1
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Cannataro VL, Glasmacher KA, Hampson CE. Mutations, substitutions, and selection: Linking mutagenic processes to cancer using evolutionary theory. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167268. [PMID: 38823460 DOI: 10.1016/j.bbadis.2024.167268] [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: 02/14/2024] [Revised: 04/25/2024] [Accepted: 05/25/2024] [Indexed: 06/03/2024]
Abstract
Cancers are the product of evolutionary events, where molecular variation occurs and accumulates in tissues and tumors. Sequencing of this molecular variation informs not only which variants are driving tumorigenesis, but also the mechanisms behind what is fueling mutagenesis. Both of these details are crucial for preventing premature deaths due to cancer, whether it is by targeting the variants driving the cancer phenotype or by measures to prevent exogenous mutations from contributing to somatic evolution. Here, we review tools to determine both molecular signatures and cancer drivers, and avenues by which these metrics may be linked.
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Affiliation(s)
| | - Kira A Glasmacher
- Emmanuel College, 400 Fenway, Boston, MA 02115, United States of America
| | - Caralynn E Hampson
- Emmanuel College, 400 Fenway, Boston, MA 02115, United States of America
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2
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Thakur A, Gizzio J, Levy RM. Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability. J Phys Chem B 2024; 128:1656-1667. [PMID: 38350894 PMCID: PMC10939730 DOI: 10.1021/acs.jpcb.3c08097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.
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Affiliation(s)
- Abhishek Thakur
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Joan Gizzio
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Ronald M Levy
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States
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3
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Cai X, Zhang J, Li L, Liu L, Tang M, Zhou X, Peng C, Li X, Chen X, Xu M, Zhang H, Wang J, Huang Y, Li T. Copy Number Alterations Predict Development of OSCC from Oral Leukoplakia. J Dent Res 2024; 103:138-146. [PMID: 38217281 DOI: 10.1177/00220345231217160] [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] [Indexed: 01/15/2024] Open
Abstract
Oral leukoplakia (OLK) is a common type of potentially malignant disorder. Early identification of the malignancy potential leads to a better management of OLK and prediction of development of oral squamous cell carcinoma (OSCC). However, there has been no effective biomarker to assess the risk of malignancy in OLK. Genomic copy number alteration (CNA) is a complex chromosomal structural variation in the genome and has been identified as a potential biomarker in multiple cancers. This study aimed to develop a predictive model for the malignant transformation risk of OLK by copy number analysis. A total of 431 OLK samples with long-term follow-up (median follow-up of 67 mo) from multiple academic centers were analyzed for CNAs. CNA events increased with the severity of hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia. More CNA events were present in patients with OLK who later developed OSCC than in those with OLK who did not. By multivariate Cox regression analysis, the OLK of the CNA scorehigh group showed an increased risk of malignant transformation than the CNA scorelow group (P < 0.001). A CNA score model was developed to accurately predict the prognosis (area under the receiver operating characteristic curve [AUC] = 0.879; 95% confidence interval [CI], 0.799-0.959) and was validated using data from 2 external centers (AUC = 0.836, 95% CI, 0.683-0.989; AUC = 0.876, 95% CI, 0.682-1.000), and all of them showed better prediction performances than histopathological grade in assessing the transformation risk of OLK. Furthermore, we performed CNA models among 4 subgroups of OLK with hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia and found that CNA score can accurately predict malignant transformation of different subgroups. CNA score may be a useful biomarker to predict malignant transformation of OLK. Subtyping of OLK by the CNA score could contribute to better management of OLK and predicting development of OSCC.
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Affiliation(s)
- X Cai
- Department of Oral Pathology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China
| | - J Zhang
- Department of Oral Pathology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China
| | - L Li
- Hunan Key Laboratory of Oral Health Research & Xiangya Stomatological Hospital & Xiangya School of Stomatology, Central South University, Changsha, Hunan, China
| | - L Liu
- Changping Laboratory, Beijing, China
| | - M Tang
- Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - X Zhou
- Department of Oral Pathology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China
| | - C Peng
- Department of Oral Pathology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China
| | - X Li
- Department of Periodontology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, China
| | - X Chen
- Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China
| | - M Xu
- Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China
| | - H Zhang
- Central Laboratory, Peking University School and Hospital of Stomatology, Beijing, China
| | - J Wang
- School of Life Sciences, Tsinghua University, Beijing, China, Tsinghua University, Beijing, China
| | - Y Huang
- Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- College of Chemistry and Molecular Engineering and Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China
| | - T Li
- Department of Oral Pathology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China
- Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China
- Laboratory of Oral Biomedicine, Henan University School of Stomatology, Kaifeng, Henan, China
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4
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Galtier N. Half a Century of Controversy: The Neutralist/Selectionist Debate in Molecular Evolution. Genome Biol Evol 2024; 16:evae003. [PMID: 38311843 PMCID: PMC10839204 DOI: 10.1093/gbe/evae003] [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] [Accepted: 01/01/2024] [Indexed: 02/06/2024] Open
Abstract
The neutral and nearly neutral theories, introduced more than 50 yr ago, have raised and still raise passionate discussion regarding the forces governing molecular evolution and their relative importance. The debate, initially focused on the amount of within-species polymorphism and constancy of the substitution rate, has spread, matured, and now underlies a wide range of topics and questions. The neutralist/selectionist controversy has structured the field and influences the way molecular evolutionary scientists conceive their research.
