Predicting efficacy assessment of combined treatment of radiotherapy and nivolumab for NSCLC patients through virtual clinical trials using QSP modeling

Schreiber RD, Old LJ, Smyth MJ (2011) Cancer Immunoediting: integrating immunity’s roles in Cancer suppression and Promotion. Science 331:1565–1570. https://doi.org/10.1126/science.1203486

Article  ADS  PubMed  Google Scholar 

Upadhaya S, Neftelinov ST, Hodge J, Campbell J (2022) Challenges and opportunities in the PD1/PDL1 inhibitor clinical trial landscape. Nat Rev Drug Discov 21:482–483. https://doi.org/10.1038/d41573-022-00030-4

Article  PubMed  Google Scholar 

Chelliah V, Lazarou G, Bhatnagar S et al (2021) Quantitative systems Pharmacology Approaches for Immuno-Oncology: adding virtual patients to the Development paradigm. Clin Pharmacol Ther 109:605–618. https://doi.org/10.1002/cpt.1987

Article  PubMed  Google Scholar 

Prasad V, Mailankody S (2017) Research and development spending to bring a single Cancer drug to market and revenues after approval. JAMA Intern Med 177:1569. https://doi.org/10.1001/jamainternmed.2017.3601

Article  PubMed  PubMed Central  Google Scholar 

Bradshaw EL, Spilker ME, Zang R et al (2019) Applications of quantitative systems Pharmacology in Model-Informed Drug Discovery: perspective on Impact and opportunities. CPT Pharmacometrics Syst Pharmacol 8:777–791. https://doi.org/10.1002/psp4.12463

Article  PubMed  PubMed Central  Google Scholar 

Sové RJ, Jafarnejad M, Zhao C et al (2020) QSP-IO: a quantitative systems Pharmacology Toolbox for mechanistic Multiscale modeling for Immuno‐Oncology Applications. Clin Pharmacol Ther 9:484–497. https://doi.org/10.1002/psp4.12546

Article  Google Scholar 

Kosinsky Y, Dovedi SJ, Peskov K et al (2018) Radiation and PD-(L)1 treatment combinations: immune response and dose optimization via a predictive systems model. j Immunotherapy cancer 6:17. https://doi.org/10.1186/s40425-018-0327-9

Article  Google Scholar 

Balti A, Zugaj D, Fenneteau F et al (2021) Dynamical systems analysis as an additional tool to inform treatment outcomes: the case study of a quantitative systems pharmacology model of immuno-oncology. Chaos 31:023124. https://doi.org/10.1063/5.0022238

Article  ADS  MathSciNet  PubMed  Google Scholar 

Zugaj D, Fenneteau F, Tremblay P-O, Nekka F (2024) Dynamical behavior-based approach for the evaluation of treatment efficacy: The case of immuno-oncology. Chaos Interdiscip J Nonlinear Sci 34:013142. https://doi.org/10.1063/5.0170329

Article  MathSciNet  Google Scholar 

Ribas A, Wolchok JD (2018) Cancer immunotherapy using checkpoint blockade. Science 359:1350–1355. https://doi.org/10.1126/science.aar4060

Article  ADS  PubMed  PubMed Central  Google Scholar 

Postmus PE, Kerr KM, Oudkerk M et al (2017) Early and locally advanced non-small-cell lung cancer (NSCLC): ESMO Clinical Practice guidelines for diagnosis, treatment and follow-up. Ann Oncol 28:iv1–iv21. https://doi.org/10.1093/annonc/mdx222

Article  PubMed  Google Scholar 

Shaverdian N, Lisberg AE, Bornazyan K et al (2017) Previous radiotherapy and the clinical activity and toxicity of pembrolizumab in the treatment of non-small-cell lung cancer: a secondary analysis of the KEYNOTE-001 phase 1 trial. Lancet Oncol 18:895–903. https://doi.org/10.1016/S1470-2045(17)30380-7

Article  PubMed  PubMed Central  Google Scholar 

Bray F, Ferlay J, Soerjomataram I et al (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer. J Clin 68:394–424. https://doi.org/10.3322/caac.21492

Article  Google Scholar 

Molina JR, Yang P, Cassivi SD et al (2008) Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship. Mayo Clinic Proc. https://doi.org/10.4065/83.5.584

Article  Google Scholar 

Gettinger S, Rizvi NA, Chow LQ et al (2016) Nivolumab Monotherapy for First-Line treatment of Advanced non–small-cell Lung Cancer. JCO 34:2980–2987. https://doi.org/10.1200/JCO.2016.66.9929

Article  Google Scholar 

Topalian SL, Hodi FS, Brahmer JR et al (2019) Five-year survival and correlates among patients with Advanced Melanoma, Renal Cell Carcinoma, or non–small cell lung Cancer treated with Nivolumab. JAMA Oncol 5:1411. https://doi.org/10.1001/jamaoncol.2019.2187

Article  PubMed  PubMed Central  Google Scholar 

Kim H, Chung J-H (2019) PD-L1 testing in non-small cell lung Cancer: past, Present, and Future. J Pathol Transl Med 53:199–206. https://doi.org/10.4132/jptm.2019.04.24

Article  PubMed  PubMed Central  Google Scholar 

Grigg C, Rizvi NA (2016) PD-L1 biomarker testing for non-small cell lung cancer: truth or fiction? j Immunotherapy cancer 4:48. https://doi.org/10.1186/s40425-016-0153-x

