Ferroptosis-related gene signature correlates with the tumor immune features and predicts the prognosis of glioma patients

Background: Glioma is a malignant intracranial tumor and the most fatal cancer. The role of ferroptosis in the clinical progression of gliomas is unclear.Method: Univariate and least absolute shrinkage and selection operator (Lasso) Cox regression methods were used to develop a ferroptosis-related signature (FRSig) using a cohort of glioma patients from the Chinese Glioma Genome Atlas (CGGA), and was validated using an independent cohort of glioma patients from The Cancer Genome Atlas (TCGA). A single-sample gene set enrichment analysis (ssGSEA) was used to calculate levels of the immune infiltration. Multivariate Cox regression was used to determine the independent prognostic role of clinicopathological factors and to establish a nomogram model for clinical application.Results: We analyzed the correlations between the clinicopathological features and ferroptosis-related gene (FRG) expression and established an FRSig to calculate the risk score for individual glioma patients. Patients were stratified into two subgroups with distinct clinical outcomes. Immune cell infiltration in the glioma microenvironment and immune-related indexes were identified that significantly correlated with the FRSig, the tumor mutation burden (TMB), copy number alteration (CNA), and immune checkpoint expression was also significantly positively correlated with the FRSig score. Ultimately, an FRSig-based nomogram model was constructed using the independent prognostic factors age, World Health Organization (WHO) grade, and FRSig score.Conclusion: We established the FRSig to assess the prognosis of glioma patients. The FRSig also represented the glioma microenvironment status. Our FRSig will contribute to improve patient management and individualized therapy by offering a molecular biomarker signature for precise treatment.     

Mutational profiling of low-grade gliomas identifies prognosis and immunotherapy-related biomarkers and tumour immune microenvironment characteristics

Low-grade glioma (LGG) is a heterogeneous tumour with the median survival rate less than 10 years. Therefore, it is urgent to develop efficient immunotherapy strategies of LGG. In this study, we analysed mutation profiles based on the data of 510 LGG patients from the Cancer Genome Atlas (TCGA) database and investigated the prognostic value of mutated genes and evaluate their immune infiltration. Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to indicate the characteristics of gliomas that respond to immune checkpoint blockade (ICB) therapy. Univariate and multivariate cox regression analysis was performed to identify indicators to construct the nomogram model. 485 (95.47%) of 508 LGG samples showed gene mutation, and 9 mutated genes were significantly related to overall survival (OS), among which 6 mutated genes were significantly correlated with OS between mutation and wildtypes. Immune infiltration and immune score analyses revealed that these six mutated genes were significantly associated with tumour immune microenvironment in LGG. The response of LGG with different characteristics to ICB was evaluated by TIDE algorithm. Finally, CIC gene was screened through both univariate and multivariate Cox regression analyses, and the nomogram model was established to determine the potential prognostic value of CIC in LGG. Our study provides comprehensive analysis of mutated genes in LGG, supporting modulation of mutated genes in the management of LGG.     

High Bone Sialoprotein (BSP) Expression Correlates with Increased Tumor Grade and Predicts a Poorer Prognosis of High-Grade Glioma Patients

Objectives

To investigate the expression and prognostic value of bone sialoprotein (BSP) in glioma patients.

Methods

We determined the expression of BSP using real-time RT-PCR and immunohistochemistry in tissue microarrays containing 15 normal brain and 270 glioma samples. Cumulative survival was calculated by the Kaplan-Meier method and analyzed by the log-rank test. Univariate and multivariate analyses were performed by the stepwise forward Cox regression model.

Results

Both BSP mRNA and protein levels were significantly elevated in high-grade glioma tissues compared with those of normal brain and low-grade glioma tissues, and BSP expression positively correlated with tumor grade (P<0.001). Univariate and multivariate analysis showed high BSP expression was an independent prognostic factor for a shorter progression-free survival (PFS) and overall survival (OS) in both grade III and grade IV glioma patients [hazard ratio (HR) = 2.549 and 3.154 for grade III glioma, and HR = 1.637 and 1.574 for grade IV glioma, respectively]. Patients with low BSP expression had a significantly longer median OS and PFS than those with high BSP expression. Small extent of resection and lineage of astrocyte served as independent risk factors of both shorter PFS and OS in grade III glioma patients; GBM patients without O⁶-methylguanine (O⁶-meG) DNA methyltransferase (MGMT) methylation and Karnofsky performance score (KPS) less than 70 points were related to poor prognosis. Lack of radiotherapy related to shorter OS but not affect PFS in both grade III and grade IV glioma patients.

