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Abstract Background Acute biliary pancreatitis (ABP) is a clinical common acute abdomen. After the first pancreatitis, relapse rate is high, which seriously affects human life and health and causes great economic burdens to family and society. According to a great many research findings, endoscopic retrograde cholangiopancreatography (ERCP) is an effective treatment method. However, whether ERCP should be performed in early stage of ABP is still controversial in clinical practice. Methods Related articles were retrieved from Pubmed, Web of Science core library, Nature, Science Direct, and other databases published from January 2000 until now. The keywords included early ERCP, delayed ERCP, ABP, laparoscopy, and cholecystectomy, all which were connected by “or” and “and”. The language of articles was not restricted during the retrieval and Review Manager5.3 was employed to perform meta-analysis of experimental data. Finally, a total of 8 eligible articles were selected, including 8,801 patients. Results The results of the meta-analysis demonstrated that no remarkable differences were detected in the incidence of complications, mortality, and operation time between patients undergoing ERCP in early stage and those receiving delayed ERCP. However, the hospitalization time of patients in experimental group was notably shorter than that among patients in control group. Conclusins Early ERCP treatment is as safe as late ERCP treatment for biliary pancreatitis, and can significantly shorten the hospital stay. Hence, the therapy was worthy of clinical promotion. The research findings provided reference and basis for clinical treatment of relevant diseases.

Induced pluripotent stem cells (iPSCs) can be personalized and differentiated into neural stem cells (NSCs), thereby effectively providing a source of transplanted cells for spinal cord injury (SCI). To further improve the repair efficiency of SCI, we designed a functional neural network tissue based on TrkC-modified iPSC-derived NSCs and a CBD-NT3-modified linear-ordered collagen scaffold (LOCS). We confirmed that transplantation of this tissue regenerated neurons and synapses, improved the microenvironment of the injured area, enhanced remodeling of the extracellular matrix, and promoted functional recovery of the hind limbs in a rat SCI model with complete transection. RNA sequencing and metabolomic analyses also confirmed the repair effect of this tissue from multiple perspectives and revealed its potential mechanism for treating SCI. Together, we constructed a functional neural network tissue using human iPSCs-derived NSCs as seed cells based on the interaction of receptors and ligands for the first time. This tissue can effectively improve the therapeutic effect of SCI, thus confirming the feasibility of human iPSCs-derived NSCs and LOCS for SCI repair and providing a valuable direction for SCI research.

Abstract Triple‐negative breast cancer (TNBC) poses a challenging prognosis due to early metastasis driven by anoikis resistance. Identifying crucial regulators to overcome this resistance is vital for improving patient outcomes. In this study, a genome‐wide CRISPR/Cas9 knockout screen in TNBC cells has identified tyrosine‐protein phosphatase nonreceptor type 14 (PTPN14) as a key regulator of anoikis resistance. PTPN14 expression has shown a progressive decrease from normal breast tissue to metastatic tumors. Overexpressing PTPN14 has induced anoikis and inhibited cell proliferation in TNBC cells, while normal human breast cells are unaffected. Mechanistically, PTPN14 is identified as a key factor in dephosphorylating breast cancer antiestrogen resistance 3, a novel substrate, leading to the subsequent inhibition of PI3K/AKT and ERK signaling pathways. Local delivery of in vitro transcribed PTPN14 mRNA encapsulated by lipid nanoparticles in a TNBC mouse model has effectively inhibited tumor growth and metastasis, prolonging survival. The study underscores PTPN14 as a potential therapeutic target for metastatic TNBC, with the therapeutic strategy based on mRNA expression of PTPN14 demonstrating clinical application prospects in alleviating the burden of both primary tumors and metastatic disease.

