1
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Linder RA, Zabanavar B, Majumder A, Hoang HCS, Delgado VG, Tran R, La VT, Leemans SW, Long AD. Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes. Mol Biol Evol 2022; 39:msac248. [PMID: 36366952 PMCID: PMC9728589 DOI: 10.1093/molbev/msac248] [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] [Indexed: 11/13/2022] Open
Abstract
We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.
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Affiliation(s)
- Robert A Linder
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
| | - Behzad Zabanavar
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
| | - Arundhati Majumder
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
| | - Hannah Chiao-Shyan Hoang
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
| | - Vanessa Genesaret Delgado
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
| | - Ryan Tran
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
| | - Vy Thoai La
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
| | - Simon William Leemans
- Department of Biomedical Engineering, School of Engineering, University of California, Irvine
| | - Anthony D Long
- Department of Ecology and Evolutionary Biology, School of Biological Sciences, University of California, Irvine
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2
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Bentley MA, Yates CA, Hein J, Preston GM, Foster KR. Pleiotropic constraints promote the evolution of cooperation in cellular groups. PLoS Biol 2022; 20:e3001626. [PMID: 35658016 PMCID: PMC9166655 DOI: 10.1371/journal.pbio.3001626] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 04/11/2022] [Indexed: 12/12/2022] Open
Abstract
The evolution of cooperation in cellular groups is threatened by lineages of cheaters that proliferate at the expense of the group. These cell lineages occur within microbial communities, and multicellular organisms in the form of tumours and cancer. In contrast to an earlier study, here we show how the evolution of pleiotropic genetic architectures—which link the expression of cooperative and private traits—can protect against cheater lineages and allow cooperation to evolve. We develop an age-structured model of cellular groups and show that cooperation breaks down more slowly within groups that tie expression to a private trait than in groups that do not. We then show that this results in group selection for pleiotropy, which strongly promotes cooperation by limiting the emergence of cheater lineages. These results predict that pleiotropy will rapidly evolve, so long as groups persist long enough for cheater lineages to threaten cooperation. Our results hold when pleiotropic links can be undermined by mutations, when pleiotropy is itself costly, and in mixed-genotype groups such as those that occur in microbes. Finally, we consider features of multicellular organisms—a germ line and delayed reproductive maturity—and show that pleiotropy is again predicted to be important for maintaining cooperation. The study of cancer in multicellular organisms provides the best evidence for pleiotropic constraints, where abberant cell proliferation is linked to apoptosis, senescence, and terminal differentiation. Alongside development from a single cell, we propose that the evolution of pleiotropic constraints has been critical for cooperation in many cellular groups. The evolution of cooperation in cellular groups is threatened by lineages of cheaters that proliferate at the expense of the group. In this study, an age-structured model of cellular groups shows that pleiotropy promotes the evolution of cooperation and may have been important for the origins of multicellularity.
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Affiliation(s)
- Michael A. Bentley
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
- * E-mail: (MAB); (KRF)
| | - Christian A. Yates
- Department of Mathematical Sciences, University of Bath, Bath, United Kingdom
| | - Jotun Hein
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Gail M. Preston
- Department of Plant Sciences, University of Oxford, Oxford, United Kingdom
| | - Kevin R. Foster
- Department of Zoology, University of Oxford, Oxford, United Kingdom
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
- * E-mail: (MAB); (KRF)
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3
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Butler G, Keeton SJ, Johnson LJ, Dash PR. A phenotypic switch in the dispersal strategy of breast cancer cells selected for metastatic colonization. Proc Biol Sci 2020; 287:20202523. [PMID: 33259764 DOI: 10.1098/rspb.2020.2523] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
An important question in cancer evolution concerns which traits make a cell likely to successfully metastasize. Cell motility phenotypes, mediated by cell shape change, are strong candidates. We experimentally evolved breast cancer cells in vitro for metastatic capability, using selective regimes designed to simulate stages of metastasis, then quantified their motility behaviours using computer vision. All evolved lines showed changes to motility phenotypes, and we have identified a previously unknown density-dependent motility phenotype only seen in cells selected for colonization of decellularized lung tissue. These cells increase their rate of morphological change with an increase in migration speed when local cell density is high. However, when the local cell density is low, we find the opposite relationship: the rate of morphological change decreases with an increase in migration speed. Neither the ancestral population, nor cells selected for their ability to escape or invade extracellular matrix-like environments, displays this dynamic behavioural switch. Our results suggest that cells capable of distant-site colonization may be characterized by dynamic morphological phenotypes and the capacity to respond to the local social environment.