Conclusion

High BSP expression occurs in a significant subset of high-grade glioma patients and predicts a poorer outcome. The study identifies a potentially useful molecular marker for the categorization and targeted therapy of gliomas.     

Oncogenic reg IV is a novel prognostic marker for glioma patient survival

ABSTRACT: Aim The aberrant expression of regenerating islet-derived family member, 4 (Reg IV) has been found in various human cancers. However, the roles of Reg IV gene and its encoding product in human glioma have not been clearly understood. Therefore, the aim of this study was to investigate the clinicopathological significance of Reg IV expression in glioma. METHODS: Reg IV mRNA and protein expression in human gliomas and non-neoplastic brain tissues were respectively detected by real-time quantitative RT-PCR assay, Western blot, and immunohistochemistry. The association of Reg IV immunostaining with clinicopathological factors and prognosis of glioma patients was also statistically analyzed. RESULTS: Reg IV mRNA and protein expression levels in glioma tissues were both significantly higher than those in the corresponding non-neoplastic brain tissues (both P?相似文献   

EZH2 is a potential prognostic predictor of glioma

The enhancer of zeste homologue 2 (EZH2) is a histone H3 lysine 27 methyltransferase that promotes tumorigenesis in a variety of human malignancies by altering the expression of tumour suppressor genes. To evaluate the prognostic value of EZH2 in glioma, we analysed gene expression data and corresponding clinicopathological information from the Chinese Glioma Genome Atlas, the Cancer Genome Atlas and GTEx. Increased expression of EZH2 was significantly associated with clinicopathologic characteristics and overall survival as evaluated by univariate and multivariate Cox regression. Gene Set Enrichment Analysis revealed an association of EZH2 expression with the cell cycle, DNA replication, mismatch repair, p53 signalling and pyrimidine metabolism. We constructed a nomogram for prognosis prediction with EZH2, clinicopathologic variables and significantly correlated genes. EZH2 was demonstrated to be significantly associated with several immune checkpoints and tumour-infiltrating lymphocytes. Furthermore, the ESTIMATE and Timer Database scores indicated correlation of EZH2 expression with a more immunosuppressive microenvironment for glioblastoma than for low grade glioma. Overall, our study demonstrates that expression of EZH2 is a potential prognostic molecular marker of poor survival in glioma and identifies signalling pathways and immune checkpoints regulated by EHZ2, suggesting a direction for future application of immune therapy in glioma.     

Pyroptosis‐related molecular classification and immune microenvironment infiltration in breast cancer: A novel therapeutic target

The underlying role of pyroptosis in breast cancer (BC) remains unknown. Herein, we investigated the correlations of 33 pyroptosis‐related genes (PRGs) with immune checkpoints and immune cell infiltrations in BC patients based on The Cancer Genome Atlas cohort (n = 996) and Gene Expression Omnibus cohort (n = 3,262). Enrichment analysis revealed that these PRGs mainly functioned in pyroptosis, inflammasomes and regulation of autophagy pathway. Four prognostic independent PRGs (CASP9, TIRAP, GSDMC and IL18) were identified. Then, cluster 1/2 was recognized using consensus clustering for these four PRGs. Patients from cluster 1 had a favourable prognosis and diverse immune cell infiltrations. A nomogram was developed based on age, TNM stage, tumour subtype and pyroptosis score. Patients with the high‐risk group exhibited worse 5‐year OS, and the result was consistent in the external cohort. Additionally, high‐risk group patients were associated with downregulated immune checkpoint expression. Further analysis suggested that the high‐risk group patients were associated with a higher IC50 of paclitaxel, doxorubicin, cisplatin, methotrexate and vinorelbine. In summarizing, the pyroptosis score‐based nomogram might serve as an independent prognostic predictor and could guide medication for chemotherapy. Additionally, it may bring novel insight into the regulation of tumour immune microenvironment in BC and help to achieve precision immunotherapy.     