IntroductionSmall nucleolar RNAs (snoRNAs) are a group of non-coding RNAs enriched in the nucleus which direct post-transcriptional modifications of rRNAs, snRNAs and other molecules. Recent studies have suggested that snoRNAs have a significant role in tumor oncogenesis and can be served as prognostic markers for predicting the overall survival of tumor patients. MethodsWe screened 122 survival-related snoRNAs from public databases and eventually selected 7 snoRNAs that were most relevant to the prognosis of lower-grade glioma (LGG) patients for the establishment of the 7-snoRNA prognostic signature. Further, we combined clinical characteristics related to the prognosis of glioma patients and the 7-snoRNA prognostic signature to construct a nomogram.ResultsThe prognostic model displayed greater predictive power in both validation set and stratification analysis. Results of enrichment analysis revealed that these snoRNAs mainly participated in the post-transcriptional process such as RNA splicing, metabolism and modifications. In addition, 7-snoRNA prognostic signature were positively correlated with immune scores and expression levels of multiple immune checkpoint molecules, which can be used as potential biomarkers for immunotherapy prediction. From the results of bioinformatics analysis, we inferred that SNORD88C has a major role in the development of glioma, and then performed in vitro experiments to validate it. The results revealed that SNORD88C could promote the proliferation, invasion and migration of glioma cells. DiscussionWe established a 7-snoRNA prognostic signature and nomogram that can be applied to evaluate the survival of LGG patients with good sensitivity and specificity. In addition, SNORD88C could promote the proliferation, migration and invasion of glioma cells and is involved in a variety of biological processes related to DNA and RNA.

Objectives: We aimed to investigate the effect of physical activity (PA) on non-alcoholic fatty liver disease (NAFLD) prevalence and long-term survival, particularly in some specific population such as those with different socioeconomic status (SES).Methods: Multivariate regression and interaction analyses were conducted to deal with confounders and interacting factors.Results: Active PA was associated with lower prevalence of NAFLD in both cohorts. Individuals with active-PA had better long-term survival compared to those with inactive-PA in both cohorts, and the results were only statistically significant in NAFLD defined by US fatty liver index (USFLI). We found clear evidence that the beneficial role of PA was more obvious in individuals with better SES, and the statistical significances were presented in both two hepatic steatosis index (HSI)-NAFLD cohorts from the NHANES III and NHANES 1999–2014. Results were consistent in all sensitivity analyses.Conclusion: We demonstrated the importance of PA in decrease the prevalence and mortality of NAFLD, and highlights the need for improving SES simultaneously to increase the protective effect of PA.

Abstract Stem cells are distinctive cells that have self-renewal potential and unique ability to differentiate into multiple functional cells. Stem cell is a frontier field of life science research and has always been a hot spot in biomedical research. Recent studies have shown that long non-coding RNAs (lncRNAs) have irreplaceable roles in stem cell self-renewal and differentiation. LncRNAs play crucial roles in stem cells through a variety of regulatory mechanisms, including the recruitment of RNA-binding proteins (RBPs) to affect the stability of their mRNAs or the expression of downstream genes. RBPs interact with different RNAs to regulate gene expression at transcriptional and post-transcriptional levels and play important roles in determining the fate of stem cells. In this review, the functions of lncRNAs and their RBPs in self-renewal and differentiation of stem cell are summarized. We focus on the four regulatory mechanisms by which lncRNAs and their RBPs are involved in epigenetic regulation, signaling pathway regulation, splicing, mRNA stability and subcellular localization and further discuss other noncoding RNAs (ncRNAs) and their RBPs in the fate of stem cells. This work provides a more comprehensive understanding of the roles of lncRNAs in determining the fate of stem cells, and a further understanding of their regulatory mechanisms will provide a theoretical basis for the development of clinical regenerative medicine.

