Background: Lactate greatly contributes to the regulation of intracellular communication within the tumor microenvironment (TME). However, the role of lactate in pituitary adenoma (PA) invasion is unclear. In this study, we aimed to clarify the effects of lactate on the TME and the effects of TME on PA invasion. Methods: To explore the correlation between TME acidosis and tumor invasion, LDHA and LAMP2 expression levels were quantified in invasive (n = 32) and noninvasive (n = 32) PA samples. The correlation between immune cell infiltration and tumor invasion was evaluated in 64 PAs. Critical chemokine and key signaling pathway components were detected by qPCR, Western blotting, siRNA knockdown, and specific inhibitors. The functional consequences of CCR4 signaling inhibition were evaluated in vitro and in vivo . Results: Lactate was positively associated with PA invasion. Of the 64 PA tissues, invasive PAs were related to high infiltration of M2-like tumor-associated macrophages (TAMs) (P < 0.05). Moreover, lactate secreted from PA cells facilitated M2 polarization via the mTORC2 and ERK signaling pathways, while activated TAMs secreted CCL17 to promote PA invasion via the CCL17/CCR4/mTORC1 axis. According to univariate analysis of clinical data, high CCL17 expression was associated with larger tumor size (P = 0.0438), greater invasion (P = 0.0334), and higher susceptibility to postoperative recurrence (P = 0.0195) in human PAs. Conclusion: This study illustrates the dynamics between PA cells and immune TME in promoting PA invasion via M2 polarization. CCL17 levels in the TME are related to the PA invasiveness and clinical prognosis, and the CCL17/CCR4/mTOCR1 axis may serve as potential therapeutic targets for Pas.

In this perspective, we highlight recent examples in the development of transition metal complexes as modulators of inflammatory and autoimmune responses.

This review describes recent examples of cyclometalated iridium(iii) metal complexes that act as luminescent chemosensors for cations, anions or small molecules.

This study reports the first use of an iridium(iii) compound and its enantiomer to inhibit the H-Ras/Raf-I PPI in vitro and repress renal cancer xenografts in vivo.

Glioma is one of the most typical intracranial tumors, comprising about 80% of all brain malignancies. Several key molecular signatures have emerged as prognostic biomarkers, which indicate room for improvement in the current approach to glioma classification. In order to construct a more veracious prediction model and identify the potential prognosis-biomarker, we explore the differential expressed m 6 A RNA methylation regulators in 665 gliomas from TCGA-GBM and TCGA-LGG. Consensus clustering was applied to the m6A RNA methylation regulators, and two glioma subgroups were identified with a poorer prognosis and a higher grade of WHO classification in cluster 1. The further chi-squared test indicated that the immune infiltration was significantly enriched in cluster 1, indicating a close relation between m 6 A regulators and immune infiltration. In order to explore the potential biomarkers, the weighted gene co-expression network analysis (WGCNA), along with Least absolute shrinkage and selection operator (LASSO), between high/low immune infiltration and m 6 A cluster 1/2 groups were utilized for the hub genes, and four genes ( TAGLN2, PDPN, TIMP1, EMP3) were identified as prognostic biomarkers. Besides, a prognostic model was constructed based on the four genes with a good prediction and applicability for the overall survival (OS) of glioma patients (the area under the curve of ROC achieved 0.80 (0.76–0.83) and 0.72 (0.68–0.76) in TCGA and Chinese Glioma Genome Atlas (CGGA), respectively). Moreover, we also found PDPN and TIMP1 were highly expressed in high-grade glioma from The Human Protein Atlas database and both of them were correlated with m6A and immune cell marker in glioma tissue samples. In conclusion, we construct a novel prognostic model which provides new insights into glioma prognosis. The PDPN and TIMP1 may serve as potential biomarkers for prognosis of glioma.