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Affiliation(s)
- George Butler
- School of Biological Sciences, University of Reading, Reading, UK
| | - Shirley J Keeton
- School of Biological Sciences, University of Reading, Reading, UK
| | - Louise J Johnson
- School of Biological Sciences, University of Reading, Reading, UK
| | - Philip R Dash
- School of Biological Sciences, University of Reading, Reading, UK
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4
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Lai PL, Chen TC, Feng CY, Lin H, Ng CH, Chen Y, Hsiao M, Lu J, Huang HC. Selection of a malignant subpopulation from a colorectal cancer cell line. Oncol Lett 2020; 20:2937-2945. [PMID: 32782610 PMCID: PMC7399770 DOI: 10.3892/ol.2020.11829] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 06/16/2020] [Indexed: 01/05/2023] Open
Abstract
Colorectal cancer (CRC) is a leading cause of cancer-associated mortality worldwide; therefore, there is an emerging need for novel experimental models that allow for the identification and validation of biomarkers for CRC-specific progression. In the present study, a repeated sphere-forming assay was used as a strategy to select a malignant subpopulation from a CRC cell line, namely HCT116. The assay was validated by confirming that canonical stemness markers were upregulated in the sphere state at every generation of the selection assay. The resulting subpopulation, after eight rounds of selection, exhibited increased sphere-forming capacity in vitro and increased tumorigenicity in vivo. Furthermore, dipeptidase 1 (DPEP1) was identified as the major differentially expressed gene in the selected clone, and its depletion suppressed the elevated sphere-forming capacity in vitro and tumorigenicity in vivo. Overall, the present study established an experimental strategy to isolate a malignant subpopulation from a CRC cell line. Additionally, results from the present model revealed that DPEP1 may serve as a promising prognostic biomarker for CRC.
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Affiliation(s)
- Pei-Lun Lai
- Institute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.,Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C
| | - Ting-Chun Chen
- Institute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C
| | - Chun-Yen Feng
- Institute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C
| | - Hsuan Lin
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C
| | - Chi-Hou Ng
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C.,Genome and Systems Biology Degree Program, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C
| | - Yun Chen
- Institute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C
| | - Michael Hsiao
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C
| | - Jean Lu
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan, R.O.C.,Genome and Systems Biology Degree Program, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.,National RNAi Platform/National Core Facility Program for Biotechnology, Taipei 11529, Taiwan, R.O.C.,Department of Life Science, Tzu Chi University, Hualien 970, Taiwan, R.O.C.,Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 11490, Taiwan, R.O.C
| | - Hsiao-Chun Huang
- Institute of Molecular and Cellular Biology, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.,Genome and Systems Biology Degree Program, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.,Department of Life Science, College of Life Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C.,Graduate Institute of Electronics Engineering, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei 10617, Taiwan, R.O.C
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5
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Repeatability analysis improves the reliability of behavioral data. PLoS One 2020; 15:e0230900. [PMID: 32240211 PMCID: PMC7117744 DOI: 10.1371/journal.pone.0230900] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 03/11/2020] [Indexed: 11/19/2022] Open
Abstract
Reliability of data has become a major concern in the course of the reproducibility crisis. Especially when studying animal behavior, confounding factors such as novelty of the test apparatus can lead to a wide variability of data which may mask treatment effects and consequently lead to misinterpretation. Habituation to the test situation is a common practice to circumvent novelty induced increases in variance and to improve the reliability of the respective measurements. However, there is a lack of published empirical knowledge regarding reasonable habituation procedures and a method validation seems to be overdue. This study aimed at setting up a simple strategy to increase reliability of behavioral data measured in a familiar test apparatus. Therefore, exemplary data from mice tested in an Open Field (OF) arena were used to elucidate the potential of habituation and how reliability of measures can be confirmed by means of a repeatability analysis using the software R. On seven consecutive days, male C57BL/6J, BALB/cJ and 129S1/SvImJ mice were tested in an OF arena once daily and individual mouse behavior was recorded. A repeatability analysis was conducted with regard to repeated trials of habituation. Our data analysis revealed that monitoring animal behavior during habituation is important to determine when individual differences of the measurements are stable. Repeatability values from distance travelled and average activity increased over the habituation period, revealing that around 60% of the variance of the data can be explained by individual differences between mice. The first day of habituation was significantly different from the following 6 days. A three-day habituation period appeared to be sufficient in this study. Overall, these results emphasize the importance of habituation and in depth analysis of habituation data to define the correct starting point of the experiment for improving the reliability and reproducibility of experimental data.