Characterization and prognostic significance of alternative splicing events in lower‐grade diffuse gliomas

Alternative splicing (AS) is assumed to play important roles in the progression and prognosis of cancer. Currently, the comprehensive analysis and clinical relevance of AS in lower‐grade diffuse gliomas have not been systematically addressed. Here, we gathered alternative splicing data of lower‐grade diffuse gliomas from SpliceSeq. Based on the Percent Spliced In (PSI) values of 515 lower‐grade diffuse glioma patients from the Cancer Genome Atlas (TCGA), we performed subtype‐differential AS analysis and consensus clustering to determine robust clusters of patients. A total of 48 050 AS events in 10 787 genes in lower‐grade diffuse gliomas were profiled. Subtype‐differential splicing analysis and functional annotation revealed that spliced genes were significantly enriched in numerous cancer‐related biological phenotypes and signalling pathways. Consensus clustering using AS events identified three robust clusters of patients with distinguished pathological and prognostic features. Moreover, each cluster was also associated with distinct genomic alterations. Finally, we developed and validated an AS‐related signature with Cox proportional hazards model. The signature, significantly associated with clinical and molecular features, could serve as an independent prognostic factor for lower‐grade diffuse gliomas. Thus, our results indicated that AS events could discriminate molecular subtypes and have prognostic impact in lower‐grade diffuse gliomas.     

Kinesin family member 14 is a candidate prognostic marker for outcome of glioma patients

Background & aim: Human kinesin superfamily proteins (KIFs) are a conserved class of microtubule-dependent molecular motor proteins with adenosine triphosphatase activity and motion characteristics. As a member of KIFs, KIF14 plays an important role in the regulation of cell cycle and mitotic progression. Deregulation of KIF14 has been found in several human malignancies and also has been demonstrated to be involved in tumor progression and related to patient survival. The aim of this study was to investigate the clinicopathological significance of KIF14 expression in glioma. Methods: Real-time quantitative RT-PCR assay was performed to detect KIF14 mRNA expression, and Western blot and immunohistochemistry analyses were performed to detect KIF14 protein expression in human gliomas and non-neoplastic brain tissues, respectively. Then, the association of KIF14 immunostaining with clinicopathological factors and prognosis of glioma patients was also statistically analyzed. Results: KIF14 mRNA and protein expression were respectively increased 5.5- and 4.2-fold on average in glioma tissues relative to non-neoplastic brain tissues (both P < 0.001). Additionally, both KIF14 mRNA and protein expression increased with ascending pathological grade. Then, the high KIF14 immunostaining in glioma tissues was significantly associated with advanced pathological grade (P = 0.008), low Karnofsky performance score (KPS) (P = 0.02), high mitotic index (P = 0.005) and Ki-67 index (P = 0.008). Furthermore, both univariate and multivariate Cox regression analyses determined that KIF14 overexpression effectively predicted decreased overall survival in patients with gliomas. Conclusions: These findings offer the first convinced evidence that KIF14 expression in gliomas is tumor-specific and increased in more aggressive tumors. KIF14 might function as a candidate prognostic marker for human gliomas.     

Predicting the prognosis of glioma by pyroptosis‐related signature

Glioma is the most common malignant primary brain tumour. It is of great significance for the prognosis and personalized treatment of glioma patients to accurate identification of glioma based on biomarkers. Pyroptosis, a kind of programmed cell death, is closely related to tumour progression and tumour immune microenvironment. However, the role of pyroptosis in glioma remained unclear. Herein, we used glioma clinical and expression data from TCGA and CGGA to explore the relationship between pyroptosis and glioma. We first summarized the incidence of copy number variations and somatic mutations of 33 pyroptosis‐related genes and explored prognostic correlation of these genes. Based on pyroptosis‐related genes, three molecular subgroups of glioma related to prognosis were identified. We also found that each subgroup has unique immune and biological behaviours characteristics. Finally, based on 7 pyroptosis‐related genes (CASP3, CASP4, CASP6, CASP8, CASP9, PRKACA and ELANE), we constructed a prognosis model by Lasso and Cox regression, which had a strong predictive power for the overall survival in CGGA test cohort (p < 0.05). In summary, we explored the role of pyroptosis‐related genes in gliomas and the association of these genes with tumour immunity. We found the biomarkers valuable to diagnosis and prognosis, hence, provide reference to the development and treatment of tumorigenesis in glioma.     

