CMTM6, a previously uncharacterized protein, was identified as a critical regulator of PD-L1, which is reported as an immune checkpoint inhibitor, to modulate the T cell activities both in vitro and in vivo of other tumors. However, the role of CMTM6 has so far remained unclear in glioma. To investigate the role of CMTM6 in gliomas, we analyzed the transcriptome level, genomic profiles and its relationship with clinical practice. 1862 glioma samples with transcriptome data were enrolled in this study, including CGGA RNA-seq, TCGA RNA-seq, CGGA-microarray, GSE16011 and IVY GBM databases. Clinical information and genomic profiles containing somatic mutations and DNA copy numbers were also obtained. We found that CMTM6 expression was highly correlated with major clinical and molecular characteristics. Cases with high CMTM6 expression were more likely to be predicted as malignant entities and frequent with genomic aberrations of driver oncogenes. Moreover, gene ontology analysis based on significantly correlated genes of CMTM6 expression exhibited that CMTM6 was associated with immune responses and inflammatory activities. CMTM6 was synthetic with other immune checkpoint inhibitors. Additionally, CMTM6 was involved in immune functions via modulating T-lymphocyte-mediated anti-tumor immunity. Finally, high CMTM6 expression was associated with reduced survival time and may serve as a strong indicator of poor prognosis in gliomas. In brief, High level of CMTM6 expression is closely related to high malignant gliomas. Meanwhile, CMTM6 plays an important role in regulating T cell activation and antitumor responses. Therefore, CMTM6 is a promising target for developing immunotherapy of gliomas.

Objectives To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging. Methods A total of 194 patients with Knosp grade two and three PAs (training set: n = 97; test set: n = 97) were enrolled in this retrospective study. From CE-T1 and T2 MR images, 2553 quantitative imaging features were extracted. To select the most informative features, least absolute shrinkage and selection operator (LASSO) was performed. Subsequently, a linear support vector machine (SVM) was used to fit the predictive model. Furthermore, a nomogram was constructed by incorporating clinico-radiological risk factors and radiomics signature, and the clinical usefulness of the nomogram was validated using decision curve analysis (DCA). Results Three imaging features were selected in the training set, based on which the radiomics model yielded area under the curve (AUC) values of 0.852 and 0.826 for the training and test sets. The nomogram based on the radiomics signature and the clinico-radiological risk factors yielded an AUC of 0.899 in the training set and 0.871 in the test set. Conclusions The nomogram developed in this study might aid neurosurgeons in the pre-operative prediction of CS invasion by Knosp grade two and three PAs, which might contribute to creating surgical strategies. Key Points • Pre-operative diagnosis of CS invasion by PAs might affect creating surgical strategies • MRI might help for diagnosis of CS invasion by PAs before surgery • Radiomics might improve the CS invasion detection by MR images.

In multiple solid tumours, including gliomas, the mechanical properties change as the disease progresses. If and how mechanical cues regulate tumour cell proliferation is currently not fully studied. PIEZO1 has recently been identified as a crucial mechanosensitive cation channel in multiple solid tumours. However, we didn’t find any clinical data describing the association between PIEZO1 expression and glioma. To investigate the role of PIEZO1 in gliomas, we analysed PIEZO1 gene expression at the transcriptome level, genomic profiles and the association of PIEZO1 with clinical practice. In total, 1633 glioma samples with transcriptome data, including data from the Chinese Glioma Genome Atlas RNAseq, the Cancer Genome Atlas RNAseq and GSE16011 databases, were included in this study. Clinical information and genomic profiles including somatic mutations were also obtained. We found that PIEZO1 expression was highly correlated with malignant clinical and molecular subtypes of glioma. Gene ontology analysis showed that expression of PIEZO1 was correlated with tumour microenvironment-related genes that encode proteins involved in extracellular matrix (ECM) organization, angiogenesis and cell migration. Additionally, PIEZO1 was shown to be involved in tumour progression by serving as the central checkpoint of multiple ECM remodelling-related signalling pathways to modulate tumour cell proliferation and the tumour microenvironment in turn. Finally, high PIEZO1 expression was correlated with reduced survival time and acted as a robust biomarker for poor prognosis in gliomas. Taken together, the results indicated that high PIEZO1 expression is closely associated with highly malignant gliomas. Importantly, PIEZO1 serves as a key factor involved in sensing mechanical properties in the tumour and can regulate both tumour cells and their microenvironment to promote glioma progression, and it is also a potential therapeutic target for the treatment of gliomas.