Top

BMC Cancer

Published in:

01-12-2020 | Tyrosine Kinase Inhibitors | Research Article

The effects of combination treatments on drug resistance in chronic myeloid leukaemia: an evaluation of the tyrosine kinase inhibitors axitinib and asciminib

Authors: H. Jonathan G. Lindström, Ran Friedman

Published in: BMC Cancer | Issue 1/2020

Abstract

Background

Chronic myeloid leukaemia is in principle a treatable malignancy but drug resistance is lowering survival. Recent drug discoveries have opened up new options for drug combinations, which is a concept used in other areas for preventing drug resistance. Two of these are (I) Axitinib, which inhibits the T315I mutation of BCR-ABL1, a main source of drug resistance, and (II) Asciminib, which has been developed as an allosteric BCR-ABL1 inhibitor, targeting an entirely different binding site, and as such does not compete for binding with other drugs. These drugs offer new treatment options.

Methods

We measured the proliferation of KCL-22 cells exposed to imatinib–dasatinib, imatinib–asciminib and dasatinib–asciminib combinations and calculated combination index graphs for each case. Moreover, using the median–effect equation we calculated how much axitinib can reduce the growth advantage of T315I mutant clones in combination with available drugs. In addition, we calculated how much the total drug burden could be reduced by combinations using asciminib and other drugs, and evaluated which mutations such combinations might be sensitive to.

Results

Asciminib had synergistic interactions with imatinib or dasatinib in KCL-22 cells at high degrees of inhibition. Interestingly, some antagonism between asciminib and the other drugs was present at lower degrees on inhibition. Simulations revealed that asciminib may allow for dose reductions, and its complementary resistance profile could reduce the risk of mutation based resistance. Axitinib, however, had only a minor effect on T315I growth advantage.

Conclusions

Given how asciminib combinations were synergistic in vitro, our modelling suggests that drug combinations involving asciminib should allow for lower total drug doses, and may result in a reduced spectrum of observed resistance mutations. On the other hand, a combination involving axitinib was not shown to be useful in countering drug resistance.

Available only for authorised users

Chereda B, Melo JV. Natural course and biology of CML. Ann Hematol. 2015; 94(S2):107–21. https://doi.org/10.1007/s00277-015-2325-z.

Milojkovic D, Apperley J. Mechanisms of resistance to imatinib and second-generation tyrosine inhibitors in chronic myeloid leukemia. Clin Cancer Res. 2009; 15(24):7519–27. http://clincancerres.aacrjournals.org/content/15/24/7519.full.pdf.

Lim C, Miller GD, Bruno BJ. Resistant mutations in CML and Ph+ALL - role of ponatinib. BTT. 2014; 8:243. https://doi.org/10.2147/btt.s50734.CrossRef

Friedman R. The molecular mechanism behind resistance of the kinase FLT3 to the inhibitor quizartinib. Proteins. 2017; 85(11):2143–52. https://doi.org/10.1002/prot.25368. http://arxiv.org/abs/https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.25368.PubMedCrossRef

Georgoulia PS, Todde G, Bjelic S, Friedman R. The catalytic activity of abl1 single and compound mutations: Implications for the mechanism of drug resistance mutations in chronic myeloid leukaemia. Biochim Biophys Acta (BBA) Gen Subj. 2019; 1863(4):732–41. https://doi.org/10.1016/j.bbagen.2019.01.011.CrossRef

Buetti-Dinh A, Jensen R, Friedman R. A computational study of hedgehog signalling involved in basal cell carcinoma reveals the potential and limitation of combination therapy. BMC Cancer. 2018; 18(1):569. https://doi.org/10.1186/s12885-018-4451-1.PubMedPubMedCentralCrossRef

Buetti-Dinh A, Friedman R. Computer simulations of the signalling network in FLT3 +-acute myeloid leukaemia – indications for an optimal dosage of inhibitors against FLT3 and CDK6. BMC Bioinf. 2018; 19(1):155. https://doi.org/10.1186/s12859-018-2145-y.CrossRef