Article  Google Scholar 

Chajon E, Castelli J, Marsiglia H, De Crevoisier R (2017) The synergistic effect of radiotherapy and immunotherapy: a promising but not simple partnership. Crit Rev Oncol/Hematol 111:124–132. https://doi.org/10.1016/j.critrevonc.2017.01.017

Article  PubMed  Google Scholar 

Yang H, Jin T, Li M et al (2019) Synergistic effect of immunotherapy and radiotherapy in non-small cell lung cancer: current clinical trials and prospective challenges. Precision Clin Med 2:57–70. https://doi.org/10.1093/pcmedi/pbz004

Article  Google Scholar 

Jafarnejad M, Gong C, Gabrielson E et al (2019) A computational model of neoadjuvant PD-1 inhibition in Non-small Cell Lung Cancer. AAPS J 21:79. https://doi.org/10.1208/s12248-019-0350-x

Article  PubMed  Google Scholar 

Benzekry S, Lamont C, Beheshti A et al (2014) Classical Mathematical models for description and prediction of experimental Tumor Growth. PLoS Comput Biol 10:e1003800. https://doi.org/10.1371/journal.pcbi.1003800

Article  PubMed  PubMed Central  Google Scholar 

Dhar M, Bhattacharya P (2018) Comparison of the logistic and the Gompertz curve under different constraints. J Stat Manage Syst 21:1189–1210. https://doi.org/10.1080/09720510.2018.1488414

Article  Google Scholar 

Vaghi C, Rodallec A, Fanciullino R et al (2020) Population modeling of tumor growth curves and the reduced Gompertz model improve prediction of the age of experimental tumors. PLoS Comput Biol 16:e1007178. https://doi.org/10.1371/journal.pcbi.1007178

Article  PubMed  PubMed Central  Google Scholar 

Suleiman AA, Nogova L, Fuhr U (2013) Modeling NSCLC progression: recent advances and opportunities available. AAPS J 15:542–550. https://doi.org/10.1208/s12248-013-9461-y

Article  PubMed  PubMed Central  Google Scholar 

Geng C, Paganetti H, Grassberger C (2017) Prediction of treatment response for combined chemo- and Radiation Therapy for Non-small Cell Lung Cancer patients using a Bio-mathematical Model. Sci Rep 7:13542. https://doi.org/10.1038/s41598-017-13646-z

Article  ADS  PubMed  PubMed Central  Google Scholar 

Walle T, Martinez Monge R, Cerwenka A et al (2018) Radiation effects on antitumor immune responses: current perspectives and challenges. Ther Adv Med Oncol 10:175883401774257. https://doi.org/10.1177/1758834017742575

Article  Google Scholar 

Brenner DJ, Hlatky LR, Hahnfeldt PJ et al (1998) The Linear-Quadratic Model and Most Other Common Radiobiological models result in similar predictions of Time-Dose relationships. Radiat Res 150:83. https://doi.org/10.2307/3579648

Article  ADS  PubMed  Google Scholar 

Sachs RK, Hlatky LR, Hahnfeldt P (2001) Simple ODE models of tumor growth and anti-angiogenic or radiation treatment. Math Comput Model 33:1297–1305. https://doi.org/10.1016/S0895-7177(00)00316-2

Article  MathSciNet  Google Scholar 

Wang H, Sové RJ, Jafarnejad M et al (2020) Conducting a virtual clinical trial in HER2-Negative breast Cancer using a quantitative systems Pharmacology Model with an epigenetic modulator and Immune Checkpoint inhibitors. Front Bioeng Biotechnol 8:141. https://doi.org/10.3389/fbioe.2020.00141

Article  PubMed  PubMed Central  Google Scholar 

Eisenhauer EA, Therasse P, Bogaerts J et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45:228–247. https://doi.org/10.1016/j.ejca.2008.10.026

Article  PubMed  Google Scholar 

Ye H, Pang H, Shi X et al (2021) Nivolumab and Hypofractionated Radiotherapy in patients with Advanced Lung Cancer: ABSCOPAL-1 clinical trial. Front Oncol 11:657024. https://doi.org/10.3389/fonc.2021.657024

Article  PubMed  PubMed Central  Google Scholar 

Barbee MS, Ogunniyi A, Horvat TZ, Dang T-O (2015) Current status and future directions of the Immune checkpoint inhibitors Ipilimumab, Pembrolizumab, and Nivolumab in oncology. Ann Pharmacother 49:907–937

Article  PubMed  Google Scholar 

Zhang Z, Liu X, Chen D, Yu J (2022) Radiotherapy combined with immunotherapy: the dawn of cancer treatment. Sig Transduct Target Ther 7:258. https://doi.org/10.1038/s41392-022-01102-y

Article  Google Scholar 

Rodrigues G, Choy H, Bradley J et al (2015) Definitive radiation therapy in locally advanced non-small cell lung cancer: executive summary of an American Society for Radiation Oncology (ASTRO) evidence-based clinical practice guideline. Practical Radiation Oncol 5:141–148. https://doi.org/10.1016/j.prro.2015.02.012

Article  Google Scholar 

Ko EC, Raben D, Formenti SC (2018) The Integration of Radiotherapy with Immunotherapy for the treatment of non–small cell Lung Cancer. Clin Cancer Res 24:5792–5806. https://doi.org/10.1158/1078-0432.CCR-17-3620

Article  PubMed  Google Scholar 

Serritella AV, Shenoy NK (2023) Nivolumab Plus Ipilimumab vs Nivolumab alone in Advanced Cancers Other Than Melanoma: a Meta-analysis. JAMA Oncol 9:1441. https://doi.org/10.1001/jamaoncol.2023.3295

Article 

留言 (0)

沒有登入
gif