Prognostic significance of age related genes in patients with lower grade glioma

Glial-Cell-Line-Derived Neurotrophic Factor Promotes Glioblastoma Cell Migration and Invasion via the SMAD2/3-SERPINE1-Signaling Axis

Glial-cell-line-derived neurotrophic factor (GDNF) is highly expressed and is involved in the malignant phenotype in glioblastomas (GBMs). However, uncovering its underlying mechanism for promoting GBM progression is still a challenging work. In this study, we found that serine protease inhibitor family E member 1 (SERPINE1) was a potential downstream gene of GDNF. Further experiments confirmed that SERPINE1 was highly expressed in GBM tissues and cells, and its levels of expression and secretion were enhanced by exogenous GDNF. SERPINE1 knockdown inhibited the migration and invasion of GBM cells promoted by GDNF. Mechanistically, GDNF increased SERPINE1 by promoting the phosphorylation of SMAD2/3. In vivo experiments demonstrated that GDNF facilitated GBM growth and the expressions of proteins related to migration and invasion via SERPINE1. Collectively, our findings revealed that GDNF upregulated SERPINE1 via the SMAD2/3-signaling pathway, thereby accelerating GBM cell migration and invasion. The present work presents a new mechanism of GDNF, supporting GBM development.

A nomogram with Ki-67 in the prediction of postoperative recurrence and death for glioma

This study examined to evaluate the predictive value of a nomogram with Ki-67 in overall and disease-free survival in glioma patients, a total of 76 patients diagnosed with glioma by pathology in Tengzhou Central People's Hospital were enrolled. The baseline data and follow ups were retrospectively collected from medical records. The associations between Ki-67 and survival status were examined using log-rank test, univariate and multivariate Cox proportional hazard regression models. Calibrations were performed to validate the established nomograms. Ki-67 negative group showed of a longer OS survival time and a longer PFS survival time with log-rank test (x2 = 16.101, P < 0.001 and x2 = 16.961, P < 0.001). Age older than 50 years (HR = 2.074, 95% CI 1.097-3.923), abnormal treatment (HR = 2.932, 95% CI 1.343-6.403) and Ki-67 positive (HR = 2.722, 95% CI 1.097-6.755) were the independent predictive factors of death. High grade pathology (HR = 2.453, 95% CI 1.010-5.956) and Ki-67 positive (HR = 2.200, 95% CI 1.043-4.639) were the independent predictive factors of recurrence. The C-index for the nomogram of OS and PFS were 0.745 and 0.723, respectively. The calibration results showed that the nomogram could predict the overall and disease-free 1-year survival of glioma patients. In conclusion, the nomograms with Ki-67 as independent risk factor for OS and PFS could provide clinical consultation in the treatment and follow-up of malignant glioma.

Expressions of the satellite repeat HSAT5 and transposable elements are implicated in disease progression and survival in glioma

The glioma genome encompasses a complex array of dysregulatory events, presenting a formidable challenge in managing this devastating disease. Despite the widespread distribution of repeat and transposable elements across the human genome, their involvement in glioma's molecular pathology and patient survival remains largely unexplored. In this study, we aimed to characterize the links between the expressions of repeat/transposable elements with disease progression and survival in glioma patients. Hence, we analyzed the expression levels of satellite repeats and transposons along with genes in low-grade glioma (LGG) and high-grade glioma (HGG). Endogenous transposable elements LTR5 and HERV_a-int exhibited higher expression in HGG patients, along with immune response-related genes. Altogether, 16 transposable elements were associated with slower progression of disease in LGG patients. Conversely, 22 transposons and the HSAT5 satellite repeat were linked to a shorter event-free survival in HGG patients. Intriguingly, our weighted gene coexpression network analysis (WGCNA) disclosed that the HSAT5 satellite repeat resided in the same module network with genes implicated in chromosome segregation and nuclear division; potentially hinting at its contribution to disease pathogenesis. Collectively, we report for the first time that repeat and/or transposon expression could be related to disease progression and survival in glioma. The expressions of these elements seem to exert a protective effect during LGG-to-HGG progression, whereas they could have a detrimental impact once HGG is established. The results presented herein could serve as a foundation for further experimental work aimed at elucidating the molecular regulation of glioma genome.

