Identification of tumor antigens and immune subtypes in lower grade gliomas for mRNA vaccine development.

BACKGROUND: As an important part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against lower grade glioma (LGG) remains undefined. Immunophenotyping of tumors is an essential tool to evaluate the immune function of patients with immunodeficiency or autoimmunity. Therefore, this study aims to find the potential tumor antigen of LGG and identify the suitable population for cancer vaccination based on the immune landscape. METHOD: The genomic and clinical data of 529 patients with LGG were obtained from TCGA, the mRNA_seq data of normal brain tissue were downloaded from GTEx. Differential expression gene and mutation analysis were performed to screen out potential antigens, K-M curves were carried out to investigate the correlation between the level of potential antigens and OS and DFS of patients. TIMER dataset was used to explore the correlation between genes and immune infiltrating cells. Immunophenotyping of 529 tumor samples was based on the single-sample gene sets enrichment analysis. Cibersort and Estimate algorithm were used to explore the tumor immune microenvironment characteristics in each immune subtype. Weighted gene co-expression network analysis (WGCNA) clustered immune-related genes and screened the hub genes, and pathway enrichment analyses were performed on the hub modules related to immune subtype in the WGCNA. RESULTS: Selecting for the mutated, up-regulated, prognosis- and immune-related genes, four potential tumor antigens were identified in LGG. They were also significantly positively associated with the antigen-presenting immune cells (APCs). Three robust immune subtypes, IS1, IS2 and IS3, represented immune status "desert", "immune inhibition", and "inflamed" respectively, which might serve as a predictive parameter. Subsequently, clinicopathological features, including the codeletion status of 1p19q, IDH mutation status, tumor mutation burden, tumor stemness, etc., were significantly different among subtypes. CONCLUSION: FCGBP, FLNC, TLR7, and CSF2RA were potential antigens for developing cancer vaccination, and the patients in IS3 were considered the most suitable for vaccination in LGG.

Jun, Gal, Cd74, and C1qb as potential indicator for neuropathic pain.

Neuropathic pain is a kind of pain caused by primary or secondary impairment or dysfunction of peripheral or central nervous system. Patients with neuropathic pain were often with poor clinical outcome. We screened the differentially expressed genes between sciatic nerve injury and dorsal root ganglion gene in the sham operation model. Microarray and the spared nerve injury module were used to explore the molecular mechanism of neuropathic pain by injuries and the differentially expressed genes (DEGs) were identified out. Besides, the bioinformatics methods were used to figure out the signaling pathways and expression regulation pattern these DEGs were enriched in, which may provide a basis for the molecular research and medicine target of therapy. Besides, protein-protein interaction network analysis was performed on these selected intersection genes. A total of 40 DEGs were screened out and only pctp gene was down-regulated, the left 39 genes were all up-regulated. Then, GO and KEGG enrichment analysis were performed on these intersection genes by DAVID software. Furthermore, protein-protein interaction network analysis was used to analyze the critical genes of neuropathic pain. Finally, four genes, that is, Jun, Gal, Cd74, and C1qb were identified to have strong interactions with other genes, which may function as the prognostic and predictive genes of neuropathic pain caused by peripheral injuries. Our results suggested that four differentially expressed genes, Jun, Gal, Cd74, and C1qb, had the potential to serve as prognostic or predictive markers for neuropathic pain, suggesting a potential application in the improvement of prognostic tools and treatments.

[Independent external verification of the nomograms for predicting lymph node metastasis in penile cancer].

Objective: To evaluate the two newly established nomograms for predicting lymph node metastasis in penile cancer based on the clinical data on a large cohort of patients. METHODS: We retrospectively studied the clinical data on 93 patients with penile cancer treated in the Center for Tumor Prevention and Treatment. Using the two recently established nomograms (Bhagat nomogram and Zhu nomogram), we predicted lymph node metastasis in the patients, analyzed the differences between prediction and the results of postoperative pathology, and compared the accuracy of prediction between the two nomograms with the receiver operating characteristic (ROC) curve and the area under the curve (AUC). RESULTS: The median age of the patients was 55 (27－82) years. Positive lymph nodes were found in 31 cases (33.3%) postoperatively and in 9 (21.9%) of the 41 clinically negative cases. The AUC of the Bhagat nomogram was 0.739 and that of Zhu nomogram was 0.808, both of which were similar to the prediction accuracy of internal verification and manifested a medium predictive ability. CONCLUSIONS: The newly established Bhagat and Zhu nomograms can be used for predicting lymph node metastasis in penile cancer, but with a low precision, and therefore cannot be relied exclusively for the option of inguinal lymphadenectomy.

