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Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in Cancer Evolution

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Automated Reasoning for Systems Biology and Medicine

Part of the book series: Computational Biology ((COBO,volume 30))

Abstract

Cancer develops via the progressive accumulation of somatic mutations, which subvert the normal operation of the gene regulatory network of the cell. However, little is known about the order in which mutations are acquired in successful clones. A particular sequence of mutations may confer an early selective advantage to a clone by increasing survival or proliferation, or lead to negative selection by triggering cell death. The space of allowed sequences of mutations is therefore constrained by the gene regulatory network. Here, we introduce a methodology for the systematic exploration of the effect of every possible sequence of oncogenic mutations in a cancer cell modelled as a qualitative network. Our method uses attractor identification using binary decision diagrams and can be applied to both synchronous and asynchronous systems. We demonstrate our method using a recently developed model of ER-negative breast cancer. We show that there are differing levels of constraint in the order of mutations for different combinations of oncogenes, and that the effects of ErbB2/HER2 over-expression depend on the preceding mutations.

S. Woodhouse—Work done while author was a Post Doc Researcher at Microsoft Research Cambridge, UK.

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Notes

  1. 1.

    http://biomodelanalyzer.org/.

  2. 2.

    For simplicity, here we assume that all variables have the same range \(\{0,\ldots , N\}\). Our implementation supports individual ranges for variables.

  3. 3.

    https://github.com/Microsoft/BioModelAnalyzer.

  4. 4.

    Development builds of this interface can be accessed as a chatbot in Skype (https://join.skype.com/bot/711331aa-e775-49be-b99d-6c42fc25f6d2) or Telegram (https://telegram.me/BioModelAnalyzerBot).

References

  1. Ahmed Z, Benque D, Berezin S, Dahl ACE, Fisher J, Hall BA, Ishtiaq S, Nanavati J, Piterman N, Riechert M, Skoblov N (2017) Bringing LTL model checking to biologists. In: Bouajjani A, Monniaux D (eds) Verification, model checking, and abstract interpretation. Springer International Publishing, Cham, pp 1–13. https://doi.org/10.1007/978-3-319-52234-0_1

    Google Scholar 

  2. Arends JW (2000) Molecular interactions in the Vogelstein model of colorectal carcinoma. J Pathol 190(4):412–416. https://doi.org/10.1002/(SICI)1096-9896(200003)190:4 412::AID-PATH533 3.0.CO;2-P

  3. Aulmann S, Adler N, Rom J, Helmchen B, Schirmacher P, Sinn HP (2006) C-Myc amplifications in primary breast carcinomas and their local recurrences. J Clinic Pathol 59(4):424–428. https://doi.org/10.1136/jcp.2005.029264

    Article  Google Scholar 

  4. Autier P, Boniol M, La Vecchia C, LaVecchia C, Vatten L, Gavin A, HĂ©ry C, Heanue M (2010) Disparities in breast cancer mortality trends between 30 European countries: retrospective trend analysis of WHO mortality database. BMJ (Clinical research ed) 341:c3620. https://doi.org/10.1136/bmj.c3620

    Article  Google Scholar 

  5. Baca SC, Prandi D, Lawrence MS, Mosquera JM, Romanel A, Drier Y, Park K, Kitabayashi N, MacDonald TY, Ghandi M, Van Allen E, Kryukov GV, Sboner A, Theurillat JP, Soong TD, Nickerson E, Auclair D, Tewari A, Beltran H, Onofrio RC, Boysen G, Guiducci C, Barbieri CE, Cibulskis K, Sivachenko A, Carter SL, Saksena G, Voet D, Ramos AH, Winckler W, Cipicchio M, Ardlie K, Kantoff PW, Berger MF, Gabriel SB, Golub TR, Meyerson M, Lander ES, Elemento O, Getz G, Demichelis F, Rubin MA, Garraway LA (2013) Punctuated evolution of prostate cancer genomes. Cell 153(3):666–677. https://doi.org/10.1016/j.cell.2013.03.021