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6
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Wass AV, Butler G, Taylor TB, Dash PR, Johnson LJ. Cancer cell lines show high heritability for motility but not generation time. ROYAL SOCIETY OPEN SCIENCE 2020; 7:191645. [PMID: 32431868 PMCID: PMC7211847 DOI: 10.1098/rsos.191645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 03/06/2020] [Indexed: 06/11/2023]
Abstract
Tumour evolution depends on heritable differences between cells in traits affecting cell survival or replication. It is well established that cancer cells are genetically and phenotypically heterogeneous; however, the extent to which this phenotypic variation is heritable is far less well explored. Here, we estimate the broad-sense heritability (H 2) of two cell traits related to cancer hallmarks--cell motility and generation time--within populations of four cancer cell lines in vitro and find that motility is strongly heritable. This heritability is stable across multiple cell generations, with heritability values at the high end of those measured for a range of traits in natural populations of animals or plants. These findings confirm a central assumption of cancer evolution, provide a first quantification of the evolvability of key traits in cancer cells and indicate that there is ample raw material for experimental evolution in cancer cell lines. Generation time, a trait directly affecting cell fitness, shows substantially lower values of heritability than cell speed, consistent with its having been under directional selection removing heritable variation.
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Affiliation(s)
- Anastasia V. Wass
- School of Biological Sciences, University of Reading, Whiteknights, Reading, Berkshire RG6 6AH, UK
| | - George Butler
- School of Biological Sciences, University of Reading, Whiteknights, Reading, Berkshire RG6 6AH, UK
| | - Tiffany B. Taylor
- School of Biological Sciences, University of Reading, Whiteknights, Reading, Berkshire RG6 6AH, UK
- The Milner Centre for Evolution and Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath, Somerset BA2 7AY, UK
| | - Philip R. Dash
- School of Biological Sciences, University of Reading, Whiteknights, Reading, Berkshire RG6 6AH, UK
| | - Louise J. Johnson
- School of Biological Sciences, University of Reading, Whiteknights, Reading, Berkshire RG6 6AH, UK
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7
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Farquhar KS, Charlebois DA, Szenk M, Cohen J, Nevozhay D, Balázsi G. Role of network-mediated stochasticity in mammalian drug resistance. Nat Commun 2019; 10:2766. [PMID: 31235692 PMCID: PMC6591227 DOI: 10.1038/s41467-019-10330-w] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 05/03/2019] [Indexed: 11/11/2022] Open
Abstract
A major challenge in biology is that genetically identical cells in the same environment can display gene expression stochasticity (noise), which contributes to bet-hedging, drug tolerance, and cell-fate switching. The magnitude and timescales of stochastic fluctuations can depend on the gene regulatory network. Currently, it is unclear how gene expression noise of specific networks impacts the evolution of drug resistance in mammalian cells. Answering this question requires adjusting network noise independently from mean expression. Here, we develop positive and negative feedback-based synthetic gene circuits to decouple noise from the mean for Puromycin resistance gene expression in Chinese Hamster Ovary cells. In low Puromycin concentrations, the high-noise, positive-feedback network delays long-term adaptation, whereas it facilitates adaptation under high Puromycin concentration. Accordingly, the low-noise, negative-feedback circuit can maintain resistance by acquiring mutations while the positive-feedback circuit remains mutation-free and regains drug sensitivity. These findings may have profound implications for chemotherapeutic inefficiency and cancer relapse. The role of gene expression noise in the evolution of drug resistance in mammalian cells is unclear. Here, by uncoupling noise from mean expression of a drug resistance gene in CHO cells the authors show that noisy expression aids adaptation to high drug levels, but delays it at low drug levels.