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Affiliation(s)
- Nicolas Galtier
- ISEM, CNRS, IRD, Université de Montpellier, Montpellier, France
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5
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Pradeu T, Daignan-Fornier B, Ewald A, Germain PL, Okasha S, Plutynski A, Benzekry S, Bertolaso M, Bissell M, Brown JS, Chin-Yee B, Chin-Yee I, Clevers H, Cognet L, Darrason M, Farge E, Feunteun J, Galon J, Giroux E, Green S, Gross F, Jaulin F, Knight R, Laconi E, Larmonier N, Maley C, Mantovani A, Moreau V, Nassoy P, Rondeau E, Santamaria D, Sawai CM, Seluanov A, Sepich-Poore GD, Sisirak V, Solary E, Yvonnet S, Laplane L. Reuniting philosophy and science to advance cancer research. Biol Rev Camb Philos Soc 2023; 98:1668-1686. [PMID: 37157910 PMCID: PMC10869205 DOI: 10.1111/brv.12971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 05/10/2023]
Abstract
Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.
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Affiliation(s)
- Thomas Pradeu
- CNRS UMR5164 ImmunoConcEpT, University of Bordeaux, 146 rue Leo Saignat, Bordeaux 33076, France
- CNRS UMR8590, Institut d’Histoire et Philosophie des Sciences et des Technique, University Paris I Panthéon-Sorbonne, 13 rue du Four, Paris 75006, France
| | - Bertrand Daignan-Fornier
- CNRS UMR 5095 Institut de Biochimie et Génétique Cellulaires, University of Bordeaux, 1 rue Camille St Saens, Bordeaux 33077, France
| | - Andrew Ewald
- Departments of Cell Biology and Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Pierre-Luc Germain
- Department of Health Sciences and Technology, Institute for Neurosciences, Eidgenössische Technische Hochschule (ETH) Zürich, Universitätstrasse 2, Zürich 8092, Switzerland
- Department of Molecular Life Sciences, Laboratory of Statistical Bioinformatics, Universität Zürich, Winterthurerstrasse 190, Zurich 8057, Switzerland
| | - Samir Okasha
- Department of Philosophy, University of Bristol, Cotham House, Bristol, BS6 6JL, UK
| | - Anya Plutynski
- Department of Philosophy, Washington University in St. Louis, and Associate with Division of Biology and Biomedical Sciences, St. Louis, MO 63105, USA
| | - Sébastien Benzekry
- Computational Pharmacology and Clinical Oncology (COMPO) Unit, Inria Sophia Antipolis-Méditerranée, Cancer Research Center of Marseille, Inserm UMR1068, CNRS UMR7258, Aix Marseille University UM105, 27, bd Jean Moulin, Marseille 13005, France
| | - Marta Bertolaso
- Research Unit of Philosophy of Science and Human Development, Università Campus Bio-Medico di Roma, Via Àlvaro del Portillo, 21-00128, Rome, Italy
- Centre for Cancer Biomarkers, University of Bergen, Bergen 5007, Norway
| | - Mina Bissell
- Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, CA 94720, USA
| | - Joel S. Brown
- Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Benjamin Chin-Yee
- Division of Hematology, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, 800 Commissioners Rd E, London, ON, Canada
- Rotman Institute of Philosophy, Western University, 1151 Richmond Street North, London, ON, Canada
| | - Ian Chin-Yee
- Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, 800 Commissioners Rd E, London, ON, Canada
| | - Hans Clevers
- Pharma, Research and Early Development (pRED) of F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, Basel 4070, Switzerland
- Oncode Institute, Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center, Uppsalalaan 8, Utrecht 3584 CT, The Netherlands
| | - Laurent Cognet
- CNRS UMR 5298, Laboratoire Photonique Numérique et Nanosciences, University of Bordeaux, Rue François Mitterrand, Talence 33400, France
| | - Marie Darrason
- Department of Pneumology and Thoracic Oncology, University Hospital of Lyon, 165 Chem. du Grand Revoyet, 69310 Pierre Bénite, Lyon, France
- Lyon Institute of Philosophical Research, Lyon 3 Jean Moulin University, 1 Av. des Frères Lumière, Lyon 69007, France
| | - Emmanuel Farge
- Mechanics and Genetics of Embryonic and Tumor Development group, Institut Curie, CNRS, UMR168, Inserm, Centre Origines et conditions d’apparition de la vie (OCAV) Paris Sciences Lettres Research University, Sorbonne University, Institut Curie, 11 rue Pierre et Marie Curie, Paris 75005, France
| | - Jean Feunteun
- INSERM U981, Gustave Roussy, 114 Rue Edouard Vaillant, Villejuif 94800, France