Deininger MW, Hodgson JG, Shah NP, Cortes JE, Kim D-W, Nicolini FE, Talpaz M, Baccarani M, Müller MC, Li J, Parker WT, Lustgarten S, Clackson T, Haluska FG, Guilhot F, Kantarjian HM, Soverini S, Hochhaus A, Hughes TP, Rivera VM, Branford S. Compound mutations in BCR-ABL1 are not major drivers of primary or secondary resistance to ponatinib in CP-CML patients. Blood. 2016; 127(6):703–12. https://doi.org/10.1182/blood-2015-08-660977. http://arxiv.org/abs/http://www.bloodjournal.org/content/127/6/703.full.pdf.PubMedPubMedCentralCrossRef

Zabriskie MS, Eide CA, Tantravahi SK, Vellore NA, Estrada J, Nicolini FE, Khoury HJ, Larson RA, Konopleva M, Cortes JE, Kantarjian H, Jabbour EJ, Kornblau SM, Lipton JH, Rea D, Stenke L, Barbany G, Lange T, Hernández-Boluda J-C, Ossenkoppele GJ, Press RD, Chuah C, Goldberg SL, Wetzler M, Mahon F-X, Etienne G, Baccarani M, Soverini S, Rosti G, Rousselot P, Friedman R, Deininger M, Reynolds KR, Heaton WL, Eiring AM, Pomicter AD, Khorashad JS, Kelley TW, Baron R, Druker BJ, Deininger MW, O’Hare T. BCR-ABL1 compound mutations combining key kinase domain positions confer clinical resistance to ponatinib in Ph chromosome-positive leukemia. Cancer Cell. 2014; 26(3):428–42. https://doi.org/10.1016/j.ccr.2014.07.006.PubMedPubMedCentralCrossRef

10.

Pemovska T, Johnson E, Kontro M, Repasky GA, Chen J, Wells P, Cronin CN, McTigue M, Kallioniemi O, Porkka K, Murray BW, Wennerberg K. Axitinib effectively inhibits BCR-ABL1(T315I) with a distinct binding conformation. Nature. 2015; 519(7541):102–5. https://doi.org/10.1038/nature14119.PubMedCrossRef

11.

Byrgazov K, Lucini CB, Valent P, Hantschel O, Lion T. BCR-ABL1 compound mutants display differential and dose-dependent responses to ponatinib. Haematologica. 2017; 103(1):10–2. https://doi.org/10.3324/haematol.2017.176347.CrossRef

12.

Komarova NL, Katouli AA, Wodarz D. Combination of two but not three current targeted drugs can improve therapy of chronic myeloid leukemia. PLoS ONE. 2009; 4(2):4423. https://doi.org/10.1371/journal.pone.0004423.CrossRef

13.

Zhang J, Adrián FJ, Jahnke W, Cowan-Jacob SW, Li AG, Iacob RE, Sim T, Powers J, Dierks C, Sun F, Guo G-R, Ding Q, Okram B, Choi Y, Wojciechowski A, Deng X, Liu G, Fendrich G, Strauss A, Vajpai N, Grzesiek S, Tuntland T, Liu Y, Bursulaya B, Azam M, Manley PW, Engen JR, Daley GQ, Warmuth M, Gray NS. Targeting bcr–abl by combining allosteric with ATP-binding-site inhibitors. Nature. 2010; 463(7280):501–6. https://doi.org/10.1038/nature08675.PubMedPubMedCentralCrossRef

14.

Schoepfer J, Jahnke W, Berellini G, Buonamici S, Cotesta S, Cowan-Jacob SW, Dodd S, Drueckes P, Fabbro D, Gabriel T, Groell J-M, Grotzfeld RM, Hassan AQ, Henry C, Iyer V, Jones D, Lombardo F, Loo A, Manley PW, Pellé X, Rummel G, Salem B, Warmuth M, Wylie AA, Zoller T, Marzinzik AL, Furet P. Discovery of asciminib (ABL001), an allosteric inhibitor of the tyrosine kinase activity of BCR-ABL1. J Med Chem. 2018; 61(18):8120–35. https://doi.org/10.1021/acs.jmedchem.8b01040. PMID: 30137981. http://arxiv.org/abs/https://doi.org/10.1021/acs.jmedchem.8b01040.PubMedCrossRef

15.

