1
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Xiang Z, Liu Z, Dinh KN. Inference of chromosome selection parameters and missegregation rate in cancer from DNA-sequencing data. Sci Rep 2024; 14:17699. [PMID: 39085295 PMCID: PMC11291923 DOI: 10.1038/s41598-024-67842-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 07/16/2024] [Indexed: 08/02/2024] Open
Abstract
Aneuploidy is frequently observed in cancers and has been linked to poor patient outcome. Analysis of aneuploidy in DNA-sequencing (DNA-seq) data necessitates untangling the effects of the Copy Number Aberration (CNA) occurrence rates and the selection coefficients that act upon the resulting karyotypes. We introduce a parameter inference algorithm that takes advantage of both bulk and single-cell DNA-seq cohorts. The method is based on Approximate Bayesian Computation (ABC) and utilizes CINner, our recently introduced simulation algorithm of chromosomal instability in cancer. We examine three groups of statistics to summarize the data in the ABC routine: (A) Copy Number-based measures, (B) phylogeny tip statistics, and (C) phylogeny balance indices. Using these statistics, our method can recover both the CNA probabilities and selection parameters from ground truth data, and performs well even for data cohorts of relatively small sizes. We find that only statistics in groups A and C are well-suited for identifying CNA probabilities, and only group A carries the signals for estimating selection parameters. Moreover, the low number of CNA events at large scale compared to cell counts in single-cell samples means that statistics in group B cannot be estimated accurately using phylogeny reconstruction algorithms at the chromosome level. As data from both bulk and single-cell DNA-sequencing techniques becomes increasingly available, our inference framework promises to facilitate the analysis of distinct cancer types, differentiation between selection and neutral drift, and prediction of cancer clonal dynamics.
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Affiliation(s)
- Zijin Xiang
- Irving Institute for Cancer Dynamics and Department of Statistics, Columbia University, New York, NY, USA
| | - Zhihan Liu
- Irving Institute for Cancer Dynamics and Department of Statistics, Columbia University, New York, NY, USA
| | - Khanh N Dinh
- Irving Institute for Cancer Dynamics and Department of Statistics, Columbia University, New York, NY, USA.
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2
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Hosea R, Duan W, Meliala ITS, Li W, Wei M, Hillary S, Zhao H, Miyagishi M, Wu S, Kasim V. YY2/BUB3 Axis promotes SAC Hyperactivation and Inhibits Colorectal Cancer Progression via Regulating Chromosomal Instability. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308690. [PMID: 38682484 PMCID: PMC11234461 DOI: 10.1002/advs.202308690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 03/08/2024] [Indexed: 05/01/2024]
Abstract
Spindle assembly checkpoint (SAC) is a crucial safeguard mechanism of mitosis fidelity that ensures equal division of duplicated chromosomes to the two progeny cells. Impaired SAC can lead to chromosomal instability (CIN), a well-recognized hallmark of cancer that facilitates tumor progression; paradoxically, high CIN levels are associated with better therapeutic response and prognosis. However, the mechanism by which CIN determines tumor cell survival and therapeutic response remains poorly understood. Here, using a cross-omics approach, YY2 is identified as a mitotic regulator that promotes SAC activity by activating the transcription of budding uninhibited by benzimidazole 3 (BUB3), a component of SAC. While both conditions induce CIN, a defect in YY2/SAC activity enhances mitosis and tumor growth. Meanwhile, hyperactivation of SAC mediated by YY2/BUB3 triggers a delay in mitosis and suppresses growth. Furthermore, it is revealed that YY2/BUB3-mediated excessive CIN causes higher cell death rates and drug sensitivity, whereas residual tumor cells that survived DNA damage-based therapy have moderate CIN and increased drug resistance. These results provide insights into the role of SAC activity and CIN levels in influencing tumor cell survival and drug response, as well as suggest a novel anti-tumor therapeutic strategy that combines SAC activity modulators and DNA-damage agents.