Introduction: A copper-dependent cell death, cuproptosis, involves copper binding with lipoylated tricarboxylic acid (TCA) cycle components. In cuproptosis, ferredoxin 1 (FDX1) and lipoylation act as key regulators. The mechanism of cuproptosis differs from the current knowledge of cell death, which may invigorate investigations into copper’s potential as a cancer treatment. An extremely dismal prognosis is associated with gliomas, the most prevalent primary intracranial tumor. In patients with glioma, conventional therapies, such as surgery and chemotherapy, have shown limited improvement. A variety of cell death modes have been confirmed to be operative in glioma oncogenesis and participate in the tumor microenvironment (TME), implicated in glioma development and progression. In this study, we aimed to explore whether cuproptosis influences glioma oncogenesis.Methods: Gene expression profiles related to cuproptosis were comprehensively evaluated by comparing adjacent tissues from glioma tissues in The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database. Gene expression, prognostic, clinical, and pathological data of lower-grade gliomas (LGG) and glioblastoma were retrieved from TCGA and Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. The datasets were managed by “Combat” algorithm to eliminate batch effects and then combined. A consensus clustering algorithm based on the Partitioning Around Medoid (PAM) algorithm was used to classified 725 patients with LGG and glioblastoma multiforme (GBM) into two cuproptosis subtypes. According to the differentially expressed genes in the two cuproptosis subtypes, 725 patients were divided into 2 gene subtypes. Additionally, a scoring system that associated with TME was constructed to predict patient survival and patient immunotherapy outcomes. Furthermore, we constructed a prognostic CRG-score and nomogram system to predict the prognosis of glioma patients. 95 tissue specimens from 83 glioma patients undergoing surgical treatment were collected, including adjacent tissues. Using immunohistochemistry and RT-qPCR, we verified cuproptosis-related genes expression and CRG-score predictive ability in these clinical samples.Results: Our results revealed extensive regulatory mechanisms of cuproptosis-related genes in the cell cycle, TME, clinicopathological characteristics, and prognosis of glioma. We also developed a prognostic model based on cuproptosis. Through the verifications of database and clinical samples, we believe that cuproptosis affects the prognosis of glioma and potentially provides novel glioma research approaches.Conclusion: We suggest that cuproptosis has potential importance in treating gliomas and could be utilized in new glioma research efforts.

BackgroundParkinson’s disease (PD) is a common age-related chronic neurodegenerative disease. There is currently no affordable, effective, and less invasive test for PD diagnosis. Metabolite profiling in blood and blood-based gene transcripts is thought to be an ideal method for diagnosing PD.AimIn this study, the objective is to identify the potential diagnostic biomarkers of PD by analyzing microarray gene expression data of samples from PD patients.MethodsA computational approach, namely, Weighted Gene Co-expression Network Analysis (WGCNA) was used to construct co-expression gene networks and identify the key modules that were highly correlated with PD from the GSE99039 dataset. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to identify the hub genes in the key modules with strong association with PD. The selected hub genes were then used to construct a diagnostic model based on logistic regression analysis, and the Receiver Operating Characteristic (ROC) curves were used to evaluate the efficacy of the model using the GSE99039 dataset. Finally, Reverse Transcription-Polymerase Chain Reaction (RT-PCR) was used to validate the hub genes.ResultsWGCNA identified two key modules associated with inflammation and immune response. Seven hub genes, LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3 were identified from the two modules and used to construct diagnostic models. ROC analysis showed that the diagnostic model had a good diagnostic performance for PD in the training and testing datasets. Results of the RT-PCR experiments showed that there were significant differences in the mRNA expression of LILRB1, LSP1, and MBOAT7 among the seven hub genes.ConclusionThe 7-gene panel (LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3) will serve as a potential diagnostic signature for PD.

BackgroundThe relationship between smoking and depression remains controversial. This study aimed to investigate the association between smoking and depression from three aspects: smoking status, smoking volume, and smoking cessation.MethodsData from adults aged ≥20 who participated in the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 were collected. The study gathered information about the participants' smoking status (never smokers, previous smokers, occasional smokers, daily smokers), smoking quantity per day, and smoking cessation. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9), with a score ≥10 indicating the presence of clinically relevant symptoms. Multivariable logistic regression was conducted to evaluate the association of smoking status, daily smoking volume, and smoking cessation duration with depression.ResultsPrevious smokers [odds ratio (OR) = 1.25, 95% confidence interval (CI): 1.05–1.48] and occasional smokers (OR = 1.84, 95% CI: 1.39–2.45) were associated with a higher risk of depression compared with never smokers. Daily smokers had the highest risk of depression (OR = 2.37, 95% CI: 2.05–2.75). In addition, a tendency toward a positive correlation was observed between daily smoking volume and depression (OR = 1.65, 95% CI: 1.24–2.19) (P for trend < 0.05). Furthermore, the longer the smoking cessation duration, the lower the risk of depression (OR = 0.55, 95% CI: 0.39–0.79) (P for trend < 0.05).ConclusionsSmoking is a behavior that increases the risk of depression. The higher the smoking frequency and smoking volume, the higher the risk of depression, whereas smoking cessation is associated with decreased risk of depression, and the longer the smoking cessation duration, the lower the risk of depression.

