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The Emeishan large igneous province (LIP) consists of Permian flood basalts and coeval intrusive rocks with compositions varying from mafic-ultramafic rocks to syenites and granites. The volatiles in the Emeishan LIP are dominated by H2O with high H-2, indicating that the plume-derived magma was generated under a reduced condition. Picrite has minor contents of H2S without detectable SO2, and the basalt samples show no detectable H2S and SO2, indicating that the basaltic magma may have undergone sulphur-saturation during magma evolution. The delta C-13 values of CO2 and CH4 in picrites and basalts are between the values of mantle and crustal organic carbon. This, together with the distribution patterns among CH4 homologue, indicates contribution of recycled sediments to the Emeishan mantle-derived magma. The He-3/He-4 ratios of volatiles extracted from olivine and pyroxene phenocrysts of picrites vary from 01 to 0.66 Ra, and those from pyroxene separates of olivine websterite samples in the Zhubu intrusion vary from 0.92 to 15 Ra. The low He-3/He-4 ratios of the picrites from Emeishan LIP are lower than those from the Siberian LIP, but within the values of continental crust and oceanic crust. The positive correlation between He-4/(40)Arc and He-4 contents in Emeishan picrite suggests that the isotopic ratios were dramatically affected by crustal contamination rather than degassing. The He and Ar isotopes indicate that Emeishan picrite experienced addition of subducted oceanic crustal materials, and the Zhubu magma was contaminated by continental crustal materials.

Uridine phosphorylase 1 (UPP1) has been reported as an oncogene in several malignancies. In glioma, the role of UPP1 remains unclear. This study was performed to explore its role in glioma at transcriptional level. Totally, 998 glioma patients with clinical data were enrolled, including 301 mRNA microarray data from Chinese Glioma Genome Atlas (CGGA) dataset and 697 RNAseq data from The Cancer Genome Atlas (TCGA) dataset. Statistical analysis was performed with R language. UPP1 expression level was positively correlated with WHO grade of glioma. UPP1 was significantly upregulated in mesenchymal subtype and could serve as a potential biomarker for this subtype. Based on most correlated genes of UPP1, Gene ontology analysis revealed that UPP1 was profoundly associated with immune and inflammatory response. Gene Sets Variation Analysis was further performed and showed that UPP1 was particularly correlated with MHC‐II and LCK, which were mainly associated with activities of antigen‐presenting cells and T cells. Moreover, UPP1 was found to be synergistic with various immune checkpoint members, especially with PD1 pathway and B7‐H3. Finally, Kaplan‐Meier curves revealed that higher UPP1 indicated significantly shorter survival for glioma patients. Taken together, UPP1 played an oncogenic role in glioma via suppressing tumor‐related immune response., UPP1 is positively associated with WHO grade of glioma. UPP1 is mainly involved in tumor‐induced immune response, particularly associated with antigen‐presenting cell‐related immune response and T‐cell activation. High expression level of UPP1 predicts poor prognosis in glioma.

This study conducted a systematic analysis of hypoxia-related genes (HRGs) to explore new markers for predicting the prognosis of glioblastoma (GBM). The gene expression profile and corresponding methylation, copy number variation (CNV), and genomic mutation data were downloaded from The Cancer Genome Atlas database. Two GEO cohorts were used to identify HRGs. The CGGA and GSE13041 were performed as validation cohorts. The hierarchical clustering algorithm was used to cluster molecular subtypes. Univariate cox analysis was used to assess prognosis. Spearman's method was conducted to evaluate the correlation among HRGs, methylation, and CNV. Finally, 158 HRGs were identified. Two molecular subtypes with significant prognosis were classified based on the expression of HRGs. The HRGs were mainly negatively correlated with methylation but were positively correlated with the somatic CNV. Based on the distinct prognoses revealed in univariate cox analysis, a 5-HRGs prognostic risk model was constructed and validated for predicting the survival of GBM patients.