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Affiliation(s)
- Rendy Hosea
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
| | - Wei Duan
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
| | - Ian Timothy Sembiring Meliala
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
| | - Wenfang Li
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
| | - Mankun Wei
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
| | - Sharon Hillary
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
| | - Hezhao Zhao
- Department of Gastrointestinal Surgery, Chongqing University Cancer HospitalChongqing UniversityChongqing400030P. R. China
| | - Makoto Miyagishi
- Life Science Innovation, School of Integrative and Global MajorsUniversity of TsukubaTsukubaIbaraki305‐0006Japan
| | - Shourong Wu
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
- Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer HospitalChongqing UniversityChongqing400030P. R. China
| | - Vivi Kasim
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of BioengineeringChongqing UniversityChongqing400045P. R. China
- The 111 Project Laboratory of Biomechanics and Tissue Repair, College of BioengineeringChongqing UniversityChongqing400044P. R. China
- Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer HospitalChongqing UniversityChongqing400030P. R. China
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3
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Dinh KN, Vázquez-García I, Chan A, Malhotra R, Weiner A, McPherson AW, Tavaré S. CINner: modeling and simulation of chromosomal instability in cancer at single-cell resolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.03.587939. [PMID: 38617259 PMCID: PMC11014621 DOI: 10.1101/2024.04.03.587939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types. We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) further uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions. Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.
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Affiliation(s)
- Khanh N. Dinh
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- Department of Statistics, Columbia University, New York, NY, USA
| | - Ignacio Vázquez-García
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew Chan
- Case Western Reserve University, Cleveland, OH, USA
| | - Rhea Malhotra
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Stanford University, Palo Alto, CA, USA
| | - Adam Weiner
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Andrew W. McPherson
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simon Tavaré
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- Department of Statistics, Columbia University, New York, NY, USA
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4
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Lynch A, Bradford S, Burkard ME. The reckoning of chromosomal instability: past, present, future. Chromosome Res 2024; 32:2. [PMID: 38367036 DOI: 10.1007/s10577-024-09746-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 01/11/2024] [Accepted: 01/27/2024] [Indexed: 02/19/2024]
Abstract
Quantitative measures of CIN are crucial to our understanding of its role in cancer. Technological advances have changed the way CIN is quantified, offering increased accuracy and insight. Here, we review measures of CIN through its rise as a field, discuss considerations for its measurement, and look forward to future quantification of CIN.
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Affiliation(s)
- Andrew Lynch
- UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA
- McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI, USA
- Division of Hematology/Oncology, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Shermineh Bradford
- UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA
- McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI, USA
- Division of Hematology/Oncology, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Mark E Burkard
- UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA.
- McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI, USA.
- Division of Hematology/Oncology, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
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5
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Lu B, Curtius K, Graham TA, Yang Z, Barnes CP. CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples. Genome Biol 2023; 24:144. [PMID: 37340508 PMCID: PMC10283241 DOI: 10.1186/s13059-023-02983-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 06/08/2023] [Indexed: 06/22/2023] Open
Abstract
Phylogenetic trees based on copy number profiles from multiple samples of a patient are helpful to understand cancer evolution. Here, we develop a new maximum likelihood method, CNETML, to infer phylogenies from such data. CNETML is the first program to jointly infer the tree topology, node ages, and mutation rates from total copy numbers of longitudinal samples. Our extensive simulations suggest CNETML performs well on copy numbers relative to ploidy and under slight violation of model assumptions. The application of CNETML to real data generates results consistent with previous discoveries and provides novel early copy number events for further investigation.
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Affiliation(s)
- Bingxin Lu
- Department of Cell and Developmental Biology, University College London, London, UK.
- UCL Genetics Institute, University College London, London, UK.
| | - Kit Curtius
- Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Trevor A Graham
- Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - Ziheng Yang
- Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Chris P Barnes
- Department of Cell and Developmental Biology, University College London, London, UK.
- UCL Genetics Institute, University College London, London, UK.
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6
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Bakhoum SF. Targeting the undruggable. Science 2023; 380:47. [PMID: 37023189 DOI: 10.1126/science.adg7671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
Journey through basic biology reveals a way to treat chromosomally unstable cancers.
