Spatial competition constrains resistance to targeted cancer therapy

Adaptive therapy (AT) aims to control tumour burden by maintaining therapy-sensitive cells to exploit their competition with resistant cells. This relies on the assumption that resistant cells have impaired cellular fitness. Here, using a model of resistance to a pharmacological cyclin-dependent kinase inhibitor (CDKi), we show that this assumption is valid when competition between cells is spatially structured. We generate CDKi-resistant cancer cells and find that they have reduced proliferative fitness and stably rewired cell cycle control pathways. Low-dose CDKi outperforms high-dose CDKi in controlling tumour burden and resistance in tumour spheroids, but not in monolayer culture. Mathematical modelling indicates that tumour spatial structure amplifies the fitness penalty of resistant cells, and identifies their relative fitness as a critical determinant of the clinical benefit of AT. Our results justify further investigation of AT with kinase inhibitors.Adaptive therapy aims to control tumours by exploiting competition between therapy-sensitive and resistant cells. Here, the authors show that tumour spatial structure is a critical parameter for adaptive therapy as competition for space increases fitness differentials, allowing suppression of resistance with low-dose treatments.

[1]  F. Bunz,et al.  Cdk2 Is Required for p53-Independent G2/M Checkpoint Control , 2010, PLoS genetics.

[2]  S H Kim,et al.  Exploiting chemical libraries, structure, and genomics in the search for kinase inhibitors. , 1998, Science.

[3]  Robert J Gillies,et al.  Evolutionary approaches to prolong progression-free survival in breast cancer. , 2012, Cancer research.

[4]  D. Gillespie Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

[5]  G. Shapiro,et al.  Targeting CDK 4 and CDK 6 : From Discovery to Therapy , 2015 .

[6]  J. Cicenas,et al.  The CDK inhibitors in cancer research and therapy , 2011, Journal of Cancer Research and Clinical Oncology.

[7]  N. McGranahan,et al.  Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. , 2015, Cancer cell.

[8]  Juergen Friedrich,et al.  Spheroid-based drug screen: considerations and practical approach , 2009, Nature Protocols.

[9]  A. Musacchio,et al.  Molecular basis of drug resistance in aurora kinases. , 2008, Chemistry & biology.

[10]  Karl A. Merrick,et al.  Chemical-genetic analysis of cyclin dependent kinase 2 function reveals an important role in cellular transformation by multiple oncogenic pathways , 2012, Proceedings of the National Academy of Sciences.

[11]  Jane Fridlyand,et al.  Widespread potential for growth-factor-driven resistance to anticancer kinase inhibitors , 2012, Nature.

[12]  W. Kaelin,et al.  Selective killing of transformed cells by cyclin/cyclin-dependent kinase 2 antagonists. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[13]  H. Schättler,et al.  Application of mathematical models to metronomic chemotherapy: What can be inferred from minimal parameterized models? , 2017, Cancer Letters.

[14]  Karline Soetaert,et al.  Solving Differential Equations in R: Package deSolve , 2010 .

[15]  R. Gatenby A change of strategy in the war on cancer , 2009, Nature.

[16]  R. Gatenby,et al.  Adaptive vs continuous cancer therapy: Exploiting space and trade-offs in drug scheduling , 2017 .

[17]  B. Frieden,et al.  Adaptive therapy. , 2009, Cancer research.

[18]  N. Curtin,et al.  Preclinical in vitro and in vivo evaluation of the potent and specific cyclin-dependent kinase 2 inhibitor NU6102 and a water soluble prodrug NU6301. , 2011, European journal of cancer.

[19]  E. T. Gawlinski,et al.  A cellular automaton model of early tumor growth and invasion. , 2001, Journal of theoretical biology.

[20]  L. Butler,et al.  Therapeutic response to CDK4/6 inhibition in breast cancer defined by ex vivo analyses of human tumors , 2012, Cell cycle.

[21]  Robert J Woods,et al.  How to Use a Chemotherapeutic Agent When Resistance to It Threatens the Patient , 2017, PLoS biology.

[22]  G. Shapiro,et al.  Targeting CDK4 and CDK6: From Discovery to Therapy. , 2016, Cancer discovery.

[23]  Xin Huang,et al.  The cyclin-dependent kinase 4/6 inhibitor palbociclib in combination with letrozole versus letrozole alone as first-line treatment of oestrogen receptor-positive, HER2-negative, advanced breast cancer (PALOMA-1/TRIO-18): a randomised phase 2 study. , 2015, The Lancet. Oncology.

[24]  Pierre Dubus,et al.  Cdk1 is sufficient to drive the mammalian cell cycle , 2007, Nature.

[25]  F. McCormick,et al.  The RB and p53 pathways in cancer. , 2002, Cancer cell.

[26]  Yonghong Xiao,et al.  Pattern of retinoblastoma pathway inactivation dictates response to CDK4/6 inhibition in GBM , 2010, Proceedings of the National Academy of Sciences.

