Predictions of overall survival (OS) and progression-free survival (PFS) for specific therapeutic interventions in newly diagnosed glioblastoma multiforme (GBM) using Cellworks Singula: myCare-024-04.

Abstract

2053 Background: Comprehensive molecular profiling reveals significant differences in treatment response among GBM patients. A mechanistic multi-omics biology model allows biosimulation of molecular effects of cell signaling, drugs and radiation on patient-specific in silico diseased cells. The Cellworks Singula Therapy Response Index (TRI) identifies the magnitude of disease control and survival for specific anti-tumor strategies. TRI ranks the anticipated outcome of each therapy with a continuous TRI Score, 0 to 100, for each patient’s unique genomic network. Methods: TRI’s ability to predict OS and PFS was prospectively evaluated in a retrospective cohort of 270 IDH wildtype GBM patients from The Cancer Genome Atlas (TCGA) with known clinical outcomes treated with physician prescribed therapies (PPT). The median age was 57.5 years for 162 males and 108 females. There were 73 MGMT methylated with median OS deceased of 17.1 months and living of 9.5 months and median PFS of 6.5 months. There were 197 MGMT unmethylated with median OS deceased of 14.0 months and living of 13.6 months and median PFS of 6.0 months. Stratified random sampling was used to split the data into independent training (N = 153) and validation (N = 117) subjects. Multivariate Cox Proportional Hazard and Proportional Odds models were used to model OS and PFS as a function of the pre-defined Singula TRI and clinical thresholds. Cox Proportional Hazards (PH) regression and likelihood ratio (LR) tests were used on the independent validation subjects to assess the hypothesis that Singula is predictive of OS and PFS above and beyond standard clinical factors. Results: In the validation set, Singula TRI was significantly predictive of OS and PFS in univariate analyses and remained significantly predictive in multivariate analyses which included age, sex, MGMT methylation status and drug class. Singula TRI facilitates selection of optimal personalized therapies by providing patient-specific estimates of OS and PFS for 18 NCCN guideline GBM therapies. Conclusions: Cellworks Singula was strongly predictive of OS and PFS and provided predictive value beyond physician prescribed therapy, patient age, sex and MGMT methylation status. This information may be used to estimate increases in OS and PFS when comparing Singula TRI recommended therapies versus standard care. These positive results suggest the utility of biosimulation-informed therapy selection to improve survival of GBM and merits validation in prospective clinical studies. [Table: see text]