Wylie AA, Schoepfer J, Jahnke W, Cowan-Jacob SW, Loo A, Furet P, Marzinzik AL, Pelle X, Donovan J, Zhu W, Buonamici S, Hassan AQ, Lombardo F, Iyer V, Palmer M, Berellini G, Dodd S, Thohan S, Bitter H, Branford S, Ross DM, Hughes TP, Petruzzelli L, Vanasse KG, Warmuth M, Hofmann F, Keen NJ, Sellers WR. The allosteric inhibitor ABL001 enables dual targeting of BCR–ABL1. Nature. 2017; 543(7647):733–7. https://doi.org/10.1038/nature21702.PubMedCrossRef

16.

Eide CA, Zabriskie MS, Stevens SLS, Antelope O, Vellore NA, Than H, Schultz AR, Clair P, Bowler AD, Pomicter AD, Yan D, Senina AV, Qiang W, Kelley TW, Szankasi P, Heinrich MC, Tyner JW, Rea D, Cayuela J-M, Kim D-W, Tognon CE, O’Hare T, Druker BJ, Deininger MW. Combining the allosteric inhibitor asciminib with ponatinib suppresses emergence of and restores efficacy against highly resistant bcr-abl1 mutants. Cancer Cell. 2019; 36(4):431–4435. https://doi.org/10.1016/j.ccell.2019.08.004.PubMedPubMedCentralCrossRef

17.

Katouli AA, Komarova NL. Optimizing combination therapies with existing and future CML drugs. PLoS ONE. 2010; 5(8):12300. https://doi.org/10.1371/journal.pone.0012300.CrossRef

18.

Hegreness M, Shoresh N, Damian D, Hartl D, Kishony R. Accelerated evolution of resistance in multidrug environments. Proc Natl Acad Sci. 2008; 105(37):13977–81. https://doi.org/10.1073/pnas.0805965105.PubMedCrossRefPubMedCentral

19.

Lindström HJG, de Wijn AS, Friedman R. Stochastic modelling of tyrosine kinase inhibitor rotation therapy in chronic myeloid leukaemia. BMC Cancer. 2019; 19(1):508. https://doi.org/10.1186/s12885-019-5690-5.PubMedPubMedCentralCrossRef

20.

Shah NP, Skaggs BJ, Branford S, Hughes TP, Nicoll JM, Paquette RL, Sawyers CL. Sequential ABL kinase inhibitor therapy selects for compound drug-resistant BCR-ABL mutations with altered oncogenic potency. J Clin Invest. 2007; 117(9):2562–9. https://doi.org/10.1172/jci30890.PubMedPubMedCentralCrossRef

21.

Leder K, Foo J, Skaggs B, Gorre M, Sawyers CL, Michor F. Fitness conferred by BCR-ABL kinase domain mutations determines the risk of pre-existing resistance in chronic myeloid leukemia. PLoS ONE. 2011; 6(11):27682. https://doi.org/10.1371/journal.pone.0027682.CrossRef

22.

Preziosi L. Cancer modelling and simulation. Boca Raton: CRC Press; 2003.CrossRef

23.

Friedman R, Boye K, Flatmark K. Molecular modelling and simulations in cancer research. Biochim Biophys Acta (BBA) Rev Cancer. 2013; 1836(1):1–14. https://doi.org/10.1016/j.bbcan.2013.02.001.CrossRef

24.

Metzcar J, Wang Y, Heiland R, Macklin P. A review of cell-based computational modeling in cancer biology. JCO Clin Cancer Inform. 2019; 3:1–13. https://doi.org/10.1200/cci.18.00069. PMID: 30715927. http://arxiv.org/abs/https://doi.org/10.1200/CCI.18.00069.PubMedCrossRef

25.

Buetti-Dinh A, Pivkin IV, Friedman R. S100A4 and its role in metastasis – simulations of knockout and amplification of epithelial growth factor receptor and matrix metalloproteinases. Mol BioSyst. 2015; 11(8):2247–54. https://doi.org/10.1039/c5mb00302d.PubMedCrossRef

26.

