Classification of Brainstem Gliomas Based on Tumor Microenvironment Status

SIMPLE SUMMARY: The tumor microenvironment (TME) is vital in tumor biology, impacting tumor recurrence, prognosis, and treatment response. Brainstem gliomas (BSGs) are challenging gliomas that originate in the brainstem and have distinct clinical and genomic profiles from other brain gliomas. However, the inter-tumor heterogeneity of the TME in BSGs and its correlation with clinical and biological characteristics remain unknown, hindering the development of novel BSG therapies. In this study, we utilized transcriptional data from a BSG cohort and employed established signatures to assess the TME status and classify BSGs accordingly. Subsequently, we found an association between the TME classification and patient prognosis as well as the tumor phenotype. Furthermore, we explored key genes or radiomics features that can determine classification and potentially facilitate clinical applications. This research aims to enhance our understanding of TME heterogeneity in BSGs and to provide insights for improving diagnosis and treatment. ABSTRACT: The inter-tumor heterogeneity of the tumor microenvironment (TME) and how it correlates with clinical profiles and biological characteristics in brainstem gliomas (BSGs) remain unknown, dampening the development of novel therapeutics against BSGs. The TME status was determined with a list of pan-cancer conserved gene expression signatures using a single-sample gene set enrichment analysis (ssGSEA) and was subsequently clustered via consensus clustering. BSGs exhibited a high inter-tumor TME heterogeneity and were classified into four clusters: “immune-enriched, fibrotic”, “immune-enriched, non-fibrotic”, “fibrotic”, and “depleted”. The “fibrotic” cluster had a higher proportion of diffuse intrinsic pontine gliomas (p = 0.041), and “PA-like” tumors were more likely to be “immune-enriched, fibrotic” (p = 0.044). The four TME clusters exhibited distinct overall survival (p < 0.001) and independently impacted BSG outcomes. A four-gene panel as well as a radiomics approach were constructed to identify the TME clusters and achieved high accuracy for determining the classification. Together, BSGs exhibited high inter-tumor heterogeneity in the TME and were classified into four clusters with distinct clinical outcomes and tumor biological properties. The TME classification was accurately identified using a four-gene panel that can potentially be examined with the immunohistochemical method and a non-invasive radiomics method, facilitating its clinical application.