T-cell receptors provide potential prognostic signatures for breast cancer

Although T-cell receptors (TCRs) are related to the progression of breast cancer (BC), their prognostic values remain unclear. We downloaded the messenger RNA (mRNA) profiles and corresponding clinical information of 1413 BC patients from the Cancer Genome Atlas and Gene Expression Omnibus database, respectively. The different expression analysis of 104 TCRs in BC samples was performed, and the consensus clustering based on 104 TCRs was performed by using the K-mean method of R language. Univariate cox regression analysis was used to screen TCRs significantly associated with the prognosis of BC, and LASSO Cox analysis was applied to optimize key TCRs. The risk score was calculated using the prognostic model constructed based on six optimal TCRs, and multivariate Cox regression analysis was used to determine whether it was an independent prognostic signature. Finally, the nomogram was constructed to predict the overall survival of BC patients. Six optimal TCRs (ZAP70, GRAP2, NFKBIE, IFNG, NFKBIA, and PAK5), which were favorable for the prognosis of BC patients, were screened. Risk score could reliably predict the prognosis of BC patients as an independent prognostic signature. In addition, when bringing into two independent prognostic signatures, age and risk score, the nomogram model could better predict the overall survival of BC patients. Our results suggested that the poor prognosis of BC patients with high risk might be due to an immunosuppressive microenvironment. In summary, a prognostic risk model based on six TCRs was established and could efficiently predict the prognosis of BC patients.     

A novel tailored immune gene pairs signature for overall survival prediction in lower-grade gliomas

Lower-grade gliomas (LGGs) have a good prognosis with a wide range of overall survival (OS) outcomes. An accurate prognostic system can better predict survival time. An RNA-Sequencing (RNA-seq) prognostic signature showed a better predictive power than clinical predictor models. A signature constructed using gene pairs can transcend changes from biological heterogeneity, technical biases, and different measurement platforms. RNA-seq coupled with corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Immune-related gene pairs (IRGPs) were used to establish a prognostic signature through univariate and multivariate Cox proportional hazards regression. Weighted gene co-expression network analysis (WGCNA) was used to evaluate module eigengenes correlating with immune cell infiltration and to construct gene co-expression networks. Samples in the training and testing cohorts were dichotomized into high- and low-risk groups. Risk score was identified as an independent predictor, and exhibited a closed relationship with prognosis. WGCNA presented a gene set that was positively correlated with age, WHO grade, isocitrate dehydrogenase (IDH) mutation status, 1p/19 codeletion, risk score, and immune cell infiltrations (CD4 T cells, B cells, dendritic cells, and macrophages). A nomogram comprising of age, WHO grade, 1p/19q codeletion, and three gene pairs (BIRC5|SSTR2, BMP2|TNFRSF12A, and NRG3|TGFB2) was established as a tool for predicting OS. The IPGPs signature, which is associated with immune cell infiltration, is a novel tailored tool for individual-level prediction.     

Decreased expression of microRNA-200b is an independent unfavorable prognostic factor for glioma patients