Buetti-Dinh A, O’Hare T, Friedman R. Sensitivity analysis of the NPM-ALK signalling network reveals important pathways for anaplastic large cell lymphoma combination therapy. PLoS ONE. 2016; 11(9):0163011. https://doi.org/10.1371/journal.pone.0163011.CrossRef

27.

Mumenthaler SM, Foo J, Leder K, Choi NC, Agus DB, Pao W, Mallick P, Michor F. Evolutionary modeling of combination treatment strategies to overcome resistance to tyrosine kinase inhibitors in non-small cell lung cancer. Mol Pharm. 2011; 8(6):2069–79. https://doi.org/10.1021/mp200270v. PMID: 21995722. http://arxiv.org/abs/https://doi.org/10.1021/mp200270v.PubMedPubMedCentralCrossRef

28.

Chakrabarti S, Michor F. Pharmacokinetics and drug interactions determine optimum combination strategies in computational models of cancer evolution. Cancer Res. 2017; 77(14):3908–21. https://doi.org/10.1158/0008-5472.can-16-2871. http://cancerres.aacrjournals.org/content/early/2017/06/30/0008-5472.CAN-16-2871.full.pdf.

29.

Kaveh K, Takahashi Y, Farrar MA, Storme G, Guido M, Piepenburg J, Penning J, Foo J, Leder KZ, Hui SK. Combination therapeutics of nilotinib and radiation in acute lymphoblastic leukemia as an effective method against drug-resistance. PLoS Comput Biol. 2017; 13(7):1005482. https://doi.org/10.1371/journal.pcbi.1005482.CrossRef

30.

Chou T-C, Talalay P. Generalized equations for the analysis of inhibitions of michaelis-menten and higher-order kinetic systems with two or more mutually exclusive and nonexclusive inhibitors. Eur J Biochem. 2005; 115(1):207–16. https://doi.org/10.1111/j.1432-1033.1981.tb06218.x. https://febs.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1432-1033.1981.tb06218.x.

31.

Chou T-C, Talalay P. Quantitative analysis of dose-effect relationships: The combined effects of multiple drugs or enzyme inhibitors. Adv Enzyme Regul. 1984; 22:27–55. https://doi.org/10.1016/0065-2571(84)90007-4.PubMedCrossRef

32.

Soverini S, Rosti G, Iacobucci I, Baccarani M, Martinelli G. Choosing the best second-line tyrosine kinase inhibitor in imatinib-resistant chronic myeloid leukemia patients harboring bcr-abl kinase domain mutations: How reliable is the IC 50 ?. Oncologist. 2011; 16(6):868–76. https://doi.org/10.1634/theoncologist.2010-0388. http://theoncologist.alphamedpress.org/content/16/6/868.full.pdf+html.

33.

Zabriskie MS, Eide CA, Yan D, Vellore NA, Pomicter AD, Savage SL, Druker BJ, Deininger MW, O’Hare T. Extreme mutational selectivity of axitinib limits its potential use as a targeted therapeutic for BCR-ABL1-positive leukemia. Leukemia. 2015; 30(6):1418–21. https://doi.org/10.1038/leu.2015.318.PubMedPubMedCentralCrossRef

34.

Redaelli S, Mologni L, Rostagno R, Piazza R, Magistroni V, Ceccon M, Viltadi M, Flynn D, Gambacorti-Passerini C. Three novel patient-derived BCR/ABL mutants show different sensitivity to second and third generation tyrosine kinase inhibitors. Am J Hematol. 2012; 87(11):125–8. https://doi.org/10.1002/ajh.23338. http://arxiv.org/abs/https://onlinelibrary.wiley.com/doi/pdf/10.1002/ajh.23338.CrossRef

35.

Deguchi Y, Kimura S, Ashihara E, Niwa T, Hodohara K, Fujiyama Y, Maekawa T. Comparison of imatinib, dasatinib, nilotinib and INNO-406 in imatinib-resistant cell lines. Leuk Res. 2008; 32(6):980–3. https://doi.org/10.1016/j.leukres.2007.11.008.PubMedCrossRef

36.

