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Abstract Background Pituitary neuroendocrine tumors (PitNET) are among the most common intracranial tumors. Despite a frequent benign course, aggressive behavior can occur. Tumor behavior is known to be under the influence of the tumor microenvironment (TME). However, the relationship between TME cells and aggressive tumor behavior has not been adequately explored in PitNET. Methods We performed differential expression analysis as well as gene expression program identification based on single-cell RNA sequencing to comparatively characterize the transcriptome of seven gonadotroph and three lactotroph PitNET and correlate it with clinical features using bulk RNA-seq data from an independent cohort of 134 PitNET. Tumor immune infiltration was quantified via immunostaining on tissue sections of gonadotroph and lactotroph PitNET. Results In lactotroph PitNET, we detect a highly proliferative gene profile with significantly increased expression levels in aggressively growing tumors within bulk RNA-seq data of an independent cohort of 134 PitNET samples. We also report high intratumoral heterogeneity in gonadotroph PitNET (GoPN) and lactotroph PitNET (LaPN) and identify signatures of epithelial, endocrine, and immunological gene networks in both subtypes. A comparison of their TME composition shows enrichment of SPP1+ macrophages and CD4+ T cells in GoPN, as well as enrichment of CD4/CD8 double-negative T cells (DN) and natural killer cells (NK) in LaPN. Also notable is the presence of proliferative lymphocytes, the occurrence of which positively correlates with more aggressive tumor behavior in the bulk RNA-seq cohort. However, increased CD8+ T and NK cell abundances correlate significantly with reduced aggressiveness indicating potential anti-tumoral effects. Conclusions Our study expands the knowledge of the differences in cellular composition of gonadotroph and lactotroph PitNET subtypes. It lays the foundation for further studies on the influence of lymphoid cells on the variable aggressive behavior of PitNET. Regarding the treatment of drug-resistant lactotroph PitNET, proliferative lymphocytes, CD8+ T, and NK cells could represent potentially valuable targets for developing new cancer immunotherapies.

Abstract Background Cancer metabolism influences multiple aspects of tumorigenesis and causes diversity across malignancies. Although comprehensive research has extended our knowledge of molecular subgroups in medulloblastoma (MB), discrete analysis of metabolic heterogeneity is currently lacking. This study seeks to improve our understanding of metabolic phenotypes in MB and their impact on patients’ outcomes. Methods Data from four independent MB cohorts encompassing 1,288 patients were analysed. We explored metabolic characteristics of 902 patients (ICGC and MAGIC cohorts) on bulk RNA level. Moreover, data from 491 patients (ICGC cohort) were searched for DNA alterations in genes regulating cell metabolism. To determine the role of intratumoral metabolic differences, we examined single-cell RNA-sequencing (scRNA-seq) data from 34 additional patients. Findings on metabolic heterogeneity were correlated to clinical data. Results Established MB groups exhibit substantial differences in metabolic gene expression. By employing unsupervised analyses, we identified three clusters of group 3 and 4 samples with distinct metabolic features in ICGC and MAGIC cohorts. Analysis of scRNA-seq data confirmed our results of intertumoral heterogeneity underlying the according differences in metabolic gene expression. On DNA level, we discovered clear associations between altered regulatory genes involved in MB development and lipid metabolism. Additionally, we determined the prognostic value of metabolic gene expression in MB and showed that expression of genes involved in metabolism of inositol phosphates and nucleotides correlates with patient survival. Conclusion Our research underlines the biological and clinical relevance of metabolic alterations in MB. Thus, distinct metabolic signatures presented here might be the first step towards future metabolism-targeted therapeutic options. Graphical Abstract