| | - Jérôme Galon
- INSERM UMRS1138, Integrative Cancer Immunology, Cordelier Research Center, Sorbonne Université, Université Paris Cité, 15 rue de l’École de Médecine, Paris 75006, France
| | - Elodie Giroux
- Lyon Institute of Philosophical Research, Lyon 3 Jean Moulin University, 1 Av. des Frères Lumière, Lyon 69007, France
| | - Sara Green
- Section for History and Philosophy of Science, Department of Science Education, University of Copenhagen, Rådmandsgade 64, Copenhagen 2200, Denmark
| | - Fridolin Gross
- CNRS UMR5164 ImmunoConcEpT, University of Bordeaux, 146 rue Leo Saignat, Bordeaux 33076, France
| | - Fanny Jaulin
- INSERM U1279, Gustave Roussy, 114 Rue Edouard Vaillant, Villejuif 94800, France
| | - Rob Knight
- Department of Bioengineering, University of California San Diego, 3223 Voigt Dr, La Jolla, CA 92093, USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Ezio Laconi
- Department of Biomedical Sciences, School of Medicine, University of Cagliari, Via Università 40, Cagliari 09124, Italy
| | - Nicolas Larmonier
- CNRS UMR5164 ImmunoConcEpT, University of Bordeaux, 146 rue Leo Saignat, Bordeaux 33076, France
| | - Carlo Maley
- Arizona Cancer Evolution Center, Arizona State University, 427 East Tyler Mall, Tempe, AZ 85287, USA
- School of Life Sciences, Arizona State University, 427 East Tyler Mall, Tempe, AZ 85287, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, 1001 S McAllister Ave, Tempe, AZ 85287, USA
- Biodesign Center for Mechanisms of Evolution, Arizona State University, 1001 S McAllister Ave, Tempe, AZ 85287, USA
- Center for Evolution and Medicine, Arizona State University, 427 East Tyler Mall, Tempe, AZ 85287, USA
| | - Alberto Mantovani
- Department of Biomedical Sciences, Humanitas University, 4 Via Rita Levi Montalcini, 20090 Pieve Emanuele, Milan, Italy
- Department of Immunology and Inflammation, Istituto Clinico Humanitas Humanitas Cancer Center (IRCCS) Humanitas Research Hospital, Via Manzoni 56, Rozzano, Milan 20089, Italy
- The William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Violaine Moreau
- INSERM UMR1312, Bordeaux Institute of Oncology (BRIC), University of Bordeaux, 146 Rue Léo Saignat, Bordeaux 33076, France
| | - Pierre Nassoy
- CNRS UMR 5298, Laboratoire Photonique Numérique et Nanosciences, University of Bordeaux, Rue François Mitterrand, Talence 33400, France
| | - Elena Rondeau
- INSERM U1111, ENS Lyon and Centre International de Recherche en Infectionlogie (CIRI), 46 Allée d’Italie, Lyon 69007, France
| | - David Santamaria
- Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, Consejo Superior de Investigaciones Científicas (CSIC)-University of Salamanca, Salamanca 37007, Spain
| | - Catherine M. Sawai
- INSERM UMR1312, Bordeaux Institute of Oncology (BRIC), University of Bordeaux, 146 Rue Léo Saignat, Bordeaux 33076, France
| | - Andrei Seluanov
- Department of Biology and Medicine, University of Rochester, Rochester, NY 14627, USA
| | | | - Vanja Sisirak
- CNRS UMR5164 ImmunoConcEpT, University of Bordeaux, 146 rue Leo Saignat, Bordeaux 33076, France
| | - Eric Solary
- INSERM U1287, Gustave Roussy, 114 Rue Edouard Vaillant, Villejuif 94800, France
- Département d’hématologie, Gustave Roussy, 114 Rue Edouard Vaillant, Villejuif 94800, France
- Université Paris-Saclay, Faculté de Médecine, 63 Rue Gabriel Péri, Le Kremlin-Bicêtre 94270, France
| | - Sarah Yvonnet
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3B, Copenhagen DK-2200, Denmark
| | - Lucie Laplane
- CNRS UMR8590, Institut d’Histoire et Philosophie des Sciences et des Technique, University Paris I Panthéon-Sorbonne, 13 rue du Four, Paris 75006, France
- INSERM U1287, Gustave Roussy, 114 Rue Edouard Vaillant, Villejuif 94800, France
- Center for Biology and Society, College of Liberal Arts and Sciences, Arizona State University, 1100 S McAllister Ave, Tempe, AZ 85281, USA
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6
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Zhu X, Zhao W, Zhou Z, Gu X. Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools. J Mol Evol 2023:10.1007/s00239-023-10117-0. [PMID: 37246992 DOI: 10.1007/s00239-023-10117-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 05/09/2023] [Indexed: 05/30/2023]
Abstract
Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies.