Fatostatin induces ferroptosis through inhibition of the AKT/mTORC1/GPX4 signaling pathway in glioblastoma.

Glioblastoma multiforme (GBM) is the most common and fatal primary malignant central nervous system tumor in adults. Although there are multiple treatments, the median survival of GBM patients is unsatisfactory, which has prompted us to continuously investigate new therapeutic strategies, including new drugs and drug delivery approaches. Ferroptosis, a kind of regulated cell death (RCD), has been shown to be dysregulated in various tumors, including GBM. Fatostatin, a specific inhibitor of sterol regulatory element binding proteins (SREBPs), is involved in lipid and cholesterol synthesis and has antitumor effects in a variety of tumors. However, the effect of fatostatin has not been explored in the field of ferroptosis or GBM. In our study, through transcriptome sequencing, in vivo experiments, and in vitro experiments, we found that fatostatin induces ferroptosis by inhibiting the AKT/mTORC1/GPX4 signaling pathway in glioblastoma. In addition, fatostatin inhibits cell proliferation and the EMT process through the AKT/mTORC1 signaling pathway. We also designed a p28-functionalized PLGA nanoparticle loaded with fatostatin, which could better cross the blood-brain barrier (BBB) and be targeted to GBM. Our research identified the unprecedented effects of fatostatin in GBM and presented a novel drug-targeted delivery vehicle capable of penetrating the BBB in GBM.

Immunogenic cell death-related risk signature predicts prognosis and characterizes the tumour microenvironment in lower-grade glioma.

Lower-grade glioma (LGG) is a common malignant primary tumour in the central nervous system, and most patients eventually develop highly aggressive gliomas despite comprehensive traditional treatment. Tumour molecular subtypes and prognostic biomarkers play a crucial role in LGG diagnosis and treatment. Therefore, the identification of novel biomarkers in LGG patients is crucial for predicting the prognosis of glioma. Immunogenic cell death (ICD) is defined as regulated cell death that is sufficient to activate the adaptive immune response of immunocompetent hosts. The combination of ICD and immunotherapy might exert a greater and more persistent antitumour effect in gliomas. In our study, we explored the expression, function, and genetic alterations of 34 ICD-related genes. Using 12 ICD-related genes, including IL17RA, IL1R1, EIF2AK3, CD4, PRF1, CXCR3, CD8A, BAX, PDIA3, CASP8, MYD88, and CASP1, we constructed and validated an ICD-related risk signature via least absolute shrinkage and selection operator (LASSO) Cox regression analysis. All the information was obtained from public databases, including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and the Chinese Glioma Genome Atlas (CGGA) databases. Our results revealed that ICD-high risk groups have a poor prognosis and might be more sensitive to immune checkpoint blockade (ICB) immunotherapy. In addition, ICD-high risk groups were associated with 1p19q noncodeletion, higher WHO grade, wild type IDH, and an immunosuppressive tumour microenvironment. We verified the prognostic value of 12 ICD-related genes in TCGA and CGGA databases. Immunohistochemistry was performed to verify the expression of several ICD-related genes at the protein level. Our study provides a novel and comprehensive perspective to elucidate the underlying mechanisms of LGG prognosis and direction for future individualized cancer immunotherapy.

Exploring the inverse association of glioblastoma multiforme and Alzheimer's disease via bioinformatics analysis.

Glioblastoma multiforme (GBM) and Alzheimer's disease (AD) are two major diseases in the nervous system with a similar peak age of onset, which has the typical characteristics of high cost, difficult treatment, and poor prognosis. Epidemiological studies and a few molecular biological studies have hinted at an opposite relationship between AD and GBM. However, there are few studies on their reverse relationship, and the regulatory mechanism is still unclear, indicating that further systematic research is urgently needed. Our study firstly employs advanced bioinformatics methods to explore the inverse relationship between them and find various target drugs. We obtained the gene expression dataset from public databases (GEO, TCGA, and GTEx). Then, we identified 122 differentially expressed genes (DEGs) of AD and GBM. Four significant gene modules were identified through protein-protein interaction (PPI) and module construction, and 13 hub genes were found using cytoHubba. We constructed co-expression networks and found various target drugs through these hub genes. Functional enrichment analysis revealed that the AMPK pathway, cell cycle, and cellular senescence play important roles in AD and GBM. Our study may provide a potential direction for studying the opposite molecular mechanism of AD and GBM in the future.