    Article  Google Scholar 

  6. Basanta D, Gatenby RA, Anderson ARA (2012) Exploiting evolution to treat drug resistance: combination therapy and the double bind. Molecu Pharmac 9(4):914–921. https://doi.org/10.1021/mp200458e

    Article  Google Scholar 

  7. Blagosklonny MV, An WG, Romanova LY, Trepel J, Fojo T, Neckers L (1998) p53 inhibits hypoxia-inducible factor-stimulated transcription. J Biol Chem 273(20):11995–8

    Article  Google Scholar 

  8. 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 LA, 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

  9. Bray F, McCarron P, Parkin DM (2004) The changing global patterns of female breast cancer incidence and mortality. Breast Cancer Res 6(6):229. https://doi.org/10.1186/bcr932

    Article  Google Scholar 

  10. van den Brink GR, Offerhaus GJ (2007) The morphogenetic code and colon cancer development. Cancer Cell 11(2):109–117. https://doi.org/10.1016/j.ccr.2007.01.003

    Article  Google Scholar 

  11. Bryant RE (1986) Graph-based algorithms for boolean function manipulation. IEEE Trans Comput 100(8):677–691. https://doi.org/10.1109/TC.1986.1676819

    Article  MATH  Google Scholar 

  12. Casás-Selves M, DeGregori J (2011) How cancer shapes evolution and how evolution shapes cancer. Evolut Educat Outreach 4(4):624–634. https://doi.org/10.1007/s12052-011-0373-y, NIHMS150003

    Google Scholar 

  13. Chen Y, Olopade OI (2008) MYC in breast tumor progression. Exp Rev Anticancer Ther 8(10):1689–1698. https://doi.org/10.1586/14737140.8.10.1689

    Article  Google Scholar 

  14. Chin L, Artandi SE, Shen Q, Tam A, Lee SL, Gottlieb GJ, Greider CW, DePinho RA (1999) P53 deficiency rescues the adverse effects of telomere loss and cooperates with telomere dysfunction to accelerate carcinogenesis. Cell 97(4):527–538. https://doi.org/10.1016/S0092-8674(00)80762-X

    Article  Google Scholar 

  15. Chong CR, Jänne PA (2013) The quest to overcome resistance to EGFR-targeted therapies in cancer. Nat Med 19(11):1389–400. https://doi.org/10.1038/nm.3388, NIHMS150003

    Article  Google Scholar 

  16. Chuang R, Hall BA, Benque D, Cook B, Ishtiaq S, Piterman N, Taylor A, Vardi M, Koschmieder S, Gottgens B, Fisher J (2015) Drug target optimization in chronic myeloid leukemia using innovative computational platform. Scientif Rep 5:8190. https://doi.org/10.1038/srep08190

    Article  Google Scholar 

  17. Claessen K, Fisher J, Ishtiaq S, Piterman N, Wang Q (2013) Model-checking signal transduction networks through decreasing reachability sets. In: Computer aided verification. Springer, pp 85–100

    Google Scholar 

  18. Cook B, Fisher J, Krepska E, Piterman N (2011) Proving stabilization of biological systems. VMCAI, Springer 11:134–149. https://doi.org/10.1007/978-3-642-18275-4_11

    Article  MathSciNet  MATH  Google Scholar 

  19. Corzo C, Corominas JM, Tusquets I, Salido M, Bellet M, Fabregat X, Serrano S, Solé F (2006) The myc oncogene in breast cancer progression: from benign epithelium to invasive carcinoma. Cancer Genet Cytogenet 165(2):151–156 https://doi.org/10.1016/j.cancergencyto.2005.08.013

    Article  Google Scholar 

  20. Crasta K, Ganem NJ, Dagher R, Lantermann AB, Ivanova EV, Pan Y, Nezi L, Protopopov A, Chowdhury D, Pellman D (2012) DNA breaks and chromosome pulverization from errors in mitosis. Nature 482(7383):53–58. https://doi.org/10.1038/nature10802

    Article  Google Scholar 

  21. Cui Y, Guo G (2016) Immunomodulatory function of the tumor suppressor p53 in host immune response and the tumor microenvironment. Int J Mol Sci 17(11). https://doi.org/10.3390/ijms17111942