Background and aimAs a member of the microRNA (miR)-200 family, miR-200b has been recognized as one of the fundamental regulators of epithelial–mesenchymal transition, chemosensitivity, cell proliferation, and cell cycle. Especially in glioma, miR-200b targets the CREB1 gene and suppresses the tumor cell growth in vitro. However, its involvement in human glioma has not yet been determined. The aim of this study was to investigate the clinical significance of miR-200b expression in this disease.MethodsmiR-200b expression in 266 pairs of human gliomas and matched nonneoplastic brain tissues was measured by real-time quantitative RT-PCR assay.ResultsCompared with nonneoplastic brain tissues, the expression level of miR-200b was significantly decreased in glioma tissues (tumor vs. normal: 2.87 ± 2.05 vs. 8.78 ± 2.50, P < 0.001). Of 266 patients with gliomas, 166 (62.41%) were in low miR-200b expression group. In addition, we found that the glioma tissues from high-grade tumors (grade III and IV) had much lower miR-200b expression than glioma tissues from low grade tumors (grade I and II). Moreover, the expression level of miR-200b was positively correlated with Karnofsky performance status (KPS) scores of glioma tissues. The results of a 60-month follow-up in 266 glioma patients further demonstrated that lower miR-200b expression was correlated with worse progression-free survival and overall survival in the patients with grade III and IV gliomas. Both univariate and multivariate analyses revealed that miR-200b was an independent prognostic indicator for glioma.ConclusionThese findings prove that the decreased expression of miR-200b may be associated with malignant tumor progression and poor prognosis in patients with gliomas, suggesting the potential role of miR-200b in glioma management. miR-200b may be a novel and valuable signature for predicting the clinical outcome of patients with gliomas.     

An innovative prognostic model based on autophagy-related long noncoding RNA signature for low-grade glioma

Autophagy is a highly conserved lysosomal degradation process essential in tumorigenesis. However, the involvement of autophagy-related long noncoding RNAs (lncRNAs) in low-grade glioma (LGG) remains unclear. In this study, we established an autophagy-related lncRNA prognostic signature for patients with LGG and assess its underlying functions. We used univariate Cox, least absolute shrinkage and selection operator and multivariate Cox regression models to establish an autophagy-related lncRNA prognostic signature. Kaplan–Meier survival analysis, receiver operating characteristic curve, nomogram, C-index, calibration curve and clinical decision-making curve were used to assess the predictive capability of the identified signature. A signature comprising nine autophagy-related lncRNAs (AL136964.1, ARHGEF26-AS1, PCED1B-AS1, AS104072.1, PRKCQ-AS1, LINC00957, AS125616.1, PSMB8-AS1 and AC087741.1) was identified as a prognostic model. Patients with LGG were divided into the high- and low-risk cohorts based on the median model-based risk score. The survival analysis revealed a 10-year survival rate of 9.3% (95% CI 1.91–45.3%) and 13.48% (95% CI 4.52–40.2%) in high-risk patients in the training and validation sets, respectively, and 48.4% (95% CI 24.7–95.0%) and 48.4% (95% CI 28.04–83.4%) in low-risk patients in the training and validation sets, respectively. This finding suggested a relatively low survival in high-risk patients. In addition, the lncRNA signature was independently prognostic and potentially associated with the progression of LGG. Therefore, the 9-autophagy-related-lncRNA signature may play a crucial role in the diagnosis and treatment of LGG, which may offer new avenues for tumour-targeted therapy.

     

Development and Validation of a Nomogram for Predicting Overall Survival in Pancreatic NeuroendocrineTumors

BACKGROUND: The objective of current study was to develop and validate a nomogram to predict overall survival in pancreatic neuroendocrine tumors (PNETs). METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was queried for patients with PNETs between 2004 and 2015. Patients were randomly separated into the training set and the validation set. Cox regression model was used in training set to obtain independent prognostic factors to develop a nomogram for predicting overall survival (OS). The discrimination and calibration plots were used to evaluate the predictive accuracy of the nomogram. RESULTS: A total of 3142 patients with PNETs were collected from the SEER database. Sex, age, marital status, primary site, TNM stage, tumor grade, and therapy were associated with OS in the multivariate models. A nomogram was constructed based on these variables. The nomogram for predicting OS displayed better discrimination power than the Tumor-Node-Metastasis (TNM) stage systems 7th edition in the training set and validation set. The calibration curve indicated that the nomogram was able to accurately predict 3- and 5-year OS. CONCLUSIONS: The nomogram which could predict 3- and 5-year OS were established in this study. Our nomogram showed a good performance, suggesting that it could be served as an effective tool for prognostic evaluation of patients with PNETs.     

