{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T06:52:34Z","timestamp":1793170354179,"version":"4.5.0"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T00:00:00Z","timestamp":1756080000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T00:00:00Z","timestamp":1756080000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["R01 CA241137"],"award-info":[{"award-number":["R01 CA241137"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CMMI-2228034"],"award-info":[{"award-number":["CMMI-2228034"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Syst Biol Appl"],"DOI":"10.1038\/s41540-025-00571-5","type":"journal-article","created":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T02:57:02Z","timestamp":1756090622000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Optimal dosing of anti-cancer treatment under drug-induced plasticity"],"prefix":"10.1038","volume":"11","author":[{"given":"Einar Bjarki","family":"Gunnarsson","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benedikt Vilji","family":"Magn\u00fasson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jasmine","family":"Foo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,25]]},"reference":[{"key":"571_CR1","doi-asserted-by":"publisher","first-page":"924","DOI":"10.1038\/nrc2013","volume":"6","author":"LM Merlo","year":"2006","unstructured":"Merlo, L. M., Pepper, J. W., Reid, B. J. & Maley, C. C. Cancer as an evolutionary and ecological process. Nat. Rev. Cancer 6, 924 (2006).","journal-title":"Nat. Rev. Cancer"},{"key":"571_CR2","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1158\/2159-8290.CD-15-0439","volume":"5","author":"M Greaves","year":"2015","unstructured":"Greaves, M. Evolutionary determinants of cancer. Cancer Discov. 5, 806\u2013820 (2015).","journal-title":"Cancer Discov."},{"key":"571_CR3","doi-asserted-by":"publisher","first-page":"eaal2380","DOI":"10.1126\/science.aal2380","volume":"357","author":"WA Flavahan","year":"2017","unstructured":"Flavahan, W. A., Gaskell, E. & Bernstein, B. E. Epigenetic plasticity and the hallmarks of cancer. Science 357, eaal2380 (2017).","journal-title":"Science"},{"key":"571_CR4","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1016\/j.cell.2007.01.029","volume":"128","author":"PA Jones","year":"2007","unstructured":"Jones, P. A. & Baylin, S. B. The epigenomics of cancer. Cell 128, 683\u2013692 (2007).","journal-title":"Cell"},{"key":"571_CR5","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1038\/nrg2556","volume":"10","author":"A Brock","year":"2009","unstructured":"Brock, A., Chang, H. & Huang, S. Non-genetic heterogeneity\u2014a mutation-independent driving force for the somatic evolution of tumours. Nat. Rev. Genet. 10, 336 (2009).","journal-title":"Nat. Rev. Genet."},{"key":"571_CR6","doi-asserted-by":"publisher","first-page":"S43","DOI":"10.1016\/S1471-4914(02)02314-6","volume":"8","author":"R Brown","year":"2002","unstructured":"Brown, R. & Strathdee, G. Epigenomics and epigenetic therapy of cancer. Trends Mol. Med. 8, S43\u2013S48 (2002).","journal-title":"Trends Mol. Med."},{"key":"571_CR7","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.cell.2010.02.027","volume":"141","author":"SV Sharma","year":"2010","unstructured":"Sharma, S. V. et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell 141, 69\u201380 (2010).","journal-title":"Cell"},{"key":"571_CR8","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms7139","volume":"6","author":"A Goldman","year":"2015","unstructured":"Goldman, A. et al. Temporally sequenced anticancer drugs overcome adaptive resistance by targeting a vulnerable chemotherapy-induced phenotypic transition. Nat. Commun. 6, 6139 (2015).","journal-title":"Nat. Commun."},{"key":"571_CR9","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms10690","volume":"7","author":"M Ramirez","year":"2016","unstructured":"Ramirez, M. et al. Diverse drug-resistance mechanisms can emerge from drug-tolerant cancer persister cells. Nat. Commun. 