Accumulation of Oncogenic Mutations During Progression from Healthy Tissue to Cancer.
Humans
Colorectal Neoplasms
/ genetics
Disease Progression
Mutation
Mathematical Concepts
Oncogenes
/ genetics
Models, Genetic
Leukemia, Myelogenous, Chronic, BCR-ABL Positive
/ genetics
Neoplasms
/ genetics
Carcinogenesis
/ genetics
Mutation Accumulation
Precancerous Conditions
/ genetics
Computer Simulation
Branching process
Cancer incidence
Cancer initiation
Driver mutations
Journal
Bulletin of mathematical biology
ISSN: 1522-9602
Titre abrégé: Bull Math Biol
Pays: United States
ID NLM: 0401404
Informations de publication
Date de publication:
29 Oct 2024
29 Oct 2024
Historique:
received:
18
02
2024
accepted:
14
10
2024
medline:
30
10
2024
pubmed:
30
10
2024
entrez:
30
10
2024
Statut:
epublish
Résumé
Cancers are typically fueled by sequential accumulation of driver mutations in a previously healthy cell. Some of these mutations, such as inactivation of the first copy of a tumor suppressor gene, can be neutral, and some, like those resulting in activation of oncogenes, may provide cells with a selective growth advantage. We study a multi-type branching process that starts with healthy tissue in homeostasis and models accumulation of neutral and advantageous mutations on the way to cancer. We provide results regarding the sizes of premalignant populations and the waiting times to the first cell with a particular combination of mutations, including the waiting time to malignancy. Finally, we apply our results to two specific biological settings: initiation of colorectal cancer and age incidence of chronic myeloid leukemia. Our model allows for any order of neutral and advantageous mutations and can be applied to other evolutionary settings.
Identifiants
pubmed: 39472320
doi: 10.1007/s11538-024-01372-3
pii: 10.1007/s11538-024-01372-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
142Subventions
Organisme : National Science Foundation
ID : DMS-2045166
Informations de copyright
© 2024. The Author(s).
Références
Ancarani LU, Gasaneo G (2009) Derivatives of any order of the gaussian hypergeometric function 2F1(a, b, c; z) with respect to the parameters a, b and c. J Phys A Math Theor 42(39):395208. https://doi.org/10.1088/1751-8113/42/39/395208
doi: 10.1088/1751-8113/42/39/395208
Armitage P, Doll R (1954) The age distribution of cancer and a multi-stage theory of carcinogenesis. Br J Cancer 8(1):1–12. https://doi.org/10.1038/bjc.1954.1
doi: 10.1038/bjc.1954.1
Avanzini S, Antal T (2019) Cancer recurrence times from a branching process model. PLoS Comput Biol 15(11):e1007423. https://doi.org/10.1371/journal.pcbi.1007423
doi: 10.1371/journal.pcbi.1007423
Bozic I, Antal T, Ohtsuki H, Carter H, Kim D, Chen S, Karchin R, Kinzler KW, Vogelstein B, Nowak MA (2010) Accumulation of driver and passenger mutations during tumor progression. Proc Natl Acad Sci USA 107(43):18545–18550. https://doi.org/10.1073/pnas.1010978107
doi: 10.1073/pnas.1010978107
Bozic I, Reiter JG, Allen B, Antal T, Chatterjee K, Shah P, Moon YS, Yaqubie A, Kelly N, Le DT, Lipson EJ, Chapman PB, Diaz Luis AJ, Vogelstein B, Nowak MA (2013) Evolutionary dynamics of cancer in response to targeted combination therapy. Elife 2:e00747. https://doi.org/10.7554/eLife.00747
doi: 10.7554/eLife.00747
Campbell F, Williams GT, Appleton MA, Dixon MF, Harris M, Williams ED (1996) Post-irradiation somatic mutation and clonal stabilisation time in the human colon. Gut 39
Deininger MW, Goldman JM, Melo JV (2000) The molecular biology of chronic myeloid leukemia. Blood 96(10):3343–3356. https://doi.org/10.1182/blood.V96.10.3343
doi: 10.1182/blood.V96.10.3343
DLMF (2022) Nist digital library of mathematical functions. Release 1.1.8 of 2022-12-15, http://dlmf.nist.gov/
Durrett R, Foo J, Leder K, Mayberry J, Michor F (2011) Intratumor heterogeneity in evolutionary models of tumor progression. Genetics 188(2):461–477. https://doi.org/10.1534/genetics.110.125724
doi: 10.1534/genetics.110.125724
Durrett R, Moseley S (2010) Evolution of resistance and progression to disease during clonal expansion of cancer. Theor Popul Biol 77(1):42–48. https://doi.org/10.1016/j.tpb.2009.10.008
doi: 10.1016/j.tpb.2009.10.008
Fearon ER (2011) Molecular genetics of colorectal cancer. Annu Rev Pathol 6:479–507. https://doi.org/10.1146/annurev-pathol-011110-130235
doi: 10.1146/annurev-pathol-011110-130235
