Journal Article

Combination chemotherapy versus temozolomide for patients with methylated MGMT (m-MGMT) glioblastoma: results of computational biological modeling to predict the magnitude of treatment benefit

Lala, Deepak Anil, Poornachandra, G, Choudhary, Nikita Ray, Parashar Rajan, Nair, Prashant, Agarwal Ashish, Roy Kunal Ghosh Ghosh, Vishwas, Joseph, Kulkarni Shruthi, Castro, Michael, Pampana Anusha, Rajagopalan Swaminathan, Behura Liptimayee, Basu Sayani, Alam Aftab, Prakash Annapoorna, Kapoor Shweta

2021

Overview

BackgroundA randomized trial in glioblastoma patients with methylated-MGMT (m-MGMT) found an improvement in median survival of 16.7 months for combination therapy with temozolomide (TMZ) and lomustine, however the approach remains controversial and relatively under-utilized. Therefore, we sought to determine whether comprehensive genomic analysis can predict which patients would derive large, intermediate, or negligible benefits from the combination compared to single agent chemotherapy.MethodsComprehensive genomic information from 274 newly diagnosed patients with methylated-MGMT glioblastoma (GBM) was downloaded from TCGA. Mutation and copy number changes were input into a computational biologic model to create an avatar of disease behavior and the malignant phenotypes representing hallmark behavior of cancers. In silico responses to TMZ, lomustine, and combination treatment were biosimulated. Efficacy scores representing the effect of treatment for each treatment strategy were generated and compared to each other to ascertain the differential benefit in drug response.ResultsDifferential benefits for each drug were identified, including strong, modest-intermediate, negligible, and deleterious (harmful) effects for subgroups of patients. Similarly, the benefits of combination therapy ranged from synergy, little or negligible benefit, and deleterious effects compared to single agent approaches.ConclusionsThe benefit of combination chemotherapy is predicted to vary widely in the population. Biosimulation appears to be a useful tool to address the disease heterogeneity, drug response, and the relevance of particular clinical trials observations to individual patients. Biosimulation has potential to spare some patients the experience of over-treatment while identifying patients uniquely situated to benefit from combination treatment. Validation of this new artificial intelligence tool is needed.

• Publisher: Springer Nature B.V
• Subject: Artificial intelligence / Brain cancer / Chemotherapy / Clinical trials / Computer applications / Copy number / Genomic analysis / Glioblastoma / Patients / Phenotypes / Temozolomide