Exploiting evolutionary steering to induce collateral drug sensitivity in cancer.
Antineoplastic Agents
/ pharmacology
Clonal Evolution
Computational Biology
Computer Simulation
Drug Resistance, Neoplasm
Evolution, Molecular
Gefitinib
/ pharmacology
Genotype
Humans
Lung Neoplasms
/ drug therapy
Models, Theoretical
Molecular Medicine
Pyridones
/ pharmacology
Pyrimidinones
/ pharmacology
Stochastic Processes
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
21 04 2020
21 04 2020
Historique:
received:
08
10
2019
accepted:
18
03
2020
entrez:
23
4
2020
pubmed:
23
4
2020
medline:
4
8
2020
Statut:
epublish
Résumé
Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased fecundity or increased sensitivity to another drug. These evolutionary trade-offs can be exploited using 'evolutionary steering' to control the tumour population and delay resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here, we present an approach for evolutionary steering based on a combination of single-cell barcoding, large populations of 10
Identifiants
pubmed: 32317663
doi: 10.1038/s41467-020-15596-z
pii: 10.1038/s41467-020-15596-z
pmc: PMC7174377
doi:
Substances chimiques
Antineoplastic Agents
0
Pyridones
0
Pyrimidinones
0
trametinib
33E86K87QN
Gefitinib
S65743JHBS
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
1923Subventions
Organisme : Department of Health
ID : RP-2016-07-28
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : R01 CA185138
Pays : United States
Organisme : Wellcome Trust
ID : 202778/B/16/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A22897
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A18052
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : P01 CA091955
Pays : United States
Organisme : Wellcome Trust
ID : 105104/Z/14/Z
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : R01 CA170595
Pays : United States
Organisme : Cancer Research UK
ID : 11566
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A22909
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : R01 CA140657
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA217376
Pays : United States
Organisme : Cancer Research UK
ID : A23110
Pays : United Kingdom
Organisme : DH | National Institute for Health Research (NIHR)
ID : RP-2016-07-28
Pays : International
Organisme : Cancer Research UK
ID : A25128
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A26815
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 202778/Z/16/Z
Pays : United Kingdom
Organisme : Department of Health
ID : RP-2016-07-028
Pays : United Kingdom
Références
Zhang, J., Yang, P. L. & Gray, N. S. Targeting cancer with small molecule kinase inhibitors. Nat. Rev. Cancer 9, 28–39 (2009).
pubmed: 19104514
doi: 10.1038/nrc2559
Holohan, C., Van Schaeybroeck, S., Longley, D. B. & Johnston, P. G. Cancer drug resistance: an evolving paradigm. Nat. Rev. Cancer 13, 714–726 (2013).
pubmed: 24060863
pmcid: 24060863
doi: 10.1038/nrc3599
Meacham, C. E. & Morrison, S. J. Tumour heterogeneity and cancer cell plasticity. Nature 501, 328–337 (2013).
pubmed: 24048065
pmcid: 4521623
doi: 10.1038/nature12624
McGranahan, N. & Swanton, C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell 27, 15–26 (2015).
pubmed: 25584892
doi: 10.1016/j.ccell.2014.12.001
Pao, W. et al. Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med. 2, e73 (2005).
pubmed: 15737014
pmcid: 549606
doi: 10.1371/journal.pmed.0020073
Sharma, S. V. et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell 141, 69–80 (2010).
pubmed: 20371346
pmcid: 2851638
doi: 10.1016/j.cell.2010.02.027
Shaffer, S. M. et al. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546, 431–435 (2017).
pubmed: 28607484
pmcid: 5542814
doi: 10.1038/nature22794
Misale, S. et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature 486, 532–536 (2012).
pubmed: 22722830
pmcid: 3927413
doi: 10.1038/nature11156
Diaz, L. A. et al. The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature 486, 537–540 (2012).
pubmed: 22722843
pmcid: 3436069
doi: 10.1038/nature11219
Greaves, M. & Maley, C. C. Clonal evolution in cancer. Nature 481, 306–313 (2012).
pubmed: 22258609
pmcid: 22258609
doi: 10.1038/nature10762
Burrell, R. A. & Swanton, C. Tumour heterogeneity and the evolution of polyclonal drug resistance. Mol. Oncol. 8, 1095–1111 (2014).
pubmed: 25087573
pmcid: 5528620
doi: 10.1016/j.molonc.2014.06.005
Nichol, D., Robertson-Tessi, M., Jeavons, P. & Anderson, A. R. A. Stochasticity in the genotype–phenotype map: implications for the robustness and persistence of bet-hedging. Genetics 204, 1523–1539 (2016).