Prognostic relevance and validation of ARPC1A in the progression of low-grade glioma

Low-grade glioma (LGG) is a grade II-III glioma accompanied by distinct clinical and molecular characteristics and the studies related to its prognosis are still unclear. The objective of this study is to explore the involvement of mitochondrial-related genes SLBP, COMMD7, LSM4, TOMM34, RPP40, FKBP1A, ARPC1A, and TBCA for the prognosis of LGG. We detected differences in the expression of some of the genes by analyzing the bioinformatics dataset and combining it with RT-PCR experiments. Subsequently, a nomogram was constructed and validated for the clinical relevance of risk factors such as age, WHO grade, IDH mutation status, Ch.1p19q co-deletion status, and high and low expression of ARPC1A to predict the 1-, 3-, 5-year overall survival and prognostic relevance of ARPC1A. Gene set enrichment analysis was performed for the relevant datasets pertinent to the expression of ARPC1A to elucidate the cancer-promoting pathways involved in the LGG through KEGG and GO analysis. Transfection assays, CCK-8 assays, and flow cytometry were used to determine the proliferation rate, and apoptosis rate of the HS683 and SW1783 cell lines respectively. Western blotting was used to examine the involvement of the cancer-promoting activity of ARPC1A through MAPK signaling. In this study, the prognostic value of ARPC1A in LGG was found by bioinformatics analysis combined with experimental approach analysis and may be a significant independent risk factor. ARPC1A fosters a higher LGG proliferation rate that may control the MAP kinase signaling and could be a prominent biomarker for LGG. Future studies are warranted to explore its clinical implications.

Risk prediction and treatment assessment in glioma patients using SEER database: a prospective observational study

OBJECTIVES

To use a nomogram to predict the risk of mortality and estimate the impact of current treatment on the prognosis of glioma patients.

METHODS

A total of 3798 cases were obtained from the Surveillance Epidemiology and End Results database according to the selection criteria. A nomogram was built on the independent clinical factors screened by the variance inflation factor, univariate analyses and a multivariate Cox regression model. Then, categorising the overall population into high-risk, medium-risk and low-risk groups using nomogram-derived risk scores, to study the impact of treatment on different subgroups' survival outcomes. Furthermore, based on the postmatch cohorts, the influences of treatment on survival outcomes were assessed by the log-rank test.

RESULT

Age, race, stage of disease, histological type, histological grade, surgery, radiotherapy and chemotherapy were identified as the independent prognostic factors. A nomogram with good discrimination and consistency was built. Generally, the patients who underwent surgery, radiotherapy and chemotherapy were more likely to achieve better prognosis than those who did not, except for those who received radiotherapy in the low-risk cohort and those who underwent surgery in the high-risk cohort. Furthermore, the isocitrate dehydrogenase 1/2 (IDH1/2) wild-type patients with surgery, radiotherapy or chemotherapy tended to have higher survival probabilities, while some inconsistent results were observed in the IDH mutant-type cohort.

CONCLUSION

Surgery, radiotherapy and chemotherapy improved the prognosis, while appropriate selection of topical treatment for the low-risk or high-risk patients deserves further consideration. IDH status gene might be a reliable indicator of therapeutic effectiveness.

EMP3 as a key downstream target of miR-663a regulation interferes with MAPK/ERK signaling pathway to inhibit gallbladder cancer progression

Gallbladder carcinoma (GBC) is the most common malignancy of the biliary tract, and its molecular pathogenesis remains unclear. Here we explore the functional roles of epithelial membrane protein 3 (EMP3) in GBC progression, which is aberrantly expressed in various types of cancers. The results showed that the expression level of EMP3 was reduced in human GBC tissues compared with non-malignant tissues. Further, the low expression of EMP3 was associated with the poor prognosis of GBC patients by Kaplan-Meier analysis. The ectopic expression of EMP3 inhibited GBC cell proliferation, migration and invasion in vitro and in vivo. Conversely, the depletion of EMP3 promoted GBC cell growth and metastasis. In addition, we found that EMP3 was a target gene of miR-663a, and the downregulation of EMP3 in GBC was attributed to the overexpression of miR-663a. MiR-663a was also shown to be a tumor-promoting factor mediating GBC development. In this study, we demonstrate that downregulation of EMP3 activates MAPK/ERK signaling, which regulates GBC progression. These data reveal the mechanism by which EMP3 inhibits the progression of GBC, suggesting that the miR-663a/EMP3/MAPK/ERK axis may be a new therapeutic target for GBC treatment.