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Affiliation(s)
- Samuel F Bakhoum
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center (MSKCC), New York, NY, USA
- Department of Radiation Oncology, MSKCC, New York, NY, USA
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7
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Ban I, Tomašić L, Trakala M, Tolić IM, Pavin N. Proliferative advantage of specific aneuploid cells drives evolution of tumor karyotypes. Biophys J 2023; 122:632-645. [PMID: 36654508 PMCID: PMC9989886 DOI: 10.1016/j.bpj.2023.01.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 12/19/2022] [Accepted: 01/13/2023] [Indexed: 01/19/2023] Open
Abstract
Most tumors have abnormal karyotypes, which arise from mistakes during mitotic division of healthy euploid cells and evolve through numerous complex mechanisms. In a recent mouse model with increased chromosome missegregation, chromosome gains dominate over losses both in pretumor and tumor tissues, whereas T-cell lymphomas are characterized by gains of chromosomes 14 and 15. However, the quantitative understanding of clonal selection leading to tumor karyotype evolution remains unknown. Here we show, by introducing a mathematical model based on a concept of a macro-karyotype, that tumor karyotypes can be explained by proliferation-driven evolution of aneuploid cells. In pretumor cells, increased apoptosis and slower proliferation of cells with monosomies lead to predominant chromosome gains over losses. Tumor karyotypes with gain of one chromosome can be explained by karyotype-dependent proliferation, whereas, for those with two chromosomes, an interplay with karyotype-dependent apoptosis is an additional possible pathway. Thus, evolution of tumor-specific karyotypes requires proliferative advantage of specific aneuploid karyotypes.
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Affiliation(s)
- Ivana Ban
- Department of Physics, Faculty of Science, University of Zagreb, Bijenička cesta 32, 10000 Zagreb, Croatia
| | - Lucija Tomašić
- Department of Physics, Faculty of Science, University of Zagreb, Bijenička cesta 32, 10000 Zagreb, Croatia
| | - Marianna Trakala
- David H. Koch Institute for Integrative Cancer Research, Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Iva M Tolić
- Division of Molecular Biology, Ruđer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia
| | - Nenad Pavin
- Department of Physics, Faculty of Science, University of Zagreb, Bijenička cesta 32, 10000 Zagreb, Croatia.
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8
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Intra-tumor heterogeneity, turnover rate and karyotype space shape susceptibility to missegregation-induced extinction. PLoS Comput Biol 2023; 19:e1010815. [PMID: 36689467 PMCID: PMC9917311 DOI: 10.1371/journal.pcbi.1010815] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 02/10/2023] [Accepted: 12/12/2022] [Indexed: 01/24/2023] Open
Abstract
The phenotypic efficacy of somatic copy number alterations (SCNAs) stems from their incidence per base pair of the genome, which is orders of magnitudes greater than that of point mutations. One mitotic event stands out in its potential to significantly change a cell's SCNA burden-a chromosome missegregation. A stochastic model of chromosome mis-segregations has been previously developed to describe the evolution of SCNAs of a single chromosome type. Building upon this work, we derive a general deterministic framework for modeling missegregations of multiple chromosome types. The framework offers flexibility to model intra-tumor heterogeneity in the SCNAs of all chromosomes, as well as in missegregation- and turnover rates. The model can be used to test how selection acts upon coexisting karyotypes over hundreds of generations. We use the model to calculate missegregation-induced population extinction (MIE) curves, that separate viable from non-viable populations as a function of their turnover- and missegregation rates. Turnover- and missegregation rates estimated from scRNA-seq data are then compared to theoretical predictions. We find convergence of theoretical and empirical results in both the location of MIE curves and the necessary conditions for MIE. When a dependency of missegregation rate on karyotype is introduced, karyotypes associated with low missegregation rates act as a stabilizing refuge, rendering MIE impossible unless turnover rates are exceedingly high. Intra-tumor heterogeneity, including heterogeneity in missegregation rates, increases as tumors progress, rendering MIE unlikely.