pubmed: 27770034
pmcid: 5161283
doi: 10.1534/genetics.116.193474
Hata, A. N. et al. Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition. Nat. Med. 22, 262–269 (2016).
pubmed: 26828195
pmcid: 4900892
doi: 10.1038/nm.4040
Hall, M. D., Handley, M. D. & Gottesman, M. M. Is resistance useless? Multidrug resistance and collateral sensitivity. Trends Pharmacol. Sci. 30, 546–556 (2009).
pubmed: 19762091
pmcid: 2774243
doi: 10.1016/j.tips.2009.07.003
Luria, S. E. & Delbrück, M. Mutations of bacteria from virus sensitivity to virus resistance. Genetics 28, 491–511 (1943).
pubmed: 17247100
pmcid: 1209226
Gillies, R. J., Verduzco, D. & Gatenby, R. A. Evolutionary dynamics of carcinogenesis and why targeted therapy does not work. Nat. Rev. Cancer 12, 487–493 (2012).
pubmed: 22695393
pmcid: 4122506
doi: 10.1038/nrc3298
Imamovic, L. & Sommer, M. O. A. Use of collateral sensitivity networks to design drug cycling protocols that avoid resistance development. Sci. Transl. Med. 5, 204ra132–204ra132 (2013).
pubmed: 24068739
doi: 10.1126/scitranslmed.3006609
Pál, C., Papp, B. & Lázár, V. Collateral sensitivity of antibiotic-resistant microbes. Trends Microbiol. 23, 401–407 (2015).
pubmed: 25818802
pmcid: 5958998
doi: 10.1016/j.tim.2015.02.009
Nichol, D. et al. Steering evolution with sequential therapy to prevent the emergence of bacterial antibiotic resistance. PLoS Comput. Biol. 11, e1004493 (2015).
pubmed: 26360300
pmcid: 4567305
doi: 10.1371/journal.pcbi.1004493
Kirkman, L. A. et al. Antimalarial proteasome inhibitor reveals collateral sensitivity from intersubunit interactions and fitness cost of resistance. Proc. Natl Acad. Sci. USA 115, 201806109–E6870 (2018).
doi: 10.1073/pnas.1806109115
Zhao, B. et al. Exploiting temporal collateral sensitivity in tumor clonal evolution. Cell 165, 1–13 (2016).
doi: 10.1016/j.cell.2016.03.013
Wang, L. et al. An acquired vulnerability of drug-resistant melanoma with therapeutic potential. Cell 173, 1413–1425.e14 (2018).
pubmed: 29754815
doi: 10.1016/j.cell.2018.04.012
pmcid: 29754815
Merlo, L. M. F., Pepper, J. W., Reid, B. J. & Maley, C. C. Cancer as an evolutionary and ecological process. Nat. Rev. Cancer 6, 924–935 (2006).
pubmed: 17109012
doi: 10.1038/nrc2013
pmcid: 17109012
Gatenby, R. A., Silva, A. S., Gillies, R. J. & Frieden, B. R. Adaptive therapy. Cancer Res. 69, 4894–4903 (2009).
pubmed: 19487300
pmcid: 3728826
doi: 10.1158/0008-5472.CAN-08-3658
Gatenby, R. A., Brown, J. & Vincent, T. Lessons from applied ecology: cancer control using an evolutionary double bind. Cancer Res. 69, 7499–7502 (2009).
pubmed: 19752088
doi: 10.1158/0008-5472.CAN-09-1354
pmcid: 19752088
Basanta, D., Gatenby, R. A. & Anderson, A. R. A. Exploiting evolution to treat drug resistance: combination therapy and the double bind. Mol. Pharmaceutics 9, 914–921 (2012).
doi: 10.1021/mp200458e
Hughes, D. & Andersson, D. I. Evolutionary consequences of drug resistance: shared principles across diverse targets and organisms. Nat. Rev. Genet. 16, 459–471 (2015).
pubmed: 26149714
doi: 10.1038/nrg3922
pmcid: 26149714
Siravegna, G. et al. Clonal evolution and resistance to EGFR blockade in the blood of colorectal cancer patients. Nat. Med. 21, 795–801 (2015).
pubmed: 26030179
pmcid: 4868598
doi: 10.1038/nm.3870
Xue, Y. et al. An approach to suppress the evolution of resistance in BRAFV600E-mutant cancer. Nat. Med. 23, 929–937 (2017).
pubmed: 28714990
pmcid: 5696266
doi: 10.1038/nm.4369
Pluchino, K. M., Hall, M. D., Goldsborough, A. S., Callaghan, R. & Gottesman, M. M. Collateral sensitivity as a strategy against cancer multidrug resistance. Drug Resist. Updat. 15, 98–105 (2012).
pubmed: 22483810
pmcid: 3348266
doi: 10.1016/j.drup.2012.03.002
Zhao, B., Hemann, M. T. & Lauffenburger, D. A. Modeling tumor clonal evolution for drug combinations design. Trends Cancer 2, 144–158 (2016).
pubmed: 28435907
pmcid: 5400294
doi: 10.1016/j.trecan.2016.02.001
Turajlic, S., Sottoriva, A., Graham, T. & Swanton, C. Resolving genetic heterogeneity in cancer. Nat. Rev. Genet. 27, 1 (2019).
