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.

Chemerin enhances mesenchymal features of glioblastoma by establishing autocrine and paracrine networks in a CMKLR1-dependent manner.

Glioblastoma multiforme (GBM) with mesenchymal features exhibits enhanced chemotherapeutic resistance and results in reduced overall survival. Recent studies have suggested that there is a positive correlation between the GBM mesenchymal status and immune cell infiltration. However, the mechanisms by which GBM acquires its mesenchymal features in a tumor immune microenvironment-dependent manner remains unknown. Here, we uncovered a chemerin-mediated autocrine and paracrine network by which the mesenchymal phenotype of GBM cells is strengthened. We identified chemerin as a prognostic secretory protein mediating the mesenchymal phenotype-promoting network between tumor-associated macrophages (TAMs) and tumor cells in GBM. Mechanistically, chemerin promoted the mesenchymal features of GBM by suppressing the ubiquitin-proteasomal degradation of CMKLR1, a chemerin receptor predominantly expressed on TAMs and partially expressed on GBM cells, thereby enhancing NF-κB pathway activation. Moreover, chemerin was found to be involved in the recruitment of TAMs in the GBM tumor microenvironment. We revealed that chemerin also enhances the mesenchymal phenotype-promoting ability of TAMs and promotes their M2 polarization via a CMKLR1/NF-κB axis, which further exacerbates the mesenchymal features of GBM. Blocking the chemerin/CMKLR1 axis with 2-(α-naphthoyl) ethyltrimethylammonium iodide disrupted the mesenchymal network and suppressed tumor growth in GBM. These results suggest the therapeutic potential of targeting the chemerin/CMKLR1 axis to block the mesenchymal network in GBM.

Immunological Classification of Tumor Types and Advances in Precision Combination Immunotherapy.

Immunity is an important physiological function acquired throughout evolution as a defense system against the invasion of pathogenic microorganisms. The immune system also eliminates senescent cells and maintains homeostasis, monitoring cell mutations and preventing tumor development via the action of the immune cells and molecules. Immunotherapy often relies on the interaction of immune cells with the tumor microenvironment (TME). Based on the distribution of the number of lymphocytes (CD3 and CD8) in the center and edge of the tumor and the expression level of B7-H1/PD-L1, tumors are divided into hot tumors, cold tumors, and intermediate tumors (including immune-suppressed and isolated). This review focuses on the advances in precision combination immunotherapy, which has been widely explored in recent years, and its application in different tumor types.

Tumor Purity as an Underlying Key Factor in Glioma.

Purpose: Glioma tissues consist of not only glioma cells but also glioma-associated nontumor cells, such as stromal cells and immune cells. These nontumor cells dilute the purity of glioma cells and play important roles in glioma biology. Currently, the implications of variation in glioma purity are not sufficiently clarified.Experimental Design: Here, tumor purity was inferred for 2,249 gliomas and 29 normal brain tissues from 5 cohorts. Based on the transcriptomic profiling method, we classified CGGA and TCGA-RNAseq cohorts as the RNAseq set for discovery. Cases from TCGA-microarray, REMBRANDT, and GSE16011 cohorts were grouped as a microarray set for validation. Tissues from the CGGA cohort were reviewed for histopathologic validation.Results: We found that glioma purity was highly associated with major clinical and molecular features. Low purity cases were more likely to be diagnosed as malignant entities and independently correlated with reduced survival time. Integrating glioma purity into prognostic nomogram significantly improved the predictive validity. Moreover, most recognized prognostic indicators were no longer significantly effective under different purity conditions. These results highlighted the clinical importance of glioma purity. Further analyses found distinct genomic patterns associated with glioma purity. Low purity cases were distinguished by enhanced immune phenotypes. Macrophages, microglia, and neutrophils were mutually associated and enriched in low purity gliomas, whereas only macrophages and neutrophils served as robust indicators for poor prognosis.Conclusions: Glioma purity and relevant nontumor cells within microenvironment confer important clinical, genomic, and biological implications, which should be fully valued for precise classification and clinical prediction. Clin Cancer Res; 23(20); 6279-91. ©2017 AACR.

Expression and prognostic value of microRNAs in lower-grade glioma depends on IDH1/2 status.

Histological and genomic characteristics are widely used in glioma management and research. This study investigated their relationship to the expression and prognostic value of microRNAs (miRNAs) in lower-grade glioma (LGG). A total of 447 LGG samples with available clinical and genomic information from The Cancer Genome Atlas database were reviewed. Samples with isocitrate dehydrogenase (IDH) 1/2 mutations (n = 366) were randomly divided into training and validation sets to establish and confirm a four-miRNA-based risk classifier. We found that IDH1/2 mutation status had greater impact than histological and other genomic features on miRNA expression patterns; 361/487 (74%) of miRNAs were differentially expressed according to IDH1/2 mutation status. Importantly, there were no miRNAs with the same prognostic significance among groups with different IDH1/2 mutation status. For IDH1/2-mut LGG, a four-miRNA risk classifier (miR-10b, miR-130b, miR-1304, and miR-302b) was established that could independently distinguish cases as high or low risk of poor prognosis in both training and validation sets. The risk classifier outperformed individual miRNAs and traditional prognostic factors in terms of sensitivity and specificity. Bioinformatic analyses indicated that high-risk samples were more mitotically active than low-risk samples. Taken together, IDH1/2 mutation status had a significant influence on miRNA expression and prognostication in LGG. The four-miRNA-based risk classifier can be used for risk stratification of IDH1/2-mut LGG.

