the clinic. SIGNIFICANCE This work demonstrates that METTL3 inhibition stimulates a cell-intrinsic interferon response through dsRNA formation. This immunomodulatory mechanism is distinct from current immunotherapeutic agents and provides the molecular rationale for combination with anti-PD-1 immune-checkpoint blockade to augment antitumor immunity. This article is featured in Selected Articles from This Issue, p. 2109.
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Affiliation(s)
- Andrew A Guirguis
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
- Department of Clinical Haematology, Peter MacCallum Cancer Centre and The Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | | | - Kathy Knezevic
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | | | | | - Yih-Chih Chan
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Ali Motazedian
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Andrea Gillespie
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Dane Vassiliadis
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Enid Y N Lam
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Kevin Tran
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | | | | | | | | | - Georgia Tsagkogeorga
- Storm Therapeutics Ltd, Cambridge, United Kingdom
- Milner Therapeutics Institute, University of Cambridge, Cambridge, United Kingdom
| | | | - Joanna Obacz
- Storm Therapeutics Ltd, Cambridge, United Kingdom
| | | | - Marie Carkill
- Charles River Laboratories, Portishead, United -Kingdom
| | - Laura MacPherson
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Elanor N Wainwright
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Brian Liddicoat
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Benjamin J Blyth
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | | | | | - Mark A Dawson
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
- Department of Clinical Haematology, Peter MacCallum Cancer Centre and The Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Centre for Cancer Research, University of Melbourne, Melbourne, -Victoria, Australia
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26
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Ashouri A, Zhang C, Gaiti F. Decoding Cancer Evolution: Integrating Genetic and Non-Genetic Insights. Genes (Basel) 2023; 14:1856. [PMID: 37895205 PMCID: PMC10606072 DOI: 10.3390/genes14101856] [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: 09/01/2023] [Revised: 09/19/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
The development of cancer begins with cells transitioning from their multicellular nature to a state akin to unicellular organisms. This shift leads to a breakdown in the crucial regulators inherent to multicellularity, resulting in the emergence of diverse cancer cell subpopulations that have enhanced adaptability. The presence of different cell subpopulations within a tumour, known as intratumoural heterogeneity (ITH), poses challenges for cancer treatment. In this review, we delve into the dynamics of the shift from multicellularity to unicellularity during cancer onset and progression. We highlight the role of genetic and non-genetic factors, as well as tumour microenvironment, in promoting ITH and cancer evolution. Additionally, we shed light on the latest advancements in omics technologies that allow for in-depth analysis of tumours at the single-cell level and their spatial organization within the tissue. Obtaining such detailed information is crucial for deepening our understanding of the diverse evolutionary paths of cancer, allowing for the development of effective therapies targeting the key drivers of cancer evolution.
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Affiliation(s)
- Arghavan Ashouri
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada
| | - Chufan Zhang
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Federico Gaiti
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
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27
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Zhang J, Han X, Ma L, Xu S, Lin Y. Deciphering a global source of non-genetic heterogeneity in cancer cells. Nucleic Acids Res 2023; 51:9019-9038. [PMID: 37587722 PMCID: PMC10516630 DOI: 10.1093/nar/gkad666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 07/09/2023] [Accepted: 08/09/2023] [Indexed: 08/18/2023] Open
Abstract
Cell-to-cell variability within a clonal population, also known as non-genetic heterogeneity, has created significant challenges for intervening with diseases such as cancer. While non-genetic heterogeneity can arise from the variability in the expression of specific genes, it remains largely unclear whether and how clonal cells could be heterogeneous in the expression of the entire transcriptome. Here, we showed that gene transcriptional activity is globally modulated in individual cancer cells, leading to non-genetic heterogeneity in the global transcription rate. Such heterogeneity contributes to cell-to-cell variability in transcriptome size and displays both dynamic and static characteristics, with the global transcription rate temporally modulated in a cell-cycle-coupled manner and the time-averaged rate being distinct between cells and heritable across generations. Additional evidence indicated the role of ATP metabolism in this heterogeneity, and suggested its implication in intrinsic cancer drug tolerance. Collectively, our work shed light on the mode, mechanism, and implication of a global but often hidden source of non-genetic heterogeneity.
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Affiliation(s)
- Jianhan Zhang
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
| | - Xu Han
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
| | - Liang Ma
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
| | - Shuhui Xu
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
| | - Yihan Lin
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
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28
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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: 55] [Impact Index Per Article: 55.0] [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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Hockings H, Lakatos E, Huang W, Mossner M, Khan MA, Metcalf S, Nicolini F, Smith K, Baker AM, Graham TA, Lockley M. Adaptive therapy achieves long-term control of chemotherapy resistance in high grade ovarian cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.21.549688. [PMID: 37546942 PMCID: PMC10401956 DOI: 10.1101/2023.07.21.549688] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Drug resistance results in poor outcomes for most patients with metastatic cancer. Adaptive Therapy (AT) proposes to address this by exploiting presumed fitness costs incurred by drug-resistant cells when drug is absent, and prescribing dose reductions to allow fitter, sensitive cells to re-grow and re-sensitise the tumour. However, empirical evidence for treatment-induced fitness change is lacking. We show that fitness costs in chemotherapy-resistant ovarian cancer cause selective decline and apoptosis of resistant populations in low-resource conditions. Moreover, carboplatin AT caused fluctuations in sensitive/resistant tumour population size in vitro and significantly extended survival of tumour-bearing mice. In sequential blood-derived cell-free DNA and tumour samples obtained longitudinally from ovarian cancer patients during treatment, we inferred resistant cancer cell population size through therapy and observed it correlated strongly with disease burden. These data have enabled us to launch a multicentre, phase 2 randomised controlled trial (ACTOv) to evaluate AT in ovarian cancer.