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Affiliation(s)
- Kevin S Farquhar
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA.,Genetics and Epigenetics Graduate Program, The University of Texas MD Anderson Cancer Center, UT Health Graduate School of Biomedical Sciences, Houston, TX, 77030, USA
| | - Daniel A Charlebois
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA.,Department of Physics, University of Alberta, Edmonton, AB, 4-181 CCIS, T6G-2E1, Canada
| | - Mariola Szenk
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA.,Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Joseph Cohen
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Dmitry Nevozhay
- School of Biomedicine, Far Eastern Federal University, 8 Sukhanova Street, Vladivostok, 690950, Russia.,Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Gábor Balázsi
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA. .,Genetics and Epigenetics Graduate Program, The University of Texas MD Anderson Cancer Center, UT Health Graduate School of Biomedical Sciences, Houston, TX, 77030, USA. .,Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA. .,Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
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8
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Verma N, Franchitto M, Zonfrilli A, Cialfi S, Palermo R, Talora C. DNA Damage Stress: Cui Prodest? Int J Mol Sci 2019; 20:E1073. [PMID: 30832234 PMCID: PMC6429504 DOI: 10.3390/ijms20051073] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 02/18/2019] [Accepted: 02/26/2019] [Indexed: 12/25/2022] Open
Abstract
DNA is an entity shielded by mechanisms that maintain genomic stability and are essential for living cells; however, DNA is constantly subject to assaults from the environment throughout the cellular life span, making the genome susceptible to mutation and irreparable damage. Cells are prepared to mend such events through cell death as an extrema ratio to solve those threats from a multicellular perspective. However, in cells under various stress conditions, checkpoint mechanisms are activated to allow cells to have enough time to repair the damaged DNA. In yeast, entry into the cell cycle when damage is not completely repaired represents an adaptive mechanism to cope with stressful conditions. In multicellular organisms, entry into cell cycle with damaged DNA is strictly forbidden. However, in cancer development, individual cells undergo checkpoint adaptation, in which most cells die, but some survive acquiring advantageous mutations and selfishly evolve a conflictual behavior. In this review, we focus on how, in cancer development, cells rely on checkpoint adaptation to escape DNA stress and ultimately to cell death.
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Affiliation(s)
- Nagendra Verma
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Matteo Franchitto
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Azzurra Zonfrilli
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Samantha Cialfi
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Rocco Palermo
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Claudio Talora
- Department of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
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9
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Van den Bergh B, Swings T, Fauvart M, Michiels J. Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution. Microbiol Mol Biol Rev 2018; 82:e00008-18. [PMID: 30045954 PMCID: PMC6094045 DOI: 10.1128/mmbr.00008-18] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.
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Affiliation(s)
- Bram Van den Bergh
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
- Douglas Lab, Department of Entomology, Cornell University, Ithaca, New York, USA
| | - Toon Swings
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
| | - Maarten Fauvart
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
- imec, Leuven, Belgium
| | - Jan Michiels
- Laboratory of Symbiotic and Pathogenic Interactions, Centre of Microbial and Plant Genetics, KU Leuven-University of Leuven, Leuven, Belgium
- Michiels Lab, Center for Microbiology, VIB, Leuven, Belgium
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10
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Zhang J, Späth SS, Marjani SL, Zhang W, Pan X. Characterization of cancer genomic heterogeneity by next-generation sequencing advances precision medicine in cancer treatment. PRECISION CLINICAL MEDICINE 2018; 1:29-48. [PMID: 30687561 PMCID: PMC6333046 DOI: 10.1093/pcmedi/pby007] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 05/10/2018] [Accepted: 05/21/2018] [Indexed: 02/05/2023] Open
Abstract
Cancer is a heterogeneous disease with unique genomic and phenotypic features that differ
between individual patients and even among individual tumor regions. In recent years,
large-scale genomic studies and new next-generation sequencing technologies have uncovered
more scientific details about tumor heterogeneity, with significant implications for the
choice of specific molecular biomarkers and clinical decision making. Genomic
heterogeneity significantly contributes to the generation of a diverse cell population
during tumor development and progression, representing a determining factor for variation
in tumor treatment response. It has been considered a prominent contributor to therapeutic
failure, and increases the likelihood of resistance to future therapies in most common
cancers. The understanding of molecular heterogeneity in cancer is a fundamental component
of precision oncology, enabling the identification of genomic alteration of key genes and
pathways that can be targeted therapeutically. Here, we review the emerging knowledge of
tumor genomics and heterogeneity, as well as potential implications for precision medicine
in cancer treatment and new therapeutic discoveries. An analysis and interpretation of the
TCGA database was included.