Machioka, K. et al. Establishment and characterization of two cabazitaxel-resistant prostate cancer cell lines. Oncotarget 9, 16185–16196 (2018).
pubmed: 29662635
pmcid: 5882326
doi: 10.18632/oncotarget.24609
Fuentes-Hernandez, A. et al. Using a sequential regimen to eliminate bacteria at sublethal antibiotic dosages. PLoS Biol. 13, e1002104 (2015).
pubmed: 25853342
pmcid: 4390231
doi: 10.1371/journal.pbio.1002104
Hata, A. N. et al. Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition. Nat. Med. 22, 262–269 (2016).
pubmed: 26828195
pmcid: 4900892
doi: 10.1038/nm.4040
Shibue, T. & Weinberg, R. A. EMT, CSCs, and drug resistance: the mechanistic link and clinical implications. Nat. Rev. Clin. Oncol. 14, 611–629 (2017).
pubmed: 28397828
pmcid: 5720366
doi: 10.1038/nrclinonc.2017.44
Raoof, S. et al. Targeting FGFR overcomes EMT-mediated resistance in EGFR mutant non-small cell lung cancer. Oncogene 350, 1–15 (2019).
Gottesman, M. M. & Pastan, I. Biochemistry of multidrug resistance mediated by the multidrug transporter. Annu. Rev. Biochem. 62, 385–427 (1993).
pubmed: 8102521
doi: 10.1146/annurev.bi.62.070193.002125
pmcid: 8102521
Wright, S. The roles of mutation, inbreeding, crossbreeding and selection in evolution. In Proc. Sixth International Congress of Genetics, Vol. 1, 356–366 (1932).
Engelman, J. A. et al. MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science 316, 1039–1043 (2007).
pubmed: 17463250
doi: 10.1126/science.1141478
Bhang, H.-E. C. et al. Studying clonal dynamics in response to cancer therapy using high-complexity barcoding. Nat. Med. 21, 440–448 (2015).
pubmed: 25849130
doi: 10.1038/nm.3841
Van Emburgh, B. O. et al. Acquired RAS or EGFR mutations and duration of response to EGFR blockade in colorectal cancer. Nat. Commun. 7, 283ra254 (2016).
Domínguez-Vigil, I. G., Moreno-Martínez, A. K., Wang, J. Y., Roehrl, M. H. A. & Barrera-Saldaña, H. A. The dawn of the liquid biopsy in the fight against cancer. Oncotarget 9, 2912–2922 (2018).
pubmed: 29416824
doi: 10.18632/oncotarget.23131
Mullighan, C. G., Williams, R. T., Downing, J. R. & Sherr, C. J. Failure of CDKN2A/B (INK4A/B-ARF)-mediated tumor suppression and resistance to targeted therapy in acute lymphoblastic leukemia induced by BCR-ABL. Genes Dev. 22, 1411–1415 (2008).
pubmed: 18519632
pmcid: 2732413
doi: 10.1101/gad.1673908
Dongre, A. & Weinberg, R. A. New insights into the mechanisms of epithelial–mesenchymal transition and implications for cancer. Nat. Rev. Mol. Cell Biol. 20, 69–84 (2019). 2018 20:2.
pubmed: 30459476
doi: 10.1038/s41580-018-0080-4
Greve, G. et al. The pan-HDAC inhibitor panobinostat acts as a sensitizer for erlotinib activity in EGFR-mutated and -wildtype non-small cell lung cancer cells. BMC Cancer 15, 1–10 (2015).
doi: 10.1186/s12885-015-1967-5
Damaskos, C. et al. Histone deacetylase inhibitors as a novel targeted therapy against non-small cell lung cancer: where are we now and what should we expect? Anticancer Res. 38, 37–43 (2018).
pubmed: 29277754
Gautschi, O., Mack, P. C., Davies, A. M., Lara, P. N. Jr & Gandara, D. R. Aurora kinase inhibitors: a new class of targeted drugs in cancer. Clin. Lung Cancer 8, 93–98 (2006).
pubmed: 17026809
doi: 10.3816/CLC.2006.n.036
Shah, K. N. et al. Aurora kinase A drives the evolution of resistance to third-generation EGFR inhibitors in lung cancer. Nat. Med. 25, 111–118 (2019).
pubmed: 30478424
doi: 10.1038/s41591-018-0264-7
Delbaldo, C. et al. Benefits of adding a drug to a single-agent or a 2-agent chemotherapy regimen in advanced non-small-cell lung cancer: a meta-analysis. JAMA 292, 470–484 (2004).
pubmed: 15280345
doi: 10.1001/jama.292.4.470
Carrick, S. et al. Single agent versus combination chemotherapy for metastatic breast cancer. Cochrane Database Syst. Rev. 34, 27 (2009).