7, 10690 (2016).","journal-title":"Nat. Commun."},{"key":"571_CR10","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1038\/nm.4040","volume":"22","author":"AN Hata","year":"2016","unstructured":"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\u2013269 (2016).","journal-title":"Nat. Med."},{"key":"571_CR11","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1038\/nature22794","volume":"546","author":"SM Shaffer","year":"2017","unstructured":"Shaffer, S. M. et al. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546, 431 (2017).","journal-title":"Nature"},{"key":"571_CR12","doi-asserted-by":"publisher","first-page":"13679","DOI":"10.1073\/pnas.1712064115","volume":"114","author":"Y Su","year":"2017","unstructured":"Su, Y. et al. Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance. Proc. Natl. Acad. Sci. USA 114, 13679\u201313684 (2017).","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"571_CR13","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1016\/j.cell.2019.06.024","volume":"178","author":"C Neftel","year":"2019","unstructured":"Neftel, C. et al. An integrative model of cellular states, plasticity, and genetics for glioblastoma. Cell 178, 835\u2013849 (2019).","journal-title":"Cell"},{"key":"571_CR14","doi-asserted-by":"publisher","first-page":"110162","DOI":"10.1016\/j.jtbi.2020.110162","volume":"490","author":"EB Gunnarsson","year":"2020","unstructured":"Gunnarsson, E. B., De, S., Leder, K. & Foo, J. Understanding the role of phenotypic switching in cancer drug resistance. J. Theor. Biol. 490, 110162 (2020).","journal-title":"J. Theor. Biol."},{"key":"571_CR15","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms3467","volume":"4","author":"AO Pisco","year":"2013","unstructured":"Pisco, A. O. et al. Non-darwinian dynamics in therapy-induced cancer drug resistance. Nat. Commun. 4, 2467 (2013).","journal-title":"Nat. Commun."},{"key":"571_CR16","doi-asserted-by":"crossref","unstructured":"Vipparthi, K. et al. Emergence of hybrid states of stem-like cancer cells correlates with poor prognosis in oral cancer. IScience 25, 104317 (2022).","DOI":"10.1016\/j.isci.2022.104317"},{"key":"571_CR17","doi-asserted-by":"publisher","first-page":"976","DOI":"10.1038\/s41588-022-01105-z","volume":"54","author":"M Russo","year":"2022","unstructured":"Russo, M. et al. A modified fluctuation-test framework characterizes the population dynamics and mutation rate of colorectal cancer persister cells. Nat. Genet. 54, 976\u2013984 (2022).","journal-title":"Nat. Genet."},{"key":"571_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13059-016-0963-7","volume":"17","author":"B Szikriszt","year":"2016","unstructured":"Szikriszt, B. et al. A comprehensive survey of the mutagenic impact of common cancer cytotoxics. Genome Biol. 17, 1\u201316 (2016).","journal-title":"Genome Biol."},{"key":"571_CR19","doi-asserted-by":"publisher","first-page":"a026617","DOI":"10.1101\/cshperspect.a026617","volume":"7","author":"S Venkatesan","year":"2017","unstructured":"Venkatesan, S., Swanton, C., Taylor, B. S. & Costello, J. F. Treatment-induced mutagenesis and selective pressures sculpt cancer evolution. Cold Spring Harb. Perspect. Med. 7, a026617 (2017).","journal-title":"Cold Spring Harb. Perspect. Med."