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 The Cancer Genome Atlas (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, which 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.

We present a practical guide for the implementation of recently revised National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease (AD). Major revisions from previous consensus criteria are: (i) recognition that AD neuropathologic changes may occur in the apparent absence of cognitive impairment, (ii) an “ABC” score for AD neuropathologic change that incorporates histopathologic assessments of amyloid β deposits (A), staging of neurofibrillary tangles (B), and scoring of neuritic plaques (C), and (iii) more detailed approaches for assessing commonly co-morbid conditions such as Lewy body disease, vascular brain injury, hippocampal sclerosis, and TAR DNA binding protein (TDP)-43 immunoreactive inclusions. Recommendations also are made for the minimum sampling of brain, preferred staining methods with acceptable alternatives, reporting of results, and clinico-pathologic correlations.