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RNA epigenetic modification take part in many biology processes, and the N6-methyladenosine (m6A) methylation of specific mRNAs in endometrial cancer (EC) tissues play a key role in regulating the tumorigenicity of EC, but the specific mechanism still unknown and need to be investigated in the future. Here, we found that m6A reader protein YTHDF2 expression was significantly upregulated in EC compare to tumor adjacent tissues, YTHDF2 was then identified to inhibit the proliferation and invasion of EC cell lines. Mechanistically, the m6A reader YTHDF2 bind the methylation sites of target transcripts IRS1 and promoted IRS1 mRNA degradation, consequently inhibiting the expression of IRS1 and inhibiting IRS1/AKT signaling pathway, finally inhibit the tumorigenicity of EC. Thus, we demonstrated that YTHDF2 inhibited the proliferation and invasion of EC via inhibiting IRS1 expression in m6A epigenetic way, which suggests a potential therapeutic target for EC.Background Glioblastoma (GBM) is the most common primary malignant intracranial tumor and closely related to metabolic alteration. buy FGF401 However, few accepted prognostic models are currently available, especially models based on metabolic genes. Methods The transcriptome data were obtained for all of the patients diagnosed with GBM from the Gene Expression Omnibus (GEO) (training cohort, n=369) and The Cancer Genome Atlas (TCGA) (validation cohort, n=152) with the following variables age at diagnosis, sex, follow-up and overall survival (OS). Metabolic genes according to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were contracted, and a Lasso regression model was constructed. Survival was assessed by univariate or multivariate Cox proportional hazards regression and Kaplan-Meier analysis, and an independent external validation was also conducted to examine the model. Results There were 341 metabolic genes showed significant differences between normal brain and GBM tissues in both the training and validation cohorts, among which 56 genes were dramatically correlated to the OS of patients. Lasso regression revealed that the metabolic prognostic model was composed of 18 genes, including COX10, COMT, and GPX2 with protective effects, as well as OCRL and RRM2 with unfavorable effects. Patients classified as high-risk by the risk score from this model had markedly shorter OS than low-risk patients (P less then 0.0001), and this significant result was also observed in independent external validation (P less then 0.001). Conclusions The prognosis of GBM was dramatically related to metabolic pathways, and our metabolic prognostic model had high accuracy and application value in predicting the OS of GBM patients.Non-small-cell-lung cancer accounts for 80-85% of all forms of lung cancer as leading cause of cancer-related death in human. Despite remarkable advances in the diagnosis and therapy of lung cancer, no significant improvements have thus far been achieved in terms of patients’ prognosis. Here, we investigated the role of INSL4 – a member of the relaxin-family – in NSCLC. We overexpressed INSL4 in NSCLC cells to analyse in vitro the growth rate and the tumourigenic features. We investigated the signalling pathways engaged in INSL4 overexpressing cells and the tumour growth ability by studying the tumour development in a patient derived tumour xenograft mouse model. We found an INSL4 cell growth promoting effect in vitro in H1299 cells and in vivo in NOD/SCID mice. Surprisingly, in NSCLC-A549 cells, INSL4 overexpression has not similar effect, despite huge basal INSL4-mRNA expression respect to H1299. The INSL4-mRNA analysis of eight different NSCLC-derived cell lines, revealed highly difference in the INSL4-mRNA amount. Transfection of NSCLC lines with INSL4-Myc showed huge level of INSL4-mRNA with a very low amount of protein expressed. Notably, similar discrepancy has been observed in NSCLC patients. However, in a cohort of NSCLC patients analysing a database, we found a significant inverse correlation between INSL4 expression and Overall Survival. By combining the in vitro and in vivo results, suggest that in patients whose NSCLC adenocarcinoma spontaneously expressed high levels of INSL4 post-transcriptional modifications affecting INSL4 do not allow to assess precision therapy in selected patients without consider protein INSL4 amount.Cross talk between tumors and the immune microenvironment play a critical role in the malignant progression. The osteoclast-associated receptor (OSCAR) is a regulator of lymphocyte differentiation and maturation, but little is known about the role of OSCAR in multiple cancer types. We comprehensively analyzed OSCAR expression and explored its correlation with prognosis in multiple cancer types using Oncomine, TIMER, Gene GEPIA2 and CCLE. We examined OSCAR expression correlations with lymph node metastasis and pathological stage across tumor samples using UALCAN and GEPIA2. We analyzed the effects of OSCAR on survival using the Kaplan Meier plotter. We explored genes co-expressed with OSCAR using the LinkedOmics database and analyzed associated gene ontologies using Metascape. Further, we examined the correlation between OSCAR expression and immunocyte infiltration, markers of epithelial-mesenchymal transition, and lymphocyte subtypes using TIMER. OSCAR mRNA levels were upregulated in most cancer types compared with adjacent normal tissues. Higher expression of OSCAR correlated with lymph node metastasis or advanced stage subgroups. High expression of OSCAR was related to low tumor purity, with increased levels of M2 macrophage polarization, T cells exhaustion, and mesenchymal phenotype in most cancer types. We also showed that the strength of OSCAR expression influence in malignant progression and inhibitory immune microenvironment is mitigated by the infiltration of natural killer cells. These findings shed light on the pro-carcinogenic role of OSCAR in most cancer types and indicate OSCAR could be targeted in future therapeutics to reverse the inhibitory immune microenvironment.Background Understanding risk factors for vascular invasion (VI) is crucial for assessing the risk of recurrence and overall prognosis of hepatocellular carcinoma (HCC). This study aimed to construct a prognostic long non-coding RNA (lncRNA) signature and a ceRNA Network associated with vascular invasion in HCC. Methods Differentially expressed genes (DEGs) of HCC patients associated with VI were identified by analyzing data from TCGA. Weighted gene co-expression network analysis (WGCNA) was used to identify associations between gene expression modules and clinical features. A VI-related prognostic lncRNA signature was then established using univariate, LASSO and multivariate Cox proportional hazards regression analyses. Based on the hub modules identified by the WGCNA, we constructed a VI-related lncRNA-miRNA-mRNA ceRNA network and screened hub lncRNAs for further research. Finally, we conducted in vitro and in vivo experiments to determine the biological roles of the identified hub gene BBOX1-AS1. Results The key module related to VI and OS was identified using WGCNA, after which a prognostic model consisting of eight lncRNAs was established, and verified using time-dependent receiver operating characteristic (ROC) curve analysis.