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Affiliation(s)
- Xunuo Zhu
- Innovation Institute for Artificial Intelligence in Medicine, Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Wenyi Zhao
- Innovation Institute for Artificial Intelligence in Medicine, Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Zhan Zhou
- Innovation Institute for Artificial Intelligence in Medicine, Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322000, China.
- Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, 310058, China.
| | - Xun Gu
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA, 50011, USA.
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7
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Mandell JD, Cannataro VL, Townsend JP. Estimation of Neutral Mutation Rates and Quantification of Somatic Variant Selection Using cancereffectsizeR. Cancer Res 2023; 83:500-505. [PMID: 36469362 PMCID: PMC9929515 DOI: 10.1158/0008-5472.can-22-1508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 10/11/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
Somatic nucleotide mutations can contribute to cancer cell survival, proliferation, and pathogenesis. Although research has focused on identifying which mutations are "drivers" versus "passengers," quantifying the proliferative effects of specific variants within clinically relevant contexts could reveal novel aspects of cancer biology. To enable researchers to estimate these cancer effects, we developed cancereffectsizeR, an R package that organizes somatic variant data, facilitates mutational signature analysis, calculates site-specific mutation rates, and tests models of selection. Built-in models support effect estimation from single nucleotides to genes. Users can also estimate epistatic effects between paired sets of variants, or design and test custom models. The utility of cancer effect was validated by showing in a pan-cancer dataset that somatic variants classified as likely pathogenic or pathogenic in ClinVar exhibit substantially higher effects than most other variants. Indeed, cancer effect was a better predictor of pathogenic status than variant prevalence or functional impact scores. In addition, the application of this approach toward pairwise epistasis in lung adenocarcinoma showed that driver mutations in BRAF, EGFR, or KRAS typically reduce selection for alterations in the other two genes. Companion reference data packages support analyses using the hg19 or hg38 human genome builds, and a reference data builder enables use with any species or custom genome build with available genomic and transcriptomic data. A reference manual, tutorial, and public source code repository are available at https://townsend-lab-yale.github.io/cancereffectsizeR. Comprehensive estimation of cancer effects of somatic mutations can provide insights into oncogenic trajectories, with implications for cancer prognosis and treatment. SIGNIFICANCE An R package provides streamlined, customizable estimation of underlying nucleotide mutation rates and of the oncogenic and epistatic effects of mutations in cancer cohorts.
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Affiliation(s)
- Jeffrey D. Mandell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut
| | | | - Jeffrey P. Townsend
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
- Genetics, Genomics, and Epigenetics Research Program, Yale Cancer Center, New Haven, Connecticut
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut
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8
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Evo-devo perspectives on cancer. Essays Biochem 2022; 66:797-815. [PMID: 36250956 DOI: 10.1042/ebc20220041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/22/2022] [Accepted: 09/26/2022] [Indexed: 12/13/2022]
Abstract
The integration of evolutionary and developmental approaches into the field of evolutionary developmental biology has opened new areas of inquiry- from understanding the evolution of development and its underlying genetic and molecular mechanisms to addressing the role of development in evolution. For the last several decades, the terms 'evolution' and 'development' have been increasingly linked to cancer, in many different frameworks and contexts. This mini-review, as part of a special issue on Evolutionary Developmental Biology, discusses the main areas in cancer research that have been addressed through the lenses of both evolutionary and developmental biology, though not always fully or explicitly integrated in an evo-devo framework. First, it briefly introduces the current views on carcinogenesis that invoke evolutionary and/or developmental perspectives. Then, it discusses the main mechanisms proposed to have specifically evolved to suppress cancer during the evolution of multicellularity. Lastly, it considers whether the evolution of multicellularity and development was shaped by the threat of cancer (a cancer-evo-devo perspective), and/or whether the evolution of developmental programs and life history traits can shape cancer resistance/risk in various lineages (an evo-devo-cancer perspective). A proper evolutionary developmental framework for cancer, both as a disease and in terms of its natural history (in the context of the evolution of multicellularity and development as well as life history traits), could bridge the currently disparate evolutionary and developmental perspectives and uncover aspects that will provide new insights for cancer prevention and treatment.
