The characterization of the tumor microenvironment (TME) in high grade gliomas (HGG) has generated significant interest in an effort to understand how neoplastic lesions in the central nervous system (CNS) are supported and to devise novel therapeutic targets. The TME of the CNS contains unique and specialized cells, including the resident myeloid cells, microglia. Myeloid involvement in HGG, such as glioblastoma, is associated with poor outcomes. Glioma‐associated microglia and infiltrating monocytes/macrophages (GAM) accumulate within the neoplastic lesion where they facilitate tumor growth and drive immunosuppression. However, it has been difficult to differentiate whether microglia and macrophages have similar or distinct roles in pathology, and if the spatial organization of these cells informs outcomes. Here, we characterize the tumor–stroma border and identify peritumoral GAM (PGAM) as a unique subpopulation of GAM. Using data mining and analyses of samples derived from both murine and human sources we show that PGAM exhibit a pro‐inflammatory and chemotactic phenotype that is associated with peripheral monocyte recruitment, and decreased overall survival. PGAM act as a unique subset of GAM at the tumor–stroma interface. We define a novel gene signature to identify these cells and suggest that PGAM constitute a cellular target of the TME.

Genomic analysis of a patients' tumor is the cornerstone of precision oncology, but it doesn't address whether metastases should be treated differently. Here we tested whether comparative scRNA-seq of a primary small intestinal neuroendocrine tumor to a matched liver metastasis could guide treatment of a patients' metastatic disease. Following surgery, the patient was put on maintenance treatment with a somatostatin analog. However, the scRNA-seq analysis revealed that the neuroendocrine epithelial cells in the liver metastasis were less differentiated and expressed relatively little SSTR2, the predominant somatostatin receptor. There were also differences in the tumor microenvironments. RNA expression of vascular endothelial growth factors was higher in the primary tumor cells, reflected by an increased number of endothelial cells. Interestingly, vascular expression of the major VEGF receptors was considerably higher in the liver metastasis, indicating that the metastatic vasculature may be primed for expansion and susceptible to treatment with angiogenesis inhibitors. The patient eventually progressed on sandostatin and although consideration was given to adding an angiogenesis inhibitor to her regimen, her disease progression involved non-liver metastases which had not been characterized. Although in this specific case comparative scRNA-seq did not alter treatment, its potential to help guide therapy of metastatic disease was clearly demonstrated.

Background: Myeloid involvement in High Grade Gliomas, such as Glioblastoma, has become apparent and detrimental to disease outcomes. There is great interest in characterizing the HGG tumor microenvironment to understand how neoplastic lesions are supported, and to devise novel therapeutic targets. The tumor microenvironment of the central nervous system is unique as it contains neural and specialized glial cells, including the resident myeloid cells, microglia. Glioma‐associated microglia and peripherally infiltrating monocytes/macrophages (GAM) accumulate within the neoplastic lesion where they facilitate tumor growth and drive immunosuppression. A longstanding limitation has been the ability to accurately differentiate microglia and macrophage roles in pathology, and identify the consequences of the spatial organization of these cells. Results: Here we characterize the tumor‐stroma border and identify peripheral glioma-associated microglia (PGAM) at the tumor leading edge as a unique subpopulation of GAM. Using data mining and analyses of samples derived from both murine and human sources, we show that PGAM exhibit a pro‐inflammatory and chemotactic phenotype that is associated with peripheral monocyte recruitment, poorly enhancing radiomic features, and decreased overall survival. Conclusions: PGAM act as a unique subset of GAM, at the tumor-stroma interface, corresponding to disease outcomes. We propose the application of a novel gene signature to identify these cells, and suggest that PGAM constitute a cellular target of the TME.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease for which potent therapies have limited efficacy. Several studies have described the transcriptomic landscape of PDAC tumors to provide insight into potentially actionable gene expression signatures to improve patient outcomes. Despite centralization efforts from multiple organizations and increased transparency requirements from funding agencies and publishers, analysis of public PDAC data remains difficult. Bioinformatic pitfalls litter public transcriptomic data, such as subtle inclusion of low-purity and non-adenocarcinoma cases. These pitfalls can introduce non-specificity to gene signatures without appropriate data curation, which can negatively impact findings. To reduce barriers to analysis, we have created pdacR (http://pdacR.bmi.stonybrook.edu, github.com/rmoffitt/pdacR), an open-source software package and web-tool with annotated datasets from landmark studies and an interface for user-friendly analysis in clustering, differential expression, survival, and dimensionality reduction. Using this tool, we present a multi-dataset analysis of PDAC transcriptomics that confirms the basal-like/classical model over alternatives.