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Affiliation(s)
- Helen Hockings
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Eszter Lakatos
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Weini Huang
- School of Mathematical Sciences, Queen Mary University of London, London, UK
| | - Maximilian Mossner
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Mohammed Ateeb Khan
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Stephen Metcalf
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Francesco Nicolini
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Kane Smith
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Ann-Marie Baker
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Trevor A. Graham
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
| | - Michelle Lockley
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
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30
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O'Connor D, Demeulemeester J, Conde L, Kirkwood A, Fung K, Papaleonidopoulou F, Bloye G, Farah N, Rahman S, Hancock J, Bateman C, Inglott S, Mee J, Herrero J, Van Loo P, Moorman AV, Vora A, Mansour MR. The Clinicogenomic Landscape of Induction Failure in Childhood and Young Adult T-Cell Acute Lymphoblastic Leukemia. J Clin Oncol 2023; 41:3545-3556. [PMID: 37098241 PMCID: PMC10306434 DOI: 10.1200/jco.22.02734] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/30/2023] [Accepted: 03/06/2023] [Indexed: 04/27/2023] Open
Abstract
PURPOSE Failure to respond to induction chemotherapy portends a poor outcome in childhood acute lymphoblastic leukemia (ALL) and is more frequent in T-cell ALL (T-ALL) than B-cell ALL. We aimed to address the limited understanding of clinical and genetic factors that influence outcome in a cohort of patients with T-ALL induction failure (IF). METHODS We studied all cases of T-ALL IF on two consecutive multinational randomized trials, UKALL2003 and UKALL2011, to define risk factors, treatment, and outcomes. We performed multiomic profiling to characterize the genomic landscape. RESULTS IF occurred in 10.3% of cases and was significantly associated with increasing age, occurring in 20% of patients age 16 years and older. Five-year overall survival (OS) rates were 52.1% in IF and 90.2% in responsive patients (P < .001). Despite increased use of nelarabine-based chemotherapy consolidated by hematopoietic stem-cell transplant in UKALL2011, there was no improvement in outcome. Persistent end-of-consolidation molecular residual disease resulted in a significantly worse outcome (5-year OS, 14.3% v 68.5%; HR, 4.10; 95% CI, 1.35 to 12.45; P = .0071). Genomic profiling revealed a heterogeneous picture with 25 different initiating lesions converging on 10 subtype-defining genes. There was a remarkable abundance of TAL1 noncoding lesions, associated with a dismal outcome (5-year OS, 12.5%). Combining TAL1 lesions with mutations in the MYC and RAS pathways produces a genetic stratifier that identifies patients highly likely to fail conventional therapy (5-year OS, 23.1% v 86.4%; HR, 6.84; 95% CI, 2.78 to 16.78; P < .0001) and who should therefore be considered for experimental agents. CONCLUSION The outcome of IF in T-ALL remains poor with current therapy. The lack of a unifying genetic driver suggests alternative approaches, particularly using immunotherapy, are urgently needed.
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Affiliation(s)
- David O'Connor
- UCL Cancer Institute, University College London, London, United Kingdom
- Department of Haematology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Jonas Demeulemeester
- The Francis Crick Institute, London, United Kingdom
- VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium
- Department of Oncology, Laboratory for Integrative Cancer Genomics, KU Leuven, Leuven, Belgium
| | - Lucia Conde
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Amy Kirkwood
- CR UK & UCL Cancer Trials Centre, UCL Cancer Institute, UCL, London, United Kingdom
| | - Kent Fung
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Foteini Papaleonidopoulou
- UCL Cancer Institute, University College London, London, United Kingdom
- The Francis Crick Institute, London, United Kingdom
| | - Gianna Bloye
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Nadine Farah
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Sunniyat Rahman
- UCL Cancer Institute, University College London, London, United Kingdom
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
| | - Jeremy Hancock
- South West Genomic Laboratory Hub, North Bristol NHS Trust, Bristol, United Kingdom
| | | | - Sarah Inglott
- Department of Haematology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Jon Mee
- Cancer Research UK Clinical Trials Unit, University of Birmingham, Birmingham, United Kingdom
| | - Javier Herrero
- UCL Cancer Institute, University College London, London, United Kingdom
| | - Peter Van Loo
- The Francis Crick Institute, London, United Kingdom
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Anthony V. Moorman
- Wolfson Childhood Cancer Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Ajay Vora
- Department of Haematology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Marc R. Mansour
- UCL Cancer Institute, University College London, London, United Kingdom
- Department of Developmental Biology and Cancer, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
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Howland KK, Brock A. Cellular barcoding tracks heterogeneous clones through selective pressures and phenotypic transitions. Trends Cancer 2023; 9:591-601. [PMID: 37105856 PMCID: PMC10339273 DOI: 10.1016/j.trecan.2023.03.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/27/2023] [Accepted: 03/28/2023] [Indexed: 04/29/2023]
Abstract
Genomic DNA barcoding has emerged as a sensitive and flexible tool to measure the fates of clonal subpopulations within a heterogeneous cancer cell population. Coupling cellular barcoding with single-cell transcriptomics permits the longitudinal analysis of molecular mechanisms with detailed clone-level resolution. Numerous recent studies have employed these tools to track clonal cell states in cancer progression and treatment response. With these new technologies comes the opportunity to examine longstanding questions about the origins and contributions of tumor cell heterogeneity and the roles of selection and phenotypic plasticity in disease progression and treatment.
