Re-convolving the compositional landscape of primary and recurrent glioblastoma using single nucleus RNA sequencing

Glioblastoma is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex tissue harboring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma margin is therapeutically and prognostically important. Here, we used single-nucleus RNA sequencing (snRNAseq) of primary and recurrent glioma to define compositional ‘tissue-states’ that correlate with radiographic and histopathologic features. We found that glioma cells can be clustered into proliferative, astrocyte-like/mesenchymal, and progenitor-like/proneural states in both the primary and post-treatment recurrence settings. We focused on non-neoplastic microenvironment cells including oligodendrocytes, myeloid cells, neurons, and astrocytes - the latter two are under-represented in single-cell RNAseq studies. Cell type-specific signatures of the astrocyte-like/mesenchymal glioma, and a subpopulation of non-neoplastic astrocytes correlated with poor prognosis, the latter correlated with glioma recurrence. Notably, astrocytes were enriched for metabolic and neurodegenerative gene signatures. Leveraging snRNAseq-derived compositional information, we define three tissue-states that correlate with radiographic localization of primary and recurrent glioma. Our findings define a compositional approach to the glioma microenvironment and reveal prognostically and anatomically relevant features paving the way to new mechanistic and therapeutic discoveries. ### Competing Interest Statement The authors have declared no competing interest.