Abstract Understanding the spatial distribution characteristics and formation mechanism of urban facilities (city functional components) constitutes the basis of urban layout optimization. Currently, research on the overall distribution of the various types of city functional components is lacking. In this study, by applying the gradient analysis method common in ecology, we considered 13 types of city functional components (80,214 individuals in total) in large, medium and small Chinese cities (9 cities in total) to carry out quantitative analysis of the distribution of components along urban–rural gradients through density distribution curves. The results indicated that: (1) a higher density of city functional components near the city centre revealed an obvious aggregated distribution; (2) the spatial distribution dynamics of city functional components were related to the city size, providing a reference for the rational distribution of components in cities of different sizes; (3) the distribution of city functional components was affected by their ecosystem services. This study offers a new perspective for the application of ecological methods in the examination of the distribution of city functional components.

Abstract Methyltransferase-like 7B (METTL7B) is a member of the methyltransferase-like protein family that plays an important role in the development and progression of tumors. However, its prognostic value and the correlation of METTL7B expression and tumor immunity in some cancers remain unclear. By analyzing online data, we found that METTL7B is abnormally overexpressed in multiple human tumors and plays an important role in the overall survival (OS) of patients with 8 cancer types and disease-free survival (DFS) of patients with 5 cancer types. Remarkably, METTL7B expression was positively correlated with the OS and DFS of patients with lower-grade glioma (LGG). In addition, a positive correlation between METTL7B expression and immune cell infiltration in LGG was observed. Moreover, we identified a strong correlation between METTL7B expression and immune checkpoint gene expression in kidney chromophobe (KICH), LGG and pheochromocytoma and paraganglioma (PCPG). Furthermore, METTL7B was involved in the extracellular matrix (ECM) and immune-related pathways in LGGs. Finally, in vitro experiments showed that knockdown of METTL7B inhibited the growth, migration, invasion and the epithelial–mesenchymal transition (EMT) of LGG cells. METTL7B expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in LGG.

Abstract Background Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression. Methods We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers. Results We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells. Conclusions In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

BackgroundFrontal sinus exposure is a common consequence of frontal craniotomy. Cerebrospinal fluid leakage and infection are the major postoperative complications that may occur as a result of the open frontal sinus. The successful filling of the open frontal sinus provides an approach to prevent significant complications caused by frontal sinus exposure.ObjectiveThis article describes a new technique to reconstruct the exposed frontal sinus cavity with the combined application of gelatin sponge and a vascularized pericranial flap.MethodsA total of 140 patients underwent frontal sinus reconstruction using gelfoam and vascularized pericranial flaps from 2016 to 2021. Gelatin sponge was used to fill the frontal sinus, and a vascularized pericranial flap was used to cover the frontal sinus when the bone flap was retracted.ResultsPostoperative cerebrospinal fluid leakage and infection did not occur in any patient.ConclusionOur results validated the effectiveness of our technique in the prevention of exposed frontal sinus-related postoperative complications.

