A single-cell based precision medicine approach using glioblastoma patient-specific models

This study presents a framework for precision medicine in glioblastoma (GBM) using a patient-specific, single-cell approach. Multi-omic single-cell analysis (snRNA-seq, snATAC-seq) was performed on a primary tumor sample, corresponding mouse xenografts (PDXs) subjected to standard of care (SOC) therapy, and a recurrent tumor at autopsy. The scSYGNAL platform identified a network of 52 regulators mediating treatment-induced shifts in xenograft tumor-cell states, also reflected in recurrence. Integrating this with single-cell ATAC-seq data, consensus networks modulating cell state transitions were developed. The framework enables matching targeted therapies to active regulatory networks, providing a single-cell-based precision medicine approach for individual GBM patients.

James H. Park, Abdullah H. Feroze, Samuel N. Emerson, Anca B. Mihalas, C. Dirk Keene, Patrick J. Cimino, Adrian Lopez Garcia de Lomanas, Kavya Kannan, Wei-Ju Wu, Serdar Turkarslan, Nitin S. Baliga, Anoop P. Patel