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9
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Cannataro VL, Kudalkar S, Dasari K, Gaffney SG, Lazowski HM, Jackson LK, Yildiz I, Das RK, Gould Rothberg BE, Anderson KS, Townsend JP. APOBEC mutagenesis and selection for NFE2L2 contribute to the origin of lung squamous-cell carcinoma. Lung Cancer 2022; 171:34-41. [PMID: 35872531 PMCID: PMC10126952 DOI: 10.1016/j.lungcan.2022.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/01/2022] [Accepted: 07/06/2022] [Indexed: 10/17/2022]
Abstract
Lung squamous-cell carcinoma originates as a consequence of oncogenic molecular variants arising from diverse mutagenic processes such as tobacco, defective homologous recombination, aging, and cytidine deamination by APOBEC proteins. Only some of the many variants generated by these processes actually contribute to tumorigenesis. Therefore, molecular investigation of mutagenic processes such as cytidine deamination by APOBEC should also determine whether the mutations produced by these processes contribute substantially to the growth and survival of cancer. Here, we determine the processes that gave rise to mutations of 681 lung squamous-cell carcinomas, and quantify the probability that each mutation was the product of each process. We then calculate the contribution of each mutation to increases in cellular proliferation and survival. We performed in vitro experiments to determine cytidine deamination activity of APOBEC3B against oligonucleotides corresponding with genomic sequences that give rise to variants of high cancer effect size. The largest APOBEC-related cancer effects are attributable to mutations in PIK3CA and NFE2L2. We demonstrate that APOBEC effectively deaminates NFE2L2 at the locations that confer high cancer effect. Overall, we demonstrate that APOBEC activity can lead to mutations in NFE2L2 that have large contributions to cancer cell growth and survival, and that NFE2L2 is an attractive potential target for therapeutic intervention.
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Affiliation(s)
| | | | | | - Stephen G Gaffney
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | | | | | - Isil Yildiz
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA; Department of Pathology, VACT Healthcare System, West Haven, CT, USA
| | - Rahul K Das
- Yale Cancer Center, Yale University, New Haven, CT, USA
| | | | - Karen S Anderson
- Department of Pharmacology, Yale University, New Haven, CT, USA; Yale Cancer Center, Yale University, New Haven, CT, USA; Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, USA
| | - Jeffrey P Townsend
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA; Yale Cancer Center, Yale University, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
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10
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Qing T, Mohsen H, Cannataro VL, Marczyk M, Rozenblit M, Foldi J, Murray M, Townsend JP, Kluger Y, Gerstein M, Pusztai L. Cancer Relevance of Human Genes. J Natl Cancer Inst 2022; 114:988-995. [PMID: 35417011 PMCID: PMC9275765 DOI: 10.1093/jnci/djac068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 01/03/2022] [Accepted: 03/29/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND We hypothesize that genes that directly or indirectly interact with core cancer genes (CCGs) in a comprehensive gene-gene interaction network may have functional importance in cancer. METHODS We categorized 12 767 human genes into CCGs (n = 468), 1 (n = 5467), 2 (n = 5573), 3 (n = 915), and more than 3 steps (n = 416) removed from the nearest CCG in the Search Tool for the Retrieval of Interacting Genes/Proteins network. We estimated cancer-relevant functional importance in these neighborhood categories using 1) gene dependency score, which reflects the effect of a gene on cell viability after knockdown; 2) somatic mutation frequency in The Cancer Genome Atlas; 3) effect size that estimates to what extent a mutation in a gene enhances cell survival; and 4) negative selection pressure of germline protein-truncating variants in healthy populations. RESULTS Cancer biology-related functional importance of genes decreases as their distance from the CCGs increases. Genes closer to cancer genes show greater connectedness in the network, have greater importance in maintaining cancer cell viability, are under greater negative germline selection pressure, and have higher somatic mutation frequency in cancer. Based on these 4 metrics, we provide cancer relevance annotation to known human genes. CONCLUSIONS A large number of human genes are connected to CCGs and could influence cancer biology to various extent when dysregulated; any given mutation may be functionally important in one but not in another individual depending on genomic context.
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Affiliation(s)
- Tao Qing
- Breast Medical Oncology, School of Medicine, Yale University, New Haven, CT, USA
| | - Hussein Mohsen
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
| | | | - Michal Marczyk
- Breast Medical Oncology, School of Medicine, Yale University, New Haven, CT, USA
- Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Mariya Rozenblit
- Breast Medical Oncology, School of Medicine, Yale University, New Haven, CT, USA
| | - Julia Foldi
- Breast Medical Oncology, School of Medicine, Yale University, New Haven, CT, USA
| | - Michael Murray
- Department of Genetics, Yale Center for Genomic Health, New Haven, CT, USA
| | - Jeffrey P Townsend
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Yuval Kluger
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
- Department of Pathology, School of Medicine, Yale University, New Haven, CT, USA
- Applied Mathematics Program, Yale University, New Haven, CT, USA
| | - Mark Gerstein
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, USA
- Department of Computer Science, Yale University, New Haven, CT, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT, USA
| | - Lajos Pusztai
- Breast Medical Oncology, School of Medicine, Yale University, New Haven, CT, USA
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11
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Cannataro VL, Mandell JD, Townsend JP. Attribution of Cancer Origins to Endogenous, Exogenous, and Preventable Mutational Processes. Mol Biol Evol 2022; 39:msac084. [PMID: 35580068 PMCID: PMC9113445 DOI: 10.1093/molbev/msac084] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Mutational processes in tumors create distinctive patterns of mutations, composed of neutral "passenger" mutations and oncogenic drivers that have quantifiable effects on the proliferation and survival of cancer cell lineages. Increases in proliferation and survival are mediated by natural selection, which can be quantified by comparing the frequency at which we detect substitutions to the frequency at which we expect to detect substitutions assuming neutrality. Most of the variants detectable with whole-exome sequencing in tumors are neutral or nearly neutral in effect, and thus the processes generating the majority of mutations may not be the primary sources of the tumorigenic mutations. Across 24 cancer types, we identify the contributions of mutational processes to each oncogenic variant and quantify the degree to which each process contributes to tumorigenesis. We demonstrate that the origination of variants driving melanomas and lung cancers is predominantly attributable to the preventable, exogenous mutational processes associated with ultraviolet light and tobacco exposure, respectively, whereas the origination of selected variants in gliomas and prostate adenocarcinomas is largely attributable to endogenous processes associated with aging. Preventable mutations associated with pathogen exposure and apolipoprotein B mRNA-editing enzyme activity account for a large proportion of the cancer effect within head-and-neck, bladder, cervical, and breast cancers. These attributions complement epidemiological approaches-revealing the burden of cancer driven by single-nucleotide variants caused by either endogenous or exogenous, nonpreventable, or preventable processes, and crucially inform public health strategies.
