In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer.

Despite the fact that the local immunological microenvironment shapes the prognosis of colorectal cancer, immunotherapy has shown no benefit for the vast majority of colorectal cancer patients. A better understanding of the complex immunological interplay within the microenvironment is required. In this study, we utilized wet lab migration experiments and quantitative histological data of human colorectal cancer tissue samples (n = 20) including tumor cells, lymphocytes, stroma, and necrosis to generate a multiagent spatial model. The resulting data accurately reflected a wide range of situations of successful and failed immune surveillance. Validation of simulated tissue outcomes on an independent set of human colorectal cancer specimens (n = 37) revealed the model recapitulated the spatial layout typically found in human tumors. Stroma slowed down tumor growth in a lymphocyte-deprived environment but promoted immune escape in a lymphocyte-enriched environment. A subgroup of tumors with less stroma and high numbers of immune cells showed high rates of tumor control. These findings were validated using data from colorectal cancer patients (n = 261). Low-density stroma and high lymphocyte levels showed increased overall survival (hazard ratio 0.322, P = 0.0219) as compared with high stroma and high lymphocyte levels. To guide immunotherapy in colorectal cancer, simulation of immunotherapy in preestablished tumors showed that a complex landscape with optimal stroma permeabilization and immune cell activation is able to markedly increase therapy response in silico These results can help guide the rational design of complex therapeutic interventions, which target the colorectal cancer microenvironment. Cancer Res; 77(22); 6442-52. ©2017 AACR.

[1]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of human colon and rectal cancer , 2012, Nature.

[2]  Nektarios A. Valous,et al.  Detailed resolution analysis reveals spatial T cell heterogeneity in the invasive margin of colorectal cancer liver metastases associated with improved survival , 2017, Oncoimmunology.

[3]  Eric Bonabeau,et al.  Agent-based modeling: Methods and techniques for simulating human systems , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  N. Meropol,et al.  In vitro migration of cytotoxic T lymphocyte derived from a colon carcinoma patient is dependent on CCL2 and CCR2 , 2011, Journal of Translational Medicine.

[5]  H. Kocher,et al.  The desmoplastic stroma of pancreatic cancer is a barrier to immune cell infiltration , 2013, Oncoimmunology.

[6]  L. D. de Pillis,et al.  A cellular automata model of tumor-immune system interactions. , 2006, Journal of theoretical biology.

[7]  S. Elmore.  Apoptosis: A Review of Programmed Cell Death , 2007, Toxicologic pathology.

[8]  Giulio Gabbiani,et al.  The stroma reaction myofibroblast: a key player in the control of tumor cell behavior. , 2004, The International journal of developmental biology.

[9]  E. Seim,et al.  Association between invasiveness, inflammatory reaction, desmoplasia and survival in colorectal cancer. , 1989, Journal of clinical pathology.

[10]  P. Cattiaux,et al.  A Biased Competition Theory of Cytotoxic T Lymphocyte Interaction with Tumor Nodules , 2015, PloS one.

[11]  M. Hidalgo,et al.  Pancreatic cancer: from state-of-the-art treatments to promising novel therapies , 2015, Nature Reviews Clinical Oncology.

[12]  Mario Paolucci,et al.  On agent-based modeling and computational social science , 2014, Front. Psychol..

[13]  Axel Benner,et al.  Localization and density of immune cells in the invasive margin of human colorectal cancer liver metastases are prognostic for response to chemotherapy. , 2011, Cancer research.

[14]  Martin A. Nowak,et al.  A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity , 2015, Nature.

[15]  Umar Mahmood,et al.  Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival. , 2014, Cancer cell.

[16]  Joshua M. Epstein,et al.  Modelling to contain pandemics , 2009, Nature.

[17]  Jakob Nikolas Kather,et al.  Identification of a characteristic vascular belt zone in human colorectal cancer , 2017, PloS one.

[18]  Jan Poleszczuk,et al.  Cancer Stem Cell Plasticity as Tumor Growth Promoter and Catalyst of Population Collapse , 2015, bioRxiv.

[19]  Miguel A F Sanjuán,et al.  Dynamics of the cell-mediated immune response to tumour growth , 2017, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[20]  D. Foley,et al.  The economy needs agent-based modelling , 2009, Nature.

[21]  Zlatko Trajanoski,et al.  Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade , 2016, bioRxiv.

[22]  Hector Gomez,et al.  Full-scale, three-dimensional simulation of early-stage tumor growth: The onset of malignancy , 2017 .

[23]  S. H. Sabzpoushan,et al.  An agent-based model of avascular tumor growth: Immune response tendency to prevent cancer development , 2017, Simul..

[24]  G. An,et al.  The Basic Immune Simulator: An agent-based model to study the interactions between innate and adaptive immunity , 2007, Theoretical Biology and Medical Modelling.

