Integrating Systems Biology and an Ex Vivo Human Tumor Model Elucidates PD-1 Blockade Response Dynamics

Munisha Smalley; Michelle Przedborski; Saravanan Thiyagarajan; Moriah Pellowe; Amit Verma; Nilesh Brijwani; Debika Datta; Misti Jain; Basavaraja U Shanthappa; Vidushi Kapoor; Kodaganur S Gopinath; D C Doval; K S Sabitha; Gaspar Taroncher-Oldenburg; Biswanath Majumder; Pradip Majumder; Mohammad Kohandel; Aaron Goldman

doi:10.1016/j.isci.2020.101229

Integrating Systems Biology and an Ex Vivo Human Tumor Model Elucidates PD-1 Blockade Response Dynamics

iScience. 2020 Jun 26;23(6):101229. doi: 10.1016/j.isci.2020.101229. Epub 2020 Jun 2.

Authors

Munisha Smalley¹, Michelle Przedborski², Saravanan Thiyagarajan³, Moriah Pellowe², Amit Verma⁴, Nilesh Brijwani³, Debika Datta³, Misti Jain³, Basavaraja U Shanthappa³, Vidushi Kapoor³, Kodaganur S Gopinath⁵, D C Doval⁶, K S Sabitha⁷, Gaspar Taroncher-Oldenburg⁸, Biswanath Majumder³, Pradip Majumder³, Mohammad Kohandel⁹, Aaron Goldman¹⁰

Affiliations

¹ Integrative Immuno-Oncology Center, Mitra Biotech, Woburn, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Division of Engineering in Medicine, Brigham and Women's Hospital, Boston, MA, USA.
² University of Waterloo, Department of Applied Mathematics, Waterloo, ON N2L 3G1, Canada.
³ Integrative Immuno-Oncology Center, Mitra Biotech, Woburn, MA, USA.
⁴ Max Super Speciality Hospital, New Delhi, India.
⁵ Bangalore Institute of Oncology, Bangalore, India.
⁶ Rajiv Gandhi Cancer Institute & Research Centre, New Delhi, India.
⁷ Kidwai Memorial Institute of Oncology, Bangalore, India.
⁸ Gaspar Taroncher-Oldenburg Consulting, Philadelphia, PA, USA.
⁹ University of Waterloo, Department of Applied Mathematics, Waterloo, ON N2L 3G1, Canada. Electronic address: kohandel@uwaterloo.ca.
¹⁰ Department of Medicine, Harvard Medical School, Boston, MA, USA; Division of Engineering in Medicine, Brigham and Women's Hospital, Boston, MA, USA. Electronic address: agoldman@bwh.harvard.edu.

Abstract

Ex vivo human tumor models have emerged as promising, yet complex tools to study cancer immunotherapy response dynamics. Here, we present a strategy that integrates empirical data from an ex vivo human system with computational models to interpret the response dynamics of a clinically prescribed PD-1 inhibitor, nivolumab, in head and neck squamous cell carcinoma (HNSCC) biopsies (N = 50). Using biological assays, we show that drug-induced variance stratifies samples by T helper type 1 (Th1)-related pathways. We then built a systems biology network and mathematical framework of local and global sensitivity analyses to simulate and estimate antitumor phenotypes, which implicate a dynamic role for the induction of Th1-related cytokines and T cell proliferation patterns. Together, we describe a multi-disciplinary strategy to analyze and interpret the response dynamics of PD-1 blockade using heterogeneous ex vivo data and in silico simulations, which could provide researchers a powerful toolset to interrogate immune checkpoint inhibitors.

Keywords: Biological Sciences; Cancer Systems Biology; Immunology; Systems Biology.