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9
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Bühler M, Fahrländer J, Sauter A, Becker M, Wistorf E, Steinfath M, Stolz A. GPER1 links estrogens to centrosome amplification and chromosomal instability in human colon cells. Life Sci Alliance 2022; 6:6/1/e202201499. [PMID: 36384894 PMCID: PMC9670797 DOI: 10.26508/lsa.202201499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 10/24/2022] [Accepted: 10/25/2022] [Indexed: 11/17/2022] Open
Abstract
The role of the alternate G protein-coupled estrogen receptor 1 (GPER1) in colorectal cancer (CRC) development and progression is unclear, not least because of conflicting clinical and experimental evidence for pro- and anti-tumorigenic activities. Here, we show that low concentrations of the estrogenic GPER1 ligands, 17β-estradiol, bisphenol A, and diethylstilbestrol cause the generation of lagging chromosomes in normal colon and CRC cell lines, which manifest in whole chromosomal instability and aneuploidy. Mechanistically, (xeno)estrogens triggered centrosome amplification by inducing centriole overduplication that leads to transient multipolar mitotic spindles, chromosome alignment defects, and mitotic laggards. Remarkably, we could demonstrate a significant role of estrogen-activated GPER1 in centrosome amplification and increased karyotype variability. Indeed, both gene-specific knockdown and inhibition of GPER1 effectively restored normal centrosome numbers and karyotype stability in cells exposed to 17β-estradiol, bisphenol A, or diethylstilbestrol. Thus, our results reveal a novel link between estrogen-activated GPER1 and the induction of key CRC-prone lesions, supporting a pivotal role of the alternate estrogen receptor in colon neoplastic transformation and tumor progression.
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Affiliation(s)
| | | | | | | | | | | | - Ailine Stolz
- Department of Experimental Toxicology and ZEBET, German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R), Berlin, Germany
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10
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Kaufmann TL, Petkovic M, Watkins TBK, Colliver EC, Laskina S, Thapa N, Minussi DC, Navin N, Swanton C, Van Loo P, Haase K, Tarabichi M, Schwarz RF. MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution. Genome Biol 2022; 23:241. [PMID: 36376909 PMCID: PMC9661799 DOI: 10.1186/s13059-022-02794-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 10/12/2022] [Indexed: 11/16/2022] Open
Abstract
Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.
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Affiliation(s)
- Tom L Kaufmann
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany.
- Department of Electrical Engineering & Computer Science, Technische Universität Berlin, Marchstr. 23, 10587, Berlin, Germany.
- BIFOLD, Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.
| | - Marina Petkovic
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany
- Department of Biology, Humboldt University of Berlin, Unter den Linden 6, 10099, Berlin, Germany
- Division of Oncology and Hematology, Department of Pediatrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | | | | | - Sofya Laskina
- Department of Mathematics and Computer Science, Free University of Berlin, Berlin, Germany
| | - Nisha Thapa
- UCL Medical School, University College London, London, UK
| | - Darlan C Minussi
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nicholas Navin
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Charles Swanton
- The Francis Crick Institute, London, UK
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Department of Medical Oncology, University College London Hospitals, London, UK
| | - Peter Van Loo
- The Francis Crick Institute, London, UK
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kerstin Haase
- Division of Oncology and Hematology, Department of Pediatrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Maxime Tarabichi
- The Francis Crick Institute, London, UK
- Institute for Interdisciplinary Research, Université Libre de Bruxelles, Brussels, Belgium
| | - Roland F Schwarz
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany.
- BIFOLD, Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.
- Institute for Computational Cancer Biology, Center for Integrated Oncology (CIO) and Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
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11
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Lynch AR, Arp NL, Zhou AS, Weaver BA, Burkard ME. Quantifying chromosomal instability from intratumoral karyotype diversity using agent-based modeling and Bayesian inference. eLife 2022; 11:e69799. [PMID: 35380536 PMCID: PMC9054132 DOI: 10.7554/elife.69799] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 04/01/2022] [Indexed: 12/03/2022] Open
Abstract
Chromosomal instability (CIN)-persistent chromosome gain or loss through abnormal mitotic segregation-is a hallmark of cancer that drives aneuploidy. Intrinsic chromosome mis-segregation rate, a measure of CIN, can inform prognosis and is a promising biomarker for response to anti-microtubule agents. However, existing methodologies to measure this rate are labor intensive, indirect, and confounded by selection against aneuploid cells, which reduces observable diversity. We developed a framework to measure CIN, accounting for karyotype selection, using simulations with various levels of CIN and models of selection. To identify the model parameters that best fit karyotype data from single-cell sequencing, we used approximate Bayesian computation to infer mis-segregation rates and karyotype selection. Experimental validation confirmed the extensive chromosome mis-segregation rates caused by the chemotherapy paclitaxel (18.5 ± 0.5/division). Extending this approach to clinical samples revealed that inferred rates fell within direct observations of cancer cell lines. This work provides the necessary framework to quantify CIN in human tumors and develop it as a predictive biomarker.