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Affiliation(s)
- Jialing Zhang
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT USA
| | | | - Sadie L Marjani
- Department of Biology, Central Connecticut State University, New Britain, CT, USA
| | - Wengeng Zhang
- Precision Medicine Key Laboratory of Sichuan Province & Precision Medicine Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xinghua Pan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University.,Guangdong Provincial Key Laboratory of Single Cell Technology and Application, Guangzhou, Guangdong Province, China.,Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT USA
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11
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Obolski U, Ram Y, Hadany L. Key issues review: evolution on rugged adaptive landscapes. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2018; 81:012602. [PMID: 29051394 DOI: 10.1088/1361-6633/aa94d4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Adaptive landscapes represent a mapping between genotype and fitness. Rugged adaptive landscapes contain two or more adaptive peaks: allele combinations with higher fitness than any of their neighbors in the genetic space. How do populations evolve on such rugged landscapes? Evolutionary biologists have struggled with this question since it was first introduced in the 1930s by Sewall Wright. Discoveries in the fields of genetics and biochemistry inspired various mathematical models of adaptive landscapes. The development of landscape models led to numerous theoretical studies analyzing evolution on rugged landscapes under different biological conditions. The large body of theoretical work suggests that adaptive landscapes are major determinants of the progress and outcome of evolutionary processes. Recent technological advances in molecular biology and microbiology allow experimenters to measure adaptive values of large sets of allele combinations and construct empirical adaptive landscapes for the first time. Such empirical landscapes have already been generated in bacteria, yeast, viruses, and fungi, and are contributing to new insights about evolution on adaptive landscapes. In this Key Issues Review we will: (i) introduce the concept of adaptive landscapes; (ii) review the major theoretical studies of evolution on rugged landscapes; (iii) review some of the recently obtained empirical adaptive landscapes; (iv) discuss recent mathematical and statistical analyses motivated by empirical adaptive landscapes, as well as provide the reader with instructions and source code to implement simulations of evolution on adaptive landscapes; and (v) discuss possible future directions for this exciting field.
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12
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Taylor TB, Wass AV, Johnson LJ, Dash P. Resource competition promotes tumour expansion in experimentally evolved cancer. BMC Evol Biol 2017; 17:268. [PMID: 29281983 PMCID: PMC5745887 DOI: 10.1186/s12862-017-1117-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 12/14/2017] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Tumour progression involves a series of phenotypic changes to cancer cells, each of which presents therapeutic targets. Here, using techniques adapted from microbial experimental evolution, we investigate the evolution of tumour spreading - a precursor for metastasis and tissue invasion - in environments with varied resource supply. Evolutionary theory predicts that competition for resources within a population will select for individuals to move away from a natal site (i.e. disperse), facilitating the colonisation of unexploited resources and decreasing competition between kin. RESULTS After approximately 100 generations in environments with low resource supply, we find that MCF7 breast cancer spheroids (small in vitro tumours) show increased spreading. Conversely, spreading slows compared to the ancestor where resource supply is high. Common garden experiments confirm that the evolutionary responses differ between selection lines; with lines evolved under low resource supply showing phenotypic plasticity in spheroid spreading rate. These differences in spreading behaviour between selection lines are heritable (stable across multiple generations), and show that the divergently evolved lines differ in their response to resource supply. CONCLUSIONS We observe dispersal-like behaviour and an increased sensitivity to resource availability in our selection lines, which may be a response to selection, or alternatively may be due to epigenetic changes, provoked by prolonged resource limitation, that have persisted across many cell generations. Different clinical strategies may be needed depending on whether or not tumour progression is due to natural selection. This study highlights the effectiveness of experimental evolution approaches in cancer cell populations and demonstrates how simple model systems might enable us to observe and measure key selective drivers of clinically important traits.
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Affiliation(s)
- Tiffany B Taylor
- School of Biological Sciences, University of Reading, Whiteknights, Reading, RG6 6AH, UK. .,Milner Centre for Evolution and Department of Biology and Biochemistry, University of Bath, Claverton Down Road, Bath, BA2 7AY, UK.