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Affiliation(s)
| | - Jeffrey D. Mandell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Jeffrey P. Townsend
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
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12
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DNA Methyltransferases and DNA Damage. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1389:349-361. [DOI: 10.1007/978-3-031-11454-0_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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13
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Dasari K, Somarelli JA, Kumar S, Townsend JP. The somatic molecular evolution of cancer: Mutation, selection, and epistasis. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 165:56-65. [PMID: 34364910 DOI: 10.1016/j.pbiomolbio.2021.08.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 07/30/2021] [Accepted: 08/03/2021] [Indexed: 12/17/2022]
Abstract
Cancer progression has been attributed to somatic changes in single-nucleotide variants, copy-number aberrations, loss of heterozygosity, chromosomal instability, epistatic interactions, and the tumor microenvironment. It is not entirely clear which of these changes are essential and which are ancillary to cancer. The dynamic nature of cancer evolution in a patient can be illuminated using several concepts and tools from classical evolutionary biology. Neutral mutation rates in cancer cells are calculable from genomic data such as synonymous mutations, and selective pressures are calculable from rates of fixation occurring beyond the expectation by neutral mutation and drift. However, these cancer effect sizes of mutations are complicated by epistatic interactions that can determine the likely sequence of gene mutations. In turn, longitudinal phylogenetic analyses of somatic cancer progression offer an opportunity to identify key moments in cancer evolution, relating the timing of driver mutations to corresponding landmarks in the clinical timeline. These analyses reveal temporal aspects of genetic and phenotypic change during tumorigenesis and across clinical timescales. Using a related framework, clonal deconvolution, physical locations of clones, and their phylogenetic relations can be used to infer tumor migration histories. Additionally, genetic interactions with the tumor microenvironment can be analyzed with longstanding approaches applied to organismal genotype-by-environment interactions. Fitness landscapes for cancer evolution relating to genotype, phenotype, and environment could enable more accurate, personalized therapeutic strategies. An understanding of the trajectories underlying the evolution of neoplasms, primary, and metastatic tumors promises fundamental advances toward accurate and personalized predictions of therapeutic response.
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Affiliation(s)
| | | | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, and Department of Biology, Temple University, Philadelphia, PA, 19122, USA
| | - Jeffrey P Townsend
- Yale College, New Haven, CT, USA; Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA; Yale Cancer Center, Yale University, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
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14
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Abstract
Our capacity to study individual cells has enabled a new level of resolution for understanding complex biological systems such as multicellular organisms or microbial communities. Not surprisingly, several methods have been developed in recent years with a formidable potential to investigate the somatic evolution of single cells in both healthy and pathological tissues. However, single-cell sequencing data can be quite noisy due to different technical biases, so inferences resulting from these new methods need to be carefully contrasted. Here, I introduce CellCoal, a software tool for the coalescent simulation of single-cell sequencing genotypes. CellCoal simulates the history of single-cell samples obtained from somatic cell populations with different demographic histories and produces single-nucleotide variants under a variety of mutation models, sequencing read counts, and genotype likelihoods, considering allelic imbalance, allelic dropout, amplification, and sequencing errors, typical of this type of data. CellCoal is a flexible tool that can be used to understand the implications of different somatic evolutionary processes at the single-cell level, and to benchmark dedicated bioinformatic tools for the analysis of single-cell sequencing data. CellCoal is available at https://github.com/dapogon/cellcoal.