FAIM2 is a potential pan-cancer biomarker for prognosis and immune infiltration.

Fas apoptosis inhibitory molecule 2 (FAIM2) is an important member of the transmembrane BAX inhibitor motif containing (TMBIM) family. However, the role of FAIM2 in tumor prognosis and immune infiltration has rarely been studied. Here, we conducted a pan-cancer analysis to explore the role of FAIM2 in various tumors and further verified the results in glioma through molecular biology experiment. FAIM2 expression and clinical stages in tumor samples and para-cancerous samples were analyzed by TIMER2 database, GEPIA database, and the TISIDB database. The role of FAIM2 on prognosis was analyzed via GEPIA2. We utilized the ESTIMATE algorithm to evaluate the ImmuneScore and StromalScore of various tumors. In addition, we explored the correlation between FAIM2 expression and tumor immune cell infiltration by the TIMER2 database. The immune checkpoint genes, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methylation related to FAIM2 were analyzed based on the TCGA database. The correlation between FAIM2 expression with Copy number variations (CNV) and methylation is explored by GSCA database. Protein-Protein Interaction (PPI) analysis was obtained from the STRING database and the CellMiner database was used to explore the association between FAIM2 expression and drug response. FAIM2 co-expression genes were studied by the LinkedOmics database. Immunohistochemistry, Western Blotting Analysis, Cell Viability Assay, Colony Formation Assay, and Edu staining assay were used in the molecular biology experiments section. The FAIM2 expression was down-regulated in most tumors and highly expressed FAIM2 was associated with a better prognosis in several cancers. FAIM2 plays an essential role in the tumor microenvironment and is closely associated with immune Infiltration in various tumors. The expression of FAIM2 was closely correlated to TMB, MSI, MMR, CNV, and DNA methylation. Furthermore, FAIM2 related genes in the PPI network and its co-expression genes in glioma are involved in a large number of immune-related pathways. Molecular biology experiments verified a cancer suppressor role for FAIM2 in glioma. FAIM2 may serve as a potential pan-cancer biomarker for prognosis and immune infiltration, especially in glioma. Moreover, this study might provide a potential target for tumor immunotherapy.

Identification of immunogenic cell death-related gene classification patterns and immune infiltration characterization in ischemic stroke based on machine learning.

Ischemic stroke (IS) accounts for more than 80% of strokes and is one of the leading causes of death and disability in the world. Due to the narrow time window for treatment and the frequent occurrence of severe bleeding, patients benefit less from early intravenous thrombolytic drug therapy. Therefore, there is an urgent need to explore the molecular mechanisms poststroke to drive the development of new therapeutic approaches. Immunogenic cell death (ICD) is a type of regulatory cell death (RCD) that is sufficient to activate the adaptive immune response of immunocompetent hosts. Although there is growing evidence that ICD regulation of immune responses and immune responses plays an important role in the development of IS, the role of ICD in the pathogenesis of IS has rarely been explored. In this study, we systematically evaluated ICD-related genes in IS. The expression profiles of ICD-related genes in IS and normal control samples were systematically explored. We conducted consensus clustering, immune infiltration analysis, and functional enrichment analysis of IS samples using ICD differentially expressed genes. The results showed that IS patients could be classified into two clusters and that the immune infiltration profile was altered in different clusters. In addition, we performed machine learning to screen nine signature genes that can be used to predict the occurrence of disease. We also constructed nomogram models based on the nine risk genes (CASP1, CASP8, ENTPD1, FOXP3, HSP90AA1, IFNA1, IL1R1, MYD88, and NT5E) and explored the immune infiltration correlation, gene-miRNA, and gene-TF regulatory network of the nine risk genes. Our study may provide a valuable reference for further elucidation of the pathogenesis of IS and provide directions for drug screening, personalized therapy, and immunotherapy for IS.

TMCO1 expression promotes cell proliferation and induces epithelial-mesenchymal transformation in human gliomas.