Spinal cord injury (SCI) usually results in permanent functional impairment and is considered a worldwide medical problem. However, both motor and sensory functions can spontaneously recover to varying extents in humans and animals with incomplete SCI. This study observed a significant spontaneous hindlimb locomotor recovery in Sprague-Dawley rats at four weeks after post-right-side spinal cord hemisection at thoracic 8 (T8). To verify whether the above spontaneous recovery derives from the ipsilateral axonal or neuronal regeneration to reconnect the lesion site, we resected either the scar tissue or right side T7 spinal cord at five weeks post-T8 hemisected injury. The results showed that the spontaneously achieved right hindlimb locomotor function had little change after resection. Furthermore, when T7 left hemisection was performed five weeks after the initial injury, the spontaneously achieved right hindlimb locomotor function was dramatically abolished. A similar result could also be observed when T7 transection was performed after the initial hemisection. The results indicated that it might be the contralateral axonal remolding rather than the ipsilateral axonal or neuronal regeneration beyond the lesion site responsible for the spontaneous hindlimb locomotor recovery. The immunostaining analyses and corticospinal tracts (CSTs) tracing results confirmed this hypothesis. We detected no substantial neuronal and CST regeneration throughout the lesion site; however, significantly more CST fibers were observed to sprout from the contralateral side at the lumbar 4 (L4) spinal cord in the hemisection model rats than in intact ones. In conclusion, this study verified that contralateral CST sprouting, but not ipsilateral CST or neuronal regeneration, is primarily responsible for the spontaneous locomotor recovery in hemisection SCI rats.

Abstract In current research on soft grippers, pneumatically actuated soft grippers are generally fabricated using fully soft materials, which have the advantage of flexibility as well as the disadvantages of a small gripping force and slow response speed. To improve these characteristics, a novel pneumatic soft gripper with a jointed endoskeleton structure (E-Gripper) is developed, in which the muscle actuating function has been separated from the force bearing function. The soft action of an E-Gripper finger is performed by some air chambers surrounded by multilayer rubber embedded in the restraining fiber. The gripping force is borne and transferred by the rigid endoskeleton within the E-Gripper finger. Thus, the gripping force and action response speed can be increased while the flexibility is maintained. Through experiments, the bending angle of each finger segment, response time, and gripping force of the E-Gripper have been measured, which provides a basis for designing and controlling the soft gripper. The test results have shown that the maximum gripping force of the E-Gripper can be 35 N, which is three times greater than that of a fully soft gripper (FS-Gripper) of the same size. At the maximum charging pressure of 150 kPa, the response time is 1.123 s faster than that of the FS-Gripper. The research results indicate that the flexibility of a pneumatic soft gripper is not only maintained in the case of the E-Gripper, but its gripping force is also obviously increased, and the response time is reduced. The E-Gripper thus shows great potential for future development and applications.

IntroductionGlioma is the most common primary cancer of the central nervous system with dismal prognosis. Long noncoding RNAs (lncRNAs) have been discovered to play key roles in tumorigenesis in various cancers, including glioma. Because of the relevance between immune infiltrating and clinical outcome of glioma, identifying immune-related lncRNAs is urgent for better personalized management.Materials and methodsSingle-sample gene set enrichment analysis (ssGSEA) was applied to estimate immune infiltration, and glioma samples were divided into high immune cell infiltration group and low immune cell infiltration group. After screening differentially expressed lncRNAs in two immune groups, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune-related prognostic signature. Additionally, we explored the correlation between immune infiltration and the prognostic signature.ResultsA total of 653 samples were appropriate for further analyses, and 10 lncRNAs were identified as immune-related lncRNAs in glioma. After univariate Cox regression and LASSO Cox regression analysis, six lncRNAs were identified to construct a prognostic signature for glioma, which could be taken as independent prognostic factors in both univariate and multivariate Cox regression analyses. Moreover, risk score was significantly correlated with all the 29 immune-related checkpoint expression (p < 0.05) in ssGSEA except neutrophils (p = 0.43).ConclusionThe study constructed an immune-related prognostic signature for glioma, which contributed to improve clinical outcome prediction and guide immunotherapy.