Co-amplified with PDGFRA, IGFBP7 is a prognostic biomarker correlated with the immune infiltrations of glioma

BACKGROUND

A subgroup of glioma carry genetic 4q12 amplification including platelet derived growth factor receptor α (PDGFRA) and insulin like growth factor binding protein 7 (IGFBP7). However, the prognosis of PDGFRA and IGFBP7 in glioma is unclear.

METHODS

The prognosis of PDGFRA and IGFBP7 was determined using cox regression and Kaplan-Meier survival analysis. Pathways associated with IGFBP7 were analyzed through gene set enrichment analysis (GSEA). Immune profiling of glioma was determined using "ESTIMATE" and "TIMER" database.

RESULTS

PDGFRA amplification or expression was not correlated with the outcomes of glioblastoma (GBM). IGFBP7 but not PDGFRA was over-expressed in GBM. IGFBP7 over-expression was correlated with the unfavorable outcomes of GBM. In lower grade glioma (LGG), PDGFRA over-expression was not correlated with the unfavorable prognosis of LGG, while, IGFBP7 was a prognostic biomarker of LGG. LGG patients with IGFBP7 lower expressions had prolonged clinical overall survival. Combination of IDH mutation, LGG grade and IGFBP7 achieved even better prognostic effects in LGG. Moreover, IGFBP7 was over-expressed in glioma patients with wild type IDH or with high grades. IGFBP7 over-expression was correlated with the unfavorable outcomes of glioma. Furthermore, IGFBP7 was hypo-methylated in GBM or LGG patients without IDH mutations. IGFBP7 hyper-methylation was correlated with the lower overall survival of GBM or LGG. LGG patients with wild type IDH and with IGFBP7 hypo-methylation demonstrated even worse prognosis. IGFBP7 was associated with multiple immune-related signaling pathways in GBM or LGG. The stromal score, immune score and the infiltrations of immune cells were also correlated with IGFBP7 and the prognosis of LGG.

CONCLUSIONS

IGFBP7 but not PDGFRA served an ideal prognostic marker and therapeutic target of glioma.

Aberrant methylation of Serpine1 mediates lung injury in neonatal mice prenatally exposed to intrauterine inflammation

Background

Intrauterine inflammation (IUI) alters epigenetic modifications in offspring, leading to lung injury. However, the epigenetic mechanism underlying IUI-induced lung injury remains uncertain. In the present study, we aim to investigate the effect of IUI on lung development, and to identify the key molecule involved in this process and its epigenetic regulatory mechanism.

Results

Serpine1 was upregulated in the lung tissue of neonatal mice with IUI. Intranasal delivery of Serpine1 siRNA markedly reversed IUI-induced lung injury. Serpine1 overexpression substantially promoted cell senescence of both human and murine lung epithelial cells, reflected by decreased cell proliferation and increased senescence-associated β-galactosidase activity, G0/G1 cell fraction, senescence marker, and oxidative and DNA damage marker expression. IUI decreased the methylation level of the Serpine1 promoter, and methylation of the promoter led to transcriptional repression of Serpine1. Furthermore, IUI promoted the expression of Tet1 potentially through TNF-α, while Tet1 facilitated the demethylation of Serpine1 promoter. DNA pull-down and ChIP assays revealed that the Serpine1 promoter was regulated by Rela and Hdac2. DNA demethylation increased the recruitment of Rela to the Serpine1 promoter and induced the release of Hdac2.

Conclusion

Increased Serpine1 expression mediated by DNA demethylation causes lung injury in neonatal mice with IUI. Therefore, therapeutic interventions targeting Serpine1 may effectively prevent IUI-induced lung injury.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00901-8.

