Variability in the Solid Cancer Cell Population and Its Consequences for Cancer Diagnostics and Treatment
Authors:
Brychtová Veronika; Valík Dalibor; Vojtěšek Bořivoj
Authors place of work:
Regionální centrum aplikované molekulární onkologie, Masarykův onkologický ústav, Brno
Published in the journal:
Klin Onkol 2018; 31(Supplementum 2): 5-13
Category:
Review
doi:
https://doi.org/10.14735/amko20182S5
Summary
Background:
Cancer develops as a result of somatic mutations and evolutionary processes with a Darwinian character. Tumors evolve by dynamic clonal expansion and selection to form genetically diverse cell subpopulations adapted to different tumor microenvironmental conditions. Within cancer cells, the genome is shaped by various selective pressures. Cancer evolution often follows a branched trajectory with divergent subclones evolving simultaneously. Clonal diversity within the same tumor results in genetic, epigenetic and phenotypic variability in tumor mass, which represents a major obstacle for the development of efficient diagnostics and personalized treatment. Advances in sequencing techniques have enabled a better understanding of the growth, progression and response to cancer treatment in heterogeneous cancers. Concurrently, understanding the mechanisms involved and monitoring changes in cancer clones during disease progression may improve the efficiency of cancer therapy.
Aim:
In this review, we summarize available data on intratumor heterogeneity. We show how intratumor heterogeneity, arising from clonal diversity, manifests itself at various levels, including at the genetic, epigenetic, and protein levels. We describe how phylogenetics, a powerful systems biology approach, can help trace clonal evolution during cancer progression and metastasis formation. We also highlight the main problems caused by intratumor heterogeneity, which hinders the development of novel diagnostics and therapies.
Key words:
cancer evolution – intratumor heterogeneity – cancer phylogenetics – clonal evolution
The work was supported by the project MEYS – NPS I – LO1413
The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.
The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.
Accepted: 8. 8. 2018
Zdroje
1. Cairns J. Mutation selection and the natural history of cancer. Nature 1975; 255 (5505): 197–200.
2. Nowell PC. The clonal evolution of tumor cell populations. Science 1976; 194 (4260): 23–28.
3. Sottoriva A, Barnes CP, Graham TA. Catch my drift? Making sense of genomic intra-tumour heterogeneity. Biochim Biophys Acta 2017; 1867 (2): 95–100. doi: 10.1016/j.bbcan.2016.12.003.
4. Merlo LM, Pepper JW, Reid BJ et al. Cancer as an evolutionary and ecological process. Nat Rev Cancer 2006; 6 (12): 924–935. doi: 10.1038/nrc2013.
5. Navin NE, Hicks J. Tracing the tumor lineage. Mol Oncol 2010; 4 (3): 267–283. doi: 10.1016/j.molonc.2010.04.010.
6. Fisher R, Pusztai L, Swanton C. Cancer heterogeneity: implications for targeted therapeutics. Br J Cancer 2013; 108 (3): 479–485. doi: 10.1038/bjc.2012.581.
7. McGranahan N, Swanton C. Clonal heterogeneity and tumor evolution: past, present and the future. Cell 2017; 168 (4): 613–628. doi: 10.1016/j.cell.2017.01.018.
8. Cancer.org. [online]. The history of cancer. Available from: https: //www.cancer.org/cancer/cancer-basics/history-of-cancer.html.
9. Hansmann’s ideas of the nature of cancer: description and analysis. In: Bignold LP, Coghlan BL, Jersmann HPA (eds). David Paul Von Hansemann: contributions to oncology. Basel: Birkhäuser 2007: 75–90.
10. Heppner GH. Tumor heterogeneity. Cancer Res 1984; 44 (6): 2259–2265.
11. Epstein JI, Egevad L, Amin MB et al. The 2014 International Society of Urological Pathology (ISUP) consensus conference on gleason grading of prostatic carcinoma definition of grading patterns and proposal for a new grading system. Am J Surg Pathol 2016; 40 (2): 244–252. doi: 10.1097/PAS.0000000000000530.