| | - Anastasia V Wass
- School of Biological Sciences, University of Reading, Whiteknights, Reading, RG6 6AH, UK
| | - Louise J Johnson
- School of Biological Sciences, University of Reading, Whiteknights, Reading, RG6 6AH, UK
| | - Phil Dash
- School of Biological Sciences, University of Reading, Whiteknights, Reading, RG6 6AH, UK
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13
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Bahar E, Kim H, Yoon H. ER Stress-Mediated Signaling: Action Potential and Ca(2+) as Key Players. Int J Mol Sci 2016; 17:ijms17091558. [PMID: 27649160 PMCID: PMC5037829 DOI: 10.3390/ijms17091558] [Citation(s) in RCA: 149] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 09/06/2016] [Accepted: 09/09/2016] [Indexed: 01/24/2023] Open
Abstract
The proper functioning of the endoplasmic reticulum (ER) is crucial for multiple cellular activities and survival. Disturbances in the normal ER functions lead to the accumulation and aggregation of unfolded proteins, which initiates an adaptive response, the unfolded protein response (UPR), in order to regain normal ER functions. Failure to activate the adaptive response initiates the process of programmed cell death or apoptosis. Apoptosis plays an important role in cell elimination, which is essential for embryogenesis, development, and tissue homeostasis. Impaired apoptosis can lead to the development of various pathological conditions, such as neurodegenerative and autoimmune diseases, cancer, or acquired immune deficiency syndrome (AIDS). Calcium (Ca(2+)) is one of the key regulators of cell survival and it can induce ER stress-mediated apoptosis in response to various conditions. Ca(2+) regulates cell death both at the early and late stages of apoptosis. Severe Ca(2+) dysregulation can promote cell death through apoptosis. Action potential, an electrical signal transmitted along the neurons and muscle fibers, is important for conveying information to, from, and within the brain. Upon the initiation of the action potential, increased levels of cytosolic Ca(2+) (depolarization) lead to the activation of the ER stress response involved in the initiation of apoptosis. In this review, we discuss the involvement of Ca(2+) and action potential in ER stress-mediated apoptosis.
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Affiliation(s)
- Entaz Bahar
- College of Pharmacy, Research Institute of Pharmaceutical Sciences, Gyeongsang National University, Jinju 52828, Gyeongnam, Korea.
| | - Hyongsuk Kim
- Department of Electronics Engineering, Chonbuk National University, Jeonju 54896, Jeonbuk, Korea.
| | - Hyonok Yoon
- College of Pharmacy, Research Institute of Pharmaceutical Sciences, Gyeongsang National University, Jinju 52828, Gyeongnam, Korea.
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14
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van Niekerk G, Loos B, Nell T, Engelbrecht AM. Cancer tolerance, resistance, pathogenicity and virulence: deconstructing the disease state. Future Oncol 2016; 12:1369-80. [DOI: 10.2217/fon-2015-0024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Immunologists have recently taken note of the fact that a host not only resists infection, but also exhibits a capacity to manage the pathology associated with such infection – a concept referred to as tolerance. Here we explore how the tolerance/resistance (T/R) framework can be implemented within an oncological context and explore a number of implications. In particular, the T/R framework distinguishes between pathology manifesting from extensive tumor burden, versus cancers intrinsically expressing a more pathogenic phenotype. Consequently, the T/R framework provides novel methodology in studying the nature of cancer pathology and for marker identification. Additionally, this framework may aid in redefining the therapeutic end point under suitable circumstances: establishing cancer as a chronic, manageable disease.
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Affiliation(s)
- Gustav van Niekerk
- Department of Physiological Sciences, Private Bag X1, Matieland, Stellenbosch 7600, South Africa
| | - Benjamin Loos
- Department of Physiological Sciences, Private Bag X1, Matieland, Stellenbosch 7600, South Africa
| | - Theo Nell
- Department of Physiological Sciences, Private Bag X1, Matieland, Stellenbosch 7600, South Africa
| | - Anna-Mart Engelbrecht
- Department of Physiological Sciences, Private Bag X1, Matieland, Stellenbosch 7600, South Africa
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15
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Wang G, Chen L, Yu B, Zellmer L, Xu N, Liao DJ. Learning about the Importance of Mutation Prevention from Curable Cancers and Benign Tumors. J Cancer 2016; 7:436-45. [PMID: 26918057 PMCID: PMC4749364 DOI: 10.7150/jca.13832] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2015] [Accepted: 12/03/2015] [Indexed: 01/08/2023] Open
Abstract
Some cancers can be cured by chemotherapy or radiotherapy, presumably because they are derived from those cell types that not only can die easily but also have already been equipped with mobility and adaptability, which would later allow the cancers to metastasize without the acquisition of additional mutations. From a viewpoint of biological dispersal, invasive and metastatic cells may, among other possibilities, have been initial losers in the competition for resources with other cancer cells in the same primary tumor and thus have had to look for new habitats in order to survive. If this is really the case, manipulation of their ecosystems, such as by slightly ameliorating their hardship, may prevent metastasis. Since new mutations may occur, especially during and after therapy, to drive progression of cancer cells to metastasis and therapy-resistance, preventing new mutations from occurring should be a key principle for the development of new anticancer drugs. Such new drugs should be able to kill cancer cells very quickly without leaving the surviving cells enough time to develop new mutations and select resistant or metastatic clones. This principle questions the traditional use and the future development of genotoxic drugs for cancer therapy.