Foo J, Leder K, Zhu J (2014) Escape times for branching processes with random mutational fitness effects. Stoch Process Their Appl 124(11):3661–3697. https://doi.org/10.1016/j.spa.2014.06.003
doi: 10.1016/j.spa.2014.06.003
Komarova NL, Wodarz D (2005) Drug resistance in cancer: principles of emergence and prevention. Proc Natl Acad Sci USA 102(27):9714–9719. https://doi.org/10.1073/pnas.0501870102
doi: 10.1073/pnas.0501870102
Lee-Six H, Øbro NF, Shepherd MS, Grossmann S, Dawson K, Belmonte M, Osborne RJ, Huntly BJ, Martincorena I, Anderson E, O’Neill L, Stratton MR, Laurenti E, Green AR, Kent DG, Campbell PJ (2018) Population dynamics of normal human blood inferred from somatic mutations. Nature 561
Meza R, Jeon J, Moolgavkar SH, Luebeck EG (2008) Age-specific incidence of cancer: phases, transitions, and biological implications. Proc Natl Acad Sci USA 105(42):16284–16289. https://doi.org/10.1073/pnas.0801151105
doi: 10.1073/pnas.0801151105
Michor F, Iwasa Y, Nowak MA (2006) The age incidence of chronic myeloid leukemia can be explained by a one-mutation model. Proc Natl Acad Sci USA 103(40):14931–14934. https://doi.org/10.1073/pnas.0607006103
doi: 10.1073/pnas.0607006103
Mitchell E, Chapman MS, Williams N, Dawson KJ, Mende N, Calderbank EF, Jung H, Mitchell T, Coorens TH, Spencer DH, Machado H, Lee-Six H, Davies M, Hayler D, Fabre MA, Mahbubani K, Abascal F, Cagan A, Vassiliou GS, Baxter J, Martincorena I, Stratton MR, Kent DG, Chatterjee K, Parsy KS, Green AR, Nangalia J, Laurenti E, Campbell PJ (2022) Clonal dynamics of haematopoiesis across the human lifespan. Nature 606
Morin PJ, Sparks AB, Korinek V, Barker N, Clevers H, Vogelstein B, Kinzler KW (1997) Activation of β-catenin-Tcf signaling in colon cancer by mutations in β-catenin or APC. Science 275(5307):1787–1790. https://doi.org/10.1126/science.275.5307.1787
doi: 10.1126/science.275.5307.1787
Nicholson AM, Olpe C, Hoyle A, Thorsen AS, Rus T, Colombé M, Brunton-Sim R, Kemp R, Marks K, Quirke P et al (2018) Fixation and spread of somatic mutations in adult human colonic epithelium. Cell Stem Cell 22(6):909–918. https://doi.org/10.1016/j.stem.2018.04.020
doi: 10.1016/j.stem.2018.04.020
Nicholson MD, Antal T (2019) Competing evolutionary paths in growing populations with applications to multidrug resistance. PLoS Comput Biol 15:1–25. https://doi.org/10.1371/journal.pcbi.1006866
doi: 10.1371/journal.pcbi.1006866
Nicholson MD, Cheek D, Antal T (2023) Sequential mutations in exponentially growing populations. PLoS Comput Biol 19(7):1–32. https://doi.org/10.1371/journal.pcbi.1011289
doi: 10.1371/journal.pcbi.1011289
Paterson C, Clevers H, Bozic I (2020) Mathematical model of colorectal cancer initiation. Proc Natl Acad Sci USA 117(34):20681–20688. https://doi.org/10.1073/pnas.2003771117
doi: 10.1073/pnas.2003771117
Potten CS, Booth C, Hargreaves D (2003) The small intestine as a model for evaluating adult tissue stem cell drug targets. Cell Prolif. https://doi.org/10.1046/j.1365-2184.2003.00264.x
doi: 10.1046/j.1365-2184.2003.00264.x
Snippert HJ, Schepers AG, Van Es JH, Simons BD, Clevers H (2014) Biased competition between Lgr5 intestinal stem cells driven by oncogenic mutation induces clonal expansion. EMBO Rep 15(1):62–69. https://doi.org/10.1002/embr.201337799
doi: 10.1002/embr.201337799
Tomasetti C, Marchionni L, Nowak MA, Parmigiani G, Vogelstein B (2015) Only three driver gene mutations are required for the development of lung and colorectal cancers. Proc Natl Acad Sci USA 112(1):118–123. https://doi.org/10.1073/pnas.1421839112
doi: 10.1073/pnas.1421839112
Vogelstein B, Kinzler KW (2004) Cancer genes and the pathways they control. Nat Med 10(8):789–799. https://doi.org/10.1038/nm1087
doi: 10.1038/nm1087
Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr, Kinzler KW (2013) Cancer genome landscapes. Science 339(6127):1546–1558. https://doi.org/10.1126/science.1235122
doi: 10.1126/science.1235122
Wang Y, Boland CR, Goel A, Wodarz D, Komarova NL (2022) Aspirin’s effect on kinetic parameters of cells contributes to its role in reducing incidence of advanced colorectal adenomas, shown by a multiscale computational study. Elife 11:e71953. https://doi.org/10.7554/eLife.71953
doi: 10.7554/eLife.71953
Zhang R, Ukogu OA, Bozic I (2023) Waiting times in a branching process model of colorectal cancer initiation. Theor Popul Biol 151:44–63. https://doi.org/10.1016/j.tpb.2023.04.001
doi: 10.1016/j.tpb.2023.04.001