1
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Riew TR, Kim YS. Mutational Landscapes of Normal Skin and Their Potential Implications in the Development of Skin Cancer: A Comprehensive Narrative Review. J Clin Med 2024; 13:4815. [PMID: 39200957 PMCID: PMC11355262 DOI: 10.3390/jcm13164815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Revised: 08/11/2024] [Accepted: 08/13/2024] [Indexed: 09/02/2024] Open
Abstract
Recent evidence suggests that physiologically normal skin harbors pervasive mutant clones with cancer drivers. Normal skin has the highest burden of somatic mutations due to persistent ultraviolet exposure throughout life. The mutation burden exponentially increases with age and is further modified by skin site, sun-damage history, and skin phototype. Driver gene profiles in normal skin are similar to those in cutaneous squamous cell carcinoma where NOTCH family, FAT family, and TP53 are consistently reported, while other reported profiles include PPM1D, KMT2D, ASXL1, and RBM10. Normal skin seldom harbors canonical hotspot mutations with therapeutic relevance. The pathologic role of mutant clones with cancer drivers in normal skin is classically considered precursors for skin cancer; however, recent evidence also suggests their putative cancer-protective role. Copy number alterations and other structural variants are rare in normal skin with loss in 9q region encompassing NOTCH1 being the most common. Study methodologies should be carefully designed to obtain an adequate number of cells for sequencing, and a comparable number of cells and read depth across samples. In conclusion, this review provides mutational landscapes of normal skin and discusses their potential implications in the development of skin cancer, highlighting the role of driver genes in early malignant progression.
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Affiliation(s)
- Tae-Ryong Riew
- Department of Anatomy, Catholic Neuroscience Institute, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
- Department of Biomedicine and Health Sciences, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Yoon-Seob Kim
- Department of Dermatology, Bucheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
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2
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Danciu DP, Hooli J, Martin-Villalba A, Marciniak-Czochra A. Mathematics of neural stem cells: Linking data and processes. Cells Dev 2023; 174:203849. [PMID: 37179018 DOI: 10.1016/j.cdev.2023.203849] [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: 02/03/2023] [Revised: 04/29/2023] [Accepted: 05/05/2023] [Indexed: 05/15/2023]
Abstract
Adult stem cells are described as a discrete population of cells that stand at the top of a hierarchy of progressively differentiating cells. Through their unique ability to self-renew and differentiate, they regulate the number of end-differentiated cells that contribute to tissue physiology. The question of how discrete, continuous, or reversible the transitions through these hierarchies are and the precise parameters that determine the ultimate performance of stem cells in adulthood are the subject of intense research. In this review, we explain how mathematical modelling has improved the mechanistic understanding of stem cell dynamics in the adult brain. We also discuss how single-cell sequencing has influenced the understanding of cell states or cell types. Finally, we discuss how the combination of single-cell sequencing technologies and mathematical modelling provides a unique opportunity to answer some burning questions in the field of stem cell biology.
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Affiliation(s)
- Diana-Patricia Danciu
- Heidelberg University, Institute of Mathematics (IMA), Im Neuenheimer Feld 205, 69120 Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Jooa Hooli
- Heidelberg University, Institute of Mathematics (IMA), Im Neuenheimer Feld 205, 69120 Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), Im Neuenheimer Feld 205, 69120 Heidelberg, Germany; Heidelberg University, Faculty of Biosciences, Im Neuenheimer Feld 234, 69120 Heidelberg, Germany; German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Ana Martin-Villalba
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Anna Marciniak-Czochra
- Heidelberg University, Institute of Mathematics (IMA), Im Neuenheimer Feld 205, 69120 Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), Im Neuenheimer Feld 205, 69120 Heidelberg, Germany.
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3
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West J, Robertson-Tessi M, Anderson ARA. Agent-based methods facilitate integrative science in cancer. Trends Cell Biol 2023; 33:300-311. [PMID: 36404257 PMCID: PMC10918696 DOI: 10.1016/j.tcb.2022.10.006] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 10/25/2022] [Accepted: 10/31/2022] [Indexed: 11/19/2022]
Abstract
In this opinion, we highlight agent-based modeling as a key tool for exploration of cell-cell and cell-environment interactions that drive cancer progression, therapeutic resistance, and metastasis. These biological phenomena are particularly suited to be captured at the cell-scale resolution possible only within agent-based or individual-based mathematical models. These modeling approaches complement experimental work (in vitro and in vivo systems) through parameterization and data extrapolation but also feed forward to drive new experiments that test model-generated predictions.
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Affiliation(s)
- Jeffrey West
- Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
| | - Mark Robertson-Tessi
- Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
| | - Alexander R A Anderson
- Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
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4
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Homeostasis limits keratinocyte evolution. Proc Natl Acad Sci U S A 2022; 119:e2006487119. [PMID: 35998218 PMCID: PMC9436311 DOI: 10.1073/pnas.2006487119] [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: 12/02/2022] Open
Abstract
Human skin is riddled with mutations creating subclones of variable sizes. Some of these mutations are driver mutations, implicated in cancer development and progression, that appear to be under positive selection due to their relative sizes. We show how these driver and nondriver “passenger” mutations encode their history of division and loss within the tissue using a simple model combined with realistic mutation tracking. Using a three-dimensional in silico homeostatic epidermis model, we reveal that many mutations likely lack functional heterogeneity and are, instead, simply those that arise earlier in life within the basal layer. We use our model to reveal how functional differences conveyed by driver mutations could lead to a persistence phenotype while maintaining homeostasis. Recent studies have revealed that normal human tissues accumulate many somatic mutations. In particular, human skin is riddled with mutations, with multiple subclones of variable sizes. Driver mutations are frequent and tend to have larger subclone sizes, suggesting selection. To begin to understand the histories encoded by these complex somatic mutations, we incorporated genomes into a simple agent-based skin-cell model whose prime directive is homeostasis. In this model, stem-cell survival is random and dependent on proximity to the basement membrane. This simple homeostatic skin model recapitulates the observed log-linear distributions of somatic mutations, where most mutations are found in increasingly smaller subclones that are typically lost with time. Hence, neutral mutations are “passengers” whose fates depend on the random survival of their stem cells, where a rarer larger subclone reflects the survival and spread of mutations acquired earlier in life. The model can also maintain homeostasis and accumulate more frequent and larger driver subclones if these mutations (NOTCH1 and TP53) confer relatively higher persistence in normal skin or during tissue damage (sunlight). Therefore, a relatively simple model of epithelial turnover indicates how observed passenger and driver somatic mutations could accumulate without violating the prime directive of homeostasis in normal human tissues.