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Affiliation(s)
- Gangshi Wang
- 1. Department of Geriatric Gastroenterology, Chinese PLA General Hospital, Beijing 100853, P.R. China
| | - Lichan Chen
- 2. Hormel Institute, University of Minnesota, Austin, MN 55912, USA
| | - Baofa Yu
- 3. Beijing Baofa Cancer Hospital, Shahe Wangzhuang Gong Ye Yuan, Chang Pin Qu, Beijing 102206, P.R. China
| | - Lucas Zellmer
- 2. Hormel Institute, University of Minnesota, Austin, MN 55912, USA
| | - Ningzhi Xu
- 4. Laboratory of Cell and Molecular Biology, Cancer Institute, Chinese Academy of Medical Science, Beijing 100021, P.R. China
| | - D Joshua Liao
- 5. D. Joshua Liao, Clinical Research Center, Guizhou Medical University Hospital, Guizhou, Guiyang 550004, P.R. China
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16
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Liu B, Ezeogu L, Zellmer L, Yu B, Xu N, Joshua Liao D. Protecting the normal in order to better kill the cancer. Cancer Med 2015; 4:1394-403. [PMID: 26177855 PMCID: PMC4567024 DOI: 10.1002/cam4.488] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Revised: 05/21/2015] [Accepted: 05/27/2015] [Indexed: 12/23/2022] Open
Abstract
Chemotherapy is the only option for oncologists when a cancer has widely spread to different body sites. However, almost all currently available chemotherapeutic drugs will eventually encounter resistance after their initial positive effect, mainly because cancer cells develop genetic alterations, collectively coined herein as mutations, to adapt to the therapy. Some patients may still respond to a second chemo drug, but few cases respond to a third one. Since it takes time for cancer cells to develop new mutations and then select those life-sustaining ones via clonal expansion, "run against time for mutations to emerge" should be a crucial principle for treatment of those currently incurable cancers. Since cancer cells constantly change to adapt to the therapy whereas normal cells are stable, it may be a better strategy to shift our focus from killing cancer cells per se to protecting normal cells from chemotherapeutic toxicity. This new strategy requires the development of new drugs that are nongenotoxic and can quickly, in just hours or days, kill cancer cells without leaving the still-alive cells with time to develop mutations, and that should have their toxicities confined to only one or few organs, so that specific protections can be developed and applied.
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Affiliation(s)
- Bingya Liu
- Shanghai Key Laboratory of Gastric Neoplasms, Ruijin Hospital, Shanghai Jiao Tong University School of MedicineShanghai, 200025, China
| | - Lewis Ezeogu
- Hormel Institute, University of MinnesotaAustin, Minnesota, 55912
| | - Lucas Zellmer
- Hormel Institute, University of MinnesotaAustin, Minnesota, 55912
| | - Baofa Yu
- Beijing Baofa Cancer Hospital, Shahe Wangzhuang Gong Ye YuanChang Pin Qu, Beijing, 102206, China
| | - Ningzhi Xu
- Laboratory of Cell and Molecular Biology, Cancer Institute, Chinese Academy of Medical ScienceBeijing, 100021, China
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17
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Arnal A, Ujvari B, Crespi B, Gatenby RA, Tissot T, Vittecoq M, Ewald PW, Casali A, Ducasse H, Jacqueline C, Missé D, Renaud F, Roche B, Thomas F. Evolutionary perspective of cancer: myth, metaphors, and reality. Evol Appl 2015; 8:541-4. [PMID: 26136820 PMCID: PMC4479510 DOI: 10.1111/eva.12265] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Accepted: 04/14/2015] [Indexed: 12/31/2022] Open
Abstract
The evolutionary perspective of cancer (which origins and dynamics result from evolutionary processes) has gained significant international recognition over the past decade and generated a wave of enthusiasm among researchers. In this context, several authors proposed that insights into evolutionary and adaptation dynamics of cancers can be gained by studying the evolutionary strategies of organisms. Although this reasoning is fundamentally correct, in our opinion, it contains a potential risk of excessive adaptationism, potentially leading to the suggestion of complex adaptations that are unlikely to evolve among cancerous cells. For example, the ability of recognizing related conspecifics and adjusting accordingly behaviors as in certain free-living species appears unlikely in cancer. Indeed, despite their rapid evolutionary rate, malignant cells are under selective pressures for their altered lifestyle for only few decades. In addition, even though cancer cells can theoretically display highly sophisticated adaptive responses, it would be crucial to determine the frequency of their occurrence in patients with cancer, before therapeutic applications can be considered. Scientists who try to explain oncogenesis will need in the future to critically evaluate the metaphorical comparison of selective processes affecting cancerous cells with those affecting organisms. This approach seems essential for the applications of evolutionary biology to understand the origin of cancers, with prophylactic and therapeutic applications.