[25]  B. Zhu,et al.  T-cell exhaustion in the tumor microenvironment , 2015, Cell Death and Disease.

[26]  M. Okada,et al.  [New response evaluation criteria in solid tumours-revised RECIST guideline (version 1.1)]. , 2009, Gan to kagaku ryoho. Cancer & chemotherapy.

[27]  Sara T Brookes,et al.  Subgroup analyses in randomized trials: risks of subgroup-specific analyses; power and sample size for the interaction test. , 2004, Journal of clinical epidemiology.

[28]  I. Mellman,et al.  Elements of cancer immunity and the cancer–immune set point , 2017, Nature.

[29]  I. Caramalho,et al.  Visualizing CTL/melanoma cell interactions: multiple hits must be delivered for tumour cell annihilation , 2008, Journal of cellular and molecular medicine.

[30]  Drew M. Pardoll,et al.  The blockade of immune checkpoints in cancer immunotherapy , 2012, Nature Reviews Cancer.

[31]  M. Koch,et al.  Tumoral Immune Cell Exploitation in Colorectal Cancer Metastases Can Be Targeted Effectively by Anti-CCR5 Therapy in Cancer Patients. , 2016, Cancer cell.

[32]  B. Hall,et al.  Tumor Induced Stromal Reprogramming Drives Lymph Node Transformation , 2016, Nature Immunology.

[33]  D. V. Von Hoff,et al.  Tumor-stroma interactions in pancreatic ductal adenocarcinoma , 2007, Molecular Cancer Therapeutics.

[34]  J. Allison.  Immune Checkpoint Blockade in Cancer Therapy , 2008 .

[35]  Z. Trajanoski,et al.  Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome , 2006, Science.

[36]  T. Giese,et al.  Prevailing Role of Contact Guidance in Intrastromal T-cell Trapping in Human Pancreatic Cancer , 2014, Clinical Cancer Research.

[37]  E. Puré,et al.  Can Targeting Stroma Pave the Way to Enhanced Antitumor Immunity and Immunotherapy of Solid Tumors? , 2016, Cancer Immunology Research.

[38]  Abbas Ahmadi,et al.  Simulation-based optimization of radiotherapy: Agent-based modeling and reinforcement learning , 2017, Math. Comput. Simul..

[39]  Miguel A. F. Sanjuán,et al.  Destruction of solid tumors by immune cells , 2017, Commun. Nonlinear Sci. Numer. Simul..

[40]  M. Nowak,et al.  An exactly solvable, spatial model of mutation accumulation in cancer , 2016, Scientific Reports.

[41]  Alan D. Lopez,et al.  Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study , 2017, JAMA oncology.

[42]  R. Schreiber,et al.  The immunobiology of cancer immunosurveillance and immunoediting. , 2004, Immunity.

[43]  Hans J. Tanke,et al.  The Carcinoma–Stromal Ratio of Colon Carcinoma Is an Independent Factor for Survival Compared to Lymph Node Status and Tumor Stage , 2007, Cellular oncology : the official journal of the International Society for Cellular Oncology.

[44]  H. Enderling,et al.  Agent-based modeling of cancer stem cell driven solid tumor growth , 2015, bioRxiv.

[45]  Jakob Nikolas Kather,et al.  Continuous representation of tumor microvessel density and detection of angiogenic hotspots in histological whole-slide images , 2015, Oncotarget.

[46]  T. Blankenstein,et al.  Immunotherapy: target the stroma to hit the tumor. , 2005, Trends in molecular medicine.

[47]  A. Friedl,et al.  Colorectal cancer desmoplastic reaction up-regulates collagen synthesis and restricts cancer cell invasion , 2011, Cell and Tissue Research.

[48]  Philippe Bousso,et al.  Two-photon imaging of intratumoral CD8+ T cell cytotoxic activity during adoptive T cell therapy in mice. , 2008, The Journal of clinical investigation.

[49]  Miguel A F Sanjuán,et al.  A Validated Mathematical Model of Tumor Growth Including Tumor–Host Interaction, Cell-Mediated Immune Response and Chemotherapy , 2014, Bulletin of Mathematical Biology.

[50]  Pornpimol Charoentong,et al.  Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade , 2016, bioRxiv.

[51]  Antoni Ribas,et al.  Current developments in cancer vaccines and cellular immunotherapy. , 2003, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[52]  M. Krummel,et al.  Tumor-infiltrating lymphocytes are dynamically desensitized to antigen but are maintained by homeostatic cytokine. , 2016, JCI insight.

[53]  Ralph Weissleder,et al.  Regulatory T cells reversibly suppress cytotoxic T cell function independent of effector differentiation. , 2006, Immunity.