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Affiliation(s)
- Andrew R Lynch
- Carbone Cancer Center, University of Wisconsin-MadisonMadisonUnited States
- McArdle Laboratory for Cancer Research, University of Wisconsin-MadisonMadisonUnited States
| | - Nicholas L Arp
- Carbone Cancer Center, University of Wisconsin-MadisonMadisonUnited States
| | - Amber S Zhou
- Carbone Cancer Center, University of Wisconsin-MadisonMadisonUnited States
- McArdle Laboratory for Cancer Research, University of Wisconsin-MadisonMadisonUnited States
| | - Beth A Weaver
- Carbone Cancer Center, University of Wisconsin-MadisonMadisonUnited States
- McArdle Laboratory for Cancer Research, University of Wisconsin-MadisonMadisonUnited States
- Department of Cell and Regenerative Biology, University of WisconsinMadisonUnited States
| | - Mark E Burkard
- Carbone Cancer Center, University of Wisconsin-MadisonMadisonUnited States
- McArdle Laboratory for Cancer Research, University of Wisconsin-MadisonMadisonUnited States
- Division of Hematology Medical Oncology and Palliative Care, Department of Medicine University of WisconsinMadisonUnited States
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12
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Ortiz-González A, González-Pérez PP, Cárdenas-García M, Hernández-Linares MG. In silico Prediction on the PI3K/AKT/mTOR Pathway of the Antiproliferative Effect of O. joconostle in Breast Cancer Models. Cancer Inform 2022; 21:11769351221087028. [PMID: 35356703 PMCID: PMC8958723 DOI: 10.1177/11769351221087028] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 02/22/2022] [Indexed: 01/21/2023] Open
Abstract
The search for new cancer treatments from traditional medicine involves developing studies to understand at the molecular level different cell signaling pathways involved in cancer development. In this work, we present a model of the PI3K/Akt/mTOR pathway, which plays a key role in cell cycle regulation and is related to cell survival, proliferation, and growth in cancer, as well as resistance to antitumor therapies, so finding drugs that act on this pathway is ideal to propose a new adjuvant treatment. The aim of this work was to model, simulate and predict in silico using the Big Data-Cellulat platform the possible targets in the PI3K/Akt/mTOR pathway on which the Opuntia joconostle extract acts, as well as to indicate the concentration range to be used to find the mean lethal dose in in vitro experiments on breast cancer cells. The in silico results show that, in a cancer cell, the activation of JAK and STAT, as well as PI3K and Akt is related to the effect of cell proliferation, angiogenesis, and inhibition of apoptosis, and that the extract of O. joconostle has an antiproliferative effect on breast cancer cells by inhibiting cell proliferation, regulating the cell cycle and inhibiting apoptosis through this signaling pathway . In vitro it was demonstrated that the extract shows an antiproliferative effect, causing the arrest of cells in the G2/M phase of the cell cycle. Therefore, it is concluded that the use of in silico tools is a valuable method to perform virtual experiments and discover new treatments. The use of this type of model supports in vitro experimentation, reducing the costs and number of experiments in the real laboratory.