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Affiliation(s)
- Audrey Arnal
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France
| | - Beata Ujvari
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University Waurn Ponds, Vic., Australia
| | - Bernard Crespi
- Department of Biological Sciences, Simon Fraser University Burnaby, BC, Canada
| | - Robert A Gatenby
- Department of Radiology, H. Lee Moffitt Cancer Center & Research Institute Tampa, FL, USA
| | - Tazzio Tissot
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France
| | - Marion Vittecoq
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France ; Centre de Recherche de la Tour du Valat, Arles France
| | - Paul W Ewald
- Department of Biology and the Program on Disease Evolution, University of Louisville Louisville, KY, USA
| | - Andreu Casali
- Institute for Research in Biomedicine (IRB Barcelona) Barcelona, Spain
| | - Hugo Ducasse
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France
| | - Camille Jacqueline
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France
| | - Dorothée Missé
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France
| | - François Renaud
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France
| | - Benjamin Roche
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France ; International Center for Mathematical and Computational Modelling of Complex Systems (UMI IRD/UPMC UMMISCO) Bondy Cedex, France
| | - Frédéric Thomas
- MIVEGEC, UMR IRD/CNRS/UM 5290 Montpellier Cedex 5, France ; CREEC Montpellier Cedex 5, France
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18
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Abstract
Subclonal cancer populations change spatially and temporally during the disease course. Studies are revealing branched evolutionary cancer growth with low-frequency driver events present in subpopulations of cells, providing escape mechanisms for targeted therapeutic approaches. Despite such complexity, evidence is emerging for parallel evolution of subclones, mediated through distinct somatic events converging on the same gene, signal transduction pathway, or protein complex in different subclones within the same tumor. Tumors may follow gradualist paths (microevolution) as well as major shifts in evolutionary trajectories (macroevolution). Although macroevolution has been subject to considerable controversy in post-Darwinian evolutionary theory, we review evidence that such nongradual, saltatory leaps, driven through chromosomal rearrangements or genome doubling, may be particularly relevant to tumor evolution. Adapting cancer care to the challenges imposed by tumor micro- and macroevolution and developing deeper insight into parallel evolutionary events may prove central to improving outcome and reducing drug development costs.
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Affiliation(s)
- Marco Gerlinger
- Cancer Research UK London Research Institute, London, United Kingdom WC2A 3LY;
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Abstract
Multiple subclonal populations of tumor cells can coexist within the same tumor. This intra-tumor heterogeneity will have clinical implications and it is therefore important to identify factors that drive or suppress such heterogeneous tumor progression. Evolutionary biology can provide important insights into this process. In particular, experimental evolution studies of microbial populations, which exist as clonal populations that can diversify into multiple subclones, have revealed important evolutionary processes driving heterogeneity within a population. There are transferrable lessons that can be learnt from these studies that will help us to understand the process of intra-tumor heterogeneity in the clinical setting. In this review, we summarize drivers of microbial diversity that have been identified, such as mutation rate and environmental influences, and discuss how knowledge gained from microbial experimental evolution studies may guide us to identify and understand important selective factors that promote intra-tumor heterogeneity. Furthermore, we discuss how these factors could be used to direct and optimize research efforts to improve patient care, focusing on therapeutic resistance. Finally, we emphasize the need for longitudinal studies to address the impact of these potential tumor heterogeneity-promoting factors on drug resistance, metastatic potential and clinical outcome.
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