12. Marusyk A, Polyak K. Tumor heterogeneity: causes and consequences. Biochim Biophys Acta 2009; 1805 (1): 105–117. doi: 10.1016/j.bbcan.2009.11.002.
13. Michor F, Polyak K. The origins and implications of intratumor heterogeneity. Cancer Prev Res (Phila) 2010; 3 (11): 1361–1364. doi: 10.1158/1940-6207.CAPR-10-0234.
14. Heppner GH, Miller BE. Tumor heterogeneity: biological implications and therapeutic consequences. Cancer Metastasis Rev 1983; 2 (1): 5–23.
15. Burrell RA, McGranahan N, Bartek J et al. The causes and consequences of genetic heterogeneity in cancer evolution. Nature 2013; 501 (7467): 338–345. doi: 10.1038/nature12625.
16. Gerashchenko TS, Denisov EV, Litviakov NV et al. Intratumor heterogeneity: nature and biological significance. Biochemistry (Mosc) 2013; 78 (11): 1201–1215. doi: 10.1134/S0006297913110011.
17. Merid SK, Goranskaya D, Alexeyenko A. Distinguishing between driver and passenger mutations in individual cancer genomes by network enrichment analysis. BMC Bioinformatics 2014; 15: 308. doi: 10.1186/1471-2105-15-308.
18. Kim YA, Cho DY, Przytycka TM. Understanding genotype-phenotype effects in cancer via network approaches. PLoS Comput Biol 2016; 12 (3): e1004747. doi: 10.1371/journal.pcbi.1004747.
19. Rosenthal R, McGranahan N, Herrero J et al. Deciphering genetic intratumor heterogeneity and its impact on cancer evolution. Annu Rev Cancer Biol 2017; 1: 223–240. doi: 10.1146/annurev-cancerbio-042516-011348.
20. Pleasance ED, Cheetham RK, Stephens PJ et al. A comprehensive catalogue of somatic mutations from a human cancer genome. Nature 2010; 463 (7278): 191–196. doi: 10.1038/nature08658.
21. International Cancer Genome Consortium, Hudson TJ, Anderson W et al. International network of cancer genome projects. Nature 2010; 464 (7291): 993–998. doi: 10.1038/nature08987.
22. Hodis E, Watson IR, Kryukov GV et al. A landscape of driver mutations in melanoma. Cell 2012; 150 (2): 251–263. doi: 10.1016/j.cell.2012.06.024.
23. Cancer Genome Atlas Research Network, McLendon R, Friedman A et al. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008; 455 (7216): 1061–1068. doi: 10.1038/nature07385.
24. Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA et al. Cancer genome atlas research network. the cancer genome atlas pan-cancer analysis project. Nat Genet 2013; 45 (10): 1113–1120. doi: 10.1038/ng.2764.
25. Cancer Genome Atlas Research Network, Agrawal N, Akbani R et al. Integrated genomic characterization of papillary thyroid carcinoma. Cell 2014; 159 (3): 676–690. doi: 10.1016/j.cell.2014.09.050.
26. Lawrence MS, Stojanov P, Polak P et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 2013; 499 (7457): 214–218. doi: 10.1038/nature12213.
27. Vogelstein B, Papadopoulos N, Velculescu VE et al. Cancer genome landscapes. Science 2013; 339 (6127): 1546–1558. doi: 10.1126/science.1235122.
28. Solimini NL, Xu Q, Mermel CH et al. Recurrent hemizygous deletions in cancers may optimize proliferative potential. Science 2012; 337 (6090): 104–109. doi: 10.1126/science.1219580.
29. Feinberg AP, Vogelstein B. Hypomethylation distinguishes genes of some human cancers from their normal counterparts. Nature 1983; 301 (5895): 89–92.
30. Goelz SE, Vogelstein B, Hamilton SR et al. Hypomethylation of DNA from benign and malignant human colon neoplasms. Science 1985; 228 (4696): 187–190.
