Investigating tumor-host response dynamics in preclinical immunotherapy experiments using a stepwise mathematical modeling strategy

Mathematical Biosciences - Tập 366 - Trang 109106 - 2023
Angela M. Jarrett1,2, Patrick N. Song3, Kirsten Reeves3,4, Ernesto A.B.F. Lima1,2, Benjamin Larimer3,5, Thomas E. Yankeelov1,2,6,7,8,9, Anna G. Sorace3,5,10
1Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, USA
2Livestrong Cancer Institutes, The University of Texas at Austin, USA
3Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama USA
4Graduate Biomedical Sciences, University of Alabama at Birmingham, Birmingham, Alabama USA
5O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama USA
6Departments of Biomedical Engineering, The University of Texas at Austin, USA
7Diagnostic Medicine, The University of Texas at Austin, USA
8Oncology, The University of Texas at Austin, USA
9Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
10Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA.

Tài liệu tham khảo

Esfahani, 2020, A review of cancer immunotherapy: from the past, to the present, to the future, Curr. Oncol, 27, S87, 10.3747/co.27.5223 Waldman, 2020, A guide to cancer immunotherapy: from T cell basic science to clinical practice, Nat. Rev. Immunol, 20, 651, 10.1038/s41577-020-0306-5 Sharma, 2017, Primary, adaptive, and acquired resistance to cancer immunotherapy, Cell, 168, 707, 10.1016/j.cell.2017.01.017 Darvin, 2018, Immune checkpoint inhibitors: recent progress and potential biomarkers, Exp. Mol. Med., 50, 1, 10.1038/s12276-018-0191-1 Shieh, 2021, Response to immune checkpoint inhibitor treatment in advanced cervical cancer and biomarker study, Front. Med. (Lausanne), 8 Haslam, 2019, Estimation of the Percentage of US patients with cancer who are eligible for and respond to checkpoint inhibitor immunotherapy drugs, JAMA Netw Open, 2, 10.1001/jamanetworkopen.2019.2535 Nakamura, 2017, Targeting cancer-related inflammation in the era of immunotherapy, Immunol. Cell Biol., 95, 325, 10.1038/icb.2016.126 Wang, 2019, simulation of a clinical trial with anti-CTLA-4 and anti-PD-L1 immunotherapies in metastatic breast cancer using a systems pharmacology model, R Soc. Open Sci., 6, 10.1098/rsos.190366 Butner, 2020, Mathematical prediction of clinical outcomes in advanced cancer patients treated with checkpoint inhibitor immunotherapy, Sci. Adv., 6, eaay6298, 10.1126/sciadv.aay6298 Syed, 2023, Immune-checkpoint inhibitor therapy response evaluation using oncophysics-based mathematical models, Wiley Interdiscip Rev. Nanomed Nanobiotechnol, 15, e1855, 10.1002/wnan.1855 Reeves, 2022, (18)F-FMISO PET imaging identifies hypoxia and immunosuppressive tumor microenvironments and guides targeted Evofosfamide therapy in tumors refractory to PD-1 and CTLA-4 inhibition, Clin. Cancer Res, 28, 327, 10.1158/1078-0432.CCR-21-2394 Jain, 2005, Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy, Science, 307, 58, 10.1126/science.1104819 Harris, 2002, Hypoxia–a key regulatory factor in tumour growth, Nat. Rev. Cancer, 2, 38, 10.1038/nrc704 Vaupel, 2004, Tumor hypoxia and malignant progression, Methods Enzymol, 381, 335, 10.1016/S0076-6879(04)81023-1 Bannoud, N., et al., Hypoxia supports differentiation of terminally exhausted CD8 T cells. Front. Immunol, 2021. 12: p. 660944. Noman, 2019, Improving cancer immunotherapy by targeting the hypoxic tumor microenvironment: new opportunities and challenges, Cells, 8, 10.3390/cells8091083 Zheng, 2018, Increased vessel perfusion predicts the efficacy of immune checkpoint blockade, J. Clin. Invest, 128, 2104, 10.1172/JCI96582 Sorace, 2020, Imaging for response assessment in cancer clinical trials, Semin. Nucl. Med, 50, 488, 10.1053/j.semnuclmed.2020.05.001 Napier, 2022, Preclinical PET imaging of Granzyme B shows promotion of immunological response following combination paclitaxel and immune checkpoint inhibition in triple negative breast cancer, Pharmaceutics, 14, 10.3390/pharmaceutics14020440 Larimer, 2019, The effectiveness of checkpoint inhibitor combinations and administration timing can be measured by Granzyme B PET imaging, Clin. Cancer Res, 25, 1196, 