    Article  Google Scholar 

  22. D’Antonio M, Tamayo P, Mesirov JP, Frazer KA (2016) Kataegis expression signature in breast cancer is associated with late onset, better prognosis, and higher HER2 levels. Cell Rep 16(3):672–683. https://doi.org/10.1016/j.celrep.2016.06.026

    Article  Google Scholar 

  23. Davis A, Gao R (1867) Navin N (2017) Tumor evolution: linear, branching, neutral or punctuated? Biochimica et Biophysica Acta Rev Cancer 2:151–161. https://doi.org/10.1016/j.bbcan.2017.01.003

    Article  Google Scholar 

  24. Ding L, Ley TJ, Larson DE, Miller CA, Koboldt DC, Welch JS, Ritchey JK, Young MA, Lamprecht T, McLellan MD, McMichael JF, Wallis JW, Lu C, Shen D, Harris CC, Dooling DJ, Fulton RS, Fulton LL, Chen K, Schmidt H, Kalicki-Veizer J, Magrini VJ, Cook L, McGrath SD, Vickery TL, Wendl MC, Heath S, Watson MA, Link DC, Tomasson MH, Shannon WD, Payton JE, Kulkarni S, Westervelt P, Walter MJ, Graubert TA, Mardis ER, Wilson RK, DiPersio JF (2012) Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature 481(7382):506–510. https://doi.org/10.1038/nature10738

    Article  Google Scholar 

  25. Evan GI, Wyllie AH, Gilbert CS, Littlewood TD, Land H, Brooks M, Waters CM, Penn LZ, Hancock DC (1992) Induction of apoptosis in fibroblasts by c-myc protein. Cell 69(1):119–28

    Article  Google Scholar 

  26. Fearon ER, Vogelstein B (1990) A genetic model for colorectal tumorigenesis. Cell 61(5):759–767. https://doi.org/10.1016/0092-8674(90)90186-I

    Article  Google Scholar 

  27. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D, Bray F (2015) Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 136(5):E359–E386, https://doi.org/10.1002/ijc.29210. arXiv:1011.1669v3

    Article  Google Scholar 

  28. Flanagan L, Van Weelden K, Ammerman C, Ethier SP, Welsh J (1999) SUM-159PT cells: a novel estrogen independent human breast cancer model system. Breast cancer research and treatment 58(3):193–204

    Article  Google Scholar 

  29. Gao R, Davis A, McDonald TO, Sei E, Shi X, Wang Y, Tsai PC, Casasent A, Waters J, Zhang H, Meric-Bernstam F, Michor F, Navin NE (2016) Punctuated copy number evolution and clonal stasis in triple-negative breast cancer. Nat Genet 48(10):1119–30. https://doi.org/10.1038/ng.3641, 15334406

    Article  Google Scholar 

  30. Garg A, Di Cara A, Xenarios I, Mendoza L, De Micheli G (2008) Synchronous versus asynchronous modeling of gene regulatory networks. Bioinformatics 24(17):1917–1925. https://doi.org/10.1093/bioinformatics/btn336

    Article  Google Scholar 

  31. Gray JW (2003) Evidence emerges for early metastasis and parallel evolution of primary and metastatic tumors. Cancer Cell 4(1):4–6. https://doi.org/10.1016/S1535-6108(03)00167-3

    Article  Google Scholar 

  32. Greaves M, Maley CC (2012) Clonal evolution in cancer. Nature 481(7381):306–13. https://doi.org/10.1038/nature10762

    Article  Google Scholar 

  33. Greenman CD, Pleasance ED, Newman S, Yang F, Fu B, Nik-Zainal S, Jones D, Lau KW, Carter N, Edwards PA, Futreal PA, Stratton MR, Campbell PJ (2012) Estimation of rearrangement phylogeny for cancer genomes. Genom Res 22(2):346–361. https://doi.org/10.1101/gr.118414.110

    Article  Google Scholar 

  34. Hanahan D, Weinberg RA (2011) Hallmarks of cancer: The next generation. Cell 144(5):646–674. https://doi.org/10.1016/j.cell.2011.02.013, 0208024