31. Greger V, Debus N, Lohmann D et al. Frequency and parental origin of hypermethylated RB1 alleles in retinoblastoma. Hum Genet 1994; 94 (5): 491–496.
32. Graff JR, Gabrielson E, Fujii H et al. Methylation patterns of the E-cadherin 5‘ CpG island are unstable and reflect the dynamic, heterogeneous loss of E-cadherin expression during metastatic progression. J Biol Chem 2000; 275 (4): 2727–2732.
33. Kane MF, Loda M, Gaida GM et al. Methylation of the hMLH1 promoter correlates with lack of expression of hMLH1 in sporadic colon tumors and mismatch repair-defective human tumor cell lines. Cancer Res 1997; 57 (5): 808–811.
34. Mack SC, Hubert CG, Miller TE et al. An epigenetic gateway to brain tumor cell identity. Nat Neurosci 2015; 19 (1): 10–19. doi: 10.1038/nn.4190.
35. Mazor T, Pankov A, Johnson BE et al. DNA methylation somatic mutations converge on the cell cycle and define similar evolutionary histories in brain tumors. Cancer Cell 2015; 28 (3): 307–317. doi: 10.1016/j.ccell.2015.07. 012.
36. Aryee MJ, Liu W, Engelmann JC et al. DNA methylation alterations exhibit intraindividual stability and interindividual heterogeneity in prostate cancer metastases. Sci Transl Med 2013; 5 (169): 169ra110. doi: 10.1126/scitranslmed.3005211.
37. Marusyk A, Almendro V, and Polyak K. Intra-tumour heterogeneity: a looking glass for cancer? Nat Rev Cancer 2012; 12 (5): 323–334. doi: 10.1038/nrc3261.
38. Kreso A, O’Brien CA, van Galen P et al. Variable clonal repopulation dynamics influence chemotherapy response in colorectal cancer. Science 2103; 339 (6119): 543–548. doi: 10.1126/science.1227670.
39. Katz E, Skorecki K, Tzukerman M. Niche-dependent tumorigenic capacity of malignant ovarian ascites-derived cancer cell subpopulations. Clin Cancer Res 2009; 15 (1): 70–80. doi: 10.1158/1078-0432.CCR-08-1233.
40. Abelson S, Shamai Y, Berger L et al. Intratumoral heterogeneity in the self-renewal and tumorigenic differentiation of ovarian cancer. Stem Cells 2012; 30 (3): 415–424. doi: 10.1002/stem.1029.
41. Alizadeh AA, Aranda V, Bardelli A et al. Toward understanding and exploiting tumor heterogeneity. Nat Med 2015; 21 (8): 846–853. doi: 10.1038/nm.3915.
42. Burrell RA, Swanton C. Re-evaluating clonal dominance in cancer evolution. Trends Cancer 2016; 2 (5): 263–276. doi: 10.1016/j.trecan.2016.04.002.
43. Marusyk A, Polyak K. Tumor heterogeneity: causes and consequences. Biochim Biophys Acta 2010; 1805 (1): 105–117. doi: 10.1016/j.bbcan.2009.11.002.
44. Marusyk A, Tabassum D, Altrock P. Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature 2014; 514 (7520): 54–58. doi: 10.1038/nature13556.
45. Cleary AS, Leonard TL, Gestl SA et al. Tumour cell heterogeneity maintained by cooperating subclones in Wnt-driven mammary cancers. Nature 2014; 508 (7494): 113–117. doi: 10.1038/nature13187.
46. Keats JJ, Chesi M, Egan JB et al. Clonal competition with alternating dom-inance in multiple myeloma. Blood 2012; 120 (5): 1067–1076. doi: 10.1182/blood-2012-01-405985.
47. Kim T, Yoshida K, Kim YK et al. Clonal dynamics in a single AML case tracked for 9 years reveals the complexity of leukemia progression. Leukemia 2015; 30 (2): 295–302. doi: 10.1038/leu.2015.264.