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5
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Negri VA, Watt FM. Understanding Human Epidermal Stem Cells at Single-Cell Resolution. J Invest Dermatol 2022; 142:2061-2067. [PMID: 35570025 PMCID: PMC9826868 DOI: 10.1016/j.jid.2022.04.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 03/20/2022] [Accepted: 04/01/2022] [Indexed: 01/13/2023]
Abstract
The human epidermis is one of the first tissues in which the existence of stem cells was recognized and is one of the few in which ex vivo expansion for tissue repair is established clinically. Nevertheless, the nature of stem cells has been elusive. Using clonal growth assays of cultured keratinocytes as a quantitative measure of their abundance, several candidate stem cell markers have been described. Recently, the volume and quality of single-cell RNA-sequencing datasets have increased exponentially, providing new opportunities to explore the nature of epidermal stem cells and test the validity of in vitro experimental models.
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Affiliation(s)
- Victor Augusti Negri
- Centre for Gene Therapy and Regenerative Medicine, Faculty of Life Sciences & Medicine, School of Basic & Medical Biosciences, King’s College London, London, United Kingdom
| | - Fiona M. Watt
- Centre for Gene Therapy and Regenerative Medicine, Faculty of Life Sciences & Medicine, School of Basic & Medical Biosciences, King’s College London, London, United Kingdom,Directors' Research Unit, European Molecular Biology Laboratory, Heidelberg, Germany,Correspondence: Fiona M. Watt, Centre for Gene Therapy and Regenerative Medicine, King’s College London, Floor 28, Tower Wing, Guy’s Hospital, Great Maze Pond, London SE1 9RT, United Kingdom.
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6
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Gabbutt C, Wright NA, Baker A, Shibata D, Graham TA. Lineage tracing in human tissues. J Pathol 2022; 257:501-512. [PMID: 35415852 PMCID: PMC9253082 DOI: 10.1002/path.5911] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 03/21/2022] [Accepted: 04/09/2022] [Indexed: 11/11/2022]
Abstract
The dynamical process of cell division that underpins homeostasis in the human body cannot be directly observed in vivo, but instead is measurable from the pattern of somatic genetic or epigenetic mutations that accrue in tissues over an individual's lifetime. Because somatic mutations are heritable, they serve as natural lineage tracing markers that delineate clonal expansions. Mathematical analysis of the distribution of somatic clone sizes gives a quantitative readout of the rates of cell birth, death, and replacement. In this review we explore the broad range of somatic mutation types that have been used for lineage tracing in human tissues, introduce the mathematical concepts used to infer dynamical information from these clone size data, and discuss the insights of this lineage tracing approach for our understanding of homeostasis and cancer development. We use the human colon as a particularly instructive exemplar tissue. There is a rich history of human somatic cell dynamics surreptitiously written into the cell genomes that is being uncovered by advances in sequencing and careful mathematical analysis lineage of tracing data. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Calum Gabbutt
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and DentistryQueen Mary University of LondonLondonUK
- Centre for Evolution and CancerInstitute of Cancer ResearchSuttonUK
- London Interdisciplinary Doctoral Training Programme (LIDo)LondonUK
| | - Nicholas A Wright
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and DentistryQueen Mary University of LondonLondonUK
| | - Ann‐Marie Baker
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and DentistryQueen Mary University of LondonLondonUK
- Centre for Evolution and CancerInstitute of Cancer ResearchSuttonUK
| | - Darryl Shibata
- Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Trevor A Graham
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and DentistryQueen Mary University of LondonLondonUK
- Centre for Evolution and CancerInstitute of Cancer ResearchSuttonUK
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7
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Gabbutt C, Schenck RO, Weisenberger DJ, Kimberley C, Berner A, Househam J, Lakatos E, Robertson-Tessi M, Martin I, Patel R, Clark SK, Latchford A, Barnes CP, Leedham SJ, Anderson ARA, Graham TA, Shibata D. Fluctuating methylation clocks for cell lineage tracing at high temporal resolution in human tissues. Nat Biotechnol 2022; 40:720-730. [PMID: 34980912 PMCID: PMC9110299 DOI: 10.1038/s41587-021-01109-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 09/28/2021] [Indexed: 02/07/2023]
Abstract
Molecular clocks that record cell ancestry mutate too slowly to measure the short-timescale dynamics of cell renewal in adult tissues. Here, we show that fluctuating DNA methylation marks can be used as clocks in cells where ongoing methylation and demethylation cause repeated 'flip-flops' between methylated and unmethylated states. We identify endogenous fluctuating CpG (fCpG) sites using standard methylation arrays and develop a mathematical model to quantitatively measure human adult stem cell dynamics from these data. Small intestinal crypts were inferred to contain slightly more stem cells than the colon, with slower stem cell replacement in the small intestine. Germline APC mutation increased the number of replacements per crypt. In blood, we measured rapid expansion of acute leukemia and slower growth of chronic disease. Thus, the patterns of human somatic cell birth and death are measurable with fluctuating methylation clocks (FMCs).
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Affiliation(s)
- Calum Gabbutt
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Department of Cell and Developmental Biology, University College London, London, UK
- London Interdisciplinary Doctoral Training Programme (LIDo), London, UK
| | - Ryan O Schenck
- Integrated Mathematical Oncology Department, Moffitt Cancer Center, Tampa, FL, USA
- Intestinal Stem Cell Biology Lab, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Daniel J Weisenberger
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher Kimberley
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Alison Berner
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Jacob Househam
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Eszter Lakatos
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Mark Robertson-Tessi
- Integrated Mathematical Oncology Department, Moffitt Cancer Center, Tampa, FL, USA
| | - Isabel Martin
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- St. Mark's Hospital, Harrow, London, UK
| | - Roshani Patel
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- St. Mark's Hospital, Harrow, London, UK
| | - Susan K Clark
- St. Mark's Hospital, Harrow, London, UK
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Andrew Latchford
- St. Mark's Hospital, Harrow, London, UK
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Chris P Barnes
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Simon J Leedham
- Intestinal Stem Cell Biology Lab, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Trevor A Graham
- Evolution and Cancer Laboratory, Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
| | - Darryl Shibata
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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8
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Schenck RO, Brosula G, West J, Leedham S, Shibata D, Anderson AR. Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models. Mol Biol Evol 2022; 39:msac058. [PMID: 35298641 PMCID: PMC9034688 DOI: 10.1093/molbev/msac058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Research over the past two decades has made substantial inroads into our understanding of somatic mutations. Recently, these studies have focused on understanding their presence in homeostatic tissue. In parallel, agent-based mechanistic models have emerged as an important tool for understanding somatic mutation in tissue; yet no common methodology currently exists to provide base-pair resolution data for these models. Here, we present Gattaca as the first method for introducing and tracking somatic mutations at the base-pair resolution within agent-based models that typically lack nuclei. With nuclei that incorporate human reference genomes, mutational context, and sequence coverage/error information, Gattaca is able to realistically evolve sequence data, facilitating comparisons between in silico cell tissue modeling with experimental human somatic mutation data. This user-friendly method, incorporated into each in silico cell, allows us to fully capture somatic mutation spectra and evolution.