O’Hare T, Walters DK, Stoffregen EP, Jia T, Manley PW, Mestan J, Cowan-Jacob SW, Lee FY, Heinrich MC, Deininger MWN, Druker BJ. In vitroActivity of bcr-abl inhibitors AMN107 and BMS-354825 against clinically relevant imatinib-resistant abl kinase domain mutants. Cancer Res. 2005; 65(11):4500–5. https://doi.org/10.1158/0008-5472.can-05-0259. http://arxiv.org/abs/http://cancerres.aacrjournals.org/content/65/11/4500.full.pdf.PubMedCrossRef

37.

O’Hare T, Shakespeare WC, Zhu X, Eide CA, Rivera VM, Wang F, Adrian LT, Zhou T, Huang W-S, Xu Q, Metcalf CA, Tyner JW, Loriaux MM, Corbin AS, Wardwell S, Ning Y, Keats JA, Wang Y, Sundaramoorthi R, Thomas M, Zhou D, Snodgrass J, Commodore L, Sawyer TK, Dalgarno DC, Deininger MWN, Druker BJ, Clackson T. AP24534, a pan-BCR-ABL inhibitor for chronic myeloid leukemia, potently inhibits the T315I mutant and overcomes mutation-based resistance. Cancer Cell. 2009; 16(5):401–12. https://doi.org/10.1016/j.ccr.2009.09.028.PubMedPubMedCentralCrossRef

38.

Shah NP, Nicoll JM, Nagar B, Gorre ME, Paquette RL, Kuriyan J, Sawyers CL. Multiple BCR-ABL kinase domain mutations confer polyclonal resistance to the tyrosine kinase inhibitor imatinib (STI571) in chronic phase and blast crisis chronic myeloid leukemia. Cancer Cell. 2002; 2(2):117–25. https://doi.org/10.1016/s1535-6108(02)00096-x.PubMedCrossRef

39.

Azam M, Latek RR, Daley GQ. Mechanisms of autoinhibition and STI-571/imatinib resistance revealed by mutagenesis of BCR-ABL. Cell. 2003; 112(6):831–43. https://doi.org/10.1016/s0092-8674(03)00190-9.

40.

Weisberg E, Manley PW, Breitenstein W, Brüggen J, Cowan-Jacob SW, Ray A, Huntly B, Fabbro D, Fendrich G, Hall-Meyers E, Kung AL, Mestan J, Daley GQ, Callahan L, Catley L, Cavazza C, Mohammed A, Neuberg D, Wright RD, Gilliland DG, Griffin JD. Characterization of AMN107, a selective inhibitor of native and mutant bcr-abl. Cancer Cell. 2005; 7(2):129–41. https://doi.org/10.1016/j.ccr.2005.01.007.PubMedCrossRef

41.

Burgess MR, Skaggs BJ, Shah NP, Lee FY, Sawyers CL. Comparative analysis of two clinically active BCR-ABL kinase inhibitors reveals the role of conformation-specific binding in resistance. Proc Natl Acad Sci. 2005; 102(9):3395–400. https://doi.org/10.1073/pnas.0409770102. http://arxiv.org/abs/https://www.pnas.org/content/102/9/3395.full.pdf.PubMedCrossRefPubMedCentral

42.

Manley PW, Cowan-Jacob SW, Mestan J. Advances in the structural biology, design and clinical development of bcr-abl kinase inhibitors for the treatment of chronic myeloid leukaemia. Biochim Biophys Acta (BBA) Proteins Proteomics. 2005; 1754(1-2):3–13. https://doi.org/10.1016/j.bbapap.2005.07.040. Inhibitors of Protein Kinases (4th International Conference, Inhibitors of Protein Kinases) and Associated Workshop: Modelling of Specific Molecular Recognition Processes (Warsaw, Poland, June 25-29, 2005).CrossRef

43.

Ray A, Cowan-Jacob SW, Manley PW, Mestan J, Griffin JD. Identification of BCR-ABL point mutations conferring resistance to the abl kinase inhibitor AMN107 (nilotinib) by a random mutagenesis study. Blood. 2007; 109(11):5011–5. https://doi.org/10.1182/blood-2006-01-015347. http://arxiv.org/abs/http://www.bloodjournal.org/content/109/11/5011.full.pdf.PubMedCrossRef

44.