[27]  Nicolas Stransky,et al.  Targeting cancer with kinase inhibitors. , 2015, The Journal of clinical investigation.

[28]  J. Folkman,et al.  Antiangiogenic scheduling of chemotherapy improves efficacy against experimental drug-resistant cancer. , 2000, Cancer research.

[29]  Robert A Gatenby,et al.  A theoretical quantitative model for evolution of cancer chemotherapy resistance , 2010, Biology Direct.

[30]  Raja R Srinivas,et al.  Exploiting Temporal Collateral Sensitivity in Tumor Clonal Evolution , 2016, Cell.

[31]  V. Velculescu,et al.  Expression of p16 and Retinoblastoma Determines Response to CDK4/6 Inhibition in Ovarian Cancer , 2011, Clinical Cancer Research.

[32]  L. Krasinska,et al.  Selective chemical inhibition as a tool to study Cdk1 and Cdk2 functions in the cell cycle , 2008, Cell cycle.

[33]  M. Clausen,et al.  FDA-approved small-molecule kinase inhibitors. , 2015, Trends in pharmacological sciences.

[34]  E. T. Gawlinski,et al.  A Cellular Automaton Model of Early Tumor Growth and Invasion: The Effects of Native Tissue Vascularity and Increased Anaerobic Tumor Metabolism , 2001 .

[35]  Pierre Dubus,et al.  Cyclin-dependent kinase 2 is essential for meiosis but not for mitotic cell division in mice , 2003, Nature Genetics.

[36]  Delyan P. Ivanov,et al.  Multiplexing Spheroid Volume, Resazurin and Acid Phosphatase Viability Assays for High-Throughput Screening of Tumour Spheroids and Stem Cell Neurospheres , 2014, PloS one.

[37]  P. Kaldis,et al.  Cdk2 Knockout Mice Are Viable , 2003, Current Biology.

[38]  Sabrina L. Spencer,et al.  The Proliferation-Quiescence Decision Is Controlled by a Bifurcation in CDK2 Activity at Mitotic Exit , 2013, Cell.

[39]  W. Wiedemeyer,et al.  Cyclin E1 and RTK/RAS signaling drive CDK inhibitor resistance via activation of E2F and ETS , 2014, Oncotarget.

[40]  F. Michor,et al.  Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort , 2015, Cell.

[41]  Anne-Marie Duchemin,et al.  Pharmacologic inhibition of CDK4/6: mechanistic evidence for selective activity or acquired resistance in acute myeloid leukemia. , 2007, Blood.

[42]  Philip Gerlee,et al.  The model muddle: in search of tumor growth laws. , 2012, Cancer research.

[43]  Barbara Mayer,et al.  Differences in therapeutic indexes of combination metronomic chemotherapy and an anti-VEGFR-2 antibody in multidrug-resistant human breast cancer xenografts. , 2002, Clinical cancer research : an official journal of the American Association for Cancer Research.

[44]  M. Caligiuri,et al.  Pharmacologic inhibition of CDK 4 / 6 : mechanistic evidence for selective activity or acquired resistance in acute myeloid leukemia , 2007 .

[45]  P. Hahnfeldt,et al.  Tumor development under angiogenic signaling: a dynamical theory of tumor growth, treatment response, and postvascular dormancy. , 1999, Cancer research.

[46]  Martin Wasser,et al.  Cyclin-dependent kinase 1 (Cdk1) is essential for cell division and suppression of DNA re-replication but not for liver regeneration , 2012, Proceedings of the National Academy of Sciences.

[47]  D. Heitjan,et al.  CDK 4/6 Inhibitor Palbociclib (PD0332991) in Rb+ Advanced Breast Cancer: Phase II Activity, Safety, and Predictive Biomarker Assessment , 2014, Clinical Cancer Research.

[48]  William Pao,et al.  The Impact of Microenvironmental Heterogeneity on the Evolution of Drug Resistance in Cancer Cells , 2015, Cancer informatics.

[49]  Krishnendu Chatterjee,et al.  Evolutionary dynamics of cancer in response to targeted combination therapy , 2013, eLife.

[50]  F. Hoh,et al.  An integrated chemical biology approach provides insight into Cdk2 functional redundancy and inhibitor sensitivity. , 2012, Chemistry & biology.

[51]  Chao Zhang,et al.  Switching Cdk2 on or off with small molecules to reveal requirements in human cell proliferation. , 2011, Molecular cell.

[52]  M. Barbacid,et al.  Cdk2 suppresses cellular senescence induced by the c-myc oncogene , 2010, Nature Cell Biology.

[53]  R. Gillies,et al.  Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer , 2016, Science Translational Medicine.

[54]  Luis-Miguel Chevin,et al.  On measuring selection in experimental evolution , 2010, Biology Letters.

[55]  Frank McCormick,et al.  Proliferation of cancer cells despite CDK2 inhibition. , 2003, Cancer cell.