RT Journal Article
SR Electronic
T1 The immune checkpoint kick start: Optimization of neoadjuvant combination therapy using game theory
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 349142
DO 10.1101/349142
A1 Jeffrey West
A1 Mark Robertson-Tessi
A1 Kimberly Luddy
A1 Derek S. Park
A1 Drew F.K. Williamson
A1 Cathal Harmon
A1 Hung T. Khong
A1 Joel Brown
A1 Alexander R.A. Anderson
YR 2018
UL http://biorxiv.org/content/early/2018/06/18/349142.abstract
AB An upcoming clinical trial at the Moffitt Cancer Center for women with stage 2/3 ER+breast cancer combines an aromatase inhibitor and a PD-L1 checkpoint inhibitor, and aims to lower a preoperative endocrine prognostic index (PEPI) that correlates with relapse-free survival. PEPI is fundamentally a static index, measured at the end of neoadjuvant therapy before surgery. We develop a mathematical model of the essential components of the PEPI score in order to identify successful combination therapy regimens that minimize both tumor burden and metastatic potential, based on time-dependent trade-offs in the system. We consider two molecular traits, CCR7 and PD-L1 which correlate with treatment response and increased metastatic risk. We use a matrix game model with the four phenotypic strategies to examine the frequency-dependent interactions of cancer cells. This game was embedded into an ecological model of tumor population growth dynamics. The resulting model predicts both evolutionary and ecological dynamics that track with changes in the PEPI score. We consider various treatment regimens based on combinations of the two therapies with drug holidays. By considering the trade off between tumor burden and metastatic potential, the optimal therapy plan was found to be a 1 month kick start of the immune checkpoint inhibitor followed by five months of continuous combination therapy. Relative to a protocol with both therapeutics given together from the start, this delayed regimen results in transient sub-optimal tumor regression while maintaining a phenotypic constitution that is more amenable to fast tumor regression for the final five months of therapy. The mathematical model provides a useful abstraction of clinical intuition, enabling hypothesis generation and testing of clinical assumptions.