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Affiliation(s)
- Ryan O. Schenck
- Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX37BN, United Kingdom
| | - Gabriel Brosula
- Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Jeffrey West
- Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Simon Leedham
- Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Darryl Shibata
- Department of Pathology, University of Southern California, Keck School of Medicine, Los Angeles, CA 90033, USA
| | - Alexander R.A. Anderson
- Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
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9
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Poon GYP, Watson CJ, Fisher DS, Blundell JR. Synonymous mutations reveal genome-wide levels of positive selection in healthy tissues. Nat Genet 2021; 53:1597-1605. [PMID: 34737428 DOI: 10.1038/s41588-021-00957-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 09/20/2021] [Indexed: 01/02/2023]
Abstract
Genetic alterations under positive selection in healthy tissues have implications for cancer risk. However, total levels of positive selection across the genome remain unknown. Passenger mutations are influenced by all driver mutations, regardless of type or location in the genome. Therefore, the total number of passengers can be used to estimate the total number of drivers-including unidentified drivers outside of cancer genes that are traditionally missed. Here we analyze the variant allele frequency spectrum of synonymous mutations from healthy blood and esophagus to quantify levels of missing positive selection. In blood, we find that only 30% of passengers can be explained by single-nucleotide variants in driver genes, suggesting high levels of positive selection for mutations elsewhere in the genome. In contrast, more than half of all passengers in the esophagus can be explained by just the two driver genes NOTCH1 and TP53, suggesting little positive selection elsewhere.
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Affiliation(s)
- Gladys Y P Poon
- Early Detection Programme, CRUK Cambridge Cancer Centre, University of Cambridge, Cambridge, UK.
- Department of Oncology, University of Cambridge, Cambridge, UK.
| | - Caroline J Watson
- Early Detection Programme, CRUK Cambridge Cancer Centre, University of Cambridge, Cambridge, UK
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Daniel S Fisher
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Jamie R Blundell
- Early Detection Programme, CRUK Cambridge Cancer Centre, University of Cambridge, Cambridge, UK.
- Department of Oncology, University of Cambridge, Cambridge, UK.
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10
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Strinkovsky L, Havkin E, Shalom-Feuerstein R, Savir Y. Spatial correlations constrain cellular lifespan and pattern formation in corneal epithelium homeostasis. eLife 2021; 10:56404. [PMID: 33433326 PMCID: PMC7803374 DOI: 10.7554/elife.56404] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 12/08/2020] [Indexed: 02/06/2023] Open
Abstract
Homeostasis in adult tissues relies on the replication dynamics of stem cells, their progenitors and the spatial balance between them. This spatial and kinetic coordination is crucial to the successful maintenance of tissue size and its replenishment with new cells. However, our understanding of the role of cellular replicative lifespan and spatial correlation between cells in shaping tissue integrity is still lacking. We developed a mathematical model for the stochastic spatial dynamics that underlie the rejuvenation of corneal epithelium. Our model takes into account different spatial correlations between cell replication and cell removal. We derive the tradeoffs between replicative lifespan, spatial correlation length, and tissue rejuvenation dynamics. We determine the conditions that allow homeostasis and are consistent with biological timescales, pattern formation, and mutants phenotypes. Our results can be extended to any cellular system in which spatial homeostasis is maintained through cell replication.
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Affiliation(s)
- Lior Strinkovsky
- Department of Physiology, Biophysics and System Biology, Faculty of Medicine, Technion, Haifa, Israel
| | - Evgeny Havkin
- Department of Physiology, Biophysics and System Biology, Faculty of Medicine, Technion, Haifa, Israel
| | - Ruby Shalom-Feuerstein
- Department of Genetics & Developmental Biology, Faculty of Medicine, Technion, Haifa, Israel.,The Rappaport Family Institute for Research in the Medical Sciences, Technion, Haifa, Israel
| | - Yonatan Savir
- Department of Physiology, Biophysics and System Biology, Faculty of Medicine, Technion, Haifa, Israel.,The Rappaport Family Institute for Research in the Medical Sciences, Technion, Haifa, Israel
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11
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Noninvasive Assessment of Epidermal Genomic Markers of UV Exposure in Skin. J Invest Dermatol 2020; 141:124-131.e2. [PMID: 32553564 DOI: 10.1016/j.jid.2020.05.093] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 05/01/2020] [Accepted: 05/01/2020] [Indexed: 01/04/2023]
Abstract
The measurement of UV-induced DNA damage as a dosimeter of exposure and predictor of skin cancer risk has been proposed by multiple groups. Although UV-induced mutations and adducts are present in normal-appearing UV-exposed epidermis, sampling normal nonlesional skin requires noninvasive methods to extract epidermal DNA for analysis. Here, we demonstrate the feasibility of such an approach, termed surfactant-based tissue acquisition for molecular profiling. Sampling in patients was performed using a felt-tip pen soaked in a mixture of surfactants (Brij-30/N-decyl-N,N-dimethyl-3-ammonio-1-propanesulfonate). In mice, we show that the epidermis can be selectively removed without scarring, with complete healing within 2 weeks. We exposed hairless mice to low-dose UV radiation over a period of 3 months and serially sampled them through up to 2 months following the cessation of UV exposure, observing a progressive increase in a UV signature mutational burden. To test whether surfactant-based tissue acquisition for molecular profiling could be applied to human patients, samples were collected from sun-exposed and sun-protected areas, which were then subjected to high-depth targeted exome sequencing. Extensive UV-driven mosaicism and substantially increased mutational loads in sun-exposed versus sun-protected areas were observed, suggesting that genomic measures, as an integrated readout of DNA damage, repair, and clonal expansion, may be informative markers of UV exposure.