10.1158/1078-0432.CCR-18-2407 Lim, 1993, An efficient radiosynthesis of [18F]fluoromisonidazole, Appl. Radiat. Isot, 44, 1085, 10.1016/0969-8043(93)90110-V Tang, 2005, Fully automated one-pot synthesis of [18F]fluoromisonidazole, Nucl. Med. Biol, 32, 553, 10.1016/j.nucmedbio.2005.03.010 Sorace, 2017, Quantitative [(18)F]FMISO PET Imaging Shows Reduction of Hypoxia Following Trastuzumab in a Murine Model of HER2+ Breast Cancer, Mol. Imaging Biol, 19, 130, 10.1007/s11307-016-0994-1 Hanahan, 2011, Hallmarks of cancer: the next generation, Cell, 144, 646, 10.1016/j.cell.2011.02.013 Folkman, 1971, Tumor Angiogenesis - Therapeutic Implications, New England J. Med., 285 Schaaf, 2018, Defining the role of the tumor vasculature in antitumor immunity and immunotherapy, Cell Death Dis, 9, 115, 10.1038/s41419-017-0061-0 Wei, 2018, Fundamental mechanisms of immune checkpoint blockade therapy, Cancer Discov, 8, 1069, 10.1158/2159-8290.CD-18-0367 Granier, 2017, Mechanisms of action and rationale for the use of checkpoint inhibitors in cancer, ESMO Open,, 2, 10.1136/esmoopen-2017-000213 Chow, 2014, Chemokines in cancer, Cancer Immunol. Res, 2, 1125, 10.1158/2326-6066.CIR-14-0160 Briukhovetska, 2021, Interleukins in cancer: from biology to therapy, Nat. Rev. Cancer, 21, 481, 10.1038/s41568-021-00363-z Wang, 2008, Tumor necrosis factor and cancer, buddies or foes?, Acta Pharmacol. Sin, 29, 1275, 10.1111/j.1745-7254.2008.00889.x Roland, 2009, Cytokine levels correlate with immune cell infiltration after anti-VEGF therapy in preclinical mouse models of breast cancer, PLoS ONE, 4, e7669, 10.1371/journal.pone.0007669 Chew, 2012, Immune microenvironment in tumor progression: characteristics and challenges for therapy, J. Oncol., 2012, 10.1155/2012/608406 McBride, 1986, Induction of tolerance to a murine fibrosarcoma in two zones of dosage–the involvement of suppressor cells, Br. J. Cancer, 53, 707, 10.1038/bjc.1986.122 Mahapatro, 2021, Cytokine-mediated crosstalk between immune cells and epithelial cells in the gut, Cells, 10, 10.3390/cells10010111 Salemme, 2021, The crosstalk between tumor cells and the immune microenvironment in breast cancer: implications for immunotherapy, Front. Oncol., 11, 10.3389/fonc.2021.610303 Jarrett, 2019, Experimentally-driven mathematical modeling to improve combination targeted and cytotoxic therapy for HER2+ breast cancer, Sci. Rep, 9, 12830, 10.1038/s41598-019-49073-5 Selby, 2013, Anti-CTLA-4 antibodies of IgG2a isotype enhance antitumor activity through reduction of intratumoral regulatory T cells, Cancer Immunol. Res, 1, 32, 10.1158/2326-6066.CIR-13-0013 Selby, 2016, Preclinical development of ipilimumab and nivolumab combination immunotherapy: mouse tumor models, in vitro functional studies, and cynomolgus macaque toxicology, PLoS ONE, 11, 10.1371/journal.pone.0161779 Strogatz, 2000 Jarrett, 2018, Mathematical modelling of trastuzumab-induced immune response in an in vivo murine model of HER2+ breast cancer, Math Med. Biol Bloom, 2020, Anti-HER2 induced myeloid cell alterations correspond with increasing vascular maturation in a murine model of HER2+ breast cancer, BMC Cancer, 20, 359, 10.1186/s12885-020-06868-4 Noman, 2015, Hypoxia: a key player in antitumor immune response. A review in the theme: cellular responses to Hypoxia, Am. J. Physiol. Cell Physiol, 309, C569, 10.1152/ajpcell.00207.2015 Lestini, 2016, Optimal design for informative protocols in xenograft tumor growth inhibition experiments in mice, AAPS J., 18, 1233, 10.1208/s12248-016-9924-z Cárdenas, 2022, Model-informed experimental design recommendations for distinguishing intrinsic and acquired targeted therapeutic resistance in head and neck cancer, NPJ Syst. Biol. Appl., 8, 32, 10.1038/s41540-022-00244-7 Bandara, 2009, Optimal experimental design for parameter estimation of a cell signaling model, PLoS Comput. Biol, 5, 10.1371/journal.pcbi.1000558 Jarrett, 2020, Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: background, History, Challenges, and Opportunities, J. Clin. Med., 9 Lima, 2022, Optimizing combination therapy in a murine model of HER2+ breast cancer, Comput. Methods Appl. Mech. Eng, 402