},{"key":"571_CR20","doi-asserted-by":"publisher","first-page":"1473","DOI":"10.1126\/science.aav4474","volume":"366","author":"M Russo","year":"2019","unstructured":"Russo, M. et al. Adaptive mutability of colorectal cancers in response to targeted therapies. Science 366, 1473\u20131480 (2019).","journal-title":"Science"},{"key":"571_CR21","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.1126\/science.aau8768","volume":"368","author":"A Cipponi","year":"2020","unstructured":"Cipponi, A. et al. Mtor signaling orchestrates stress-induced mutagenesis, facilitating adaptive evolution in cancer. Science 368, 1127\u20131131 (2020).","journal-title":"Science"},{"key":"571_CR22","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1038\/nrc1369","volume":"4","author":"RS Kerbel","year":"2004","unstructured":"Kerbel, R. S. & Kamen, B. A. The anti-angiogenic basis of metronomic chemotherapy. Nat. Rev. Cancer 4, 423\u2013436 (2004).","journal-title":"Nat. Rev. Cancer"},{"key":"571_CR23","first-page":"163","volume":"70","author":"L Norton","year":"1986","unstructured":"Norton, L. The Norton-Simon hypothesis revisited. Cancer Treat. Rep. 70, 163\u2013169 (1986).","journal-title":"Cancer Treat. Rep."},{"key":"571_CR24","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1038\/nrc3819","volume":"14","author":"R Brown","year":"2014","unstructured":"Brown, R., Curry, E., Magnani, L., Wilhelm-Benartzi, C. S. & Borley, J. Poised epigenetic states and acquired drug resistance in cancer. Nat. Rev. Cancer 14, 747\u2013753 (2014).","journal-title":"Nat. Rev. Cancer"},{"key":"571_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1200\/CCI.18.00087","volume":"3","author":"JM Greene","year":"2019","unstructured":"Greene, J. M., Gevertz, J. L. & Sontag, E. D. Mathematical approach to differentiate spontaneous and induced evolution to drug resistance during cancer treatment. JCO Clin. Cancer Inform. 3, 1\u201320 (2019).","journal-title":"JCO Clin. Cancer Inform."},{"key":"571_CR26","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.jtbi.2019.05.005","volume":"474","author":"AR Akhmetzhanov","year":"2019","unstructured":"Akhmetzhanov, A. R. et al. Modelling bistable tumour population dynamics to design effective treatment strategies. J. Theor. Biol. 474, 88\u2013102 (2019).","journal-title":"J. Theor. Biol."},{"key":"571_CR27","doi-asserted-by":"publisher","first-page":"501","DOI":"10.3389\/fbioe.2020.00501","volume":"8","author":"JM Greene","year":"2020","unstructured":"Greene, J. M., Sanchez-Tapia, C. & Sontag, E. D. Mathematical details on a cancer resistance model. Front. Bioeng. Biotechnol. 8, 501 (2020).","journal-title":"Front. Bioeng. Biotechnol."},{"key":"571_CR28","doi-asserted-by":"publisher","first-page":"e1009418","DOI":"10.1371\/journal.pcbi.1009418","volume":"17","author":"T Kuosmanen","year":"2021","unstructured":"Kuosmanen, T. et al. Drug-induced resistance evolution necessitates less aggressive treatment. PLoS Comput. Biol. 17, e1009418 (2021).","journal-title":"PLoS Comput. Biol."},{"key":"571_CR29","doi-asserted-by":"publisher","first-page":"e1010319","DOI":"10.1371\/journal.pcbi.1010319","volume":"18","author":"E Angelini","year":"2022","unstructured":"Angelini, E., Wang, Y., Zhou, J. X., Qian, H. & Huang, S. A model for the intrinsic limit of cancer therapy: duality of treatment-induced cell death and treatment-induced stemness. PLOS Comput. Biol. 18, e1010319 (2022).","journal-title":"PLOS Comput. Biol."},{"key":"571_CR30","doi-asserted-by":"publisher","first-page":"023018","DOI":"10.1103\/mh5v-lcyw","volume":"3","author":"M Corigliano","year":"2025","unstructured":"Corigliano, M., Di Bernardo, A., Cosentino Lagomarsino, M. & Pompei, S. Optimal treatment for drug-induced cancer persisters involves release periods and intermediate drug doses. PRX Life 3, 023018 (2025).","journal-title":"PRX Life"},{"key":"571_CR31","doi-asserted-by":"publisher","first-page":"5427","DOI":"10.1038\/sj.onc.1205600","volume":"21","author":"M Esteller","year":"2002","unstructured":"Esteller, M. Cpg island hypermethylation and tumor suppressor genes: a booming present, a brighter future. Oncogene 21, 5427\u20135440 (2002).","journal-title":"Oncogene"},{"key":"571_CR32","doi-asserted-by":"publisher","first-page":"1152","DOI":"10.3389\/fonc.2020.01152","volume":"10","author":"S Romero-Garcia","year":"2020","unstructured":"Romero-Garcia, S., Prado-Garcia, H. & Carlos-Reyes, A. Role of DNA methylation in the resistance to therapy in solid tumors. Front. Oncol. 