Functional drug susceptibility testing using single-cell mass predicts treatment outcome in patient-derived cancer neurosphere models

Functional precision medicine aims to match individual cancer patients to optimal treatment through ex vivo drug susceptibility testing on patient-derived cells. However, few functional diagnostic assays have been validated against patient outcomes at scale because of limitations of such assays. Here, we describe a high-throughput assay that detects subtle changes in the mass of individual drug-treated cancer cells as a surrogate biomarker for patient treatment response. To validate this approach, we determined ex vivo response to temozolomide in a retrospective cohort of 69 glioblastoma patient-derived neurosphere models with matched patient survival and genomics. Temozolomide-induced changes in cell mass distributions predict patient overall survival similarly to O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation and may aid in predictions in gliomas with mismatch-repair variants of unknown significance, where MGMT is not predictive. Our findings suggest cell mass is a promising functional biomarker for cancers and drugs that lack genomic biomarkers.

Automated summary

This study describes a high-throughput assay that detects subtle changes in the mass of individual drug-treated cancer cells as a potential biomarker for patient treatment response. Validation of this approach in glioblastoma patient-derived neurosphere models showed that changes in cell mass distributions could predict patient overall survival, especially in gliomas with mismatch-repair variants where MGMT is not predictive. This finding suggests that cell mass may be a promising functional biomarker for cancers and drugs lacking genomic biomarkers.