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Affiliation(s)
- Kennedy K Howland
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78734, USA
| | - Amy Brock
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78734, USA.
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Li SQ, Chen M, Huang XY, Wang H, Chang YJ. Challenges facing minimal residual disease testing for acute myeloid leukemia and promising strategies to overcome them. Expert Rev Hematol 2023; 16:981-990. [PMID: 37978882 DOI: 10.1080/17474086.2023.2285985] [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: 08/24/2023] [Accepted: 11/16/2023] [Indexed: 11/19/2023]
Abstract
INTRODUCTION Minimal residual disease (MRD) has been an important biomarker for relapse prediction and treatment choice in patients with acute myeloid leukemia (AML). False-positive or false-negative MRD results due to the low specificity and sensitivity of techniques such as multiparameter flow cytometry (MFC), real-time quantitative polymerase chain reaction, and next-generation sequencing, as well as the biological characteristics of residual leukemia cells, including antigen shift, clone involution, heterogeneous genome of the blast cells, and lack of specific targets, all restrict the clinical use of MRD. AREAS COVERED We summarized the challenges of the techniques for MRD detection, and their application in the clinical setting. We also discussed strategies to overcome these challenges, such as the MFC MRD method based on leukemia stem cells, single-cell DNA sequencing or single-cell RNA sequencing for the investigation of biological characteristics of residual leukemia cells, and the potential of omics techniques for MRD detection. We further noted out that prospective clinical trials are needed to answer clinical questions related to MRD in patients with AML. EXPERT OPINION MRD is an important biomarker for individual therapy of patients with AML. In the future, it is important to increase the specificity and sensitivity of the detection techniques.
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Affiliation(s)
- Si-Qi Li
- National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Peking University People's Hospital & Peking University Institute of Hematology, Beijing, Xicheng District, P.R.C
| | - Man Chen
- Department of Laboratory Medicine, Hebei Yanda Ludaopei Hospital, Langfang, Hebei, P.R.C
| | - Xi-Yi Huang
- Department of Experimental Medicine, School of Public Health, Xiamen University, Xiamen, P.R.C
| | - Hui Wang
- Department of Laboratory Medicine, Hebei Yanda Ludaopei Hospital, Langfang, Hebei, P.R.C
| | - Ying-Jun Chang
- National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Peking University People's Hospital & Peking University Institute of Hematology, Beijing, Xicheng District, P.R.C
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Tshering LF, Luo F, Russ S, Szenk M, Rubel D, Tutuska K, Rail JG, Balázsi G, Shen MM, Talos F. Immune mechanisms shape the clonal landscape during early progression of prostate cancer. Dev Cell 2023; 58:1071-1086.e8. [PMID: 37148881 PMCID: PMC10330387 DOI: 10.1016/j.devcel.2023.04.010] [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: 03/19/2022] [Revised: 12/18/2022] [Accepted: 04/14/2023] [Indexed: 05/08/2023]
Abstract
Understanding the role of the immune microenvironment in modulating intratumor heterogeneity is essential for effective cancer therapies. Using multicolor lineage tracing in genetically engineered mouse models and single-cell transcriptomics, we show that slowly progressing tumors contain a multiclonal landscape of relatively homogeneous subpopulations within a well-organized tumor microenvironment. In more advanced and aggressive tumors, however, the multiclonal landscape develops into competing dominant and minor clones accompanied by a disordered microenvironment. We demonstrate that this dominant/minor landscape is associated with differential immunoediting, in which minor clones are marked by an increased expression of IFNγ-response genes and the T cell-activating chemokines Cxcl9 and Cxcl11. Furthermore, immunomodulation of the IFNγ pathway can rescue minor clones from elimination. Notably, the immune-specific gene signature of minor clones exhibits a prognostic value for biochemical recurrence-free survival in human prostate cancer. These findings suggest new immunotherapy approaches for modulating clonal fitness and tumor progression in prostate cancer.
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Affiliation(s)
- Lara F Tshering
- Department of Urology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Pathology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Fu Luo
- Department of Urology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Pathology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Savanah Russ
- Department of Urology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Pathology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Mariola Szenk
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Diana Rubel
- Department of Urology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Pathology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Karis Tutuska
- Department of Urology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Pathology, Stony Brook University, Stony Brook, NY 11794, USA
| | - James G Rail
- Department of Urology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Pathology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Gábor Balázsi
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Michael M Shen
- Departments of Medicine, Genetics & Development, Urology, and Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA.
| | - Flaminia Talos
- Department of Urology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Pathology, Stony Brook University, Stony Brook, NY 11794, USA; Departments of Medicine, Genetics & Development, Urology, and Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY 11794, USA.
