Mucin 1 and poly I:C activates dendritic cells and effectively eradicates pituitary tumors as a prophylactic vaccine

The biological behavior and clinical outcome of pituitary adenoma are affected by the microenvironment

BACKGROUND

Pituitary adenoma is one of the most common brain tumors. Most pituitary adenomas are benign and can be cured by surgery and/or medication. However, some pituitary adenomas show aggressive growth with a fast growth rate and are resistant to conventional treatments such as surgery, drug therapy, and radiation therapy. These tumors, referred to as refractory pituitary adenomas, often relapse or regrow in the early postoperative period. The tumor microenvironment (TME) has recently been identified as an important factor affecting the biological manifestations of tumors and acts as the main battlefield between the tumor and the host immune system.

MAIN BODY

In this review, we focus on describing TME in pituitary adenomas and refractory pituitary adenomas. Research on the immune microenvironment of pituitary adenomas is currently focused on immune cells such as macrophages and lymphocytes, and extensive research and experimental verifications are still required regarding other components of the TME. In particular, studies are needed to determine the role of the TME in the specific biological behaviors of refractory pituitary adenomas, such as high invasion, fast recurrence rate, and high tolerance to traditional treatments and to identify the mechanisms involved.

CONCLUSION

Overall, we summarize the similarities and differences between the TME of pituitary adenomas and refractory pituitary adenomas as well as the changes in the biological behavior of pituitary adenomas that may be caused by the microenvironment. These changes greatly affect the outcome of patients.

A novel risk model based on the correlation between the expression of basement membrane genes and immune infiltration to predict the invasiveness of pituitary adenomas

Objective

Invasive pituitary adenomas (IPAs) are common tumors of the nervous system tumors for which invasive growth can lead to difficult total resection and a high recurrence rate. The basement membrane (BM) is a special type of extracellular matrix and plays an important role in the invasion of pituitary adenomas (PAs). The aim of this study was to develop a risk model for predicting the invasiveness of PAs by analyzing the correlation between the expression of BM genes and immune infiltration.

Methods

Four datasets, featuring samples IPAs and non-invasive pituitary adenomas (NIPAs), were obtained from the Gene Expression Omnibus database (GEO). R software was then used to identify differentially expressed genes (DEGs) and analyze their functional enrichment. Protein-protein interaction (PPI) network was used to screen BM genes, which were analyzed for immune infiltration; this led to the generation of a risk model based on the correlation between the expression of BM genes and immunity. A calibration curve and receiver operating characteristic (ROC) curve were used to evaluate and validate the model. Subsequently, the differential expression levels of BM genes between IPA and NIPA samples collected in surgery were verified by Quantitative Polymerase Chain Reaction (qPCR) and the prediction model was further evaluated. Finally, based on our analysis, we recommend potential drug targets for the treatment of IPAs.

Results

The merged dataset identified 248 DEGs that were mainly enriching in signal transduction, the extracellular matrix and channel activity. The PPI network identified 11 BM genes from the DEGs: SPARCL1, GPC3, LAMA1, SDC4, GPC4, ADAMTS8, LAMA2, LAMC3, SMOC1, LUM and THBS2. Based on the complex correlation between these 11 genes and immune infiltration, a risk model was established to predict PAs invasiveness. Calibration curve and ROC curve analysis (area under the curve [AUC]: 0.7886194) confirmed the good predictive ability of the model. The consistency between the qPCR results and the bioinformatics results confirmed the reliability of data mining.

Conclusion

Using a variety of bioinformatics methods, we developed a novel risk model to predict the probability of PAs invasion based on the correlation between 11 BM genes and immune infiltration. These findings may facilitate closer surveillance and early diagnosis to prevent or treat IPAs in patients and improve the clinical awareness of patients at high risk of IPAs.