48. Lawrence MS, Stojanov P, Polak P et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 2013; 499 (7457): 214–218. doi: 10.1038/nature12213.
49. Bolli N, Avet-Loiseau H, Wedge DC et al. Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. Nat Commun 2014; 5: 2997. doi: 10.1038/ncomms3997.
50. Fearon E, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell 1990; 61 (5): 759–767.
51. Nik-Zainal S, Van Loo P, Wedge DC et al. The life history of 21 breast cancers. Cell 2012; 149 (5): 994–1007. doi: 10.1016/j.cell.2012.04.023.
52. Shah SP, Roth A, Goya R et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012; 486 (7403): 395–399. doi: 10.1038/nature10933.
53. Gerlinger M, Rowan AJ, Horswell S et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 2012; 366 (10): 883–892. doi: 10.1056/NEJMoa1113205.
54. McPherson A, Roth A, Laks E et al. Divergent modes of clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer. Nat Genet 2016; 48 (7): 758–767. doi: 10.1038/ng.3573.
55. Wang Y, Waters J, Leung ML et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 2014; 512 (7513): 155–160. doi: 10.1038/nature13600.
56. Kim TM, Jung SH, An CH et al. Subclonal genomic architectures of primary and metastatic colorectal cancer based on intratumoral genetic heterogeneity. Clin Cancer Res 2015; 21 (19): 4461–4472. doi: 10.1158/1078-0432.CCR-14-2413.
57. Yates LR, Gerstung M, Knappskog S et al. Subclonal diversification of primary breast cancer revealed by multiregion sequencing. Nat Med 2015; 21 (7): 751–759. doi: 10.1038/nm.3886.
58. Boutros PC, Fraser M, Harding NJ et al. Spatial genomic heterogeneity within localized, multifocal prostate cancer. Nat Genet 2015; 47 (7): 736–745. doi: 10.1038/ng. 3315.
59. Ling S, Hu Z, Yang Z et al. Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution. Proc Natl Acad Sci U S A 2015; 112 (47): E6496–E6505. doi: 10.1073/pnas.1519556 112.
60. Kang H, Salomon MP, Sottoriva A et al. Many private mutations originate from the first few divisions of a human colorectal adenoma. J Pathol 2015; 237 (3): 355–362. doi: 10.1002/path.4581.
61. Sottoriva A, Kang H, Ma Z et al. A big bang model of human colorectal tumor growth. Nat Genet 2015; 47 (3): 209–216. doi: 10.1038/ng.3214.
62. Bashashati A, Ha G, Tone A et al. Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling. J Pathol 2013; 231 (1): 21–34. doi: 10.1002/path.4230.
63. Harbst K, Lauss M, Cirenajwis H et al. Multiregion whole-exome sequencing uncovers the genetic evolution and mutational heterogeneity of early-stage metastatic melanoma. Cancer Res 2016; 76 (16): 4765–4774. doi: 10.1158/0008-5472.CAN-15-3476.
64. Gerlinger M, Horswell S, Larkin J et al. Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat Genet 2014; 46 (3): 225–233. doi: 10.1038/ng.2891.
65. Thirlwell C, Will OC, Domingo E et al. Clonality assessment and clonal ordering of individual neoplastic crypts shows polyclonality of colorectal adenomas. Gastroenterology 2010; 138 (4): 1441–1454. doi: 10.1053/j.gastro.2010.01.033.
66. Campbell PJ, Yachida S, Mudie LJ et al. The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature 2010; 467 (7319): 1109–1113. doi: 10.1038/nature09460.
67. Shah SP, Roth A, Goya R et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012; 486 (7403): 395–399. doi: 10.1038/nature10933.
68. Williams MJ, Werner B, Barnes CP et al. Identification of neutral tumor evolution across cancer types. Nat Genet 2016; 48 (3): 238–244. doi: 10.1038/ng.3489.