    Article  Google Scholar 

  35. Hollestelle A, Nagel JHA, Smid M, Lam S, Elstrodt F, Wasielewski M, Ng SS, French PJ, Peeters JK, Rozendaal MJ, Riaz M, Koopman DG, Ten Hagen TLM, De Leeuw BHCGM, Zwarthoff EC, Teunisse A, Van Der Spek PJ, Klijn JGM, Dinjens WNM, Ethier SP, Clevers H, Jochemsen AG, Den Bakker MA, Foekens JA, Martens JWM, Schutte M (2010) Distinct gene mutation profiles among luminal-type and basal-type breast cancer cell lines. Breast Cancer Res Treatm 121(1):53–64. https://doi.org/10.1007/s10549-009-0460-8

    Article  Google Scholar 

  36. Holliday DL, Speirs V (2011) Choosing the right cell line for breast cancer research. Breast cancer research : BCR 13:215. https://doi.org/10.1186/bcr2889

    Article  Google Scholar 

  37. Hruban RH, Goggins M, Parsons J, Kern SE (2000) Progression model for pancreatic cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 6(8):2969–72

    Google Scholar 

  38. Hurvitz S, Mead M (2015) Triple-negative breast cancer. Current Opinion in Obstetrics and Gynecology p 1, https://doi.org/10.1097/GCO.0000000000000239

  39. Independent UK Panel on Breast Cancer Screening (2012) The benefits and harms of breast cancer screening: an independent review. Lancet (London, England) 380(9855):1778–86. https://doi.org/10.1016/S0140-6736(12)61611-0

    Article  Google Scholar 

  40. Knuth DE (2009) The art of computer programming: bitwise tricks & techniques; Binary Decision Diagrams, vol 4, Fascicle 1. Addison-Wesley

    Google Scholar 

  41. Kuukasjärvi T, Karhu R, Tanner M, Kähkönen M, Schäffer A, Nupponen N, Pennanen S, Kallioniemi A, Kallioniemi OP, Isola J (1997) Genetic heterogeneity and clonal evolution underlying development of asynchronous metastasis in human breast cancer. Cancer Res 57(8):1597–604

    Google Scholar 

  42. Land H, Chen AC, Morgenstern JP, Parada LF, Weinberg RA (1986) Behavior of myc and ras oncogenes in transformation of rat embryo fibroblasts. Mol Cell Biol 6(6):1917–1925

    Article  Google Scholar 

  43. Lasfargues EY, Ozzello L (1958) Cultivation of human breast carcinomas. J Nat Cancer Institute 21(6):1131–47

    Google Scholar 

  44. Maley CC, Galipeau PC, Finley JC, Wongsurawat VJ, Li X, Sanchez CA, Paulson TG, Blount PL, Risques RA, Rabinovitch PS, Reid BJ (2006) Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nat Genet 38(4):468–73. https://doi.org/10.1038/ng1768

    Article  Google Scholar 

  45. Martincorena I, Roshan A, Gerstung M, Ellis P, Van Loo P, McLaren S, Wedge DC, Fullam A, Alexandrov LB, Tubio JM, Stebbings L, Menzies A, Widaa S, Stratton MR, Jones PH, Campbell PJ (2015) High burden and pervasive positive selection of somatic mutations in normal human skin (Supplement). Science 348(6237):880–886. https://doi.org/10.1126/science.aaa6806

    Article  Google Scholar 

  46. Murphy DJ, Junttila MR, Pouyet L, Karnezis A, Shchors K, Bui DA, Brown-Swigart L, Johnson L, Evan GI (2008) Distinct thresholds govern Myc’s biological output in vivo. Cancer cell 14(6):447–57. https://doi.org/10.1016/j.ccr.2008.10.018

