Protocol for mathematical prediction of patient response and survival to immune checkpoint inhibitor immunotherapy

被引:1
|
作者
Butner, Joseph D. [1 ]
Farhat, Maguy [2 ]
Cristini, Vittorio [1 ,3 ,4 ,5 ]
Chung, Caroline [2 ]
Wang, Zhihui [1 ,3 ,6 ,7 ]
机构
[1] Houston Methodist Res Inst, Math Med Program, Houston, TX 77030 USA
[2] Univ Texas MD Anderson Canc Ctr, Dept Radiat Oncol, Houston, TX 77030 USA
[3] Houston Methodist Res Inst, Neal Canc Ctr, Houston, TX 77030 USA
[4] Univ Texas MD Anderson Canc Ctr, Dept Imaging Phys, Houston, TX 77230 USA
[5] Weill Cornell Med, Grad Sch Med Sci, Physiol Biophys & Syst Biol Program, New York, NY 10065 USA
[6] Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10065 USA
[7] Texas A&M Univ, Dept Med Educ, Sch Med, Bryan, TX 77807 USA
来源
STAR PROTOCOLS | 2022年 / 3卷 / 04期
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Biotechnology and bioengineering; Cancer; Health Sciences; Immunology; Systems biology;
D O I
10.1016/j.xpro.2022.101886
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
This protocol describes the application of a mechanistic mathematical model of immune checkpoint inhibitor (ICI) immunotherapy to patient tumor imaging data for predicting solid tumor response and patient survival under ICI intervention. We describe steps for data collection and processing, data pipelines, and approaches to increase precision. The protocol is highly predictive as early as the first restaging after treatment start and can be used with standard-of-care imaging measures. For complete details on the use and execution of this protocol, please refer to Butner et al. (2020)1 and Butner et al. (2021).2
引用
收藏
页数:17
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