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.

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.

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To decrease vaccine-associated and vaccine-derived poliomyelitis, it is a reasonable option to select sequential schedules during this special transition from OPV to IPV-only immunization schedule, which coincides with the current WHO recommendations.

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.