    Article  Google Scholar 

  47. Nik-Zainal S, Van Loo P, Wedge DC, Alexandrov LB, Greenman CD, Lau KW, Raine K, Jones D, Marshall J, Ramakrishna M, Shlien A, Cooke SL, Hinton J, Menzies A, Stebbings LA, Leroy C, Jia M, Rance R, Mudie LJ, Gamble SJ, Stephens PJ, McLaren S, Tarpey PS, Papaemmanuil E, Davies HR, Varela I, McBride DJ, Bignell GR, Leung K, Butler AP, Teague JW, Martin S, Jönsson G, Mariani O, Boyault S, Miron P, Fatima A, Langerød A, Aparicio SAJR, Tutt A, Sieuwerts AM, Borg Å, Thomas G, Salomon AV, Richardson AL, Børresen-Dale AL, Futreal PA, Stratton MR, Campbell PJ, Breast Cancer Working Group of the International Cancer Genome Consortium (2012) The life history of 21 breast cancers. Cell 149(5):994–1007. https://doi.org/10.1016/j.cell.2012.04.023

    Article  Google Scholar 

  48. Notta F, Chan-Seng-Yue M, Lemire M, Li Y, Wilson GW, Connor AA, Denroche RE, Liang SB, Brown AM, Kim JC, Wang T, Simpson JT, Beck T, Borgida A, Buchner N, Chadwick D, Hafezi-Bakhtiari S, Dick JE, Heisler L, Hollingsworth MA, Ibrahimov E, Jang GH, Johns J, Jorgensen LG, Law C, Ludkovski O, Lungu I, Ng K, Pasternack D, Petersen GM, Shlush LI, Timms L, Tsao MS, Wilson JM, Yung CK, Zogopoulos G, Bartlett JM, Alexandrov LB, Real FX, Cleary SP, Roehrl MH, McPherson JD, Stein LD, Hudson TJ, Campbell PJ, Gallinger S (2016) A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns. Nature 538(7625):378–382. https://doi.org/10.1038/nature19823, NIHMS150003

    Article  Google Scholar 

  49. Ortmann CA, Kent DG, Nangalia J, Silber Y, Wedge DC, Grinfeld J, Baxter EJ, Massie CE, Papaemmanuil E, Menon S, Godfrey AL, Dimitropoulou D, Guglielmelli P, Bellosillo B, Besses C, Döhner K, Harrison CN, Vassiliou GS, Vannucchi A, Campbell PJ, Green AR (2015) Effect of Mutation Order on Myeloproliferative Neoplasms. The New England journal of medicine 372(7):601–612. https://doi.org/10.1056/NEJMoa1412098, N Engl J Med 2011;365:981-92. Copyright

    Article  Google Scholar 

  50. Robanus-Maandag EC, Bosch CAJ, Kristel PM, Hart AAM, Faneyte IF, Nederlof PM, Peterse JL, van de Vijver MJ (2003) Association of C-MYC amplification with progression from the in situ to the invasive stage in C-MYC-amplified breast carcinomas. J Pathol 201(1):75–82. https://doi.org/10.1002/path.1385

    Article  Google Scholar 

  51. Roerink SF, Sasaki N, Lee-Six H, Young MD, Alexandrov LB, Behjati S, Mitchell TJ, Grossmann S, Lightfoot H, Egan DA, Pronk A, Smakman N, van Gorp J, Anderson E, Gamble SJ, Alder C, van de Wetering M, Campbell PJ, Stratton MR, Clevers H (2018) Intra-tumour diversification in colorectal cancer at the single-cell level. Nature. https://doi.org/10.1038/s41586-018-0024-3

    Article  Google Scholar 

  52. Rowley M, Ohashi A, Mondal G, Mills L, Yang L, Zhang L, Sundsbak R, Shapiro V, Muders MH, Smyrk T, Couch FJ (2011) Inactivation of Brca2 promotes Trp53-associated but inhibits KrasG12D-dependent pancreatic cancer development in mice. Gastroenterology 140(4):1303–1313.e1–3, https://doi.org/10.1053/j.gastro.2010.12.039

    Article  Google Scholar 

  53. Sánchez-Rivera FJ, Jacks T (2015) Applications of the CRISPR-Cas9 system in cancer biology. Nat Rev Cancer 15(7):387–95. https://doi.org/10.1038/nrc3950

