Patient-derived surgical samples reveal the cellular and molecular signatures of glioblastoma infiltration in distinct radiological zones.

Glioblastoma (GBM) is one of the deadliest cancers, largely due to its nearly inevitable recurrence driven by residual tumor cells. Recent evidence suggests that performing supratotal resections that extend into non-contrast-enhancing (nCE) tumor regions may prolong survival. However, tumor infiltration in these areas has not been fully characterized. Our goal was to define the cellular landscape of the GBM periphery and its clinical relevance. To accomplish this, we prospectively collected 161 biopsies from 45 GBM patients. The samples were classified using magnetic resonance imaging (MRI) as either enhancing tumor, nCE tumor, vasogenic edema, or radiologically normal tissue. We performed immunohistochemistry with MIB1 staining to detect proliferative cells and measure cell density. We also performed transcriptional profiling, selecting immune, glial, and vascular markers from single-cell RNA sequencing data. We analyzed the associations with the extent of resection and patient outcomes. Most nCE tumor biopsies displayed neoplastic features, including high cellularity, proliferative markers, and loss of oligodendrocyte signatures. However, some regions labeled as edema by MRI also contained infiltrating tumor cells and were associated with disease progression. Therefore, although MRI-based classification of nCE tumor regions is generally accurate, it underestimates infiltration within edema-labeled areas. Furthermore, in patients who underwent gross-total resection, high peripheral cellularity predicted earlier local recurrence. This suggests that assessing cell density in the periphery can improve recurrence risk prediction. Regarding the tumor microenvironment analysis, immune-related phenotypes were associated with a worse prognosis only after complete resection of the enhancing tumor. Furthermore, our gene panel, particularly the oligodendrocyte markers, provides prognostic insights depending on both biopsy location and resection extent. These findings support the integration of histological and molecular evaluations of the tumor periphery into surgical and therapeutic decision-making processes. This approach offers a path to better patient stratification and outcome prediction in GBM.