MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma

Significance Molecular analysis of surgically resected glioblastomas (GBM) samples has uncovered phenotypically and clinically distinct tumor subtypes. However, little is known about the molecular features of the glioma margins that are left behind after surgery. To address this key issue, we performed RNA-sequencing (RNA-seq) and histological analysis on MRI-guided biopsies from the contrast-enhancing core and nonenhancing margins of GBM. Computational deconvolution of the RNA-seq data revealed that cellular composition, including nonneoplastic cells, is a major determinant of the expression patterns at the margins of GBM. The different GBM subtypes show distinct expression patterns that relate the contrast enhancing centers to the nonenhancing margins of tumors. Understanding these patterns may provide a means to infer the molecular and cellular features of residual disease. Glioblastomas (GBMs) diffusely infiltrate the brain, making complete removal by surgical resection impossible. The mixture of neoplastic and nonneoplastic cells that remain after surgery form the biological context for adjuvant therapeutic intervention and recurrence. We performed RNA-sequencing (RNA-seq) and histological analysis on radiographically guided biopsies taken from different regions of GBM and showed that the tissue contained within the contrast-enhancing (CE) core of tumors have different cellular and molecular compositions compared with tissue from the nonenhancing (NE) margins of tumors. Comparisons with the The Cancer Genome Atlas dataset showed that the samples from CE regions resembled the proneural, classical, or mesenchymal subtypes of GBM, whereas the samples from the NE regions predominantly resembled the neural subtype. Computational deconvolution of the RNA-seq data revealed that contributions from nonneoplastic brain cells significantly influence the expression pattern in the NE samples. Gene ontology analysis showed that the cell type-specific expression patterns were functionally distinct and highly enriched in genes associated with the corresponding cell phenotypes. Comparing the RNA-seq data from the GBM samples to that of nonneoplastic brain revealed that the differentially expressed genes are distributed across multiple cell types. Notably, the patterns of cell type-specific alterations varied between the different GBM subtypes: the NE regions of proneural tumors were enriched in oligodendrocyte progenitor genes, whereas the NE regions of mesenchymal GBM were enriched in astrocytic and microglial genes. These subtype-specific patterns provide new insights into molecular and cellular composition of the infiltrative margins of GBM.