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Wang Y, Zhang X, Wang Z. Cellular barcoding: From developmental tracing to anti-tumor drug discovery. Cancer Lett 2023:216281. [PMID: 37336285 DOI: 10.1016/j.canlet.2023.216281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/31/2023] [Accepted: 06/10/2023] [Indexed: 06/21/2023]
Abstract
Clonal evolution has gained immense attention in explaining cancer cell status, history, and fate during cancer progression. Current single-cell or spatial transcriptome technologies have broadened our understanding of various mechanisms underlying cancer initiation, relapse, and drug resistance. However, technical challenges still hinder a better understanding of the dynamics of distinctive phenotypic states and abnormal trajectories from normal physiological transition to malignant stages. Cellular barcoding enabled lineage tracing on parallelly massive cells at single-cell resolution through different mechanisms lately, enabling new insights into exploring developmental trajectories, cancer progression, and targeted therapies. This review summarizes the latest noteworthy and robust strategies for different types of cellular barcodes. To introduce the major characteristics, advantages and limitations of these different strategies, this review will further guide in choosing or improving cellular barcoding technologies and their applications in cancer research.
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Affiliation(s)
- Yuqing Wang
- Medical Center of Hematology, The Second Affiliated Hospital, Army Medical University, Chongqing, 40037, China; State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 40037, China
| | - Xi Zhang
- Medical Center of Hematology, The Second Affiliated Hospital, Army Medical University, Chongqing, 40037, China; State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 40037, China; Jinfeng Laboratory, Chongqing, 401329, China.
| | - Zheng Wang
- Medical Center of Hematology, The Second Affiliated Hospital, Army Medical University, Chongqing, 40037, China; State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 40037, China; Bio-Med Informatics Research Center & Clinical Research Center, The Second Affiliated Hospital, Army Medical University, Chongqing, 400037, China; Jinfeng Laboratory, Chongqing, 401329, China.
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Tian L, Chen F, Macosko EZ. The expanding vistas of spatial transcriptomics. Nat Biotechnol 2023; 41:773-782. [PMID: 36192637 PMCID: PMC10091579 DOI: 10.1038/s41587-022-01448-2] [Citation(s) in RCA: 102] [Impact Index Per Article: 102.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 07/26/2022] [Indexed: 11/09/2022]
Abstract
The formation and maintenance of tissue integrity requires complex, coordinated activities by thousands of genes and their encoded products. Until recently, transcript levels could only be quantified for a few genes in tissues, but advances in DNA sequencing, oligonucleotide synthesis and fluorescence microscopy have enabled the invention of a suite of spatial transcriptomics technologies capable of measuring the expression of many, or all, genes in situ. These technologies have evolved rapidly in sensitivity, multiplexing and throughput. As such, they have enabled the determination of the cell-type architecture of tissues, the querying of cell-cell interactions and the monitoring of molecular interactions between tissue components. The rapidly evolving spatial genomics landscape will enable generalized high-throughput genomic measurements and perturbations to be performed in the context of tissues. These advances will empower hypothesis generation and biological discovery and bridge the worlds of tissue biology and genomics.
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Affiliation(s)
- Luyi Tian
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Fei Chen
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Harvard Stem Cell and Regenerative Biology, Cambridge, MA, USA.
| | - Evan Z Macosko
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
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36
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Johnson MS, Venkataram S, Kryazhimskiy S. Best Practices in Designing, Sequencing, and Identifying Random DNA Barcodes. J Mol Evol 2023; 91:263-280. [PMID: 36651964 PMCID: PMC10276077 DOI: 10.1007/s00239-022-10083-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 12/15/2022] [Indexed: 01/19/2023]
Abstract
Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.
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Affiliation(s)
- Milo S Johnson
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Sandeep Venkataram
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA, 92093, USA
| | - Sergey Kryazhimskiy
- Department of Ecology, Behavior and Evolution, University of California San Diego, La Jolla, CA, 92093, USA.
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Grody EI, Abraham A, Shukla V, Goyal Y. Toward a systems-level probing of tumor clonality. iScience 2023; 26:106574. [PMID: 37192968 PMCID: PMC10182304 DOI: 10.1016/j.isci.2023.106574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023] Open
Abstract
Cancer has been described as a genetic disease that clonally evolves in the face of selective pressures imposed by cell-intrinsic and extrinsic factors. Although classical models based on genetic data predominantly propose Darwinian mechanisms of cancer evolution, recent single-cell profiling of cancers has described unprecedented heterogeneity in tumors providing support for alternative models of branched and neutral evolution through both genetic and non-genetic mechanisms. Emerging evidence points to a complex interplay between genetic, non-genetic, and extrinsic environmental factors in shaping the evolution of tumors. In this perspective, we briefly discuss the role of cell-intrinsic and extrinsic factors that shape clonal behaviors during tumor progression, metastasis, and drug resistance. Taking examples of pre-malignant states associated with hematological malignancies and esophageal cancer, we discuss recent paradigms of tumor evolution and prospective approaches to further enhance our understanding of this spatiotemporally regulated process.
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Affiliation(s)
- Emanuelle I. Grody
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL 60208, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Ajay Abraham
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Center for Human Immunobiology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Vipul Shukla
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Center for Human Immunobiology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Corresponding author
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL 60208, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Corresponding author
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Salavaty A, Azadian E, Naik SH, Currie PD. Clonal selection parallels between normal and cancer tissues. Trends Genet 2023; 39:358-380. [PMID: 36842901 DOI: 10.1016/j.tig.2023.01.007] [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: 07/27/2022] [Revised: 01/12/2023] [Accepted: 01/26/2023] [Indexed: 02/28/2023]
Abstract
Clonal selection and drift drive both normal tissue and cancer development. However, the biological mechanisms and environmental conditions underpinning these processes remain to be elucidated. Clonal selection models are centered in Darwinian evolutionary theory, where some clones with the fittest features are selected and populate the tissue or tumor. We suggest that different subclasses of stem cells, each of which is responsible for a distinct feature of the selection process, share common features between normal and cancer conditions. While active stem cells populate the tissue, dormant cells account for tissue replenishment/regeneration in both normal and cancerous tissues. We also discuss potential mechanisms that drive clonal drift, their interactions with clonal selection, and their similarities during normal and cancer tissue development.