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Affiliation(s)
- Alejandra Ortiz-González
- Laboratorio de Fisiología Celular, Facultad de Medicina, Benemérita Universidad Autónoma de Puebla, Puebla, PUE, México
| | - Pedro Pablo González-Pérez
- Departamento de Matemáticas Aplicadas y Sistemas, Universidad Autónoma Metropolitana, Unidad Cuajimalpa, México
| | - Maura Cárdenas-García
- Laboratorio de Fisiología Celular, Facultad de Medicina, Benemérita Universidad Autónoma de Puebla, Puebla, PUE, México
| | - María Guadalupe Hernández-Linares
- Laboratorio de Investigación del Jardín Botánico, Centro de Química, Instituto de Ciencias, Benemérita Universidad Autónoma de Puebla, Puebla, PUE, México
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13
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Baudoin NC, Bloomfield M. Karyotype Aberrations in Action: The Evolution of Cancer Genomes and the Tumor Microenvironment. Genes (Basel) 2021; 12:558. [PMID: 33921421 PMCID: PMC8068843 DOI: 10.3390/genes12040558] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 03/27/2021] [Accepted: 04/06/2021] [Indexed: 12/12/2022] Open
Abstract
Cancer is a disease of cellular evolution. For this cellular evolution to take place, a population of cells must contain functional heterogeneity and an assessment of this heterogeneity in the form of natural selection. Cancer cells from advanced malignancies are genomically and functionally very different compared to the healthy cells from which they evolved. Genomic alterations include aneuploidy (numerical and structural changes in chromosome content) and polyploidy (e.g., whole genome doubling), which can have considerable effects on cell physiology and phenotype. Likewise, conditions in the tumor microenvironment are spatially heterogeneous and vastly different than in healthy tissues, resulting in a number of environmental niches that play important roles in driving the evolution of tumor cells. While a number of studies have documented abnormal conditions of the tumor microenvironment and the cellular consequences of aneuploidy and polyploidy, a thorough overview of the interplay between karyotypically abnormal cells and the tissue and tumor microenvironments is not available. Here, we examine the evidence for how this interaction may unfold during tumor evolution. We describe a bidirectional interplay in which aneuploid and polyploid cells alter and shape the microenvironment in which they and their progeny reside; in turn, this microenvironment modulates the rate of genesis for new karyotype aberrations and selects for cells that are most fit under a given condition. We conclude by discussing the importance of this interaction for tumor evolution and the possibility of leveraging our understanding of this interplay for cancer therapy.
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Affiliation(s)
- Nicolaas C. Baudoin
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Biological Sciences and Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA 24061, USA
| | - Mathew Bloomfield
- Department of Biological Sciences and Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA 24061, USA
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14
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Kimmel GJ, Dane M, Heiser LM, Altrock PM, Andor N. Integrating Mathematical Modeling with High-Throughput Imaging Explains How Polyploid Populations Behave in Nutrient-Sparse Environments. Cancer Res 2020; 80:5109-5120. [PMID: 32938640 DOI: 10.1158/0008-5472.can-20-1231] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 06/30/2020] [Accepted: 09/11/2020] [Indexed: 12/22/2022]
Abstract
Breast cancer progresses in a multistep process from primary tumor growth and stroma invasion to metastasis. Nutrient-limiting environments promote chemotaxis with aggressive morphologies characteristic of invasion. It is unknown how coexisting cells differ in their response to nutrient limitations and how this impacts invasion of the metapopulation as a whole. In this study, we integrate mathematical modeling with microenvironmental perturbation data to investigate invasion in nutrient-limiting environments inhabited by one or two cancer cell subpopulations. Subpopulations were defined by their energy efficiency and chemotactic ability. Invasion distance traveled by a homogeneous population was estimated. For heterogeneous populations, results suggest that an imbalance between nutrient efficacy and chemotactic superiority accelerates invasion. Such imbalance will spatially segregate the two populations and only one type will dominate at the invasion front. Only if these two phenotypes are balanced, the two subpopulations compete for the same space, which decelerates invasion. We investigate ploidy as a candidate biomarker of this phenotypic heterogeneity and discuss its potential to inform the dose of mTOR inhibitors (mTOR-I) that can inhibit chemotaxis just enough to facilitate such competition. SIGNIFICANCE: This study identifies the double-edged sword of high ploidy as a prerequisite to personalize combination therapies with cytotoxic drugs and inhibitors of signal transduction pathways such as mTOR-Is. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/22/5109/F1.large.jpg.
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Affiliation(s)
- Gregory J Kimmel
- Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, Florida
| | - Mark Dane
- Department of Biomedical Engineering, OHSU Center for Spatial Systems Biomedicine, Knight Cancer Institute, Oregon Health & Sciences University, Portland, Oregon
| | - Laura M Heiser
- Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, Florida.,Department of Biomedical Engineering, OHSU Center for Spatial Systems Biomedicine, Knight Cancer Institute, Oregon Health & Sciences University, Portland, Oregon
| | - Philipp M Altrock
- Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, Florida
| | - Noemi Andor
- Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, Florida.
