Deciphering the longitudinal trajectories of glioblastoma ecosystems by integrative single-cell genomics
Avishay Spitzer, Kevin C. Johnson, Masashi Nomura, Luciano Garofano, Djamel Nehar-Belaid, Noam Galili Darnell, Alissa Greenwald, Lillian Bussema, Young Taek Oh, Frederick S. Varn, Fulvio D’Angelo, Simon Gritsch, Kevin Anderson, Simona Migliozzi, L. Nicolas Gonzalez Castro, Tamrin Chowdhury, Nicolas Robine, Catherine Reeves, Jong Bae Park, Anuja Lipsa, Frank Hertel, Anna Golebiewska, Simone P. Niclou, Labeeba Nusrat, Sorcha Kellet, Sunit Das, Hyo-Eun Moon, Sun Ha Paek, Franck Bielle, Alice Laurenge, Anna Luisa Di Stefano, Bertrand Mathon, Alberto Pïcca, Marc Sanson, Shota Tanaka, Nobuhito Saito, David M. Ashley, Stephen T. Keir, Keith L. Ligon, Jason T. Huse, W.K. Alfred Yung, Anna Lasorella, Antonio Iavarone, Roel G.W. Verhaak, Itay Tirosh, Mario L. Suvà
Abstract
The evolution of isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) after standard-of-care therapy remains poorly understood. Here we analyzed matched primary and recurrent GBMs from 59 patients using single-nucleus RNA sequencing and bulk DNA sequencing, assessing the longitudinal evolution of the GBM ecosystem across layers of cellular and molecular heterogeneity. The most consistent change was a lower malignant cell fraction at recurrence and a reciprocal increase in glial and neuronal cell types in the tumor microenvironment (TME). The predominant malignant cell state differed between most matched pairs, but no states were exclusive or highly enriched in either time point, nor was there a consistent longitudinal trajectory across the cohort. Nevertheless, specific trajectories were enriched in subsets of patients. Changes in malignant state abundances mirrored changes in TME composition and baseline profiles, reflecting the co-evolution of the GBM ecosystem. Our study provides a blueprint of GBM’s diverse longitudinal trajectories and highlights the treatment and TME modifiers that shape them. Comparison of paired primary and recurrent glioblastomas at the single-cell transcriptomic level describes molecular and cellular trajectories associated with tumor recurrence, highlighting extensive heterogeneity and microenvironmental co-evolution.