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Affiliation(s)
- Adrian Salavaty
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia; Systems Biology Institute Australia, Monash University, Clayton, VIC 3800, Australia.
| | - Esmaeel Azadian
- Immunology Division, Walter and Eliza Hall Institute, Parkville, VIC, Australia; Department of Medical Biology, University of Melbourne, Parkville, VIC, Australia; Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Shalin H Naik
- Immunology Division, Walter and Eliza Hall Institute, Parkville, VIC, Australia; Department of Medical Biology, University of Melbourne, Parkville, VIC, Australia; Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Peter D Currie
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC 3800, Australia; EMBL Australia, Monash University, Clayton, VIC 3800, Australia.
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Ueda K. Review: MDMX plays a central role in leukemic transformation and may be a promising target for leukemia prevention strategies. Exp Hematol 2023:S0301-472X(23)00161-3. [PMID: 37086813 DOI: 10.1016/j.exphem.2023.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 04/24/2023]
Abstract
Acute myeloid leukemia (AML) is a fatal disease resulting from preleukemic hematopoietic conditions including asymptomatic clonal hematopoiesis. The accumulation of genetic changes is one of the causes of leukemic transformation. However, nongenetic factors including the overexpression of specific genes also contribute to preleukemic to leukemic transition. Among them, the p53 inhibitor Murine Double Minute X (MDMX) plays crucial roles especially in leukemia initiation. MDMX is broadly overexpressed in vast majority of AML cases, including in hematopoietic stem/progenitor cell (HSPC) level. Recently, high expression of MDMX in HSPC has been shown to be associated with leukemic transformation in patients with myelodysplastic syndromes, and preclinical studies demonstrated that MDMX overexpression accelerates the transformation of preleukemic murine models, including models of clonal hematopoiesis. MDMX inhibition, through activation of cell-intrinsic p53 activity, shows antileukemic effects. However, the molecular mechanisms of MDMX in provoking leukemic transformation are complicated. Both p53-dependent and independent mechanisms are involved in the progression of the disease. This review discusses the canonical and noncanonical functions of MDMX and how these functions are involved in the maintenance, expansion, and progression to malignancy of preleukemic stem cells. Moreover, strategies on how leukemic transformation could possibly be prevented by targeting MDMX in preleukemic stem cells are discussed.
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Affiliation(s)
- Koki Ueda
- Department of Blood Transfusion and Transplantation Immunology, Fukushima Medical University, Fukushima, Fukushima 9601295, Japan; Department of Cell Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA.
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40
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Look A, Burns D, Tews I, Roghanian A, Mansour S. Towards a better understanding of human iNKT cell subpopulations for improved clinical outcomes. Front Immunol 2023; 14:1176724. [PMID: 37153585 PMCID: PMC10154573 DOI: 10.3389/fimmu.2023.1176724] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/04/2023] [Indexed: 05/09/2023] Open
Abstract
Invariant natural killer T (iNKT) cells are a unique T lymphocyte population expressing semi-invariant T cell receptors (TCRs) that recognise lipid antigens presented by CD1d. iNKT cells exhibit potent anti-tumour activity through direct killing mechanisms and indirectly through triggering the activation of other anti-tumour immune cells. Because of their ability to induce potent anti-tumour responses, particularly when activated by the strong iNKT agonist αGalCer, they have been the subject of intense research to harness iNKT cell-targeted immunotherapies for cancer treatment. However, despite potent anti-tumour efficacy in pre-clinical models, the translation of iNKT cell immunotherapy into human cancer patients has been less successful. This review provides an overview of iNKT cell biology and why they are of interest within the context of cancer immunology. We focus on the iNKT anti-tumour response, the seminal studies that first reported iNKT cytotoxicity, their anti-tumour mechanisms, and the various described subsets within the iNKT cell repertoire. Finally, we discuss several barriers to the successful utilisation of iNKT cells in human cancer immunotherapy, what is required for a better understanding of human iNKT cells, and the future perspectives facilitating their exploitation for improved clinical outcomes.