Identification and Validation of a Gene Signature for Lower-Grade Gliomas Based on Pyroptosis-Related Genes to Predict Survival and Response to Immune Checkpoint Inhibitors

Pyroptosis plays a critical role in the immune response to immune checkpoint inhibitors (ICIs) by mediating the tumor immune microenvironment. However, the impact of pyroptosis-related biomarkers on the prognosis and efficacy of ICIs in patients with lower-grade gliomas (LGGs) is unclear. An unsupervised clustering analysis identified pyroptosis-related subtypes (PRSs) based on the expression profile of 47 pyroptosis-related genes in The Cancer Genome Atlas-LGG cohort. A PRS gene signature was established using univariate Cox regression, random survival forest, least absolute shrinkage and selection operator, and stepwise multivariable Cox regression analyses. The predictive power of this signature was validated in the Chinese Glioma Genome Atlas database. We also investigated the differences between high- and low-risk groups in terms of the tumor immune microenvironment, tumor mutation, and response to target therapy and ICIs. The PRS gene signature comprised eight PRS genes, which independently predicted the prognosis of LGG patients. High-risk patients had a worse overall survival than did the low-risk patients. The high-risk group also displayed a higher proportion of M1 macrophages and CD8⁺ T cells and higher immune scores, tumor mutational burden, immunophenoscore, IMmuno-PREdictive Score, MHC I association immune score, and T cell-inflamed gene expression profile scores, but lower suppressor cells scores, and were more suitable candidates for ICI treatment. Higher risk scores were more frequent in patients who responded to ICIs using data from the ImmuCellAI website. The presently established PRS gene signature can be validated in melanoma patients treated with real ICI treatment. This signature is valuable in predicting prognosis and ICI treatment of LGG patients, pending further prospective verification.

Differences in the Expression Patterns of TGFβ Isoforms and Associated Genes in Astrocytic Brain Tumors

Genes associated with the TGFβ isoforms are involved in a number of different cancers, and their effect on the progression of brain tumors is also being discussed. Using an oligonucleotide microarray method, we assessed differences in expression patterns of genes in astrocytic brain tumor sections from 43 patients at different stages of disease. Quantitative mRNA assessment of the three TGFβ isoforms was also performed by real-time RT-qPCR. Oligonucleotide microarray data were analyzed using the PL-Grid Infrastructure. The microarray analysis showed a statistically significant (p < 0.05) increase in TGFβ1 and TGFβ2 expression in G3/G4 stage relative to G2, whereas real-time RT-qPCR validation confirmed this change only for the TGFβ2 isoform (p < 0.05). The oligonucleotide microarray method allowed the identification of 16 differential genes associated with TGFβ isoforms. Analysis of the STRING database showed that the proteins encoded by the analyzed genes form a strong interaction network (p < 0.001), and a significant number of proteins are involved in carcinogenesis. Differences in expression patterns of transcripts associated with TGFβ isoforms confirm that they play a role in astrocytic brain tumor transformation. Quantitative assessment of TGFβ2 mRNA may be a valuable method to complement the diagnostic process in the future.

Recent Advances in the Role of Arid5a in Immune Diseases and Cancer

AT-rich interactive domain 5a (Arid5a) is a nucleic acid binding protein. In this review, we highlight recent advances in the association of Arid5a with inflammation and human diseases. Arid5a is known as a protein that performs dual functions. In in vitro and in vivo studies, it was found that an inflammation-dependent increase in Arid5a expression mediates both transcriptional and post-transcriptional regulatory effects that are implicated in immune regulation and cellular homeostasis. A series of publications demonstrated that inhibiting Arid5a augmented several processes, such as preventing septic shock, experimental autoimmune encephalomyelitis, acute lung injury, invasion and metastasis, immune evasion, epithelial-to-mesenchymal transition, and the M1-like tumor-associated macrophage (TAM) to M2-like TAM transition. In addition, Arid5a controls adipogenesis and obesity in mice to maintain metabolic homeostasis. Taken together, recent progress indicates that Arid5a exhibits multifaceted, both beneficial and detrimental, roles in health and disease and suggest the relevance of Arid5a as a potential therapeutic target.