10, 1152 (2020).","journal-title":"Front. Oncol."},{"key":"571_CR33","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/S0092-8674(00)81656-6","volume":"99","author":"M Okano","year":"1999","unstructured":"Okano, M., Bell, D. W., Haber, D. A. & Li, E. Dna methyltransferases dnmt3a and dnmt3b are essential for de novo methylation and mammalian development. Cell 99, 247\u2013257 (1999).","journal-title":"Cell"},{"key":"571_CR34","doi-asserted-by":"publisher","first-page":"1148","DOI":"10.1056\/NEJMra072067","volume":"358","author":"M Esteller","year":"2008","unstructured":"Esteller, M. Epigenetics in cancer. N. Engl. J. Med. 358, 1148\u20131159 (2008).","journal-title":"N. Engl. J. Med."},{"key":"571_CR35","doi-asserted-by":"publisher","DOI":"10.1038\/s41698-021-00168-1","volume":"5","author":"GE Wensink","year":"2021","unstructured":"Wensink, G. E. et al. Patient-derived organoids as a predictive biomarker for treatment response in cancer patients. npj Precis. Oncol. 5, 30 (2021).","journal-title":"npj Precis. Oncol."},{"key":"571_CR36","doi-asserted-by":"crossref","unstructured":"Jiang, S. et al. An automated organoid platform with inter-organoid homogeneity and inter-patient heterogeneity. Cell Rep. Med. 1, 100161 (2020).","DOI":"10.1016\/j.xcrm.2020.100161"},{"key":"571_CR37","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-38832-8","volume":"14","author":"PJ Tebon","year":"2023","unstructured":"Tebon, P. J. et al. Drug screening at single-organoid resolution via bioprinting and interferometry. Nat. Commun. 14, 3168 (2023).","journal-title":"Nat. Commun."},{"key":"571_CR38","doi-asserted-by":"publisher","first-page":"5184","DOI":"10.1158\/0008-5472.CAN-14-0663","volume":"74","author":"AJ Walsh","year":"2014","unstructured":"Walsh, A. J. et al. Quantitative optical imaging of primary tumor organoid metabolism predicts drug response in breast cancer. Cancer Res. 74, 5184\u20135194 (2014).","journal-title":"Cancer Res."},{"key":"571_CR39","doi-asserted-by":"publisher","first-page":"e1012256","DOI":"10.1371\/journal.pcbi.1012256","volume":"20","author":"EB Gunnarsson","year":"2024","unstructured":"Gunnarsson, E. B. et al. Understanding patient-derived tumor organoid growth through an integrated imaging and mathematical modeling framework. PLoS Comput. Biol. 20, e1012256 (2024).","journal-title":"PLoS Comput. Biol."},{"key":"571_CR40","unstructured":"FDA Modernization Act 2.0. https:\/\/www.congress.gov\/bill\/117th-congress\/senate-bill\/5002\/text (2022)."},{"key":"571_CR41","doi-asserted-by":"crossref","unstructured":"Zushin, P.-J. H. et al. FDA modernization act 2.0: transitioning beyond animal models with human cells, organoids, and AI\/ML-based approaches. J. Clin. Investig. 133, 21(2023).","DOI":"10.1172\/JCI175824"},{"key":"571_CR42","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1161\/CIRCULATIONAHA.123.065585","volume":"148","author":"SM Ahmed","year":"2023","unstructured":"Ahmed, S. M., Shivnaraine, R. V. & Wu, J. C. FDA modernization act 2.0 paves the way to computational biology and clinical trials in a dish. Circulation 148, 309\u2013311 (2023).","journal-title":"Circulation"},{"key":"571_CR43","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1111\/j.1472-8206.2008.00633.x","volume":"22","author":"S Goutelle","year":"2008","unstructured":"Goutelle, S. et al. The Hill equation: a review of its capabilities in pharmacological modelling. Fundam. Clin. Pharmacol. 22, 633\u2013648 (2008).","journal-title":"Fundam. Clin. Pharmacol."},{"key":"571_CR44","doi-asserted-by":"publisher","first-page":"930","DOI":"10.1158\/0008-5472.CAN-14-2103","volume":"75","author":"RH Chisholm","year":"2015","unstructured":"Chisholm, R. H. et al. Emergence of drug tolerance in cancer cell populations: an evolutionary outcome of selection, nongenetic instability, and stress-induced adaptation. Cancer Res. 75, 930\u2013939 (2015).","journal-title":"Cancer Res."