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12
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Colom B, Alcolea MP, Piedrafita G, Hall MWJ, Wabik A, Dentro SC, Fowler JC, Herms A, King C, Ong SH, Sood RK, Gerstung M, Martincorena I, Hall BA, Jones PH. Spatial competition shapes the dynamic mutational landscape of normal esophageal epithelium. Nat Genet 2020; 52:604-614. [PMID: 32424351 PMCID: PMC7116672 DOI: 10.1038/s41588-020-0624-3] [Citation(s) in RCA: 94] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 04/07/2020] [Indexed: 12/29/2022]
Abstract
During aging, progenitor cells acquire mutations, which may generate clones that colonize the surrounding tissue. By middle age, normal human tissues, including the esophageal epithelium (EE), become a patchwork of mutant clones. Despite their relevance for understanding aging and cancer, the processes that underpin mutational selection in normal tissues remain poorly understood. Here, we investigated this issue in the esophageal epithelium of mutagen-treated mice. Deep sequencing identified numerous mutant clones with multiple genes under positive selection, including Notch1, Notch2 and Trp53, which are also selected in human esophageal epithelium. Transgenic lineage tracing revealed strong clonal competition that evolved over time. Clone dynamics were consistent with a simple model in which the proliferative advantage conferred by positively selected mutations depends on the nature of the neighboring cells. When clones with similar competitive fitness collide, mutant cell fate reverts towards homeostasis, a constraint that explains how selection operates in normal-appearing epithelium.
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Affiliation(s)
| | - Maria P Alcolea
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
- Department of Oncology, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
| | - Gabriel Piedrafita
- Wellcome Sanger Institute, Hinxton, UK
- Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Michael W J Hall
- Wellcome Sanger Institute, Hinxton, UK
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK
| | | | - Stefan C Dentro
- Wellcome Sanger Institute, Hinxton, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | | | | | | | | | | | - Moritz Gerstung
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | | | - Benjamin A Hall
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK.
| | - Philip H Jones
- Wellcome Sanger Institute, Hinxton, UK.
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge Biomedical Campus, Cambridge, UK.
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13
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Abstract
The mechanisms that regulate the balance between stem cell duplication and differentiation in adult tissues remain in debate. Using a combination of genetic lineage tracing and marker-based assays, the quantitative statistical analysis of clone size and cell composition has provided insights into the patterns of stem cell fate across a variety of tissue types and organisms. These studies have emphasized the role of niche factors and environmental cues in promoting stem cell competence, fate priming, and stochastic renewal programs. At the same time, evidence for injury-induced "cellular reprogramming" has revealed the remarkable flexibility of cell states, allowing progenitors to reacquire self-renewal potential during regeneration. Together, these findings have questioned the nature of stem cell identity and function. Here, focusing on a range of canonical tissue types, we review how quantitative modeling-based approaches have uncovered conserved patterns of stem cell fate and provided new insights into the mechanisms that regulate self-renewal.
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Affiliation(s)
- Lemonia Chatzeli
- Wellcome Trust/CRUK Gurdon Institute, University of Cambridge, Cambridge CB2 1QN, United Kingdom
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge CB2 1QR, United Kingdom
| | - Benjamin D Simons
- Wellcome Trust/CRUK Gurdon Institute, University of Cambridge, Cambridge CB2 1QN, United Kingdom
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge CB2 1QR, United Kingdom
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Cambridge CB3 0WA, United Kingdom
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14
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McCarthy DJ, Rostom R, Huang Y, Kunz DJ, Danecek P, Bonder MJ, Hagai T, Lyu R, Wang W, Gaffney DJ, Simons BD, Stegle O, Teichmann SA. Cardelino: computational integration of somatic clonal substructure and single-cell transcriptomes. Nat Methods 2020; 17:414-421. [PMID: 32203388 DOI: 10.1038/s41592-020-0766-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 01/31/2020] [Indexed: 02/03/2023]
Abstract
Bulk and single-cell DNA sequencing has enabled reconstructing clonal substructures of somatic tissues from frequency and cooccurrence patterns of somatic variants. However, approaches to characterize phenotypic variations between clones are not established. Here we present cardelino (https://github.com/single-cell-genetics/cardelino), a computational method for inferring the clonal tree configuration and the clone of origin of individual cells assayed using single-cell RNA-seq (scRNA-seq). Cardelino flexibly integrates information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. We apply cardelino to a published cancer dataset and to newly generated matched scRNA-seq and exome-seq data from 32 human dermal fibroblast lines, identifying hundreds of differentially expressed genes between cells from different somatic clones. These genes are frequently enriched for cell cycle and proliferation pathways, indicating a role for cell division genes in somatic evolution in healthy skin.
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Affiliation(s)
- Davis J McCarthy
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,St Vincent's Institute of Medical Research, Fitzroy, Victoria, Australia.,Melbourne Integrative Genomics, School of Mathematics and Statistics/School of Biosciences, University of Melbourne, Parkville, Victoria, Australia
| | - Raghd Rostom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Yuanhua Huang
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Daniel J Kunz
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.,Department of Physics, Cavendish Laboratory, Cambridge, UK.,The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK
| | - Petr Danecek
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Marc Jan Bonder
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Tzachi Hagai
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.,School of Molecular Cell Biology and Biotechnology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Ruqian Lyu
- St Vincent's Institute of Medical Research, Fitzroy, Victoria, Australia.,Melbourne Integrative Genomics, School of Mathematics and Statistics/School of Biosciences, University of Melbourne, Parkville, Victoria, Australia
| | | | - Wenyi Wang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Benjamin D Simons
- Department of Physics, Cavendish Laboratory, Cambridge, UK.,The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK.,The Wellcome Trust/Medical Research Council Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK. .,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. .,Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany.
| | - Sarah A Teichmann
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK. .,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK. .,Department of Physics, Cavendish Laboratory, Cambridge, UK.
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15
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Williams MJ, Zapata L, Werner B, Barnes CP, Sottoriva A, Graham TA. Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios. eLife 2020; 9:e48714. [PMID: 32223898 PMCID: PMC7105384 DOI: 10.7554/elife.48714] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 03/09/2020] [Indexed: 12/22/2022] Open
Abstract
The distribution of fitness effects (DFE) defines how new mutations spread through an evolving population. The ratio of non-synonymous to synonymous mutations (dN/dS) has become a popular method to detect selection in somatic cells. However the link, in somatic evolution, between dN/dS values and fitness coefficients is missing. Here we present a quantitative model of somatic evolutionary dynamics that determines the selective coefficients of individual driver mutations from dN/dS estimates. We then measure the DFE for somatic mutant clones in ostensibly normal oesophagus and skin. We reveal a broad distribution of fitness effects, with the largest fitness increases found for TP53 and NOTCH1 mutants (proliferative bias 1-5%). This study provides the theoretical link between dN/dS values and selective coefficients in somatic evolution, and measures the DFE of mutations in human tissues.
