Superior therapy response predictions for patients with low-grade glioma (LGG) using Cellworks Singula: MyCare-009-04.

Abstract

2569 Background: Despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of LGG patients remains relatively poor. Therapy selection is often based on information considering only a single aberration and ignoring other patient-specific omics data which could potentially enable more effective treatments. The Cellworks Singula report predicts response for physician prescribed therapies (PPT) using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. We test the hypothesis that Singula is a superior predictor of progression-free survival (PFS) and overall survival (OS) compared to PPT. Methods: Singula’s ability to predict response was evaluated in an independent, randomly selected, retrospective cohort of 137 LGG patients aged 14 to 73 years treated with PPT. Patient omics data was available from TCGA. Singula uses PubMed to generate protein interaction network activated and inactivated disease pathways. We simulated the PPT for each patient and calculated the quantitative drug effect on a composite LGG disease inhibition score based on specific phenotypes while blinded to clinical response. Univariate and multivariate proportional hazards (PH) regression analyses were performed to determine if Singula provides predictive information for PFS and OS, respectively, above and beyond age and PPT. Results: In univariate analyses, Singula was a significant predictor of both PFS (HR = 3.587, p < 0.0001) and OS (HR = 3.044, p = 0.0007). In multivariate PH regression analyses, Singula (HR = 3.707, p < 0.0001) remained an independent predictor of PFS after adjustment for PPT (p = 0.3821) and patient age (p = 0.0020). Singula (HR = 2.970, p = 0.0013) was also a significant independent predictor of OS after adjustment for PPT (p = 0.0540) and patient age (p < 0.0001). Results indicate that Singula is a superior predictor of both PFS and OS compared to PPT. Singula provided alternative standard of care therapy selections for all 34 disease progressors. Conclusions: Singula is a superior predictor of PFS and OS in LGG patients compared to PPT. Singula can correctly identify non-responders to PPT and provide alternative therapy selections.