},{"key":"571_CR45","doi-asserted-by":"publisher","first-page":"2627","DOI":"10.1016\/j.bbagen.2016.06.009","volume":"1860","author":"RH Chisholm","year":"2016","unstructured":"Chisholm, R. H., Lorenzi, T. & Clairambault, J. Cell population heterogeneity and evolution towards drug resistance in cancer: biological and mathematical assessment, theoretical treatment optimisation. Biochim. Biophys. Acta (BBA)-Gen. Subj. 1860, 2627\u20132645 (2016).","journal-title":"Biochim. Biophys. Acta (BBA)-Gen. Subj."},{"key":"571_CR46","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1016\/j.matpur.2017.10.007","volume":"116","author":"C Pouchol","year":"2018","unstructured":"Pouchol, C., Clairambault, J., Lorz, A. & Tr\u00e9lat, E. Asymptotic analysis and optimal control of an integro-differential system modelling healthy and cancer cells exposed to chemotherapy. J. Math. Pures Appl. 116, 268\u2013308 (2018).","journal-title":"J. Math. Pures Appl."},{"key":"571_CR47","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1051\/m2an\/2019010","volume":"53","author":"L Almeida","year":"2019","unstructured":"Almeida, L., Bagnerini, P., Fabrini, G., Hughes, B. D. & Lorenzi, T. Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: insight from a phenotype-structured model. ESAIM Math. Model. Numer. Anal. 53, 1157\u20131190 (2019).","journal-title":"ESAIM Math. Model. Numer. Anal."},{"key":"571_CR48","doi-asserted-by":"publisher","first-page":"1314","DOI":"10.3390\/jcm9051314","volume":"9","author":"AM Jarrett","year":"2020","unstructured":"Jarrett, A. M. et al. Optimal control theory for personalized therapeutic regimens in oncology: Background, history, challenges, and opportunities. J. Clin. Med. 9, 1314 (2020).","journal-title":"J. Clin. Med."},{"key":"571_CR49","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1038\/459508a","volume":"459","author":"RA Gatenby","year":"2009","unstructured":"Gatenby, R. A. A change of strategy in the war on cancer. Nature 459, 508\u2013509 (2009).","journal-title":"Nature"},{"key":"571_CR50","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1038\/s41540-025-00560-8","volume":"11","author":"C Wu","year":"2025","unstructured":"Wu, C., Gunnarsson, E. B., Foo, J. & Leder, K. A statistical framework for detecting therapy-induced resistance from drug screens. npj Syst. Biol. Appl. 11, 88 (2025).","journal-title":"npj Syst. Biol. Appl."},{"key":"571_CR51","doi-asserted-by":"publisher","first-page":"111497","DOI":"10.1016\/j.jtbi.2023.111497","volume":"568","author":"EB Gunnarsson","year":"2023","unstructured":"Gunnarsson, E. B., Foo, J. & Leder, K. Statistical inference of the rates of cell proliferation and phenotypic switching in cancer. J. Theor. Biol. 568, 111497 (2023).","journal-title":"J. Theor. Biol."},{"key":"571_CR52","doi-asserted-by":"publisher","first-page":"6111","DOI":"10.1158\/0008-5472.CAN-13-0310","volume":"73","author":"MF McGuire","year":"2013","unstructured":"McGuire, M. F. et al. Formalizing an integrative, multidisciplinary cancer therapy discovery workflow. Cancer Res. 73, 6111\u20136117 (2013).","journal-title":"Cancer Res."},{"key":"571_CR53","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1200\/CCI.18.00068","volume":"3","author":"S Hamis","year":"2019","unstructured":"Hamis, S., Powathil, G. G. & Chaplain, M. A. Blackboard to bedside: a mathematical modeling bottom-up approach toward personalized cancer treatments. JCO Clin. Cancer Inform. 3, 1\u201311 (2019).","journal-title":"JCO Clin. Cancer Inform."},{"key":"571_CR54","unstructured":"Athreya, K. B. & Ney, P. E. Branching processes (Courier Corporation, 2004)."},{"key":"571_CR55","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1007\/s10589-011-9454-7","volume":"53","author":"M McAsey","year":"2012","unstructured":"McAsey, M., Mou, L. & Han, W. Convergence of the forward-backward sweep method in optimal control. Comput. Optim. Appl. 53, 207\u2013226 (2012).","journal-title":"Comput. Optim. Appl."