A mechanistic immunotherapy model provides patient-specific quantification of immune response and associated long-term tumor burden

Joseph Butner, Zhihui Wang, Dalia Elganainy, Marija Plodinec, George A. Calin, Prashant Dogra, Sara Nizzero, Javier Ruiz Ramírez, Caroline Chung, Eugene J. Koay, James Welsh, David S. Hong, Vittorio Cristini

Research output: Contribution to journalArticle

Abstract

A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time-course of tumour responses to immune-checkpoint inhibitors. The model takes into account intrinsic tumour-growth rates, the rates of immune activation and of tumour–immune-cell interactions, and the efficacy of immune-mediated tumour killing. For 124 patients, four cancer types and two immunotherapy agents, the model reliably described the immune responses and final tumour burden across all different cancers and drug combinations examined. In validation cohorts from four clinical trials of checkpoint inhibitors (with a total of 177 patients), the model accurately stratified the patients according to reduced or increased long-term tumour burden. We also provide model-derived quantitative measures of treatment sensitivity for specific drug–cancer combinations. The model can be used to predict responses to therapy and to quantify specific drug–cancer sensitivities in individual patients.
Original languageEnglish (US)
JournalNature Biomedical Engineering
StateAccepted/In press - Dec 2020

Fingerprint Dive into the research topics of 'A mechanistic immunotherapy model provides patient-specific quantification of immune response and associated long-term tumor burden'. Together they form a unique fingerprint.

Cite this