BackgroundGlioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.MethodsA necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.ResultsThree necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.ConclusionsOur necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment.

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Gliomas are the most aggressive and common type of malignant brain tumor, with limited treatment options and a dismal prognosis. Angiogenesis, a hallmarks of cancer, is one of two critical events in the progression of gliomas. Accumulating evidence has demonstrated that in glioma dysregulated molecules like long noncoding RNAs (lncRNAs), are closely linked to tumorigenesis and prognosis. However, the effects of and mechanisms of action of lncRNAs during tumor angiogenesis are poorly understood. The effect of lncRNA RP11-732M18.3 on angiogenesis was elucidated through an intracranial orthotopic glioma model, immunohistochemistry, and an in vitro angiogenesis assay. Co-culture experiments and cell migration assays were performed to investigate the function of lncRNA RP11-732M18.3 in vitro. lncRNA RP11-732M18.3 increased CD31+ microvessel density, and overexpression of lncRNA RP11-732M18.3 resulted in poor mouse survival. lncRNA RP11-732M18.3 promoted endothelial cell migration and tube formation. Nomogram and Kaplan-Meier survival analyses indicated that higher VEGFA is correlated with a poor prognosis. Mechanistically, lncRNA RP11-732M18.3 promotes angiogenesis by increasing the nuclear level of EP300 and facilitating the transcription and secretion of VEGFA. Our study contributes to the latest understanding of glioma angiogenesis and prognosis. lncRNA RP11-732M18.3 may be a potential treatment target in glioma.

With time, the number of samples in clinical laboratories from therapeutic drug monitoring has increased. Existing analytical methods for blood cyclosporin A (CSA) monitoring, such as high-performance liquid chromatography (HPLC) and immunoassays, have limitations including cross-reactivity, time consumption, and the complicated procedures involved. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has long been considered the reference standard owing to its high accuracy, specificity, and sensitivity. However, large numbers of blood samples, multi-step preparation procedures, and longer analytical times (2.5-20 min) are required as a consequence of the different technical strategies, to ensure good analytical performance and routine quality assurance. A stable, reliable, and high throughput detection method will save personnel time and reduce laboratory costs. Therefore, a high throughput and simple LC-MS/MS method was developed and validated for the detection of whole-blood CSA with CSA-d12 as the internal standard in the present study. Whole blood samples were prepared through a modified one-step protein precipitation method. A C18 column (50x2.1 mm, 2.7 µm) with a mobile phase flow rate of 0.5 ml/min was used for chromatographic separation with a total running time of 4.3 min to avoid the matrix effect. To protect the mass spectrometer, only part of the sample after LC separation was allowed to enter the mass spectrum, using two HPLC systems coupled to one mass spectrometry. In this way, throughput was improved with detection of two samples possible within 4.3 min using a shorter analytical time for each sample of 2.15 min. This modified LC-MS/MS method showed excellent analytical performance and demonstrated less matrix effect and a wide linear range. The design of multi-LC systems coupled with one mass spectrometry may play a notable role in the improvement of daily detection throughput, speeding up LC-MS/MS, and allowing it to be an integral part of continuous diagnostics in the near future.

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