Transmembrane and coiled-coil domains 1 (TMCO1) is a recently discovered transmembrane protein of endoplasmic reticulum (ER), which plays a critical role in maintaining calcium homeostasis. TMCO1 dysfunction has been proved to be closely related to a variety of human diseases, including glaucoma, deformities, mental retardation and tumorigenesis. However, the role of TMCO1 in gliomas remains unclear. The purpose of this study was to detect the role of TMCO1 in the pathogenesis and progression of gliomas. This study demonstrated that TMCO1 was upregulated in gliomas and its overexpression predicted poor prognosis. We also revealed that the expression of TMCO1 was associated with the World Health Organization (WHO) grade of gliomas. Knockdown of TMCO1 inhibited the proliferation and induced apoptosis of U87 and U251 cells. In addition, TMCO1 induced GBM cell migration and invasion by promoting epithelial-mesenchymal transition (EMT). These date collectively proved the crucial role of TMCO1 as a novel prognostic factor and underlying therapeutic target for glioma patients.

TMBIM1 promotes proliferation and attenuates apoptosis in glioblastoma cells by targeting the p38 MAPK signalling pathway.

Glioblastoma multiforme (GBM) is the most common and most fatal primary malignant brain tumour in adults. The average survival time of patients after diagnosis is only 12-15 months. And its characteristics of excessive proliferation and apoptosis evasion play a crucial role in the poor prognosis of patients. Therefore, it is worth investigating the molecular mechanism of GBM to find an effective therapeutic target to overcome the dilemma. In the current study, Transmembrane BAX inhibitor motif containing 1 (TMBIM1) was highly expressed in GBM tissues and high TMBIM1 expression in GBM cell lines (U87 and U251) could promote cell proliferation and inhibit cell cycle arrest. In addition, TMBIM1 could significantly attenuate GBM cell apoptosis and decrease the sensitivity of GBM cells to temozolomide (TMZ). In terms of the molecular mechanism, we revealed that TMBIM1 interferes with the p38/MAPK pathway by inhibiting p38 phosphorylation to promote cell proliferation and attenuate cell apoptosis. In vivo experiments showed that the survival time of mice in TMBIM1 knockdown group was significantly prolonged. Our discovery provided an important basis for future intensive molecular mechanism research in GBM and presented a potential target for the treatment of GBM.

Kiaa0101 serves as a prognostic marker and promotes invasion by regulating p38/snail1 pathway in glioma.

BACKGROUND: Kiaa0101, a regulator of cell proliferation, is overexpressed in many malignant tumors. However, its role in promoting invasion of glioma is poorly understood. Here, we investigated the effects of Kiaa0101 on glioma invasion and elucidated the underlying mechanisms of action. METHODS: We analyzed Kiaa0101 expression using datasets from four public databases, namely TCGA, CGGA, Gravendeel and Rembrandt as well as experimentally on 123 glioma samples via western blot (WB), RT-PCR and immunohistochemistry (IHC). We further quantified migration and invasion using wound healing and transwell assays. WB, IHC and immunofluorescence (IF) were used to detect expression of invasion related markers. Moreover, we detected tumor invasion of glioma cells in vivo in 5-week-old Balb/c nude mice. RESULTS: Kiaa0101 was upregulated in glioma, relative to non-tumor brain tissues, with the expression increasing with increase in glioma grade. Kiaa0101 mRNA expression was especially enriched in isocitrate dehydrogenase (IDH)1 wild-type glioma. Kaplan-Meier analysis, based on the aforementioned datasets, revealed that high Kiaa0101 levels were significantly associated with worse overall survival. Besides, shRNA-mediated Kiaa0101 knockdown inhibited migration and invasion of glioma cells by reducing snail1 expression both in vitro and in vivo, whereas its upregulation enhanced malignant behaviors of these cells. Furthermore, Kiaa0101 regulated snail1 expression by activating the p38MAPK signaling pathway. CONCLUSIONS: Our findings strongly indicate that Kiaa0101 is a prognostic biomarker for malignant tumors, and its inhibition may be an effective strategy for treating glioma.

Development and Verification of Glutamatergic Synapse-Associated Prognosis Signature for Lower-Grade Gliomas.