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Affiliation(s)
- Marc J Williams
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of LondonLondonUnited Kingdom
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer CenterNew YorkUnited States
| | - Luis Zapata
- Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer ResearchLondonUnited Kingdom
| | - Benjamin Werner
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of LondonLondonUnited Kingdom
| | - Chris P Barnes
- Department of Cell and Developmental Biology, University College LondonLondonUnited Kingdom
| | - Andrea Sottoriva
- Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer ResearchLondonUnited Kingdom
| | - Trevor A Graham
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of LondonLondonUnited Kingdom
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16
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Watson CJ, Papula AL, Poon GYP, Wong WH, Young AL, Druley TE, Fisher DS, Blundell JR. The evolutionary dynamics and fitness landscape of clonal hematopoiesis. Science 2020; 367:1449-1454. [PMID: 32217721 DOI: 10.1126/science.aay9333] [Citation(s) in RCA: 236] [Impact Index Per Article: 59.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 01/24/2020] [Indexed: 12/15/2022]
Abstract
Somatic mutations acquired in healthy tissues as we age are major determinants of cancer risk. Whether variants confer a fitness advantage or rise to detectable frequencies by chance remains largely unknown. Blood sequencing data from ~50,000 individuals reveal how mutation, genetic drift, and fitness shape the genetic diversity of healthy blood (clonal hematopoiesis). We show that positive selection, not drift, is the major force shaping clonal hematopoiesis, provide bounds on the number of hematopoietic stem cells, and quantify the fitness advantages of key pathogenic variants, at single-nucleotide resolution, as well as the distribution of fitness effects (fitness landscape) within commonly mutated driver genes. These data are consistent with clonal hematopoiesis being driven by a continuing risk of mutations and clonal expansions that become increasingly detectable with age.
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Affiliation(s)
- Caroline J Watson
- Department of Oncology, University of Cambridge, Cambridge, UK.
- Early Detection Programme, CRUK Cambridge Cancer Centre, University of Cambridge, Cambridge, UK
| | - A L Papula
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Gladys Y P Poon
- Department of Oncology, University of Cambridge, Cambridge, UK
- Early Detection Programme, CRUK Cambridge Cancer Centre, University of Cambridge, Cambridge, UK
| | - Wing H Wong
- Department of Pediatrics, Division of Hematology and Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew L Young
- Department of Pediatrics, Division of Hematology and Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Todd E Druley
- Department of Pediatrics, Division of Hematology and Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel S Fisher
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Jamie R Blundell
- Department of Oncology, University of Cambridge, Cambridge, UK.
- Early Detection Programme, CRUK Cambridge Cancer Centre, University of Cambridge, Cambridge, UK
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17
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Akimov Y, Bulanova D, Timonen S, Wennerberg K, Aittokallio T. Improved detection of differentially represented DNA barcodes for high-throughput clonal phenomics. Mol Syst Biol 2020; 16:e9195. [PMID: 32187448 PMCID: PMC7080434 DOI: 10.15252/msb.20199195] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 02/13/2020] [Accepted: 02/17/2020] [Indexed: 12/14/2022] Open
Abstract
Cellular DNA barcoding has become a popular approach to study heterogeneity of cell populations and to identify clones with differential response to cellular stimuli. However, there is a lack of reliable methods for statistical inference of differentially responding clones. Here, we used mixtures of DNA-barcoded cell pools to generate a realistic benchmark read count dataset for modelling a range of outcomes of clone-tracing experiments. By accounting for the statistical properties intrinsic to the DNA barcode read count data, we implemented an improved algorithm that results in a significantly lower false-positive rate, compared to current RNA-seq data analysis algorithms, especially when detecting differentially responding clones in experiments with strong selection pressure. Building on the reliable statistical methodology, we illustrate how multidimensional phenotypic profiling enables one to deconvolute phenotypically distinct clonal subpopulations within a cancer cell line. The mixture control dataset and our analysis results provide a foundation for benchmarking and improving algorithms for clone-tracing experiments.
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Affiliation(s)
- Yevhen Akimov
- Institute for Molecular Medicine Finland (FIMM)HiLIFEUniversity of HelsinkiHelsinkiFinland
| | - Daria Bulanova
- Institute for Molecular Medicine Finland (FIMM)HiLIFEUniversity of HelsinkiHelsinkiFinland
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem)University of CopenhagenCopenhagenDenmark
| | - Sanna Timonen
- Institute for Molecular Medicine Finland (FIMM)HiLIFEUniversity of HelsinkiHelsinkiFinland
| | - Krister Wennerberg
- Institute for Molecular Medicine Finland (FIMM)HiLIFEUniversity of HelsinkiHelsinkiFinland
- Biotech Research and Innovation Centre (BRIC) and Novo Nordisk Foundation Center for Stem Cell Biology (DanStem)University of CopenhagenCopenhagenDenmark
| | - Tero Aittokallio
- Institute for Molecular Medicine Finland (FIMM)HiLIFEUniversity of HelsinkiHelsinkiFinland
- Department of Mathematics and StatisticsUniversity of TurkuTurkuFinland
- Department of Cancer GeneticsInstitute for Cancer ResearchOslo University HospitalOsloNorway
- Oslo Centre for Biostatistics and Epidemiology (OCBE)Faculty of MedicineUniversity of OsloOsloNorway
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18
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Laconi E, Marongiu F, DeGregori J. Cancer as a disease of old age: changing mutational and microenvironmental landscapes. Br J Cancer 2020; 122:943-952. [PMID: 32042067 PMCID: PMC7109142 DOI: 10.1038/s41416-019-0721-1] [Citation(s) in RCA: 141] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 12/09/2019] [Accepted: 12/19/2019] [Indexed: 01/27/2023] Open
Abstract
Why do we get cancer mostly when we are old? According to current paradigms, the answer is simple: mutations accumulate in our tissues throughout life, and some of these mutations contribute to cancers. Although mutations are necessary for cancer development, a number of studies shed light on roles for ageing and exposure-dependent changes in tissue landscapes that determine the impact of oncogenic mutations on cellular fitness, placing carcinogenesis into an evolutionary framework. Natural selection has invested in somatic maintenance to maximise reproductive success. Tissue maintenance not only ensures functional robustness but also prevents the occurrence of cancer through periods of likely reproduction by limiting selection for oncogenic events in our cells. Indeed, studies in organisms ranging from flies to humans are revealing conserved mechanisms to eliminate damaged or oncogenically initiated cells from tissues. Reports of the existence of striking numbers of oncogenically initiated clones in normal tissues and of how this clonal architecture changes with age or external exposure to noxious substances provide critical insight into the early stages of cancer development. A major challenge for cancer biology will be the integration of these studies with epidemiology data into an evolutionary theory of carcinogenesis, which could have a large impact on addressing cancer risk and treatment.