Glioma is the common histological subtype of malignancy in the central nervous system, with high morbidity and mortality. Glioma cancer stem cells (CSCs) play essential roles in tumor recurrence and treatment resistance. Thus, exploring the stem cell-related genes and subtypes in glioma is important. In this study, we collected the RNA-sequencing (RNA-seq) data and clinical information of glioma patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. With the differentially expressed genes (DEGs) and weighted gene correlation network analysis (WGCNA), we identified 86 mRNA expression-based stemness index (mRNAsi)-related genes in 583 samples from TCGA RNA-seq dataset. Furthermore, these samples from TCGA database could be divided into two significantly different subtypes with different prognoses based on the mRNAsi corresponding gene, which could also be validated in the CGGA database. The clinical characteristics and immune cell infiltrate distribution of the two stemness subtypes are different. Then, functional enrichment analyses were performed to identify the different gene ontology (GO) terms and pathways in the two different subtypes. Moreover, we constructed a stemness subtype-related risk score model and nomogram to predict the prognosis of glioma patients. Finally, we selected one gene (ETV2) from the risk score model for experimental validation. The results showed that ETV2 can contribute to the invasion, migration, and epithelial-mesenchymal transition (EMT) process of glioma. In conclusion, we identified two distinct molecular subtypes and potential therapeutic targets of glioma, which could provide new insights for the development of precision diagnosis and prognostic prediction for glioma patients.

Tumor mutation burden (TMB) is a useful biomarker to predict prognosis and the efficacy of immune checkpoint inhibitors (ICIs). In this study, we aimed to explore the prognostic value of TMB and the potential association between TMB and immune infiltration in lower-grade gliomas (LGGs). Somatic mutation and RNA-sequencing (RNA-seq) data were downloaded from the Cancer Genome Atlas (TCGA) database. TMB was calculated and patients were divided into high- and low-TMB groups. After performing differential analysis between high- and low-risk groups, we identified six hub TMB and immune-related genes that were correlated with overall survival in LGGs. Then, Gene Set Enrichment Analysis was performed to screen significantly enriched GO terms between the two groups. Moreover, an immune-related risk score system was developed by LASSO Cox analysis based on the six hub genes and was validated with the Chinese Glioma Genome Atlas dataset. Using the TIMER database, we further systematically analyzed the relationships between mutants of the six hub genes and immune infiltration levels, as well as the relationships between the immune-related risk score system and the immune microenvironment in LGGs. The results showed that TMB was negatively correlated with OS and high TMB might inhibit immune infiltration in LGGs. Furthermore, the risk score system could effectively stratify patients into low- and high-risk groups in both the training and validation datasets. Multivariate Cox analysis demonstrated that TMB was not an independent prognostic factor, but the risk score was. Higher infiltration of immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells) and higher levels of immune checkpoints (PD-1, CTLA-4, LAG-3, and TIM-3) were found in patients in the high-risk group. Finally, a novel nomogram model was constructed and evaluated to estimate the overall survival of LGG patients. In summary, our study provided new insights into immune infiltration in the tumor microenvironment and immunotherapies for LGGs.

Glioblastoma multiforme (GBM) is the most aggressive primary central nervous system malignant tumor. The median survival of GBM patients is 12–15 months, and the 5 years survival rate is less than 5%. More novel molecular biomarkers are still urgently required to elucidate the mechanisms or improve the prognosis of GBM. This study aimed to explore novel biomarkers for GBM prognosis prediction. The gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets of GBM were downloaded. A total of 2241 overlapping differentially expressed genes (DEGs) were identified from TCGA and GSE7696 datasets. By univariate COX regression survival analysis, 292 survival-related genes were found among these DEGs (p < 0.05). Functional enrichment analysis was performed based on these survival-related genes. A five-gene signature (PTPRN, RGS14, G6PC3, IGFBP2, and TIMP4) was further selected by multivariable Cox regression analysis and a prognostic model of this five-gene signature was constructed. Based on this risk score system, patients in the high-risk group had significantly poorer survival results than those in the low-risk group. Moreover, with the assistance of GEPIA http://gepia.cancer-pku.cn/, all five genes were found to be differentially expressed in GBM tissues compared with normal brain tissues. Furthermore, the co-expression network of the five genes was constructed based on weighted gene co-expression network analysis (WGCNA). Finally, this five-gene signature was further validated in other datasets. In conclusion, our study identified five novel biomarkers that have potential in the prognosis prediction of GBM.