    Article  Google Scholar 

  54. Schaub MA, Henzinger TA, Fisher J (2007) Qualitative networks: a symbolic approach to analyze biological signaling networks. BMC Syst Biol 1:4. https://doi.org/10.1186/1752-0509-1-4

    Article  Google Scholar 

  55. Shah SP, Morin RD, Khattra J, Prentice L, Pugh T, Burleigh A, Delaney A, Gelmon K, Guliany R, Senz J, Steidl C, Holt RA, Jones S, Sun M, Leung G, Moore R, Severson T, Taylor GA, Teschendorff AE, Tse K, Turashvili G, Varhol R, Warren RL, Watson P, Zhao Y, Caldas C, Huntsman D, Hirst M, Marra MA, Aparicio S (2009) Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 461(7265):809–813. https://doi.org/10.1038/nature08489

    Article  Google Scholar 

  56. Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, Turashvili G, Ding J, Tse K, Haffari G, Bashashati A, Prentice LM, Khattra J, Burleigh A, Yap D, Bernard V, McPherson A, Shumansky K, Crisan A, Giuliany R, Heravi-Moussavi A, Rosner J, Lai D, Birol I, Varhol R, Tam A, Dhalla N, Zeng T, Ma K, Chan SK, Griffith M, Moradian A, Cheng SWG, Morin GB, Watson P, Gelmon K, Chia S, Chin SF, Curtis C, Rueda OM, Pharoah PD, Damaraju S, Mackey J, Hoon K, Harkins T, Tadigotla V, Sigaroudinia M, Gascard P, Tlsty T, Costello JF, Meyer IM, Eaves CJ, Wasserman WW, Jones S, Huntsman D, Hirst M, Caldas C, Marra MA, Aparicio S (2012) The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 486(7403):395–399. https://doi.org/10.1038/nature10933, NIHMS150003

    Article  Google Scholar 

  57. Shavit Y, Yordanov B, Dunn SJ, Wintersteiger CM, Hamadi Y, Kugler H (2015) Switching Gene Regulatory Networks. In: International conference on information processing in cells and tissues. Springer, Cham, pp 131–144, https://doi.org/10.1007/978-3-319-23108-2_11

    Chapter  Google Scholar 

  58. Silverbush D, Grosskurth S, Wang D, Powell F, Gottgens B, Dry J, Fisher J (2017) Cell-specific computational modeling of the PIM pathway in acute myeloid leukemia. Cancer Res 77(4):827–838. https://doi.org/10.1158/0008-5472.CAN-16-1578

    Article  Google Scholar 

  59. Skoulidis F, Cassidy LD, Pisupati V, Jonasson JG, Bjarnason H, Eyfjord JE, Karreth FA, Lim M, Barber LM, Clatworthy SA, Davies SE, Olive KP, Tuveson DA, Venkitaraman AR (2010) Germline Brca2 heterozygosity promotes KrasG12D -driven carcinogenesis in a murine model of familial pancreatic cancer. Cancer Cell 18(5):499–509. https://doi.org/10.1016/j.ccr.2010.10.015

    Article  Google Scholar 

  60. Sotiriou C, Neo SYY, McShane LM, Korn EL, Long PM, Jazaeri A, Martiat P, Fox SB, Harris AL, Liu ET (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Nat Acad Sci USA 100(18):10393–10398. https://doi.org/10.1073/pnas.1732912100

    Article  Google Scholar 

  61. Sottoriva A, Kang H, Ma Z, Graham TA, Salomon MP, Zhao J, Marjoram P, Siegmund K, Press MF, Shibata D, Curtis C (2015) A big bang model of human colorectal tumor growth. Nat Genet 47(3):209–216. https://doi.org/10.1038/ng.3214, 15334406

    Article  Google Scholar 

  62. Sprouffske K, Pepper JW, Maley CC (2011) Accurate reconstruction of the temporal order of mutations in neoplastic progression. Cancer Prevent Res 4(7):1135–1144. https://doi.org/10.1158/1940-6207.CAPR-10-0374