Prognostic and predictive value of a mRNA signature in peripheral T-cell lymphomas: A mRNA expression analysis

Current international prognostic index is widely questioned on the risk stratification of peripheral T-cell lymphoma and does not accurately predict the outcome for patients. We postulated that multiple mRNAs could combine into a model to improve risk stratification and helping clinicians make treatment decisions. In this study, the gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to screening genes in selected module which most closely related to PTCLs, and then built a mRNA signature using a LASSO Cox regression model and validated the prognostic accuracy of it. Finally, a nomogram was constructed and the performance was assessed. A total of 799 WGCNA-selected mRNAs in black module were identified, and a mRNA signature which based on DOCK2, GSTM1, H2AFY, KCNAB2, LAPTM5 and SYK for PTCLs was developed. Significantly statistical difference can be seen in overall survival of PTCLs between low-risk group and high-risk group (training set:hazard ratio [HR] 4.3, 95% CI 2.4-7.4, P < .0001; internal testing set:hazard ratio [HR] 2.4, 95% CI 1.2-4.8, P < .01; external testing set:hazard ratio [HR] 2.3, 95% CI 1.10-4.7, P = .02). Furthermore, multivariate regression demonstrated that the signature was an independently prognostic factor. Moreover, the nomogram which combined the mRNA signature and multiple clinical factors suggesting that predicted survival probability agreed well with the actual survival probability. The signature is a reliable prognostic tool for patients with PTCLs, and it has the potential for clinicians to implement personalized therapeutic regimen for patients with PTCLs.     

Increased expression of microRNA-9 predicts an unfavorable prognosis in human glioma

microRNA-9 (miR-9) has been found to be upregulated along with tumor progression of gliomas by microarray-based expression profiling, and also be strongly linked to glioblastoma subtypes. However, its prognostic value in glioma is still elusive. miR-9 expression in human gliomas and nonneoplastic brain tissues was measured by real-time quantitative RT-PCR assay. miR-9 expression in glioma tissues was significantly higher than that in corresponding nonneoplastic brain tissues (P < 0.001). The increased expression of miR-9 was more frequently observed in glioma tissues with high WHO grade than those with low WHO grade tissues (P = 0.001). The expression levels of miR-9 in glioma tissues with low Karnofsky performance score (KPS) were also significantly higher than those with high KPS (P = 0.008). Moreover, the overall survival of glioma patients with high miR-9 expression was obviously lower than that with low miR-9 expression (P < 0.001). Multivariate analysis further showed that high miR-9 expression was an independent prognostic factor for overall survival in glioma patients (P = 0.01). More importantly, the subgroup analyses indicated that the overall survival of glioma patients with high WHO grade (III–IV) was significantly worse for high miR-9 expression group than for low miR-9 expression group (P < 0.001), but no significant difference was found for patients with low WHO grade (I–II). These findings suggest for the first time that the increased expression of miR-9 may play an important role in tumor progression in human gliomas. miR-9 might be a useful marker for predicting the clinical outcome of glioma patients, especially for advanced subtypes.     

A MiRNA Signature for Defining Aggressive Phenotype and Prognosis in Gliomas

Gliomas represent a disparate group of tumours for which there are to date no cure. Thus, there is a recognized need for new diagnostic and therapeutic approaches based on increased understanding of their molecular nature. We performed the comparison of the microRNA (miRNA) profile of 8 WHO grade II gliomas and 24 higher grade tumours (2 WHO grade III and 22 glioblastomas) by using the Affymetrix GeneChip miRNA Array v. 1.0. A relative quantification method (RT-qPCR) with standard curve was used to confirm the 22 miRNA signature resulted by array analysis. The prognostic performances of the confirmed miRNAs were estimated on the Tumor Cancer Genome Atlas (TCGA) datasets. We identified 22 miRNAs distinguishing grade II gliomas from higher grade tumours. RT-qPCR confirmed the differential expression in the two patients'' groups for 13 out of the 22 miRNAs. The analysis of the Glioblastoma Multiforme (GBM) and Lower Grade Glioma (LGG) datasets from TCGA demonstrated the association with prognosis for 6 of those miRNAs. Moreover, in the GBM dataset miR-21 and miR-210 were predictors of worse prognosis in both univariable and multivariable Cox regression analyses (HR 1.19, p = 0.04, and HR 1.18, p = 0.029 respectively). Our results support a direct contribution of miRNAs to glioma cancerogenesis and suggest that miR-21 and miR-210 may play a role in the aggressive clinical behaviour of glioblastomas.