Endocrine complications are common in pediatric brain tumor patients.

The immunosuppressive tumor microenvironment present in the majority of diffuse glioma limits therapeutic response to immunotherapy. As the determinants of the glioma-associated immune response are relatively poorly understood, the study of glioma with more robust tumor-associated immune responses may be particularly useful to identify novel immunomodulatory factors that can promote T-cell effector function in glioma.

Gliomas arising in the setting of neurofibromatosis type 1 (NF1) are heterogeneous, occurring from childhood through adulthood, can be histologically low-grade or high-grade, and follow an indolent or aggressive clinical course. Comprehensive profiling of genetic alterations beyond NF1 inactivation and epigenetic classification of these tumors remain limited. Through next-generation sequencing, copy number analysis, and DNA methylation profiling of gliomas from 47 NF1 patients, we identified 2 molecular subgroups of NF1-associated gliomas. The first harbored biallelic NF1 inactivation only, occurred primarily during childhood, followed a more indolent clinical course, and had a unique epigenetic signature for which we propose the terminology "pilocytic astrocytoma, arising in the setting of NF1". The second subgroup harbored additional oncogenic alterations including CDKN2A homozygous deletion and ATRX mutation, occurred primarily during adulthood, followed a more aggressive clinical course, and was epigenetically diverse, with most tumors aligning with either high-grade astrocytoma with piloid features or various subclasses of IDH-wildtype glioblastoma. Several patients were treated with small molecule MEK inhibitors that resulted in stable disease or tumor regression when used as a single agent, but only in the context of those tumors with NF1 inactivation lacking additional oncogenic alterations. Together, these findings highlight recurrently altered pathways in NF1-associated gliomas and help inform targeted therapeutic strategies for this patient population.

Cancerous tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones, which are not observed in normal human brain samples. Importantly, by genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations identified from bulk tumor sections, we show that commonly used algorithms for inferring malignancy from single-cell transcriptomes may be inaccurate. Furthermore, we demonstrate how correlating gene expression with tumor purity in bulk samples provides the same information as differential expression analysis of malignant versus nonmalignant cells and use this approach to identify a core set of genes that is consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity in clinical specimens and clarifying the molecular profiles of distinct cellular populations in any kind of solid tumor.

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.