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Affiliation(s)
- David Posada
- Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain.,Biomedical Research Center (CINBIO), University of Vigo, Vigo, Spain.,Galicia Sur Health Research Institute, Vigo, Spain
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15
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Gottlieb B, Trifiro M, Batist G. Why Tumor Genetic Heterogeneity May Require Rethinking Cancer Genesis and Treatment. Trends Cancer 2020; 7:400-409. [PMID: 33243702 DOI: 10.1016/j.trecan.2020.10.013] [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] [Received: 07/10/2019] [Revised: 10/21/2020] [Accepted: 10/29/2020] [Indexed: 12/26/2022]
Abstract
Tumor genetic heterogeneity, in which individual tumors contain both multiple variant cancer-associated and normal genes, has been widely reported, although its significance has yet to be fully understood. We propose a genetic heterogeneity-based selection-centric hypothesis in which genetic heterogeneity, caused by the temporary reduction of DNA repair efficiency, occurs very early in human development, resulting in a small minority of cells in normal tissues acquiring cancer-associated genes that remain dormant. Cancer develops when precancer cells are selected for by altered tissue microenvironments; similar scenarios occur with development of metastases and therapeutic resistance in established cancer. This suggests that a normal cell selection treatment approach based on preferentially selecting normal cells within tumors may be effective in treating cancer.
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Affiliation(s)
- Bruce Gottlieb
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada; Segal Cancer Center, Jewish General Hospital, Montreal, Quebec, Canada; Department of Human Genetics, McGill University, Montreal, Quebec, Canada; Department of Nursing, McGill University, Montreal, Quebec, Canada.
| | - Mark Trifiro
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada; Segal Cancer Center, Jewish General Hospital, Montreal, Quebec, Canada; Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - Gerald Batist
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada; Segal Cancer Center, Jewish General Hospital, Montreal, Quebec, Canada; Department of Medicine, McGill University, Montreal, Quebec, Canada; McGill Centre for Translational Research in Cancer, McGill University, Montreal, Quebec, Canada
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16
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Tsyvina V, Zelikovsky A, Snir S, Skums P. Inference of mutability landscapes of tumors from single cell sequencing data. PLoS Comput Biol 2020; 16:e1008454. [PMID: 33253159 PMCID: PMC7728263 DOI: 10.1371/journal.pcbi.1008454] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 12/10/2020] [Accepted: 10/20/2020] [Indexed: 11/18/2022] Open
Abstract
One of the hallmarks of cancer is the extremely high mutability and genetic instability of tumor cells. Inherent heterogeneity of intra-tumor populations manifests itself in high variability of clone instability rates. Analogously to fitness landscapes, the instability rates of clonal populations form their mutability landscapes. Here, we present MULAN (MUtability LANdscape inference), a maximum-likelihood computational framework for inference of mutation rates of individual cancer subclones using single-cell sequencing data. It utilizes the partial information about the orders of mutation events provided by cancer mutation trees and extends it by inferring full evolutionary history and mutability landscape of a tumor. Evaluation of mutation rates on the level of subclones rather than individual genes allows to capture the effects of genomic interactions and epistasis. We estimate the accuracy of our approach and demonstrate that it can be used to study the evolution of genetic instability and infer tumor evolutionary history from experimental data. MULAN is available at https://github.com/compbel/MULAN.
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Affiliation(s)
- Viachaslau Tsyvina
- Department of Computer Science, Georgia State University, Atlanta, Georgia, United States of America
| | - Alex Zelikovsky
- Department of Computer Science, Georgia State University, Atlanta, Georgia, United States of America
| | - Sagi Snir
- Department of Evolutionary and Environmental Biology, University of Haifa, Haifa, Israel
| | - Pavel Skums
- Department of Computer Science, Georgia State University, Atlanta, Georgia, United States of America
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17
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Liberles DA, Chang B, Geiler-Samerotte K, Goldman A, Hey J, Kaçar B, Meyer M, Murphy W, Posada D, Storfer A. Emerging Frontiers in the Study of Molecular Evolution. J Mol Evol 2020; 88:211-226. [PMID: 32060574 PMCID: PMC7386396 DOI: 10.1007/s00239-020-09932-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
A collection of the editors of Journal of Molecular Evolution have gotten together to pose a set of key challenges and future directions for the field of molecular evolution. Topics include challenges and new directions in prebiotic chemistry and the RNA world, reconstruction of early cellular genomes and proteins, macromolecular and functional evolution, evolutionary cell biology, genome evolution, molecular evolutionary ecology, viral phylodynamics, theoretical population genomics, somatic cell molecular evolution, and directed evolution. While our effort is not meant to be exhaustive, it reflects research questions and problems in the field of molecular evolution that are exciting to our editors.