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Affiliation(s)
- Ezio Laconi
- Department of Biomedical Sciences, Section of Pathology, University of Cagliari School of Medicine, 09126, Cagliari, Italy.
| | - Fabio Marongiu
- Department of Biomedical Sciences, Section of Pathology, University of Cagliari School of Medicine, 09126, Cagliari, Italy
| | - James DeGregori
- Department of Biochemistry and Molecular Genetics, Integrated Department of Immunology, Department of Pediatrics, Department of Medicine (Section of Hematology), University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.
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19
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Hall MWJ, Jones PH, Hall BA. Relating evolutionary selection and mutant clonal dynamics in normal epithelia. J R Soc Interface 2019; 16:20190230. [PMID: 31362624 PMCID: PMC6685019 DOI: 10.1098/rsif.2019.0230] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 06/24/2019] [Indexed: 02/02/2023] Open
Abstract
Cancer develops from mutated cells in normal tissues. Whether somatic mutations alter normal cell dynamics is key to understanding cancer risk and guiding interventions to reduce it. An analysis of the first incomplete moment of size distributions of clones carrying cancer-associated mutations in normal human eyelid skin gives a good fit with neutral drift, arguing mutations do not affect cell fate. However, this suggestion conflicts with genetic evidence in the same dataset that argues for strong positive selection of a subset of mutations. This implies cells carrying these mutations have a competitive advantage over normal cells, leading to large clonal expansions within the tissue. In the normal epithelium, clone growth is constrained by the limited size of the proliferating compartment and competition with surrounding cells. We show that if these factors are taken into account, the first incomplete moment of the clone size distribution is unable to exclude non-neutral behaviour. Furthermore, experimental factors can make a non-neutral clone size distribution appear neutral. We validate these principles with a new experimental dataset showing that when experiments are appropriately designed, the first incomplete moment can be a useful indicator of non-neutral competition. Finally, we discuss the complex relationship between mutant clone sizes and genetic selection.
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Affiliation(s)
- Michael W. J. Hall
- Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- MRC Cancer Unit, University of Cambridge, Hutchison-MRC Research Centre, Box 197, Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK
| | - Philip H. Jones
- Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- MRC Cancer Unit, University of Cambridge, Hutchison-MRC Research Centre, Box 197, Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK
| | - Benjamin A. Hall
- MRC Cancer Unit, University of Cambridge, Hutchison-MRC Research Centre, Box 197, Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK
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20
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Stiehl T, Marciniak-Czochra A. How to Characterize Stem Cells? Contributions from Mathematical Modeling. CURRENT STEM CELL REPORTS 2019. [DOI: 10.1007/s40778-019-00155-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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21
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Shakiba N, Fahmy A, Jayakumaran G, McGibbon S, David L, Trcka D, Elbaz J, Puri MC, Nagy A, van der Kooy D, Goyal S, Wrana JL, Zandstra PW. Cell competition during reprogramming gives rise to dominant clones. Science 2019; 364:science.aan0925. [DOI: 10.1126/science.aan0925] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 08/02/2018] [Accepted: 02/25/2019] [Indexed: 12/25/2022]
Abstract
The ability to generate induced pluripotent stem cells from differentiated cell types has enabled researchers to engineer cell states. Although studies have identified molecular networks that reprogram cells to pluripotency, the cellular dynamics of these processes remain poorly understood. Here, by combining cellular barcoding, mathematical modeling, and lineage tracing approaches, we demonstrate that reprogramming dynamics in heterogeneous populations are driven by dominant “elite” clones. Clones arise a priori from a population of poised mouse embryonic fibroblasts derived from Wnt1-expressing cells that may represent a neural crest–derived population. This work highlights the importance of cellular dynamics in fate programming outcomes and uncovers cell competition as a mechanism by which cells with eliteness emerge to occupy and dominate the reprogramming niche.
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22
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Maher GJ, Ralph HK, Ding Z, Koelling N, Mlcochova H, Giannoulatou E, Dhami P, Paul DS, Stricker SH, Beck S, McVean G, Wilkie AOM, Goriely A. Selfish mutations dysregulating RAS-MAPK signaling are pervasive in aged human testes. Genome Res 2018; 28:1779-1790. [PMID: 30355600 PMCID: PMC6280762 DOI: 10.1101/gr.239186.118] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 10/20/2018] [Indexed: 02/07/2023]
Abstract
Mosaic mutations present in the germline have important implications for reproductive risk and disease transmission. We previously demonstrated a phenomenon occurring in the male germline, whereby specific mutations arising spontaneously in stem cells (spermatogonia) lead to clonal expansion, resulting in elevated mutation levels in sperm over time. This process, termed "selfish spermatogonial selection," explains the high spontaneous birth prevalence and strong paternal age-effect of disorders such as achondroplasia and Apert, Noonan and Costello syndromes, with direct experimental evidence currently available for specific positions of six genes (FGFR2, FGFR3, RET, PTPN11, HRAS, and KRAS). We present a discovery screen to identify novel mutations and genes showing evidence of positive selection in the male germline, by performing massively parallel simplex PCR using RainDance technology to interrogate mutational hotspots in 67 genes (51.5 kb in total) in 276 biopsies of testes from five men (median age, 83 yr). Following ultradeep sequencing (about 16,000×), development of a low-frequency variant prioritization strategy, and targeted validation, we identified 61 distinct variants present at frequencies as low as 0.06%, including 54 variants not previously directly associated with selfish selection. The majority (80%) of variants identified have previously been implicated in developmental disorders and/or oncogenesis and include mutations in six newly associated genes (BRAF, CBL, MAP2K1, MAP2K2, RAF1, and SOS1), all of which encode components of the RAS-MAPK pathway and activate signaling. Our findings extend the link between mutations dysregulating the RAS-MAPK pathway and selfish selection, and show that the aging male germline is a repository for such deleterious mutations.