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Affiliation(s)
- Alex Look
- NIHR Biomedical Research Centre, School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Daniel Burns
- NIHR Biomedical Research Centre, School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Ivo Tews
- Biological Sciences, University of Southampton, Southampton, United Kingdom
- Institute for Life Sciences, University of Southampton, Southampton, United Kingdom
| | - Ali Roghanian
- Institute for Life Sciences, University of Southampton, Southampton, United Kingdom
- Antibody and Vaccine Group, Centre for Cancer Immunology, School of Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Salah Mansour
- NIHR Biomedical Research Centre, School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
- Institute for Life Sciences, University of Southampton, Southampton, United Kingdom
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Beneyto-Calabuig S, Merbach AK, Kniffka JA, Antes M, Szu-Tu C, Rohde C, Waclawiczek A, Stelmach P, Gräßle S, Pervan P, Janssen M, Landry JJM, Benes V, Jauch A, Brough M, Bauer M, Besenbeck B, Felden J, Bäumer S, Hundemer M, Sauer T, Pabst C, Wickenhauser C, Angenendt L, Schliemann C, Trumpp A, Haas S, Scherer M, Raffel S, Müller-Tidow C, Velten L. Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia. Cell Stem Cell 2023; 30:706-721.e8. [PMID: 37098346 DOI: 10.1016/j.stem.2023.04.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 02/05/2023] [Accepted: 03/30/2023] [Indexed: 04/27/2023]
Abstract
Inter-patient variability and the similarity of healthy and leukemic stem cells (LSCs) have impeded the characterization of LSCs in acute myeloid leukemia (AML) and their differentiation landscape. Here, we introduce CloneTracer, a novel method that adds clonal resolution to single-cell RNA-seq datasets. Applied to samples from 19 AML patients, CloneTracer revealed routes of leukemic differentiation. Although residual healthy and preleukemic cells dominated the dormant stem cell compartment, active LSCs resembled their healthy counterpart and retained erythroid capacity. By contrast, downstream myeloid progenitors constituted a highly aberrant, disease-defining compartment: their gene expression and differentiation state affected both the chemotherapy response and leukemia's ability to differentiate into transcriptomically normal monocytes. Finally, we demonstrated the potential of CloneTracer to identify surface markers misregulated specifically in leukemic cells. Taken together, CloneTracer reveals a differentiation landscape that mimics its healthy counterpart and may determine biology and therapy response in AML.
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Affiliation(s)
- Sergi Beneyto-Calabuig
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Anne Kathrin Merbach
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Jonas-Alexander Kniffka
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Magdalena Antes
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Chelsea Szu-Tu
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Christian Rohde
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Alexander Waclawiczek
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Patrick Stelmach
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Sarah Gräßle
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany; Charité-Universitätsmedizin, 10117 Berlin, Germany; Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany
| | - Philip Pervan
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Maike Janssen
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Jonathan J M Landry
- Genomics Core Facility, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Vladimir Benes
- Genomics Core Facility, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Anna Jauch
- Institute of Human Genetics, University of Heidelberg, 69120 Heidelberg, Germany
| | - Michaela Brough
- Institute of Human Genetics, University of Heidelberg, 69120 Heidelberg, Germany
| | - Marcus Bauer
- Institute of Pathology, University Hospital Halle (Saale), Martin-Luther-University Halle-Wittenberg, 06112 Halle, Germany
| | - Birgit Besenbeck
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Julia Felden
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Sebastian Bäumer
- Department of Medicine A, Hematology and Oncology, University Hospital, Muenster, Germany
| | - Michael Hundemer
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Tim Sauer
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Caroline Pabst
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Claudia Wickenhauser
- Institute of Pathology, University Hospital Halle (Saale), Martin-Luther-University Halle-Wittenberg, 06112 Halle, Germany
| | - Linus Angenendt
- Department of Medicine A, Hematology and Oncology, University Hospital, Muenster, Germany; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Christoph Schliemann
- Department of Medicine A, Hematology and Oncology, University Hospital, Muenster, Germany
| | - Andreas Trumpp
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Simon Haas
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany; Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany; Charité-Universitätsmedizin, 10117 Berlin, Germany; Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany
| | - Michael Scherer
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Simon Raffel
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Carsten Müller-Tidow
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany.
| | - Lars Velten
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
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Abubakar SD, Takaki M, Haeno H. Computational modeling of locoregional recurrence with spatial structure identifies tissue-specific carcinogenic profiles. Front Oncol 2023; 13:1116210. [PMID: 37091178 PMCID: PMC10117647 DOI: 10.3389/fonc.2023.1116210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/23/2023] [Indexed: 04/08/2023] Open
Abstract
IntroductionLocal and regional recurrence after surgical intervention is a significant problem in cancer management. The multistage theory of carcinogenesis precisely places the presence of histologically normal but mutated premalignant lesions surrounding the tumor - field cancerization, as a significant cause of cancer recurrence. The relationship between tissue dynamics, cancer initiation and cancer recurrence in multistage carcinogenesis is not well known.MethodsThis study constructs a computational model for cancer initiation and recurrence by combining the Moran and branching processes in which cells requires 3 or more mutations to become malignant. In addition, a spatial structure-setting is included in the model to account for positional relativity in cell turnover towards malignant transformation. The model consists of a population of normal cells with no mutation; several populations of premalignant cells with varying number of mutations and a population of malignant cells. The model computes a stage of cancer detection and surgery to eliminate malignant cells but spares premalignant cells and then estimates the time for malignant cells to re-emerge.ResultsWe report the cellular conditions that give rise to different patterns of cancer initiation and the conditions favoring a shorter cancer recurrence by analyzing premalignant cell types at the time of surgery. In addition, the model is fitted to disease-free clinical data of 8,957 patients in 27 different cancer types; From this fitting, we estimate the turnover rate per month, relative fitness of premalignant cells, growth rate and death rate of cancer cells in each cancer type.DiscussionOur study provides insights into how to identify patients who are likely to have a shorter recurrence and where to target the therapeutic intervention.