69. Baca SC, Prandi D, Lawrence MS. Punctuated evolution of prostate cancer genomes. Cell 2013; 153 (3): 666–677. doi: 10.1016/j.cell.2013.03.021.
70. Gao R, Davis A, McDonald TO et al. Punctuated copy number evolution and clonal stasis in triple-negative breast cancer. Nat Genet 2016; 48 (10): 1119–1130. doi: 10.1038/ng.3641.
71. Davis A, Gao R, Navin N. Tumor evolution: linear, branching, neutral or punctuated? Biochim Biophys Acta 2017; 1867 (2): 151–161. doi: 10.1016/j.bbcan.2017.01.003.
72. Tsao J, Zhang J, Salovaara R et al. Tracing cell fates in human colorectal tumors from somatic microsatellite mutations: evidence of adenomas with stem cell architecture. Am J Pathol 1998; 153 (4): 1189–1200. doi: 10.1016/S0002-9440 (10) 65663-5.
73. Desper R, Jiang F, Kallioniemi OP et al. Inferring tree models of oncogenesis from comparative genomic hybridization data. J Comput Biol 1999; 6 (1): 37–51. doi: 10.1089/cmb.1999.6.37.
74. Schwartz R, Schäffer AA. The evolution of tumour phylogenetics: principles and practice. Nat Rev Genet 2017; 18 (4): 213–229. doi: 10.1038/nrg.2016.170.
75. Hanahan D, Weinberg RA. The hallmarks of cancer: the next generation. Cell 2011; 144 (5): 646–674. doi: 10.1016/j.cell.2011.02.013.
76. Martincorena I, Raine KM, Gerstung M et al. Universal Patterns of Selection in Cancer and Somatic Tissues. Cell 2017; 171 (5): 1029–1041. doi: 10.1016/j.cell.2017.09.042.
77. Wang HY, Chen Y, Tong D et al. Is the evolution in tumors Darwinian or non-Darwinian? National Science Review 2018; 5 (1): 15–17.
78. Williams MJ, Werner B, Barnes CP et al. Identification of neutral tumor evolution across cancer types. Nat Genet 2016; 48 (3): 238–244. doi: 10.1038/ng.3489.
79. Williams MJ, Werner B, Barnes CP et al. Reply: Is the evolution of tumors Darwinian or non-Darwinian? National Science Review 2018; 5 (1): 17–19. doi: 10.1093/nsr/nwx131.
80. Pennington G, Smith CA, Shackney S et al. Reconstructing tumor phylogenies from heterogeneous single-cell data. J Bioinform Comput Biol 2007; 5 (2a): 407–427.
81. Hunter KW, Amin R, Deasy S et al. Genetic insights into the morass of metastatic heterogeneity. Nat Rev Cancer 2018; 18 (4): 211–223. doi: 10.1038/nrc.2017.126.
82. Weng D, Penzner JH, Song B et al. Metastasis is an early event in mouse mammary carcinomas and is associated with cells bearing stem cell markers. Breast Cancer Res 2012; 14 (1): R18. doi: 10.1186/bcr3102.
83. Rhim AD, Thege FI, Santana SM et al. Detection of circulating pankreas epithelial cells in patients with pancreatic cystic lesions. Gastroenterology 2014; 146 (3): 647–651. doi: 10.1053/j.gastro.2013.12.007.
84. Xie T, Cho YB, Wang K et al. Patterns of somatic alterations between matched primary and metastatic colorectal tumors characterized by whole-genome sequencing. Genomics 2014; 104 (4): 234–241. doi: 10.1016/j.ygeno.2014.07.012.
85. Sanborn JZ, Chung J, Purdom E et al. Phylogenetic analyses of melanoma reveal complex patterns of metastatic dissemination. Proc Natl Acad Sci U S A 2015; 112 (35): 10995–11000. doi: 10.1073/pnas.1508074112.
86. Naxerova K, Reiter JG, Brachtel E et al. Origins of lymphatic and distant metastases in human colorectal cancer. Science 2017; 357 (6346): 55–60. doi: 10.1126/science.aai8515.
