An integrative model of cellular states, plasticity and genetics for glioblastoma

By C. Neftel, J. Laffy, M. Filbin, T. Hara, M. Shore, Gilbert J. Rahme, Alyssa R. Richman, Dana Silverbush, McKenzie L. Shaw, Christine Hebert and 48 more. Cell, 2019

2,235 citations recorded by the source corpus.

SUMMARY Diverse genetic, epigenetic and developmental programs drive glioblastoma, an incurable and poorly understood tumor, but their precise characterization remains challenging. Here we use an integrative approach spanning single-cell RNA-sequencing of 28 tumors, bulk genetic and expression analysis of 401 specimens from the TCGA, functional approaches and single-cell lineage tracing to derive a unified model of cellular states and genetic diversity in glioblastoma. We find that malignant cells in glioblastoma exist in four main cellular states that recapitulate distinct neural cell types, are influenced by the tumor microenvironment, and exhibit plasticity. The relative frequency of cells in each state varies between glioblastoma samples and is influenced by copy number amplifications of the CDK4, EGFR and PDGFRA loci, and by mutations in the NF1 locus, that each favor a defined state. Our work provides a blueprint for glioblastoma, integrating the malignant cell programs, their plasticity and their modulation by genetic drivers.

Subfields: Biophysics, Modeling and Simulation, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/674812f5e7df639c16ec392e7093ce63b8c7dcd3

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In Molecular Biology

1. Hongjun Song
2. Guo-li Ming
3. A. Marusyk
4. K. Polyak
5. Xuyu Qian
6. Adam J. Rubin
7. M. Janiszewska
8. R. Weinberg

Citations in the corpus

• A Patient-Derived Glioblastoma Organoid Model and Biobank Recapitulates Inter- and Intra-tumoral Heterogeneity. (2019, background): “For UP-8036-GBOs, we identified neoplastic populations of proliferating cells, oligodendrocyte precursor cell (OPC)-like, astrocyte-like, oligodendrocyte-like, and neuron-like cells (Figure 4I), similar to results recently reported in primary tumors (Neftel et al., 2019).”
• Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer (2019, methodology): “Instead, CNV profiling inferred by transcriptome has been used successfully to differentiate malignant cells from non-malignant cells and is a reliable method to estimate genomic alteration (Neftel et al., 2019; Patel et al., 2014; Puram et al., 2017; Tirosh et al., 2016a).”
• Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma (2020, background): “This is an open access article und tions that drive drug resistance, predict metastatic risk, and mediate plasticity (Neftel et al., 2019; Puram et al., 2017; Tirosh et al., 2016a).”
• Intratumor heterogeneity: the Rosetta stone of therapy resistance (2020, background): “In the case of brain tumors, singlecell profiling revealed four major states, associated with distinct developmental pathways hijacked by cancer cells (Neftel et al., 2019; Patel et al., 2014).”