Bioinformatic analyses reveal a distinct Notch activation induced by STAT3 phosphorylation in the mesenchymal subtype of glioblastoma.

OBJECTIVE Glioblastoma (GBM) is the most common and lethal type of malignant glioma. The Cancer Genome Atlas divides the gene expression-based classification of GBM into classical, mesenchymal, neural, and proneural subtypes, which is important for understanding GBM etiology and for designing effective personalized therapy. Signal transducer and activator of transcription 3 (STAT3), a critical transcriptional activator in tumorigenesis, is persistently phosphorylated and associated with an unfavorable prognosis in GBM. Although a set of specific targets has been identified, there have been no systematic analyses of STAT3 signaling based on GBM subtype. METHODS This study compared STAT3-associated messenger RNA, protein, and microRNA expression profiles across different subtypes of GBM. RESULTS The analyses revealed a prominent role for STAT3 in the mesenchymal but not in other GBM subtypes, which can be reliably used to classify patients with mesenchymal GBM into 2 groups according to phosphorylated STAT3 expression level. Differentially expressed genes suggest an association between Notch and STAT3 signaling in the mesenchymal subtype. Their association was validated in the U87 cell, a malignant glioma cell line annotated as mesenchymal subtype. Specific associated proteins and microRNAs further profile the STAT3 signaling among GBM subtypes. CONCLUSIONS These findings suggest a prominent role for STAT3 signaling in mesenchymal GBM and highlight the importance of identifying signaling pathways that contribute to specific cancer subtypes.

Gene Expression Profiling Stratifies IDH1-Mutant Glioma with Distinct Prognoses.

Isocitrate dehydrogenase (IDH)1 mutation is one of the most important genetic aberrations in glioma. Even several genetic events have refined its prognostic value, the genome-wide expression alteration has not been systematically profiled. In this work, RNA-seq expression data from 310 patients in the Chinese Glioma Genome Atlas database were included as training set, while another 297 patients with microarray data were used as internal validation set. An independent cohort of GSE16011 (n = 205) constituted an external validation set. Approximately one fifth of the genes were differentially expressed in LGG according to IDH1 mutation status, yielding distinct gene expression profiles. A six-gene risk signature was established for IDH1-mutant LGG to distinguish low- from high-risk cases, which had distinct prognoses. The six-gene signature was an independent prognostic factor for IDH1-mutant LGG and had superior predictive value as compared to traditional clinicopathologic factors. Moreover, we depicted the differential expression pattern in GBM attributing to various IDH1 status, which was similar to that of LGG. It suggested that the effect of IDH1 mutation is conserved across histological classifications. The six-gene signature had equal prognostic value for IDH1-mutant GBM. By combining glioma grade, IDH1 status, and the six-gene signature, all glioma patients could be classified into six subgroups. These six subgroups could be further summarized into three sets with distinct prognosis. Taken together, a gene expression profile associated with IDH1 status was identified in LGG and GBM; a risk signature based on six genes was developed with equal prognostic value for IDH1-mutant LGG and GBM. When combined with clinicopathologic factors, the six-gene signature is a tool that enables precise risk stratification and can improve clinical management.

Bioinformatic profiling identifies an immune-related risk signature for glioblastoma.

OBJECTIVE: To investigate the local immune status and its prognostic value in glioma. METHODS: A cohort of 297 glioma samples with whole genome microarray expression data from the Chinese Glioma Genome Atlas database were included for discovery. The Cancer Genome Atlas (TCGA) database was used for validation. Principal components analysis and gene set enrichment analysis were used to explore the bioinformatic implication. RESULTS: Distinct local immune status was identified according to histologic grade. Glioblastoma (GBM) exhibited an enhanced immune phenotype compared to lower grade glioma. We profiled the immune-related gene set and identified 8 genes (FOXO3, IL6, IL10, ZBTB16, CCL18, AIMP1, FCGR2B, and MMP9) with the greatest prognostic value in GBM. A local immune-related risk signature was developed from the genes to distinguish cases as high or low risk of unfavorable prognosis, which could be validated in TCGA database. High-risk patients conferred an enhanced intensity of local immune response compared to low-risk ones. Additionally, the signature exhibited different distribution based on molecular features. The signature had prognostic significance in the stratified cohorts and was identified as an independent prognostic factor for GBM. CONCLUSIONS: We profiled the immune status in glioma and established a local immune signature for GBM, which could independently identify patients with a high risk of reduced survival, indicating the relationship between prognosis and local immune response.

A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients.

