Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

BACKGROUND

A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials.

METHODS

Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors.

RESULTS

We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components.

CONCLUSIONS

Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Rel Family Transcription Factor NFAT5 Upregulates COX2 via HIF-1α Activity in Ishikawa and HEC1a Cells

Nuclear factor of activated T cells 5 (NFAT5) and cyclooxygenase 2 (COX2; PTGS2) both participate in diverse pathologies including cancer progression. However, the biological role of the NFAT5-COX2 signaling pathway in human endometrial cancer has remained elusive. The present study explored whether NFAT5 is expressed in endometrial tumors and if NFAT5 participates in cancer progression. To gain insights into the underlying mechanisms, NFAT5 protein abundance in endometrial cancer tissue was visualized by immunohistochemistry and endometrial cancer cells (Ishikawa and HEC1a) were transfected with NFAT5 or with an empty plasmid. As a result, NFAT5 expression is more abundant in high-grade than in low-grade endometrial cancer tissue. RNA sequencing analysis of NFAT5 overexpression in Ishikawa cells upregulated 37 genes and downregulated 20 genes. Genes affected included cyclooxygenase 2 and hypoxia inducible factor 1α (HIF1A). NFAT5 transfection and/or treatment with HIF-1α stabilizer exerted a strong stimulating effect on HIF-1α promoter activity as well as COX2 expression level and prostaglandin E2 receptor (PGE2) levels. Our findings suggest that activation of NFAT5-HIF-1α-COX2 axis could promote endometrial cancer progression.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

Background

A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials.

Methods

Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA-sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors.

Results

We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components.

Conclusions

Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Reciprocal fine-tuning of progesterone and prolactin-regulated gene expression in breast cancer cells

Progesterone and prolactin are two key hormones involved in development and remodeling of the mammary gland. As such, both hormones have been linked to breast cancer. Despite the overlap between biological processes ascribed to these two hormones, little is known about how co-expression of both hormones affects their individual actions. Progesterone and prolactin exert many of their effects on the mammary gland through activation of gene expression, either directly (progesterone, binding to the progesterone receptor [PR]) or indirectly (multiple transcription factors being activated downstream of prolactin, most notably STAT5). Using RNA-seq in T47D breast cancer cells, we characterized the gene expression programs regulated by progestin and prolactin, either alone or in combination. We found significant crosstalk and fine-tuning between the transcriptional programs executed by each hormone independently and in combination. We divided and characterized the transcriptional programs into four broad categories. All crosstalk/fine-tuning shown to be modulated by progesterone was dependent upon the expression of PR. Moreover, PR was recruited to enhancer regions of all regulated genes. Interestingly, despite the canonical role for STAT5 in transducing prolactin-signaling in the normal and lactating mammary gland, very few of the prolactin-regulated transcriptional programs fine-tuned by progesterone in this breast cancer cell line model system were in fact dependent upon STAT5. Cumulatively, these data suggest that the interplay of progesterone and prolactin in breast cancer impacts gene expression in a more complex and nuanced manner than previously thought, and likely through different transcriptional regulators than those observed in the normal mammary gland. Studying gene regulation when both hormones are present is most clinically relevant, particularly in the context of breast cancer.

Mapping circulating serum miRNAs to their immune-related target mRNAs

Purpose

Evidence suggests that circulating serum microRNAs (miRNAs) might preferentially target immune-related mRNAs. If this were the case, we hypothesized that immune-related mRNAs would have more predicted serum miRNA binding sites than other mRNAs and, reciprocally, that serum miRNAs would have more immune-related mRNA targets than non-serum miRNAs.

Materials and methods

We developed a consensus target predictor using the random forest framework and calculated the number of predicted miRNA–mRNA interactions in various subsets of miRNAs (serum, non-serum) and mRNAs (immune related, nonimmune related).

Results

Immune-related mRNAs were predicted to be targeted by serum miRNA more than other mRNAs. Moreover, serum miRNAs were predicted to target many more immune-related mRNA targets than non-serum miRNAs; however, these two biases in immune-related mRNAs and serum miRNAs appear to be completely independent.

Conclusion

Immune-related mRNAs have more miRNA binding sites in general, not just for serum miRNAs; likewise, serum miRNAs target many more mRNAs than non-serum miRNAs overall, regardless of whether they are immune related or not. Nevertheless, these two independent phenomena result in a significantly larger number of predicted serum miRNA–immune mRNA interactions than would be expected by chance.