Background: Lower-grade glioma (LGG) is the most common histology identified in gliomas, a heterogeneous tumor that may develop into high-grade malignant glioma that seriously shortens patient survival time. Recent studies reported that glutamatergic synapses might play an essential role in the progress of gliomas. However, the role of glutamatergic synapse-related biomarkers in LGG has not been systemically researched yet. Methods: The mRNA expression data of glioma and normal brain tissue were obtained from The Cancer Genome Atlas database and Genotype-Tissue Expression, respectively, and the Chinese Glioma Genome Atlas database was used as a validation set. Difference analysis was performed to evaluate the expression pattern of glutamatergic synapse-related genes (GSRGs) in LGG. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to construct the glutamatergic synapse-related risk signature (GSRS), and the risk score of each LGG sample was calculated based on the coefficients and expression value of selected GSRGs. Univariate and multivariate Cox regression analyses were used to investigate the prognostic value of risk score. Immunity profile and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the association between risk score and the characters of tumor microenvironment in LGG. Gene set variation analysis (GSVA) was performed to investigate the potential pathways related to GSRS. The HPA database and real-time PCR were used to identify the expression of hub genes identified in GSRS. Results: A total of 22 genes of 39 GSRGs were found differentially expressed among normal and LGG samples. Through the LASSO algorithm, 14-genes GSRS constructed were associated with the prognosis and clinicopathological features of patients with LGG. Furthermore, the risk score level was significantly positively correlated with the infiltrating level of immunosuppressive cells, including M2 macrophages and regulatory T cells. GSVA identified a series of cancer-related pathways related to GSRS, such as P13K-AKT and P53 pathways. Moreover, ATAD1, NLGN2, OXTR, and TNR, hub genes identified in GSRS, were considered as potential prognostic biomarkers in LGG. Conclusion: A 14-genes GSRS was constructed and verified in this study. We provided a novel insight into the role of GSRS in LGG through a series of bioinformatics methods.

Identification of Tumor Antigens and Immune Landscape in Glioblastoma for mRNA Vaccine Development.

Background: Clinical benefits from standard therapies against glioblastoma (GBM) are limited in part due to the intrinsic radio- and chemo-resistance. As an essential part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against GBM remains undefined. Therefore, this study aims to find the possible tumor antigens of GBM and identify the suitable population for cancer vaccination through immunophenotyping. Method: The genomic and responding clinical data of 169 GBM samples and five normal brain samples were obtained from The Cancer Genome Atlas (TCGA). The mRNA_seq data of 940 normal brain tissue were downloaded from Genotype-Tissue Expression (GTEx). Potential GBM mRNA antigens were screened out by differential expression, copy number variant (CNV), and mutation analysis. K-M survival and Cox analysis were carried out to investigate the prognostic association of potential tumor antigens. Tumor Immune Estimation Resource (TIMER) was used to explore the association between the antigens and tumor immune infiltrating cells (TIICs). Immunophenotyping of 169 samples was performed through consensus clustering based on the abundance of 22 kinds of immune cells. The characteristics of the tumor immune microenvironment (TIME) in each cluster were explored through single-sample gene set enrichment analysis based on 29 kinds of immune-related hallmarks and pathways. Weighted gene co-expression network analysis (WGCNA) was performed to cluster the genes related to immune subtypes. Finally, pathway enrichment analyses were performed to annotate the potential function of modules screened through WGCNA. Results: Two potential tumor antigens selected were significantly positively associated with the antigen-presenting immune cells (APCs) in GBM. Furthermore, the expression of antigens was verified at the protein level by Immunohistochemistry. Two robust immune subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2), representing immune status "immune inhibition" and "immune inflamed", respectively, had distinct clinical outcomes in GBM. Conclusion: ARPC1B and HK3 were potential mRNA antigens for developing GBM mRNA vaccination, and the patients in IS2 were considered the most suitable population for vaccination in GBM.

[Predictive value of human fatty acid binding protein for myocardial ischemia and injury in perioperative period of cardiac surgery].