Graphene oxide modulates dendritic cell ability to promote T cell activation and cytokine production

An important aspect of immunotherapy is the ability of dendritic cells (DCs) to prime T cell immunity, an approach that has yielded promising results in some early phase clinical trials. However, novel approaches are required to improve DC therapeutic efficacy by enhancing their uptake of, and activation by, disease relevant antigens. The carbon nano-material graphene oxide (GO) may provide a unique way to deliver antigen to innate immune cells and modify their ability to initiate effective adaptive immune responses. We have assessed whether GO of various lateral sizes affects DC activation and function in vitro and in vivo, including their ability to take up, process and present the well-defined model antigen ovalbumin (OVA). We have found that GO flakes are internalised by DCs, while having minimal effect on their viability, activation phenotype or cytokine production. Although adsorption of OVA protein to either small or large GO flakes promoted its uptake into DCs, large GO interfered with OVA processing. In terms of modulation of DC function, delivery of OVA via small GO flakes significantly enhanced DC ability to induce proliferation of OVA-specific CD4⁺ T cells, promoting granzyme B secretion in vitro. On the other hand, delivery of OVA via large GO flakes augmented DC ability to induce proliferation of OVA-specific CD8⁺ T cells, and their production of IFN-γ and granzyme B. Together, these data demonstrate the capacity of GO of different lateral dimensions to act as a promising delivery platform for DC modulation of distinct facets of the adaptive immune response, information that could be exploited for future development of targeted immunotherapies.

The Epigenomic Landscape of Pituitary Adenomas Reveals Specific Alterations and Differentiates Among Acromegaly, Cushing's Disease and Endocrine-Inactive Subtypes

Purpose: Pituitary adenomas are one of the most common benign neoplasms of the central nervous system. Although emerging evidence suggests roles for both genetic and epigenetic factors in tumorigenesis, the degree to which these factors contribute to disease remains poorly understood.Experimental Design: A multiplatform analysis was performed to identify the genomic and epigenomic underpinnings of disease among the three major subtypes of surgically resected pituitary adenomas in 48 patients: growth hormone (GH)-secreting (n = 17), adrenocorticotropic hormone (ACTH)-secreting (n = 13, including 3 silent-ACTH adenomas), and endocrine-inactive (n = 18). Whole-exome sequencing was used to profile the somatic mutational landscape, whole-transcriptome sequencing was used to identify disease-specific patterns of gene expression, and array-based DNA methylation profiling was used to examine genome-wide patterns of DNA methylation.Results: Recurrent single-nucleotide and small indel somatic mutations were infrequent among the three adenoma subtypes. However, somatic copy-number alterations (SCNA) were identified in all three pituitary adenoma subtypes. Methylation analysis revealed adenoma subtype-specific DNA methylation profiles, with GH-secreting adenomas being dominated by hypomethylated sites. Likewise, gene-expression patterns revealed adenoma subtype-specific profiles. Integrating DNA methylation and gene-expression data revealed that hypomethylation of promoter regions are related with increased expression of GH1 and SSTR5 genes in GH-secreting adenomas and POMC gene in ACTH-secreting adenomas. Finally, multispectral IHC staining of immune-related proteins showed abundant expression of PD-L1 among all three adenoma subtypes.Conclusions: Taken together, these data stress the contribution of epigenomic alterations to disease-specific etiology among adenoma subtypes and highlight potential targets for future immunotherapy-based treatments. This article reveals novel insights into the epigenomics underlying pituitary adenomas and highlights how differences in epigenomic states are related to important transcriptome alterations that define adenoma subtypes. Clin Cancer Res; 24(17); 4126-36. ©2018 AACR.

Developing immunotherapeutic strategies to target brain tumors

INTRODUCTION

Recent years have seen rapid growth in cancer treatments that enhance the anti-tumor activities of the immune system. Collectively known as immunotherapy, modulation of the immune system has shown success treating some hematological malignancies, but has yet to be successfully applied to the treatment of patients with brain tumors.

AREAS COVERED

This review highlights mechanistic insights from murine studies and compiled recent clinical trial data, focusing on the most aggressive brain tumor, glioblastoma (GBM). The field has recently accumulated a critical mass of data, and we discuss past treatment failures in the context of newly developed approaches now entering clinical trials. This article provides an overview of the immunotherapeutic armamentarium currently in development for the treatment of patients with GBM, who are in dire need of safe and effective therapies. Expert commentary: Themes that emerge include the importance of mitigating the effects of an immunosuppressive tumor microenvironment and the potential for innate immune cell activation to enhance cytotoxic anti-tumor activity. Consideration of these studies as a collective may inform the design of new immunotherapies, as well as the immune monitoring protocols for patients participating in clinical trials.