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Affiliation(s)
- Geoffrey J Maher
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
| | - Hannah K Ralph
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
| | - Zhihao Ding
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
| | - Nils Koelling
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
| | - Hana Mlcochova
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
| | - Eleni Giannoulatou
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
| | - Pawan Dhami
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, United Kingdom
| | - Dirk S Paul
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, United Kingdom
| | - Stefan H Stricker
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, United Kingdom
| | - Stephan Beck
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, United Kingdom
| | - Gilean McVean
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - Andrew O M Wilkie
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
| | - Anne Goriely
- Clinical Genetics Group, MRC-Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.,Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom
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23
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Rognoni E, Watt FM. Skin Cell Heterogeneity in Development, Wound Healing, and Cancer. Trends Cell Biol 2018; 28:709-722. [PMID: 29807713 PMCID: PMC6098245 DOI: 10.1016/j.tcb.2018.05.002] [Citation(s) in RCA: 174] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Revised: 05/01/2018] [Accepted: 05/08/2018] [Indexed: 12/14/2022]
Abstract
Skin architecture and function depend on diverse populations of epidermal cells and dermal fibroblasts. Reciprocal communication between the epidermis and dermis plays a key role in skin development, homeostasis and repair. While several stem cell populations have been identified in the epidermis with distinct locations and functions, it is now recognised that there is additional heterogeneity within the mesenchymal cells of the dermis. Here, we discuss recent insights into how these distinct cell populations are maintained and coordinated during development, homeostasis, and wound healing. We highlight the importance of the local environment, or niche, in cellular plasticity. We also discuss new mechanisms that have been identified as influencing wound repair and cancer progression.
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Affiliation(s)
- Emanuel Rognoni
- King's College London, Centre for Stem Cells and Regenerative Medicine, 28th Floor, Tower Wing, Guy's Hospital Campus, Great Maze Pond, London SE1 9RT, UK
| | - Fiona M Watt
- King's College London, Centre for Stem Cells and Regenerative Medicine, 28th Floor, Tower Wing, Guy's Hospital Campus, Great Maze Pond, London SE1 9RT, UK.
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24
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Diverse mechanisms for endogenous regeneration and repair in mammalian organs. Nature 2018; 557:322-328. [PMID: 29769669 DOI: 10.1038/s41586-018-0073-7] [Citation(s) in RCA: 104] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 03/07/2018] [Indexed: 12/11/2022]
Abstract
Mammalian organs comprise an extraordinary diversity of cell and tissue types. Regenerative organs, such as the skin and gastrointestinal tract, use resident stem cells to maintain tissue function. Organs with a lower cellular turnover, such as the liver and lungs, mostly rely on proliferation of committed progenitor cells. In many organs, injury reveals the plasticity of both resident stem cells and differentiated cells. The ability of resident cells to maintain and repair organs diminishes with age, whereas, paradoxically, the risk of cancer increases. New therapeutic approaches aim to harness cell plasticity for tissue repair and regeneration while avoiding the risk of malignant transformation of cells.
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25
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De S, Ganesan S. Looking beyond drivers and passengers in cancer genome sequencing data. Ann Oncol 2018; 28:938-945. [PMID: 27998972 DOI: 10.1093/annonc/mdw677] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Cancer arises as a result of acquired changes in the DNA sequence of the genome of somatic cells. A subset of the genetic changes, dubbed driver mutations, propels tumor growth, and the remaining changes are passengers, apparently inconsequential for neoplastic transformation. Massive genome sequencing of thousands of tumors from all major cancer types has enabled cataloging of the so-called driver and passenger mutations, and facilitated molecular classification of cancer, guiding precision medicine approach for the patients. Nonetheless, innovative analyses of cancer genomics data has led to novel, sometimes serendipitous findings that have aided to our understanding of other aspects of the biology of the disease and opened up new frontiers. For instance, emerging findings show that mutational patterns in cancer genomes can help detect signatures of known and novel DNA damage and repair processes, provide a likely chronological account of genomic changes in cancer genomes, and allow revisiting the models of cancer evolution. These findings have stimulated original approaches to identify disease etiology, stratify patients, target the disease, and monitor patient responses, complementing driver-mutation centric approaches. In this review, we discuss these emerging approaches and unexpected breakthroughs, and their implications for basic cancer research and clinical practices.
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Affiliation(s)
- S De
- Center for Cancer Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, New Brunswick, USA
| | - S Ganesan
- Center for Cancer Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, New Brunswick, USA
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26
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Lynch MD, Lynch CNS, Craythorne E, Liakath-Ali K, Mallipeddi R, Barker JN, Watt FM. Spatial constraints govern competition of mutant clones in human epidermis. Nat Commun 2017; 8:1119. [PMID: 29066762 PMCID: PMC5654977 DOI: 10.1038/s41467-017-00993-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 08/10/2017] [Indexed: 12/11/2022] Open
Abstract
Deep sequencing can detect somatic DNA mutations in tissues permitting inference of clonal relationships. This has been applied to human epidermis, where sun exposure leads to the accumulation of mutations and an increased risk of skin cancer. However, previous studies have yielded conflicting conclusions about the relative importance of positive selection and neutral drift in clonal evolution. Here, we sequenced larger areas of skin than previously, focusing on cancer-prone skin spanning five decades of life. The mutant clones identified were too large to be accounted for solely by neutral drift. Rather, using mathematical modelling and computational lattice-based simulations, we show that observed clone size distributions can be explained by a combination of neutral drift and stochastic nucleation of mutations at the boundary of expanding mutant clones that have a competitive advantage. These findings demonstrate that spatial context and cell competition cooperate to determine the fate of a mutant stem cell. Deep sequencing technologies allow for the investigation of clonal evolution in human cancers. Here the authors, combining sequencing data from human skin with mathematical modelling and simulations, suggest that the spatial context of a mutation with respect to other mutant clones may lead to differential clonal evolution.
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Affiliation(s)
- M D Lynch
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, SE1 9RT, UK.,St John's Institute of Dermatology, King's College London, London, SE1 9RT, UK
| | - C N S Lynch
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, SE1 9RT, UK
| | - E Craythorne
- St John's Institute of Dermatology, King's College London, London, SE1 9RT, UK
| | - K Liakath-Ali
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, SE1 9RT, UK
| | - R Mallipeddi
- St John's Institute of Dermatology, King's College London, London, SE1 9RT, UK
| | - J N Barker
- St John's Institute of Dermatology, King's College London, London, SE1 9RT, UK
| | - F M Watt
- Centre for Stem Cells and Regenerative Medicine, King's College London, London, SE1 9RT, UK.