Development of a Prognostic Five-Gene Signature for Diffuse Lower-Grade Glioma Patients

Background: Diffuse lower-grade gliomas (LGGs) are infiltrative and heterogeneous neoplasms. Gene signature including multiple protein-coding genes (PCGs) is widely used as a tumor marker. This study aimed to construct a multi-PCG signature to predict survival for LGG patients.

Methods: LGG data including PCG expression profiles and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Survival analysis, receiver operating characteristic (ROC) analysis, and random survival forest algorithm (RSFVH) were used to identify the prognostic PCG signature.

Results: From the training (n = 524) and test (n = 431) datasets, a five-PCG signature which can classify LGG patients into low- or high-risk group with a significantly different overall survival (log rank P < 0.001) was screened out and validated. In terms of prognosis predictive performance, the five-PCG signature is stronger than other clinical variables and IDH mutation status. Moreover, the five-PCG signature could further divide radiotherapy patients into two different risk groups. GO and KEGG analysis found that PCGs in the prognostic five-PCG signature were mainly enriched in cell cycle, apoptosis, DNA replication pathways.

Conclusions: The new five-PCG signature is a reliable prognostic marker for LGG patients and has a good prospect in clinical application.

Low expression of CDHR1 is an independent unfavorable prognostic factor in glioma

Background: Analysis of the differentially expressed genes between lower grade glioma (LGG) and glioblastoma (GBM) will identify genes involved in a more aggressive phenotype of glioma. Methods: Differentially expressed genes between GBM and LGG were identified using published datasets. Kaplan-Meier estimator was used to determine the overall survival of different groups of glioma patients. The biological functions of CDHR1 in glioma were tested using CCK-8 and trans-well assays. Results: CCDC109B, CD58, CLIC1, EFEMP2, EMP3, LAMC1, LGALS1, PDLIM1 and TNFRSF1A were over-expressed, while, CDHR1 was down-regulated in GBM in The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), GSE4412 and GSE43378 datasets. Compared with normal brain tissues, CDHR1 was down-regulated in glioma tissues. And low expression of CDHR1 was an unfavorable prognostic factor in glioma. Moreover, CDHR1 was lowly expressed in mesenchymal GBM subtype and lower expression of CDHR1 was associated with the worse clinical prognosis of GBM. Furthermore, CDHR1 was down-regulated in astrocytoma LGG subtype and low expression of CDHR1 was a bad prognosis of LGG. CDHR1 expression levels were also associated with IDH mutation. IDH mutant LGG or GBM patients were with higher CDHR1 expression. High expression of CDHR1 was a favorable prognosis in IDH mutant or IDH wild type LGG patients. CHDR1 expression was associated with MGMT methylation and CDHR1 was down-regulated in chemotherapy un-responsive LGG patients. CDHR1 was an independent prognostic factor and negatively associated with EMP3 expression. Glioma patients with low CDHR1 and high EMP3 expression had worse clinical outcomes. At last, we showed that over-expression of CDHR1 could inhibit glioma cell growth and invasion. Conclusion: Low expression of CDHR1 was an independent unfavorable prognostic factor in glioma.

Age related gene DST represents an independent prognostic factor for MYCN non-amplified neuroblastoma

Background

MYCN amplification and age are two critical prognostic factors of pediatric neuroblastoma. Previously, we had revealed the prognosis of MYCN target genes. However, the prognostic effects of age related genes in neuroblastoma are unclear.

Methods

The prognostic significance of age and MYCN amplification was determined through multivariate cox regression and Kaplan-Meier survival analysis. Genes differentially expressed in MYCN non-amplified younger neuroblastoma patients were identified using Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) datasets. The prognostic effects of age related genes ALCAM, CACNA2D3, DST, EPB41L4A and KIF1B in pediatric neuroblastoma patients were determined by Kaplan-Meier survival.