},{"key":"571_CR56","unstructured":"Sharp, J. A.Numerical Methods for Optimal Control and Parameter Estimation in the Life Sciences. Ph.D. thesis, Queensland University of Technology (2022)."},{"key":"571_CR57","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1016\/j.cell.2010.04.020","volume":"141","author":"A Roesch","year":"2010","unstructured":"Roesch, A. et al. A temporarily distinct subpopulation of slow-cycling melanoma cells is required for continuous tumor growth. Cell 141, 583\u2013594 (2010).","journal-title":"Cell"},{"key":"571_CR58","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1016\/j.ccr.2013.05.003","volume":"23","author":"A Roesch","year":"2013","unstructured":"Roesch, A. et al. Overcoming intrinsic multidrug resistance in melanoma by blocking the mitochondrial respiratory chain of slow-cycling jarid1bhigh cells. Cancer Cell 23, 811\u2013825 (2013).","journal-title":"Cancer Cell"},{"key":"571_CR59","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1016\/j.cbpa.2009.09.015","volume":"13","author":"M Niepel","year":"2009","unstructured":"Niepel, M., Spencer, S. L. & Sorger, P. K. Non-genetic cell-to-cell variability and the consequences for pharmacology. Curr. Opin. Chem. Biol. 13, 556\u2013561 (2009).","journal-title":"Curr. Opin. Chem. Biol."},{"key":"571_CR60","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1038\/nature05316","volume":"444","author":"A Sigal","year":"2006","unstructured":"Sigal, A. et al. Variability and memory of protein levels in human cells. Nature 444, 643 (2006).","journal-title":"Nature"},{"key":"571_CR61","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1126\/science.1160165","volume":"322","author":"AA Cohen","year":"2008","unstructured":"Cohen, A. A. et al. Dynamic proteomics of individual cancer cells in response to a drug. Science 322, 1511\u20131516 (2008).","journal-title":"Science"},{"key":"571_CR62","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1016\/j.cell.2011.07.026","volume":"146","author":"PB Gupta","year":"2011","unstructured":"Gupta, P. B. et al. Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells. Cell 146, 633\u2013644 (2011).","journal-title":"Cell"},{"key":"571_CR63","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1016\/j.ifacol.2021.10.262","volume":"54","author":"S Paryad-Zanjani","year":"2021","unstructured":"Paryad-Zanjani, S., Saint-Antoine, M. M. & Singh, A. Optimal scheduling of therapy to delay cancer drug resistance. IFAC-PapersOnLine 54, 239\u2013244 (2021).","journal-title":"IFAC-PapersOnLine"},{"key":"571_CR64","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1146\/annurev-micro-091213-112852","volume":"69","author":"TM Norman","year":"2015","unstructured":"Norman, T. M., Lord, N. D., Paulsson, J. & Losick, R. Stochastic switching of cell fate in microbes. Annu. Rev. Microbiol. 69, 381\u2013403 (2015).","journal-title":"Annu. Rev. Microbiol."}],"container-title":["npj Systems Biology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41540-025-00571-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41540-025-00571-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41540-025-00571-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T13:38:17Z","timestamp":1757425097000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41540-025-00571-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,25]]},"references-count":64,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["571"],"URL":"https:\/\/doi.org\/10.1038\/s41540-025-00571-5","relation":{},"ISSN":["2056-7189"],"issn-type":[{"value":"2056-7189","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,25]]},"assertion":[{"value":"6 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"98"}}