Tumor Volume Dynamics as an Early Biomarker for Patient-Specific Evolution of Resistance and Progression in Recurrent High-Grade Glioma.

Daniel J Glazar,John A Arrington,Peter A Forsyth,Natarajan Raghunand,Heiko Enderling,Solmaz Sahebjam,G Daniel Grass,Hsiang-Hsuan Michael Yu

doi:10.3390/jcm9072019

Abstract

Recurrent high-grade glioma (HGG) remains incurable with inevitable evolution of resistance and high inter-patient heterogeneity in time to progression (TTP). Here, we evaluate if early tumor volume response dynamics can calibrate a mathematical model to predict patient-specific resistance to develop opportunities for treatment adaptation for patients with a high risk of progression. A total of 95 T1-weighted contrast-enhanced (T1post) MRIs from 14 patients treated in a phase I clinical trial with hypo-fractionated stereotactic radiation (HFSRT; 6 Gy × 5) plus pembrolizumab (100 or 200 mg, every 3 weeks) and bevacizumab (10 mg/kg, every 2 weeks; NCT02313272) were delineated to derive longitudinal tumor volumes. We developed, calibrated, and validated a mathematical model that simulates and forecasts tumor volume dynamics with rate of resistance evolution as the single patient-specific parameter. Model prediction performance is evaluated based on how early progression is predicted and the number of false-negative predictions. The model with one patient-specific parameter describing the rate of evolution of resistance to therapy fits untrained data (). In a leave-one-out study, for the nine patients that had T1post tumor volumes ≥1 cm3, the model was able to predict progression on average two imaging cycles early, with a median of 9.3 (range: 3–39.3) weeks early (median progression-free survival was 27.4 weeks). Our results demonstrate that early tumor volume dynamics measured on T1post MRI has the potential to predict progression following the protocol therapy in select patients with recurrent HGG. Future work will include testing on an independent patient dataset and evaluation of the developed framework on T2/FLAIR-derived data.

Highlights

Gliomas are cancers of glial cells in the brain
Anti-angiogenic therapy, such as bevacizumab, to target vascular endothelial growth factor (VEGF), and immunotherapy, such as pembrolizumab, to target programmed death protein 1 (PD-1) on T lymphocytes have been prospectively evaluated for high-grade glioma (HGG) [5,6,7,8]
Patients with recurrent HGG were treated with hypo-fractionated stereotactic radiotherapy (HFSRT) combined with pembrolizumab and bevacizumab (NCT02313272) [9]

Summary

Introduction

Gliomas are cancers of glial cells in the brain. High-grade gliomas (HGGs) are aggressive with dismal overall survival. Eligible patients received HFSRT to the recurrent tumor (6 Gy × 5) combined with pembrolizumab (100 or 200 mg, intravenously based on dose level, every 3 weeks) and bevacizumab (10 mg/kg, intravenously every 2 weeks). The RANO criteria define radiographic progression as 25% or greater increase in the sum of the products of perpendicular diameters of the enhancing lesion, when compared with baseline or smallest tumor measurement (nadir). While contrast-enhancing volumetric changes were found to be predictive of progression-free survival (PFS), volumetric measures have not yet been incorporated into the RANO criteria [11,12,13]. We evaluate if early tumor volume dynamics in T1-weighted contrast-enhanced (T1post) measurements can be used to calibrate and validate a mathematical model of patient-specific tumor volume dynamics to predict response dynamics following therapy. We identify a subset of recurrent HGG patients for whom treatment response dynamics can accurately predict progression

Experimental Section

Findings

Discussion