    Article  Google Scholar 

  63. Sun QY, Ding LW, Tan KT, Chien W, Mayakonda A, Lin DC, Loh XY, Xiao JF, Meggendorfer M, Alpermann T, Garg M, Lim SL, Madan V, Hattori N, Nagata Y, Miyano S, Yeoh AEJ, Hou HA, Jiang YY, Takao S, Liu LZ, Tan SZ, Lill M, Hayashi M, Kinoshita A, Kantarjian HM, Kornblau SM, Ogawa S, Haferlach T, Yang H, Koeffler HP (2017) Ordering of mutations in acute myeloid leukemia with partial tandem duplication of MLL (MLL-PTD). Leukemia 31(1):1–10. https://doi.org/10.1038/leu.2016.160

    Article  Google Scholar 

  64. Tabassum DP, Polyak K (2015) Tumorigenesis: it takes a village. Nat Rev Cancer 15(8):473–483. https://doi.org/10.1038/nrc3971

    Article  Google Scholar 

  65. Takahashi K, Yamanaka S (2006) Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126(4):663–76. https://doi.org/10.1016/j.cell.2006.07.024

    Article  Google Scholar 

  66. Turajlic S, McGranahan N (1855) Swanton C (2015) Inferring mutational timing and reconstructing tumour evolutionary histories. Biochimica et Biophysica Acta Rev Cancer 2:264–275. https://doi.org/10.1016/j.bbcan.2015.03.005

    Article  Google Scholar 

  67. Wang Y, Waters J, Leung ML, Unruh A, Roh W, Shi X, Chen K, Scheet P, Vattathil S, Liang H, Multani A, Zhang H, Zhao R, Michor F, Meric-Bernstam F, Navin NE (2014) Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 512(7513):155–160. https://doi.org/10.1038/nature13600, NIHMS150003

    Article  Google Scholar 

  68. Wu X, Sun L, Wang X, Su P, Li Z, Zhang C, Wang Y, Gao P, Ma R (2016) Breast cancer invasion and metastasis by mPR\(\alpha \) through the PI3K/Akt signaling pathway. Pathol Oncol Res POR 22(3):471–6. https://doi.org/10.1007/s12253-015-0023-8

    Article  Google Scholar 

  69. Yates LR, Gerstung M, Knappskog S, Desmedt C, Gundem G, Van Loo P, Aas T, Alexandrov LB, Larsimont D, Davies H, Li Y, Ju YS, Ramakrishna M, Haugland HK, Lilleng PK, Nik-Zainal S, McLaren S, Butler A, Martin S, Glodzik D, Menzies A, Raine K, Hinton J, Jones D, Mudie LJ, Jiang B, Vincent D, Greene-Colozzi A, Adnet PY, Fatima A, Maetens M, Ignatiadis M, Stratton MR, Sotiriou C, Richardson AL, Lønning PE, Wedge DC, Campbell PJ (2015) Subclonal diversification of primary breast cancer revealed by multiregion sequencing. Nat Med 21(7):751–759. https://doi.org/10.1038/nm.3886. arXiv:1408.1149

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Biochemistry, University of Cambridge, Cambridge, UK

    Matthew A. Clarke & Jasmin Fisher

  2. Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA

    Steven Woodhouse

  3. Department of Computer Science, University of Leicester, Leicester, UK

    Nir Piterman

  4. MRC Cancer Unit, University of Cambridge, Cambridge, UK

    Benjamin A. Hall

  5. Microsoft Research Cambridge, Cambridge, UK

    Jasmin Fisher

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  3. Nir Piterman
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  4. Benjamin A. Hall
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  5. Jasmin Fisher
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Correspondence to Jasmin Fisher .

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  1. Department of Computer Science and Technology, University of Cambridge, Cambridge, UK

    Pietro Liò

  2. School of Computing, Newcastle University, Newcastle, UK

    Paolo Zuliani

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Clarke, M.A., Woodhouse, S., Piterman, N., Hall, B.A., Fisher, J. (2019). Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in Cancer Evolution. In: Liò, P., Zuliani, P. (eds) Automated Reasoning for Systems Biology and Medicine. Computational Biology, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-17297-8_5

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  • DOI: https://doi.org/10.1007/978-3-030-17297-8_5

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