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27
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Stem cell self-renewal in regeneration and cancer: Insights from mathematical modeling. ACTA ACUST UNITED AC 2017. [DOI: 10.1016/j.coisb.2017.09.006] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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28
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Fate mapping of human glioblastoma reveals an invariant stem cell hierarchy. Nature 2017; 549:227-232. [PMID: 28854171 PMCID: PMC5608080 DOI: 10.1038/nature23666] [Citation(s) in RCA: 276] [Impact Index Per Article: 39.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 07/24/2017] [Indexed: 12/30/2022]
Abstract
Human glioblastomas harbour a subpopulation of glioblastoma stem cells that drive tumorigenesis. However, the origin of intratumoural functional heterogeneity between glioblastoma cells remains poorly understood. Here we study the clonal evolution of barcoded glioblastoma cells in an unbiased way following serial xenotransplantation to define their individual fate behaviours. Independent of an evolving mutational signature, we show that the growth of glioblastoma clones in vivo is consistent with a remarkably neutral process involving a conserved proliferative hierarchy rooted in glioblastoma stem cells. In this model, slow-cycling stem-like cells give rise to a more rapidly cycling progenitor population with extensive self-maintenance capacity, which in turn generates non-proliferative cells. We also identify rare 'outlier' clones that deviate from these dynamics, and further show that chemotherapy facilitates the expansion of pre-existing drug-resistant glioblastoma stem cells. Finally, we show that functionally distinct glioblastoma stem cells can be separately targeted using epigenetic compounds, suggesting new avenues for glioblastoma-targeted therapy.
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Abbosh C, Venkatesan S, Janes SM, Fitzgerald RC, Swanton C. Evolutionary dynamics in pre-invasive neoplasia. CURRENT OPINION IN SYSTEMS BIOLOGY 2017; 2:1-8. [PMID: 30603736 PMCID: PMC6312179 DOI: 10.1016/j.coisb.2017.02.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Mutational processes occur in normal tissues from conception throughout life. Field cancerization describes the preconditioning of an area of epithelium to tumor growth. Pre-invasive lesions may arise in these fields, however only a minority of pre-invasive neoplasia progresses to overt malignancy. Within this review we discuss recent advances in our understanding of genomic instability processes in normal tissue, describe evolutionary dynamics in pre-invasive disease and highlight current evidence describing how increasing genomic instability may drive the transition from pre-invasive to invasive disease. Appreciation of the evolutionary rulebooks that operate in pre-invasive neoplasia may facilitate screening strategies, risk-stratification of pre-invasive lesions and precipitate novel preventative treatments in at-risk patient populations.
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Affiliation(s)
- Christopher Abbosh
- UCL Cancer Institute, CRUK Lung Cancer Centre of Excellence, Paul O'Gorman Building, Huntley St., London WC1E 6DD, UK
| | - Subramanian Venkatesan
- UCL Cancer Institute, CRUK Lung Cancer Centre of Excellence, Paul O'Gorman Building, Huntley St., London WC1E 6DD, UK
- Translational Cancer Therapeutics Lab, The Francis Crick Institute, 1 Midland Road, London, NW1 1AT
| | - Samuel M Janes
- Lungs for Living Research Centre, UCL Respiratory, Division of Medicine, Rayne Building, University College London, London, UK
| | - Rebecca C Fitzgerald
- MRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Cambridge, United Kingdom
| | - Charles Swanton
- UCL Cancer Institute, CRUK Lung Cancer Centre of Excellence, Paul O'Gorman Building, Huntley St., London WC1E 6DD, UK
- Translational Cancer Therapeutics Lab, The Francis Crick Institute, 1 Midland Road, London, NW1 1AT
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30
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Hu Z, Sun R, Curtis C. A population genetics perspective on the determinants of intra-tumor heterogeneity. Biochim Biophys Acta Rev Cancer 2017; 1867:109-126. [PMID: 28274726 DOI: 10.1016/j.bbcan.2017.03.001] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 03/01/2017] [Accepted: 03/02/2017] [Indexed: 12/17/2022]
Abstract
Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implications for precision medicine, the accurate quantification of heterogeneity within and between tumors has become a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evidence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
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Affiliation(s)
- Zheng Hu
- Departments of Medicine and Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ruping Sun
- Departments of Medicine and Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Christina Curtis
- Departments of Medicine and Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
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31
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Rulands S, Simons BD. Tracing cellular dynamics in tissue development, maintenance and disease. Curr Opin Cell Biol 2016; 43:38-45. [PMID: 27474807 DOI: 10.1016/j.ceb.2016.07.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Revised: 06/16/2016] [Accepted: 07/05/2016] [Indexed: 12/20/2022]
Abstract
The coordination of cell proliferation and differentiation is central to the development and maintenance of tissues, while its dysregulation underlies the transition to diseased states. By combining lineage tracing with transcriptional profiling and marker-based assays, statistical methods are delivering insights into the dynamics of stem cells and their developmental precursors. These studies have provided evidence for molecular heterogeneity and fate priming, and have revealed a role for stochasticity in stem cell fate, refocusing the search for regulatory mechanisms. At the same time, they present a quantitative platform to study the initiation and progression of disease. Here, we review how quantitative lineage tracing strategies are shaping our understanding of the cellular mechanisms of tissue development, maintenance and disease.
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Affiliation(s)
- Steffen Rulands
- Cavendish Laboratory, Department of Physics, J. J. Thomson Avenue, Cambridge CB3 0HE, UK; The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge CB2 1QN, UK; Wellcome Trust-Medical Research Council Stem Cell Institute, University of Cambridge, UK
| | - Benjamin D Simons
- Cavendish Laboratory, Department of Physics, J. J. Thomson Avenue, Cambridge CB3 0HE, UK; The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge CB2 1QN, UK; Wellcome Trust-Medical Research Council Stem Cell Institute, University of Cambridge, UK.
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32
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Martincorena I, Jones PH, Campbell PJ. Constrained positive selection on cancer mutations in normal skin. Proc Natl Acad Sci U S A 2016; 113:E1128-9. [PMID: 26884187 PMCID: PMC4780655 DOI: 10.1073/pnas.1600910113] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Affiliation(s)
- Iñigo Martincorena
- Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, United Kingdom;
| | - Philip H Jones
- Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, United Kingdom; Medical Research Council Cancer Unit, Hutchison-Medical Research Council Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0XZ, United Kingdom
| | - Peter J Campbell
- Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, United Kingdom; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, United Kingdom
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33
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Reply to Martincorena et al.: Evidence for constrained positive selection of cancer mutations in normal skin is lacking. Proc Natl Acad Sci U S A 2016; 113:E1130-1. [PMID: 26884186 DOI: 10.1073/pnas.1601045113] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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