OBJECTIVE: To evaluate the value of human fatty acid binding protein (h-FABP) in predicting myocardial ischemia and injury in the perioperative period of cardiac surgery, we observed the dynamic changes of h-FABP in perioperative period of patients underwent coronary artery bypass grafting and ventricular septal defects repairing surgery, and evaluated the relationship of h-FABP and ischemia modified albumin (IMA), CK-MB, cTnI. METHODS: Patients underwent coronary artery bypass grafting (n=30) and ventricular septal defect repairing (n=30) surgery between February 2008 and December 2008 were included in this study. Venous blood sample was obtained at preoperative, aortic clamping, aortic unclamping of 10 min, 2 h, 6 h, 12 h, 24 h for the measurements of h-FABP, IMA, cTnI and CK-MB. RESULTS: h-FABP and IMA changed in the same way at various examined time points, h-FABP changes also paralleled cTnI and CK-MB changes, h-FABP peaked early during myocardial ischemia and injury and returned to baseline level at 2 h post myocardial ischemia and injury. Linear correlation analysis showed that the peak value of h-FABP was positively correlated with IMA, CK-MB and cTnI in both CABG group (r = 0.948, 0.964 and 0.961, P < 0.05) and in the VSD group (r = 0.986, 0.978 and 0.957). CONCLUSIONS: h-FABP is an early diagnostic parameter reflecting perioperative myocardial ischemia and injury in cardiac surgery. Quantitative h-FABP monitoring could predict the severity of myocardial ischemia and injury early during cardiac surgery.

Identification of Core Genes and Screening of Potential Targets in Glioblastoma Multiforme by Integrated Bioinformatic Analysis.

Glioblastoma multiforme is the most common primary intracranial malignancy, but its etiology and pathogenesis are still unclear. With the deepening of human genome research, the research of glioma subtype screening based on core molecules has become more in-depth. In the present study, we screened out differentially expressed genes (DEGs) through reanalyzing the glioblastoma multiforme (GBM) datasets GSE90598 from the Gene Expression Omnibus (GEO), the GBM dataset TCGA-GBM and the low-grade glioma (LGG) dataset TCGA-LGG from the Cancer Genome Atlas (TCGA). A total of 150 intersecting DEGs were found, of which 48 were upregulated and 102 were downregulated. These DEGs from GSE90598 dataset were enriched using the overrepresentation method, and multiple enriched gene ontology (GO) function terms were significantly correlated with neural cell signal transduction. DEGs between GBM and LGG were analyzed by gene set enrichment analysis (GSEA), and the significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in synapse signaling and oxytocin signaling pathways. Then, a protein-protein interaction (PPI) network was constructed to assess the interaction of proteins encoded by the DEGs. MCODE identified 2 modules from the PPI network. The 11 genes with the highest degrees in module 1 were designated as core molecules, namely, GABRD, KCNC1, KCNA1, SYT1, CACNG3, OPALIN, CD163, HPCAL4, ANK3, KIF5A, and MS4A6A, which were mainly enriched in ionic signaling-related pathways. Survival analysis of the GSE83300 dataset verified the significant relationship between expression levels of the 11 core genes and survival. Finally, the core molecules of GBM and the DrugBank database were assessed by a hypergeometric test to identify 10 drugs included tetrachlorodecaoxide related to cancer and neuropsychiatric diseases. Further studies are required to explore these core genes for their potentiality in diagnosis, prognosis, and targeted therapy and explain the relationship among ionic signaling-related pathways, neuropsychiatric diseases and neurological tumors.

Integrated Analysis to Evaluate the Prognostic Value of Signature mRNAs in Glioblastoma Multiforme.

BACKGROUND: Gliomas are the most common intracranial tumors and are classified as I-IV. Among them, glioblastoma multiforme (GBM) is the most common invasive glioma with a poor prognosis. New molecular biomarkers that can predict clinical outcomes in GBM patients must be identified, which will help comprehend their pathogenesis and supply personalized treatment. Our research revealed four powerful survival indicators in GBM by reanalyzing microarray data and genetic sequencing data in public databases. Moreover, it unraveled new potential therapeutic targets which could help improve the survival time and quality of life of GBM patients. MATERIALS AND METHODS: To identify prognostic signatures in GBMs, we analyzed the gene profiling data of GBM and standard brain samples from the Gene Expression Omnibus, including four datasets and RNA sequencing data from The Cancer Genome Atlas (TCGA) containing 152 glioblastoma tissues. We performed the differential analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, weighted gene co-expression network analysis (WGCNA) and Cox regression analysis. RESULTS: After differential analysis in GSE12657, GSE15824, GSE42656 and GSE50161, overlapping differentially expressed genes were identified. We identified 110 up-regulated DEGs and 75 down-regulated DEGs in the GBM samples. Significantly enriched subclasses of the GO classification of these genes included mitotic sister chromatid separation, mitotic nuclear division and so on. In KEGG pathway analysis, the most abundant terms were ECM-receptor interaction and protein digestion and absorption. WGCNA analysis was performed on these 185 DEGs in 152 glioblastoma samples obtained from TCGA, and gene co-expression networks were constructed. We then performed a multivariate Cox analysis and established a Cox proportional hazards regression model using the top 20 genes significantly correlated with survival time. We identified a four-protein prognostic signature that could divide patients into high-risk and low-risk groups. Increased expression of SLC12A5, CCL2, IGFBP2, and PDPN was associated with increased risk scores. Finally, the K-M curves confirmed that these genes could be used as independent predictors of survival in patients with glioblastoma. CONCLUSION: Our analytical study identified a set of potential biomarkers that could predict survival and may contribute to successful treatment of GBM patients.