Ghosn, J., Taiwo, B., Seedat, S., Autran, B. & Katlama, C. HIV. The Lancet https://doi.org/10.1016/S0140-6736(18)31311-4 (2018).
Alto, B. W., Lampman, R. L., Kesavaraju, B. & Muturi, E. J. Pesticide-induced release from competition among competing Aedes aegypti and Aedes albopictus (Diptera: Culicidae). J. Med. Entomol. 50, 1240–1249 (2013).
pubmed: 24843928
doi: 10.1603/ME12135
Neve, P., Vila-Aiub, M. & Roux, F. Evolutionary-thinking in agricultural weed management. N. Phytol. 184, 783–793 (2009).
doi: 10.1111/j.1469-8137.2009.03034.x
Oliveira, E. E., Guedes, R. N. C., Tótola, M. R. & De Marco, P. Jr. Competition between insecticide-susceptible and -resistant populations of the maize weevil, Sitophilus zeamais. Chemosphere 69, 17–24 (2007).
pubmed: 17570459
doi: 10.1016/j.chemosphere.2007.04.077
Enriquez-Navas, P. M. et al. Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer. Sci. Transl. Med. 8, 327ra24 (2016).
pubmed: 26912903
pmcid: 4962860
doi: 10.1126/scitranslmed.aad7842
Gallaher, J. A., Enriquez-Navas, P. M., Luddy, K. A., Gatenby, R. A. & Anderson, A. R. A. Spatial heterogeneity and evolutionary dynamics modulate time to recurrence in continuous and adaptive cancer therapies. Cancer Res. 78, 2127–2139 (2018).
pubmed: 29382708
pmcid: 5899666
doi: 10.1158/0008-5472.CAN-17-2649
Zhang, J., Cunningham, J. J., Brown, J. S. & Gatenby, R. A. Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer. Nat. Commun. 8, 1816 (2017).
pubmed: 29180633
pmcid: 5703947
doi: 10.1038/s41467-017-01968-5
Staňková, K., Brown, J. S., Dalton, W. S. & Gatenby, R. A. Optimizing cancer treatment using game theory: a review. JAMA Oncol. 5, 96–103 (2018).
Vlachogiannis, G. et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science 359, 920–926 (2018).
pubmed: 29472484
pmcid: 6112415
doi: 10.1126/science.aao2774
Erban, R., Chapman, S. J. Stochastic modelling of reaction-diffusion processes (Cambridge Texts in Applied Mathematics). Cam. Uni. Press (2020).
Mumenthaler, S. M. et al. The impact of microenvironmental heterogeneity on the evolution of drug resistance in cancer cells. Cancer Inform. 14s4, CIN.S19338 (2015).
doi: 10.4137/CIN.S19338
Rimmer, A. et al. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nat. Genet. 46, 912–918 (2014).
pubmed: 4753679
pmcid: 4753679
doi: 10.1038/ng.3036
Sherry, S. T. et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 29, 308–311 (2001).
pubmed: 11125122
pmcid: 29783
doi: 10.1093/nar/29.1.308
Van Loo, P. et al. Allele-specific copy number analysis of tumors. Proc. Natl Acad. Sci. USA 107, 16910–16915 (2010).
pubmed: 20837533
doi: 10.1073/pnas.1009843107
pmcid: 20837533
Favero, F. et al. Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data. Ann. Oncol. 26, 64–70 (2014).
pubmed: 25319062
pmcid: 4269342
doi: 10.1093/annonc/mdu479
Torre, E. et al. Rare cell detection by single-cell RNA sequencing as guided by single-molecule RNA FISH. Cell Syst. 6, 171–179.e5 (2018).
pubmed: 29454938
pmcid: 6078200
doi: 10.1016/j.cels.2018.01.014
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).
pubmed: 29608179
pmcid: 29608179
doi: 10.1038/nbt.4096
Lin, Y. et al. Evaluating stably expressed genes in single cells. GigaScience 8, 1–10 (2019).
doi: 10.1093/gigascience/giz106