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Affiliation(s)
| | - Mitsuaki Takaki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Hiroshi Haeno
- Research Institute for Biomedical Science, Tokyo University of Science, Noda, Japan
- *Correspondence: Hiroshi Haeno,
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43
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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: 8] [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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44
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Richman LP, Goyal Y, Jiang CL, Raj A. ClonoCluster: A method for using clonal origin to inform transcriptome clustering. CELL GENOMICS 2023; 3:100247. [PMID: 36819662 PMCID: PMC9932990 DOI: 10.1016/j.xgen.2022.100247] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 09/22/2022] [Accepted: 12/16/2022] [Indexed: 01/13/2023]
Abstract
Clustering cells based on their high-dimensional profiles is an important data reduction process by which researchers infer distinct cellular states. The advent of cellular barcoding, however, provides an alternative means by which to group cells: by their clonal origin. We developed ClonoCluster, a computational method that combines both clone and transcriptome information to create hybrid clusters that weight both kinds of data with a tunable parameter. We generated hybrid clusters across six independent datasets and found that ClonoCluster generated qualitatively different clusters in all cases. The markers of these hybrid clusters were different but had equivalent fidelity to transcriptome-only clusters. The genes most strongly associated with the rearrangements in hybrid clusters were ribosomal function and extracellular matrix genes. We also developed the complementary tool Warp Factor that incorporates clone information in popular 2D visualization techniques like UMAP. Integrating ClonoCluster and Warp Factor revealed biologically relevant markers of cell identity.
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Affiliation(s)
- Lee P. Richman
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yogesh Goyal
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
| | - Connie L. Jiang
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arjun Raj
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
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45
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Bosque JJ, Calvo GF, Molina-García D, Pérez-Beteta J, García Vicente AM, Pérez-García VM. Metabolic activity grows in human cancers pushed by phenotypic variability. iScience 2023; 26:106118. [PMID: 36843844 PMCID: PMC9950952 DOI: 10.1016/j.isci.2023.106118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/30/2022] [Accepted: 01/28/2023] [Indexed: 02/05/2023] Open
Abstract
Different evolutionary processes push cancers to increasingly aggressive behaviors, energetically sustained by metabolic reprogramming. The collective signature emerging from this transition is macroscopically displayed by positron emission tomography (PET). In fact, the most readily PET measure, the maximum standardized uptake value (SUVmax), has been found to have prognostic value in different cancers. However, few works have linked the properties of this metabolic hotspot to cancer evolutionary dynamics. Here, by analyzing diagnostic PET images from 512 patients with cancer, we found that SUVmax scales superlinearly with the mean metabolic activity (SUVmean), reflecting a dynamic preferential accumulation of activity on the hotspot. Additionally, SUVmax increased with metabolic tumor volume (MTV) following a power law. The behavior from the patients data was accurately captured by a mechanistic evolutionary dynamics model of tumor growth accounting for phenotypic transitions. This suggests that non-genetic changes may suffice to fuel the observed sustained increases in tumor metabolic activity.
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Affiliation(s)
- Jesús J. Bosque
- Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain,Corresponding author
| | - Gabriel F. Calvo
- Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain
| | - David Molina-García
- Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain
| | - Julián Pérez-Beteta
- Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain
| | - Ana M. García Vicente
- Nuclear Medicine Unit, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain
| | - Víctor M. Pérez-García
- Department of Mathematics, Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain
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Ediriwickrema A, Gentles AJ, Majeti R. Single-cell genomics in AML: extending the frontiers of AML research. Blood 2023; 141:345-355. [PMID: 35926108 PMCID: PMC10082362 DOI: 10.1182/blood.2021014670] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/06/2022] [Accepted: 07/23/2022] [Indexed: 01/31/2023] Open
Abstract
The era of genomic medicine has allowed acute myeloid leukemia (AML) researchers to improve disease characterization, optimize risk-stratification systems, and develop new treatments. Although there has been significant progress, AML remains a lethal cancer because of its remarkably complex and plastic cellular architecture. This degree of heterogeneity continues to pose a major challenge, because it limits the ability to identify and therefore eradicate the cells responsible for leukemogenesis and treatment failure. In recent years, the field of single-cell genomics has led to unprecedented strides in the ability to characterize cellular heterogeneity, and it holds promise for the study of AML. In this review, we highlight advancements in single-cell technologies, outline important shortcomings in our understanding of AML biology and clinical management, and discuss how single-cell genomics can address these shortcomings as well as provide unique opportunities in basic and translational AML research.
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Affiliation(s)
- Asiri Ediriwickrema
- Division of Hematology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Cancer Institute, Stanford University School of Medicine, Stanford, CA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA
| | - Andrew J. Gentles
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA
| | - Ravindra Majeti
- Division of Hematology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Cancer Institute, Stanford University School of Medicine, Stanford, CA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA
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Van Eyndhoven LC, Verberne VPG, Bouten CVC, Singh A, Tel J. Transiently heritable fates and quorum sensing drive early IFN-I response dynamics. eLife 2023; 12:83055. [PMID: 36629318 PMCID: PMC9910831 DOI: 10.7554/elife.83055] [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: 08/30/2022] [Accepted: 01/10/2023] [Indexed: 01/12/2023] Open
Abstract
Type I interferon (IFN-I)-mediated antiviral responses are central to host defense against viral infections. Crucial is the tight and well-orchestrated control of cellular decision-making leading to the production of IFN-Is. Innovative single-cell approaches revealed that the initiation of IFN-I production is limited to only fractions of 1-3% of the total population, both found in vitro, in vivo, and across cell types, which were thought to be stochastically regulated. To challenge this dogma, we addressed the influence of various stochastic and deterministic host-intrinsic factors on dictating early IFN-I responses, using a murine fibroblast reporter model. Epigenetic drugs influenced the percentage of responding cells. Next, with the classical Luria-Delbrück fluctuation test, we provided evidence for transient heritability driving responder fates, which was verified with mathematical modeling. Finally, while studying varying cell densities, we substantiated an important role for cell density in dictating responsiveness, similar to the phenomenon of quorum sensing. Together, this systems immunology approach opens up new avenues to progress the fundamental understanding on cellular decision-making during early IFN-I responses, which can be translated to other (immune) signaling systems.