Byrgazov K, Lucini CB, Berkowitsch B, Koenig M, Haas OA, Hoermann G, Valent P, Lion T. Transposon-mediated generation of bcr-abl1-expressing transgenic cell lines for unbiased sensitivity testing of tyrosine kinase inhibitors. Oncotarget. 2016; 7(47):78083–94. https://doi.org/10.18632/oncotarget.12943.PubMedPubMedCentralCrossRef

45.

Dhillon S, Gill K. Basic pharmacokinetics. London: Clinical Phrmokinetics, Pharmaceutical Press; 2006.

46.

McElreath R. Statistical Rethinking: Chapman and Hall/CRC; 2018. https://doi.org/10.1201/9781315372495.

47.

Carpenter B, Gelman A, Hoffman MD, Lee D, Goodrich B, Betancourt M, Brubaker M, Guo J, Li P, Riddell A. Stan: A probabilistic programming language. J Stat Soft. 2017; 76(1):1–32. https://doi.org/10.18637/jss.v076.i01.

48.

Vainstein V, Eide CA, O’Hare T, Shukron O, Druker BJ. Integrating in vitro sensitivity and dose-response slope is predictive of clinical response to ABL kinase inhibitors in chronic myeloid leukemia. Blood. 2013; 122(19):3331–4. https://doi.org/10.1182/blood-2012-08-452409.PubMedPubMedCentralCrossRef

49.

Peng B, Lloyd P, Schran H. Clinical pharmacokinetics of imatinib. Clin Pharmacokinet. 2005; 44(9):879–94. https://doi.org/10.2165/00003088-200544090-00001.PubMedCrossRef

50.

Zhou L, Meng F, Yin O, Wang J, Wang Y, Wei Y, Hu P, Shen Z. Nilotinib for imatinib-resistant or -intolerant chronic myeloid leukemia in chronic phase, accelerated phase, or blast crisis: A single- and multiple-dose, open-label pharmacokinetic study in Chinese patients. Clin Ther. 2009; 31(7):1568–75. https://doi.org/10.1016/j.clinthera.2009.07.016.PubMedCrossRef

51.

Demetri GD, Lo Russo P, MacPherson IRJ, Wang D, Morgan JA, Brunton VG, Paliwal P, Agrawal S, Voi M, Evans TRJ. Phase i dose-escalation and pharmacokinetic study of dasatinib in patients with advanced solid tumors. Clin Cancer Res. 2009; 15(19):6232–40. https://doi.org/10.1158/1078-0432.ccr-09-0224.PubMedCrossRef

52.

Abbas R, Hsyu P-H. Clinical pharmacokinetics and pharmacodynamics of bosutinib. Clin Pharmacokinet. 2016; 55(10):1191–204. https://doi.org/10.1007/s40262-016-0391-6.PubMedCrossRef

53.

Cortes JE, Kantarjian H, Shah NP, Bixby D, Mauro MJ, Flinn I, O’Hare T, Hu S, Narasimhan NI, Rivera VM, Clackson T, Turner CD, Haluska FG, Druker BJ, Deininger MWN, Talpaz M. Ponatinib in refractory Philadelphia chromosome–positive leukemias. N Engl J Med. 2012; 367(22):2075–88. https://doi.org/10.1056/nejmoa1205127. PMID: 23190221. http://arxiv.org/abs/https://doi.org/10.1056/NEJMoa1205127.PubMedPubMedCentralCrossRef

54.

Smith BJ, Pithavala Y, Bu H-Z, Kang P, Hee B, Deese AJ, Pool WF, Klamerus KJ, Wu EY, Dalvie DK. Pharmacokinetics, metabolism, and excretion of [14C]Axitinib, a vascular endothelial growth factor receptor tyrosine kinase inhibitor, in humans. Drug Metab Dispos. 2014; 42(5):918–31. https://doi.org/10.1124/dmd.113.056531. http://arxiv.org/abs/http://dmd.aspetjournals.org/content/42/5/918.full.pdf.PubMedCrossRef

55.