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15
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Watkins TBK, Lim EL, Petkovic M, Elizalde S, Birkbak NJ, Wilson GA, Moore DA, Grönroos E, Rowan A, Dewhurst SM, Demeulemeester J, Dentro SC, Horswell S, Au L, Haase K, Escudero M, Rosenthal R, Bakir MA, Xu H, Litchfield K, Lu WT, Mourikis TP, Dietzen M, Spain L, Cresswell GD, Biswas D, Lamy P, Nordentoft I, Harbst K, Castro-Giner F, Yates LR, Caramia F, Jaulin F, Vicier C, Tomlinson IPM, Brastianos PK, Cho RJ, Bastian BC, Dyrskjøt L, Jönsson GB, Savas P, Loi S, Campbell PJ, Andre F, Luscombe NM, Steeghs N, Tjan-Heijnen VCG, Szallasi Z, Turajlic S, Jamal-Hanjani M, Van Loo P, Bakhoum SF, Schwarz RF, McGranahan N, Swanton C. Pervasive chromosomal instability and karyotype order in tumour evolution. Nature 2020; 587:126-132. [PMID: 32879494 PMCID: PMC7611706 DOI: 10.1038/s41586-020-2698-6] [Citation(s) in RCA: 198] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 06/24/2020] [Indexed: 12/13/2022]
Abstract
Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes1,2. The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution1,3,4. Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such as BCL9, MCL1, ARNT (also known as HIF1B), TERT and MYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompasses BCL9, MCL1 and ARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassing MYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.
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Affiliation(s)
- Thomas B K Watkins
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Emilia L Lim
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Marina Petkovic
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Sergi Elizalde
- Department of Mathematics, Dartmouth College, Hanover, NH, USA
| | - Nicolai J Birkbak
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
- Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark
| | - Gareth A Wilson
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - David A Moore
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Department of Cellular Pathology, University College London Hospitals, London, UK
| | - Eva Grönroos
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Andrew Rowan
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Sally M Dewhurst
- Laboratory for Cell Biology and Genetics, Rockefeller University, New York, NY, USA
| | - Jonas Demeulemeester
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
- Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Stefan C Dentro
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
- Oxford Big Data Institute, University of Oxford, Oxford, UK
- Experimental Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Stuart Horswell
- Department of Bioinformatics and Biostatistics, The Francis Crick Institute, London, UK
| | - Lewis Au
- Renal and Skin Units, The Royal Marsden Hospital NHS Foundation Trust, London, UK
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
| | - Kerstin Haase
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Mickael Escudero
- Department of Bioinformatics and Biostatistics, The Francis Crick Institute, London, UK
| | - Rachel Rosenthal
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Bill Lyons Informatics Centre, University College London Cancer Institute, London, UK
| | - Maise Al Bakir
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Hang Xu
- Stanford Cancer Institute, Stanford, CA, USA
| | - Kevin Litchfield
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Wei Ting Lu
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Thanos P Mourikis
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, University College London Cancer Institute, University College London, London, UK
| | - Michelle Dietzen
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, University College London Cancer Institute, University College London, London, UK
| | - Lavinia Spain
- Renal and Skin Units, The Royal Marsden Hospital NHS Foundation Trust, London, UK
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
| | - George D Cresswell
- Bioinformatics and Computational Biology Laboratory, The Francis Crick Institute, London, UK
| | - Dhruva Biswas
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Bill Lyons Informatics Centre, University College London Cancer Institute, London, UK
| | - Philippe Lamy
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Iver Nordentoft
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Katja Harbst
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
- Lund University Cancer Centre, Lund University, Lund, Sweden
| | - Francesc Castro-Giner
- Department of Biomedicine, Cancer Metastasis Laboratory, University of Basel and University Hospital Basel, Basel, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Lucy R Yates
- Wellcome Trust Sanger Institute, Hinxton, UK
- Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Franco Caramia
- Division of Research, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, Victoria, Australia
| | | | - Cécile Vicier
- Department of Medical Oncology, Institut Paoli-Calmettes, Aix-Marseille University, Marseille, France
| | - Ian P M Tomlinson
- Edinburgh Cancer Research Centre, IGMM, University of Edinburgh, Edinburgh, UK
| | - Priscilla K Brastianos
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Raymond J Cho
- Department of Dermatology, University of California, San Francisco, San Francisco, CA, USA
| | - Boris C Bastian
- Department of Dermatology, University of California, San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Lars Dyrskjøt
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Göran B Jönsson
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
- Lund University Cancer Centre, Lund University, Lund, Sweden
| | - Peter Savas
- Division of Research, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Sherene Loi
- Division of Research, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | | | - Fabrice Andre
- INSERM U981, PRISM Institute, Gustave Roussy, Villejuif, France
- Department of Medical Oncology, Gustave Roussy, Villejuif, France
- Medical School, Université Paris Saclay, Kremlin Bicetre, France
| | - Nicholas M Luscombe
- Bioinformatics and Computational Biology Laboratory, The Francis Crick Institute, London, UK
- UCL Genetics Institute, Department of Genetics, Evolution & Environment, University College London, London, UK
- Okinawa Institute of Science & Technology, Okinawa, Japan
| | - Neeltje Steeghs
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Vivianne C G Tjan-Heijnen
- Department of Medical Oncology, School of GROW, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Zoltan Szallasi
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
- 2nd Department of Pathology, SE-NAP Brain Metastasis Research Group, Semmelweis University, Budapest, Hungary
| | - Samra Turajlic
- Renal and Skin Units, The Royal Marsden Hospital NHS Foundation Trust, London, UK
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
| | - Mariam Jamal-Hanjani
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Department of Medical Oncology, University College London Hospitals, London, UK
| | - Peter Van Loo
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Samuel F Bakhoum
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Roland F Schwarz
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany.