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Affiliation(s)
- Laura C Van Eyndhoven
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
| | - Vincent PG Verberne
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
| | - Carlijn VC Bouten
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
- Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of DelawareNewarkUnited States
| | - Jurjen Tel
- Laboratory of Immunoengineering, Department of Biomedical Engineering, Eindhoven University of TechnologyEindhovenNetherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of TechnologyEindhovenNetherlands
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48
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Haghverdi L, Ludwig LS. Single-cell multi-omics and lineage tracing to dissect cell fate decision-making. Stem Cell Reports 2023; 18:13-25. [PMID: 36630900 PMCID: PMC9860164 DOI: 10.1016/j.stemcr.2022.12.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 12/07/2022] [Accepted: 12/07/2022] [Indexed: 01/12/2023] Open
Abstract
The concept of cell fate relates to the future identity of a cell, and its daughters, which is obtained via cell differentiation and division. Understanding, predicting, and manipulating cell fate has been a long-sought goal of developmental and regenerative biology. Recent insights obtained from single-cell genomic and integrative lineage-tracing approaches have further aided to identify molecular features predictive of cell fate. In this perspective, we discuss these approaches with a focus on theoretical concepts and future directions of the field to dissect molecular mechanisms underlying cell fate.
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Affiliation(s)
- Laleh Haghverdi
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany.
| | - Leif S. Ludwig
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany,Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany,Corresponding author
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49
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Abstract
Mutations in epigenetic regulators are prevalent in cancer, but their functional impact is poorly delineated aside from disrupting differentiation. In this issue of Cancer Cell, Loukas et al. zoom in on the late occurring, subclonal subset of such mutations and define the molecular mechanism behind their enrichment in cancer.
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Affiliation(s)
- Hui Shen
- Department of Epigenetics, Van Andel Institute, 333 Bostwick Avenue NE, Grand Rapids, MI 49503, USA.
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50
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Wang E, Pineda JMB, Kim WJ, Chen S, Bourcier J, Stahl M, Hogg SJ, Bewersdorf JP, Han C, Singer ME, Cui D, Erickson CE, Tittley SM, Penson AV, Knorr K, Stanley RF, Rahman J, Krishnamoorthy G, Fagin JA, Creger E, McMillan E, Mak CC, Jarvis M, Bossard C, Beaupre DM, Bradley RK, Abdel-Wahab O. Modulation of RNA splicing enhances response to BCL2 inhibition in leukemia. Cancer Cell 2023; 41:164-180.e8. [PMID: 36563682 PMCID: PMC9839614 DOI: 10.1016/j.ccell.2022.12.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 10/07/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022]
Abstract
Therapy resistance is a major challenge in the treatment of cancer. Here, we performed CRISPR-Cas9 screens across a broad range of therapies used in acute myeloid leukemia to identify genomic determinants of drug response. Our screens uncover a selective dependency on RNA splicing factors whose loss preferentially enhances response to the BCL2 inhibitor venetoclax. Loss of the splicing factor RBM10 augments response to venetoclax in leukemia yet is completely dispensable for normal hematopoiesis. Combined RBM10 and BCL2 inhibition leads to mis-splicing and inactivation of the inhibitor of apoptosis XIAP and downregulation of BCL2A1, an anti-apoptotic protein implicated in venetoclax resistance. Inhibition of splicing kinase families CLKs (CDC-like kinases) and DYRKs (dual-specificity tyrosine-regulated kinases) leads to aberrant splicing of key splicing and apoptotic factors that synergize with venetoclax, and overcomes resistance to BCL2 inhibition. Our findings underscore the importance of splicing in modulating response to therapies and provide a strategy to improve venetoclax-based treatments.
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Affiliation(s)
- Eric Wang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.
| | - Jose Mario Bello Pineda
- Public Health Sciences and Basic Sciences Divisions, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Genome Sciences, University of Washington, Seattle, WA, USA; Medical Scientist Training Program, University of Washington, Seattle, WA, USA
| | - Won Jun Kim
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sisi Chen
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jessie Bourcier
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Maximilian Stahl
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Simon J Hogg
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jan Phillipp Bewersdorf
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Cuijuan Han
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Michael E Singer
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Daniel Cui
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Caroline E Erickson
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Steven M Tittley
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alexander V Penson
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Katherine Knorr
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robert F Stanley
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jahan Rahman
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gnana Krishnamoorthy
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Division of Endocrinology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - James A Fagin
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Division of Endocrinology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | | | | | | | | | | | - Robert K Bradley
- Public Health Sciences and Basic Sciences Divisions, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Genome Sciences, University of Washington, Seattle, WA, USA.
| | - Omar Abdel-Wahab
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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