Results

In a pediatric pan-cancer analysis, age was associated with the overall survival of pediatric B-lineage acute lymphoblastic leukemia, neuroblastoma and wilms tumor in TARGET dataset. Moreover, the prognostic effects of age in neuroblastoma were validated using two independent neuroblastoma cohorts. Furthermore, age and MYCN amplification were independent prognostic factors in pediatric neuroblastoma. Compared with MYCN non-amplified older neuroblastoma patients, MYCN non-amplified younger neuroblastoma patients had better clinical outcomes. ALCAM, CACNA2D3, DST, EPB41L4A and KIF1B were highly expressed in MYCN non-amplified younger neuroblastoma patients. And the higher expression levels of ALCAM, CACNA2D3, DST, EPB41L4A or KIF1B were associated with better prognosis of MYCN non-amplified neuroblastoma patients. DST was an independent prognostic factor in MYCN non-amplified neuroblastoma patients and MYCN non-amplified neuroblastoma younger patients with higher DST expression levels had the best clinical overall survival.

Conclusions

Age related gene DST was an independent prognostic factor in MYCN non-amplified neuroblastoma. MYCN non-amplified younger neuroblastoma patients with higher DST expression levels had the best clinical overall survival.

Expression and Prognostic Value of ARID5A and its Correlation With Tumor-Infiltrating Immune Cells in Glioma

AT-rich interaction domain 5A (ARID5A) is a member of the ARID family with a function that has been linked to autoimmune as well as inflammatory diseases. Some ARID family members are involved in the initiation and progression of human cancers. However, the function of ARID5A in glioma remains unknown. In this study, ARID5A expression levels were analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) database. Subsequently, the relationship between ARID5A expression and the clinical characteristics of glioma patients was evaluated using the Chinese Glioma Genome Atlas (CGGA) database and The Cancer Genome Atlas (TCGA) database. The prognostic value of ARID5A in glioma was estimated by Kaplan-Meier analysis and the receiver operating characteristic (ROC) curve analysis. Gene ontology (GO) analysis and gene set enrichment analysis (GSEA) were performed for functional prediction. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the relationship between ARID5A and immune cell infiltration in glioma. Our results demonstrate that the expression of ARID5A was upregulated in glioma compared with that in nontumor brain tissues. High expression of ARID5A is associated with poor prognosis in glioma. We found that the expression of ARID5A was significantly upregulated with an increase in tumor malignancy. GO analysis revealed that co-expression genes of ARID5A are significantly involved in some important functions in glioma, and GSEA showed that multiple cancer-associated and immune-associated signaling pathways are enriched in the high ARID5A expression group. TIMER database indicated that ARID5A is correlated with tumor-infiltrating immune cells in glioma. Collectively, these findings indicate that ARID5A may be a potential prognostic biomarker and is correlated with immune infiltration in glioma.

Identification of pivotal genes associated with the prognosis of gastric carcinoma through integrated analysis

PURPOSE

Detecting and diagnosing gastric cancer (GC) during its early period remains greatly difficult. Our analysis was performed to detect core genes correlated with GC and explore their prognostic values.

METHODS

Microarray datasets from the Gene Expression Omnibus (GEO) (GSE54129) and The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) datasets were applied for common differentially co-expressed genes using differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Functional enrichment analysis and protein-protein interaction (PPI) network analysis of differentially co-expressed genes were performed. We identified hub genes via the CytoHubba plugin. Prognostic values of hub genes were explored. Afterward, Gene Set Enrichment Analysis (GSEA) was used to analyze survival-related hub genes. Finally, the tumor-infiltrating immune cell (TIC) abundance profiles were estimated.

RESULTS

Sixty common differentially co-expressed genes were found. Functional enrichment analysis implied that cell-cell junction organization and cell adhesion molecules were primarily enriched. Hub genes were identified using the degree, edge percolated component (EPC), maximal clique centrality (MCC), and maximum neighborhood component (MNC) algorithms, and serpin family E member 1 (SERPINE1) was highly associated with the prognosis of GC patients. Moreover, GSEA demonstrated that extracellular matrix (ECM) receptor interactions and pathways in cancers were correlated with SERPINE1 expression. CIBERSORT analysis of the proportion of TICs suggested that CD8+ T cell and T-cell regulation were negatively associated with SERPINE1 expression, showing that SERPINE1 may inhibit the immune-dominant status of the tumor microenvironment (TME) in GC.

CONCLUSIONS

Our analysis shows that SERPINE1 is closely correlated with the tumorigenesis and progression of GC. Furthermore, SERPINE1 acts as a candidate therapeutic target and prognostic biomarker of GC.

Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma

Energy metabolic processes play important roles for tumor malignancy, indicating that related protein-coding genes and regulatory upstream genes (such as long noncoding RNAs (lncRNAs)) may represent potential biomarkers for prognostic prediction. This study will develop a new energy metabolism-related lncRNA-mRNA prognostic signature for lower-grade glioma (LGG) patients. A GSE4290 dataset obtained from Gene Expression Omnibus was used for screening the differentially expressed genes (DEGs) and lncRNAs (DELs). The Cancer Genome Atlas (TCGA) dataset was used as the prognosis training set, while the Chinese Glioma Genome Atlas (CGGA) was for the validation set. Energy metabolism-related genes were collected from the Molecular Signatures Database (MsigDB), and a coexpression network was established between energy metabolism-related DEGs and DELs to identify energy metabolism-related DELs. Least absolute shrinkage and selection operator (LASSO) analysis was performed to filter the prognostic signature which underwent survival analysis and nomogram construction. A total of 1613 DEGs and 37 DELs were identified between LGG and normal brain tissues. One hundred and ten DEGs were overlapped with energy metabolism-related genes. Twenty-seven DELs could coexpress with 67 metabolism-related DEGs. LASSO regression analysis showed that 9 genes in the coexpression network were the optimal signature and used to construct the risk score. Kaplan-Meier curve analysis showed that patients with a high risk score had significantly worse OS than those with a low risk score (TCGA: HR = 3.192, 95%CI = 2.182‐4.670; CGGA: HR = 1.922, 95%CI = 1.431‐2.583). The predictive accuracy of the risk score was also high according to the AUC of the ROC curve (TCGA: 0.827; CGGA: 0.806). Multivariate Cox regression analyses revealed age, IDH1 mutation, and risk score as independent prognostic factors, and thus, a prognostic nomogram was established based on these three variables. The excellent prognostic performance of the nomogram was confirmed by calibration and discrimination analyses. In conclusion, our findings provided a new biomarker for the stratification of LGG patients with poor prognosis.

Identification of Hub Genes of Mesio Temporal Lobe Epilepsy and Prognostic Biomarkers of Brain Low-grade Gliomas Based on Bioinformatics Analysis

Mesio temporal lobe epilepsy (MTLE) syndrome is the most common form of intractable epilepsies. Meanwhile, seizures are common in patients with cancer as a consequence of brain tumors, including brain low-grade gliomas (LGG). However, the underlying molecular mechanisms of MTLE remain poorly understood. Also, the relationship between MTLE and LGG needs our attention. In this study, we aimed to investigate the hub genes and potential mechanism in MTLE, and the relationship between MTLE and LGG, the gene expression profiles (GSE88992) were downloaded from the Gene Expression Omnibus (GEO) database. Difference analysis for MTLE versus control groups under the three time points was conducted to select the differentially expressed genes (DEGs). Time series clustering analysis was used to select the trend genes. Then a series of bioinformatics analyses including functional enrichment analysis, protein-protein interaction (PPI) network and module analyses, and transcription factor (TF) and miRNA prediction were performed. Also, the overall survival analysis and expression of hub genes in LGG were performed using UALCAN from TCGA database. At 6 h, there were 351 upregulated and 80 downregulated DEGs. At 12 h, there were 499 upregulated and 231 downregulated DEGs. Additionally, 532 upregulated and 402 downregulated DEGs were obtained at 24 h. After time series clustering analysis of the DEGs, we obtained 323 uptrend and 248 downtrend genes. We identified 10 key genes with higher degrees, including C3, TIMP1, PENK, CKAP4, etc. Five PPI modules were identified by MCODE. TF analysis predicted four TFs: JUN, STAT3, NR4A2, and Myc. A total of 26,834 miRNA-mRNA pairs were predicted. Moreover, survival analysis of UALCAN suggested that C3, TIMP1, PENK, GNG2, CKAP4, TNC, JUN, STAT3, NR4A2, and Myc can be potential biomarkers for the prognosis of LGG. In summary, DEGs and hub genes were identified in the present study, which provides novel insight into the development of MTLE.