Hypoxia induced ferritin light chain (FTL) promoted epithelia mesenchymal transition and chemoresistance of glioma.

BACKGROUND: Hypoxia, a fundamental characteristic of glioma, is considered to promote tumor malignancy by inducing process of epithelial mesenchymal transition (EMT). Ferritin Light Chain (FTL) is one of the iron metabolism regulators and is overexpressed in glioma. However, relationship between hypoxia and FTL expression and its role in regulating EMT remains unclear. METHODS: Immunohistochemistry (IHC), western blot and public datasets were used to evaluate FTL level in glioma. Wound healing, transwell assays, CCK8, annexin V staining assay were used to measure migration, invasion, proliferation and apoptosis of glioma cells in vitro. Interaction between HIF1A and FTL was assessed by luciferase reporter and Chromatin immunoprecipitation (ChIP) assays. Subcutaneous xenograft model was established to investigate in vivo growth. RESULTS: FTL expression was enriched in high grade glioma (HGG) and its expression significantly associated with IDH1/2 wildtype and unfavorable prognosis of glioma patients. FTL expression positively correlated with HIF1A in glioma tissues and obviously increased in U87 and U251 cells under hypoxia in a time-dependent manner. Mechanistically, HIF-1α regulates FTL expression by directly binding to HRE-3 in FTL promoter region. Furthermore, we found that knockdown FTL dramatically repressed EMT and reduced migration and invasion of glioma by regulating AKT/GSK3ß/ ß-catenin signaling both in vitro and in vivo. Moreover, our study found downregulation FTL decreased the survival rate and increased the apoptosis of glioma cells treated with temozolomide (TMZ). FTL expression segregated glioma patients who were treated with TMZ or with high MGMT promoter methylation into survival groups in TCGA dataset. Patients with methylated MGMT who had high FTL expression presented similar prognosis with patients with unmethylated MGMT. CONCLUSION: Our study strongly suggested that hypoxia-inducible FTL was a regulator of EMT and acted not only as a prognostic marker but also a novel biomarker of response to TMZ in glioma.

Expression of Bmi-1 is a prognostic marker in bladder cancer.

BACKGROUND: The molecular mechanisms of the development and progression of bladder cancer are poorly understood. The objective of this study was to analyze the expression of Bmi-1 protein and its clinical significance in human bladder cancer. METHODS: We examined the expression of Bmi-1 mRNA and Bmi-1 protein by RT-PCR and Western blot, respectively in 14 paired bladder cancers and the adjacent normal tissues. The expression of Bmi-1 protein in 137 specimens of bladder cancer and 30 specimens of adjacent normal bladder tissue was determined by immunohistochemistry. Statistical analyses were applied to test the relationship between expression of Bmi-1, and clinicopathologic features and prognosis. RESULTS: Expression of Bmi-1 mRNA and protein was higher in bladder cancers than in the adjacent normal tissues in 14 paired samples (P < 0.01). By immunohistochemical examination, five of 30 adjacent normal bladder specimens (16.7%) versus 75 of 137 bladder cancers (54.3%) showed Bmi-1 protein expression (P < 0.05). Bmi-1 protein expression was intense in 20.6%, 54.3%, and 78.8% of tumors of histopathological stages G1, G2, and G3, respectively (P < 0.05). Expression of Bmi-1 protein was greater in invasive bladder cancers than in superficial bladder cancers (81.5% versus 32.5%, P < 0.05). In invasive bladder cancers, the expression of Bmi-1 protein in progression-free cancers was similar to that of cancers that have progressed (80.0% versus 82.4%, P > 0.5). In superficial bladder cancers, the expression of Bmi-1 protein in recurrent cases was higher than in recurrence-free cases (62.5% versus 13.7%, P < 0.05). Bmi-1 expression was positively correlated with tumor classification and TNM stage (P < 0.05), but not with tumor number (P > 0.05). Five-year survival in the group with higher Bmi-1 expression was 50.8%, while it was 78.5% in the group with lower Bmi-1 expression (P < 0.05). Patients with higher Bmi-1 expression had shorter survival time, whereas patients with lower Bmi-1 expression had longer survival time (P < 0.05). CONCLUSION: Expression of Bmi-1 was greater in bladder cancers than in the adjacent normal tissues. The examination of Bmi-1 protein expression is potentially valuable in prognostic evaluation of bladder cancer.