- German Cancer Consortium (DKTK), partner site Berlin, Berlin, Germany.
- German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Nicholas McGranahan
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Genome Evolution Research Group, University College London Cancer Institute, University College London, London, UK.
| | - Charles Swanton
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Department of Medical Oncology, University College London Hospitals, London, UK.
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16
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Yan L, Zhao Z, Wang X, Lyu T, Li J, Qi Y, Wang X, Guo X. Short-term in vitro glutamine restriction differentially impacts the chromosomal stability of transformed and non-transformed cells. Mutagenesis 2020; 35:geaa026. [PMID: 33043986 DOI: 10.1093/mutage/geaa026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 09/10/2020] [Indexed: 11/13/2022] Open
Abstract
Glutamine (Gln) is a non-essential amino acid central for generating building blocks and cellular energy in tumours and rapidly proliferating non-transformed cells. However, the influence of Gln on regulating chromosomal stability of transformed and non-transformed cells remain poorly understand. We hypothesised that Gln is required for maintaining a homeostatic level of chromosomal stability. To this end, transformed cells HeLa and A375 and non-transformed cells NCM460 and HUVEC cells were intervened with varying concentrations of Gln (10, 1, 0.1 and 0.01 mM), with or without cisplatin (0.1 µg/ml), for 24 h. The cytokinesis-block micronucleus (MN) assay was used to determine chromosomal instability (CIN), the extent of which is reflected by the frequency of MN, nucleoplasmic bridge (NPB) and nuclear bud (NB). We demonstrated an unexpected decrease in the spontaneous rate of MN, but not NPB and NB, after Gln restriction in HeLa and A375 cells. Gln restriction reduced cisplatin-induced MN, but not NPB and NB, in HeLa and A375 cells. We further revealed that Gln restriction suppressed the proliferation of HeLa cells with high CIN induced by nocodazole, partially explaining why Gln restriction decreased the frequency of spontaneous and cisplatin-induced MN in transformed cells. In contrast, Gln restriction increased MN and NB, but not NPB, in NCM460 cells. In HUVEC cells, Gln restriction increased MN, NPB and NB. Meanwhile, Gln restriction sensitised NCM460 cells to cisplatin-induced genotoxicity. A similar but more pronounced pattern was observed in HUVEC cells. Collectively, these results suggest that the in vitro influences of Gln metabolism on CIN depend on cellular contexts: Transformed cells require high Gln to fine tune their CIN in an optimal rate to maximise genomic heterogeneity and fitness, whereas non-transformed cells need high Gln to prevent CIN.
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Affiliation(s)
- Ling Yan
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
| | - Ziru Zhao
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
| | - Xiaoran Wang
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
| | - Ting Lyu
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
| | - Jianfei Li
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
| | - Yanmei Qi
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
| | - Xu Wang
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
- Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Chenggong District, Kunming, Yunnan, China
- Yunnan Environmental Society, Chenggong District, Kunming, Yunnan, China
| | - Xihan Guo
- School of Life Sciences, Yunnan Normal University, Chenggong District, Kunming, Yunnan, China
- Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Chenggong District, Kunming, Yunnan, China
- Yunnan Environmental Society, Chenggong District, Kunming, Yunnan, China
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