Menssen HD, Quinlan M, Kemp C, Tian X. Relative bioavailability and food effect evaluation for 2 tablet formulations of asciminib in a 2-arm, crossover, randomized, open-label study in healthy volunteers. Clin Pharmacol Drug Dev. 2018; 8(3):385–94. https://doi.org/10.1002/cpdd.602. http://arxiv.org/abs/https://accp1.onlinelibrary.wiley.com/doi/pdf/10.1002/cpdd.602.PubMedCrossRef

56.

Pharmaceutical Specialists in Sweden (FASS). http://fass.se. Accessed 20 Jan 2019.

57.

Michor F, Hughes TP, Iwasa Y, Branford S, Shah NP, Sawyers CL, Nowak MA. Dynamics of chronic myeloid leukaemia. Nature. 2005; 435(7046):1267–70. https://doi.org/10.1038/nature03669.PubMedCrossRef

58.

Molica M, Scalzulli E, Colafigli G, Foà R, Breccia M. Insights into the optimal use of ponatinib in patients with chronic phase chronic myeloid leukaemia. Ther Adv Hematol. 2019; 10:204062071982644. https://doi.org/10.1177/2040620719826444. http://arxiv.org/abs/https://doi.org/10.1177/2040620719826444.CrossRef

59.

Qiang W, Antelope O, Zabriskie MS, Pomicter AD, Vellore NA, Szankasi P, Rea D, Cayuela JM, Kelley TW, Deininger MW, O’Hare T. Mechanisms of resistance to the BCR-ABL1 allosteric inhibitor asciminib. Leukemia. 2017; 31(12):2844–7. https://doi.org/10.1038/leu.2017.264.PubMedCrossRefPubMedCentral

60.

Sen R, Natarajan K, Bhullar J, Shukla S, Fang H-B, Cai L, Chen Z-S, Ambudkar SV, Baer MR. The novel BCR-ABL and FLT3 inhibitor ponatinib is a potent inhibitor of the MDR-associated ATP-binding cassette transporter ABCG2. Mol Cancer Ther. 2012; 11(9):2033–44. https://doi.org/10.1158/1535-7163.mct-12-0302. http://arxiv.org/abs/http://mct.aacrjournals.org/content/11/9/2033.full.pdf.PubMedPubMedCentralCrossRef

61.

Sampah MES, Shen L, Jilek BL, Siliciano RF. Dose-response curve slope is a missing dimension in the analysis of HIV-1 drug resistance. Proc Natl Acad Sci. 2011; 108(18):7613–8. https://doi.org/10.1073/pnas.1018360108. http://arxiv.org/abs/https://www.pnas.org/content/108/18/7613.full.pdf.PubMedCrossRefPubMedCentral

Title: The effects of combination treatments on drug resistance in chronic myeloid leukaemia: an evaluation of the tyrosine kinase inhibitors axitinib and asciminib
Authors: H. Jonathan G. Lindström
Ran Friedman
Publication date: 01-12-2020
Publisher: BioMed Central
Keywords: Tyrosine Kinase Inhibitors
Targeted Therapy
Tyrosine Kinase Inhibitors
Axitinib
Bosutinib
Dasatinib
Imatinib
Nilotinib
Ponatinib
Chronic Myeloid Leukemia
Published in: BMC Cancer / Issue 1/2020
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-020-06782-9

Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras

Prof. Fabrice Barlesi

Developed by: Springer Medicine

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2020

NR2F2 plays a major role in insulin-induced epithelial-mesenchymal transition in breast cancer cells

Components of metabolic syndrome in patients with multiple myeloma and smoldering multiple myeloma

Effectiveness of the AJCC 8th edition staging system for selecting patients with T1–2N1 breast cancer for post-mastectomy radiotherapy: a joint analysis of 1986 patients from two institutions

Outcomes of patients with initially locally advanced pancreatic adenocarcinoma who did not benefit from resection: a prospective cohort study

Assessing how health information needs of individuals with colorectal cancer are met across the care continuum: an international cross-sectional survey

Three-year outcome after transanal versus laparoscopic total mesorectal excision in locally advanced rectal cancer: a multicenter comparative analysis

Keynote webinar | Spotlight on antibody–drug conjugates in cancer