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Affiliation(s)
- David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA.
| | - Belinda Chang
- Department of Ecology and Evolutionary Biology and Department of Cell and Systems Biology, University of Toronto, 25 Harbord Street, Toronto, ON, M5S 3G5, Canada
| | - Kerry Geiler-Samerotte
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA
| | - Aaron Goldman
- Department of Biology, Oberlin College and Conservatory, K123 Science Center, 119 Woodland Street, Oberlin, OH, 44074, USA
| | - Jody Hey
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA
| | - Betül Kaçar
- Department of Molecular and Cell Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Michelle Meyer
- Department of Biology, Boston College, Chestnut Hill, MA, 02467, USA
| | - William Murphy
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, 77843, USA
| | - David Posada
- Biomedical Research Center (CINBIO), University of Vigo, Vigo, Spain
| | - Andrew Storfer
- School of Biological Sciences, Washington State University, Pullman, WA, 99164, USA
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18
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Somarelli JA, Gardner H, Cannataro VL, Gunady EF, Boddy AM, Johnson NA, Fisk JN, Gaffney SG, Chuang JH, Li S, Ciccarelli FD, Panchenko AR, Megquier K, Kumar S, Dornburg A, DeGregori J, Townsend JP. Molecular Biology and Evolution of Cancer: From Discovery to Action. Mol Biol Evol 2020; 37:320-326. [PMID: 31642480 PMCID: PMC6993850 DOI: 10.1093/molbev/msz242] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Cancer progression is an evolutionary process. During this process, evolving cancer cell populations encounter restrictive ecological niches within the body, such as the primary tumor, circulatory system, and diverse metastatic sites. Efforts to prevent or delay cancer evolution-and progression-require a deep understanding of the underlying molecular evolutionary processes. Herein we discuss a suite of concepts and tools from evolutionary and ecological theory that can inform cancer biology in new and meaningful ways. We also highlight current challenges to applying these concepts, and propose ways in which incorporating these concepts could identify new therapeutic modes and vulnerabilities in cancer.
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Affiliation(s)
- Jason A Somarelli
- Department of Medicine, Duke University Medical Center, Durham, NC
- Duke Cancer Institute, Duke University Medical Center, Durham, NC
| | - Heather Gardner
- Sackler School of Graduate Biomedical Sciences, Tufts University, Medford, MA
| | | | - Ella F Gunady
- Department of Medicine, Duke University Medical Center, Durham, NC
| | - Amy M Boddy
- Department of Anthropology, University of California, Santa Barbara, CA
| | | | | | - Stephen G Gaffney
- Department of Biostatistics, Yale School of Public Health, New Haven, CT
| | | | - Sheng Li
- The Jackson Laboratory for Genomic Medicine, Farmington, CT
| | - Francesca D Ciccarelli
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London, United Kingdom
- King’s College London, London, United Kingdom
| | - Anna R Panchenko
- Department of Pathology and Molecular Medicine, School of Medicine, Queen’s University, Kingston, ON, Canada
- Ontario Institute of Cancer Research, Toronto, ON, Canada
| | - Kate Megquier
- Broad Institute, Massachusettes Institute of Technology and Harvard University
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, and Department of Biology, Temple University, Philadelphia, PA
| | - Alex Dornburg
- North Carolina Museum of Natural Sciences, Raleigh, NC
| | - James DeGregori
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Jeffrey P Townsend
- Department of Biostatistics, Yale School of Public Health, New Haven, CT
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT
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19
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Chen B, Shi Z, Chen Q, Shen X, Shibata D, Wen H, Wu CI. Tumorigenesis as the Paradigm of Quasi-neutral Molecular Evolution. Mol Biol Evol 2020; 36:1430-1441. [PMID: 30912799 DOI: 10.1093/molbev/msz075] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
In the absence of both positive and negative selections, coding sequences evolve at a neutral rate (R = 1). Such a high genomic rate is generally not achievable due to the prevalence of negative selection against codon substitutions. Remarkably, somatic evolution exhibits the seemingly neutral rate R ∼ 1 across normal and cancerous tissues. Nevertheless, R ∼ 1 may also mean that positive and negative selections are both strong, but equal in intensity. We refer to this regime as quasi-neutral. Indeed, individual genes in cancer cells often evolve at a much higher, or lower, rate than R ∼ 1. Here, we show that 1) quasi-neutrality is much more likely when populations are small (N < 50); 2) stem-cell populations in single normal tissue niches, from which tumors likely emerge, have a small N (usually <50) but selection at this stage is measurable and strong; 3) when N dips below 50, selection efficacy decreases precipitously; and 4) notably, N is smaller in the stem-cell niche of the small intestine than in the colon. Hence, the ∼70-fold higher rate of phenotypic evolution (observed as cancer risk) in the latter can be explained by the greater efficacy of selection, which then leads to the fixation of more advantageous and fewer deleterious mutations in colon cancers. In conclusion, quasi-neutral evolution sheds a new light on a general evolutionary principle that helps to explain aspects of cancer evolution.
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Affiliation(s)
- Bingjie Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Zongkun Shi
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Qingjian Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Xu Shen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Darryl Shibata
- Department of Pathology, Keck School of Medicine of the University of Southern California, Los Angeles, CA
| | - Haijun Wen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Chung-I Wu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.,CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,Department of Ecology and Evolution, University of Chicago, Chicago, IL
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20
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Affiliation(s)
- Vincent L. Cannataro
- Department of Biostatistics, Yale University, New Haven, Connecticut, United States of America
| | - Jeffrey P. Townsend
- Department of Biostatistics, Yale University, New Haven, Connecticut, United States of America
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America
- * E-mail:
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