Human sperm-associated antigen 4 as a potential biomarker of glioblastoma progression and prognosis.

Glioblastoma (GBM) is a highly lethal brain tumor, refractory to current therapies. Sperm-associated antigen 4 (SPAG4) is a novel cancer marker with unclear roles in GBM progression. This study aimed to explore the specific effects of SPAG4 on the pathogenesis of GBM. We first investigated the expression level and prognostic power of SPAG4 in patients with GBM using The Cancer Genome Atlas cohort, and then SPAG4 knockdown by RNA interference was performed to reveal the effects of SPAG4 on GBM cells. mRNA and protein expression levels were determined by real-time PCR and western blot. MTT assay was used to examine cell proliferation, and a wound healing assay was performed to detect cell migration. SPAG4 was significantly overexpressed in patients with GBM, and high expression of SPAG4 was associated with a poor prognosis. Silencing of SPAG4 significantly suppressed the proliferation and migration of GBM cells. Meanwhile, decreased expression and phosphorylation of MEK and ERK were identified after SPAG4 knockdown, suggesting that SPAG4 might regulate GBM progression by activating MEK/ERK signaling pathway. Our study revealed that SPAG4 was identified as a cancer biomarker for GBM and might be a promising target for clinical diagnosis and intervention of GBM.

Challenges in the use of zinc and its alloys as biodegradable metals: Perspective from biomechanical compatibility.

To date, more than fifty articles have been published on the feasibility studies of zinc and its alloys as biodegradable metals. These preliminary in vitro and in vivo studies showed acceptable biodegradability and reasonable biocompatibility in bone and blood microenvironments for the experimental Zn-based biodegradable metals and, for some alloy systems, superior mechanical performance over Mg-based biodegradable metals. For instance, the Zn-Li alloys exhibited higher UTS (UTS), and the Zn-Mn alloys exhibited higher elongation (more than 100%). On the one hand, similar to Mg-based biodegradable metals, insufficient strength and ductility, as well as relatively low fatigue strength, may lead to premature failure of medical devices. On the other hand, owing to the low melting point of the element Zn, several new uncertainties with regard to the mechanical properties of biomedical zinc alloys, including low creep resistance, high susceptibility to natural aging, and static recrystallization (SRX), may lead to device failure during storage at room temperature and usage at body temperature. This paper comprehensively reviews studies on these mechanical aspects of industrial Zn and Zn alloys in the last century and biomedical Zn and Zn alloys in this century. The challenges for the future design of biomedical zinc alloys as biodegradable metals to guarantee 100% mechanical compatibility are pointed out, and this will guide the mechanical property design of Zn-based biodegradable metals. STATEMENT OF SIGNIFICANCE: Previous studies on mechanical properties of industrial Zn and Zn alloys in the last century and biomedical Zn and Zn alloys in this century are comprehensively reviewed herein. The challenges for the future design of zinc-based biodegradable materials considering mechanical compatibility are pointed out. Common considerations such as strength, ductility, and fatigue behaviors are covered together with special attention on several new uncertainties including low creep resistance, high susceptibility to natural aging, and static recrystallization (SRX). These new uncertainties, which are not significantly observed in Mg-based and Fe-based materials, are largely due to the low melting point of the element Zn and may lead to device failure during storage at room temperature and clinical usage at body temperature. Future studies are urgently needed on these topics.