87. Gundem G, Van Loo P, Kremeyer B et al. The evolutionary history of lethal metastatic prostate cancer. Nature 2015; 520 (7547): 353–357. doi: 10.1038/nature14347.
88. Brastianos PK, Carter SL, Santagata S et al. Genomic characterization of brain metastases reveals branched evolution and potential therapeutic targets. Cancer Discov 2015; 5 (11): 1164–1177. doi: 10.1158/2159-8290.CD-15-0369.
89. Campbell PJ, Yachida S, Mudie LJ et al. The patterns and dynamics of genomic instability in metastatic pancreatic cancer. Nature 2010; 467 (7319): 1109–1113. doi: 10.1038/nature09460.
90. McGranahan N, Swanton C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell 2015; 27 (1): 15–26. doi: 10.1016/j.ccell.2014.12.001.
91. Mullighan CG, Phillips LA, Su X et al. Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia. Science 2008; 322 (5906): 1377–1380. doi: 10.1126/science.1164266.
92. Ding L, Ley TJ, Larson DE et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature 2012; 481 (7382): 506–510. doi: 10.1038/nature10738.
93. Almendro V, Marusyk A, Polyak K. Cellular heterogeneity and molecular evolution in cancer. Annu Rev Pathol 2013; 8: 277–302. doi: 10.1146/annurev-pathol-020712-163923.
94. Park SY, Gönen M, KimHJ et al. Cellular and genetic diversity in the progression of in situ human breast carcinomas to an invasive phenotype. J Clin Investig 2010; 120 (2): 636–644. doi: 10.1172/JCI40724.
95. Seol H, Lee HJ, Choi Y et al. Intratumoral heterogeneity of HER2 gene amplification in breast cancer: its clinicopathological significance. Mod Pathol 2012; 25 (7): 938–948. doi: 10.1038/modpathol.2012.36.
96. Mroz EA, Tward AM, Hammon RJ et al. Intra-tumor genetic heterogeneity and mortality in head and neck cancer: analysis of data from the cancer genome atlas. PLoS Med 2015; 12 (2): e1001786. doi: 10.1371/journal.pmed.1001786.
97. Ledgerwood LG, Kumar D, Eterovic AK et al. The degree of intratumor mutational heterogeneity varies by primary tumor sub-site. Oncotarget 2016; 7 (19): 27185–27198. doi: 10.18632/oncotarget.8448.
98. Sharma SV, Lee DY, Li B et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell 2010; 141 (1): 69–80. doi: 10.1016/j.cell.2010.02.027.
99. De Mattos-Arruda L, Caldas C. Cell-free circulating tumour DNA as a liquid biopsy in breast cancer. Mol Oncol 2016; 10 (3): 464–474. doi: 10.1016/j.molonc.2015.12.001.
100. Hench IB, Hench J, Tolnay M. Liquid biopsy in clinical management of breast, lung, and colorectal cancer. Front Med 2018; 5: 9. doi: 10.3389/fmed.2018.00009.
Štítky
Paediatric clinical oncology Surgery Clinical oncologyČlánok vyšiel v časopise
Clinical Oncology
2018 Číslo Supplementum 2
- Spasmolytic Effect of Metamizole
- Metamizole at a Glance and in Practice – Effective Non-Opioid Analgesic for All Ages
- Metamizole in perioperative treatment in children under 14 years – results of a questionnaire survey from practice
- Current Insights into the Antispasmodic and Analgesic Effects of Metamizole on the Gastrointestinal Tract
- Obstacle Called Vasospasm: Which Solution Is Most Effective in Microsurgery and How to Pharmacologically Assist It?
Najčítanejšie v tomto čísle
- Effect of DNA Methylation on the Development of Cancer
- Ferroptosis as a New Type of Cell Death and its Role in Cancer Treatment
- Possible Usage of p63 in Bioptic Diagnostics
- Current Methods of microRNA Analysis