Although O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation status is an important marker for glioblastoma multiforme (GBM), there is considerable variability in the clinical outcome of patients with similar methylation profiles. The present study aimed to refine the prognostic and predictive value of MGMT promoter status in GBM by identifying a micro (mi)RNA risk signature. Data from The Cancer Genome Atlas was used for this study, with MGMT promoter-methylated samples randomly divided into training and internal validation sets. Data from The Chinese Glioma Genome Atlas was used for independent validation. A five miRNA-based risk signature was established for MGMT promoter-methylated GBM to distinguish cases as high- or low-risk with distinct prognoses, which was confirmed using internal and external validation sets. Importantly, the prognostic value of the signature was significant in different cohorts stratified by clinicopathologic factors and alkylating chemotherapy, and a multivariate Cox analysis found it to be an independent prognostic marker along with age and chemotherapy. Based on these three factors, we developed a quantitative model with greater accuracy for predicting the 1-year survival of patients with MGMT promoter-methylated GBM. These results indicate that the five-miRNA signature is an independent risk predictor for GBM with MGMT promoter methylation and can be used to identify patients at high risk of unfavorable outcome and resistant to alkylating chemotherapy, underscoring its potential for personalized GBM management.

Ecdysone receptor gene from the freshwater prawn Macrobrachium nipponense: identification of different splice variants and sexually dimorphic expression, fluctuation of expression in the molt cycle and effect of eyestalk ablation.

The full-length cDNA of an ecdysone receptor gene (MnEcR) from Macrobrachium nipponense was cloned and the expression of the gene was investigated. MnEcR maintained a relatively low expression level in the early stages of embryos, but from nauplius stage, a steady increase in MnEcR expression was detected, it had the highest expression level in zoea stage. MnEcR was highly expressed in the hepatopancreas and gills among ten different tissues examined. MnEcR was rapidly upregulated in the premolt stage and rapidly downregulated in the postmolt stage. The expression of MnEcR was remarkably downregulated after eyestalk ablation in M. nipponense. An 18-amino-acid insertion/deletion and a 49-amino-acid substitution were found in the coding region of MnEcR, resulting in four splice variants: MnEcR-L1, -L2, -S1 and-S2. The expression of four splice variants of MnEcR in gonads was investigated using RT-PCR. Interestingly, the expression patterns of these splice variants differed between males and females. The dominant splice variants in testis were MnEcR-S1 and -S2, while in ovary they were MnEcR-L1 and -S2, indicating specific roles for these splice variants in male and female individuals.

[Dynamic observation on MDA, iNOS and antisuperoxide anion in the liver of rats induced by acute nickel carbonyl poisoning].

OBJECTIVE: To investigate the level of malondiadehyde (MDA), antisuperoxide anion and inducible nitric oxide synthase (iNOS) in liver of rats poisoned by nickel carbonyl in order to discuss the mechanism of acute nickel carbonyl poisoning. METHODS: Healthy SD rats were intoxicated acutely by different concentrations of nickel carbonyl (20, 135 and 250mg/m3 for low, middle and high dose groups, respectively). SD rats inhaled by chlorine (250mg/m3 for chlorine group) were used as positive control group and other healthy SD rats as normal control group. Liver of animals was taken at different time points after exposure. The levels of MDA, iNOS and antisuperoxide anion were detected by biochemical assay. RESULTS: The contents of MDA and antisuperoxide anion in the liver of high dose group were significantly higher than that of other exposed groups and control group (P < 0.01). The contents of iNOS in middle and high dose group were higher than that in low dose group and control group (P < 0.05). CONCLUSION: The oxidative damage in the liver of SD rats could be induced by carbonyl nickel in air with increasing concentrations and in an obvious dose-response relationships.

A protein interaction network for the analysis of the neuronal differentiation of neural stem cells in response to titanium dioxide nanoparticles.

The effects of titanium dioxide (TiO(2)) nanoparticles (NPs) on the differentiation of neural stem cells are reported. Our findings indicate that TiO(2) NPs lead to a differentiational tendency towards neurons from neural stem cells, suggesting TiO(2) NPs might be a beneficial inducer for neuronal differentiation. To insight into the possible molecular mechanism of the neuronal differentiation, we conducted a protein-protein interaction network (PIN) analysis. To this end, a global mapping of target proteins induced by TiO(2) NPs was first made by a 2-dimensional electrophoresis analysis. Results showed that 9 proteins were significantly changed and then they were subjected to the mass spectrometric assay. All 9 identified proteins are involved in signal, molecular chaperones, cytoskeleton, and nucleoprotein. Further, based on our experimental data and DIP, IntAct-EBI, GRID database, a protein-protein interaction network was constructed, which provides highly integrated information exhibiting the protein-protein interaction. By analysis of the gene expression, the signal pathway involving Cx43 phosphorylation, which is negatively regulated by the protein kinase C epsilon (PKCepsilon), is demonstrated. It is inferred that PKCepsilon plays a pivotal negative role in the neuronal differentiation of stem neural cells in response to the TiO(2) NPs exposure.