Development and validation of a glioma-associated mesenchymal stem cell-related gene prognostic index for predicting prognosis and guiding individualized therapy in glioma.

BACKGROUND: Recent studies have demonstrated that glioma-associated mesenchymal stem cells (GA-MSCs) are implicated in the regulation of glioma malignant progression. However, the prognostic value of GA-MSCs has not been comprehensively explored in glioma. METHODS: We extracted GA-MSCs from glioma tissues, established intracranial xenograft models in nude mice, and obtained GA-MSC-related genes (GA-MSCRGs) by using microarrays. The transcriptome data and clinical information of glioma patients were obtained from the CGGA and TCGA databases. We screened 8 prognostic GA-MSCRGs to construct a prognostic index by using the multivariate Cox regression method. The validity of the GA-MSCRGPI was verified in the training (CGGA693) and validation (TCGA and CGGA325) cohorts. The expression patterns of these 8 GA-MSCRGs were validated in 78 glioma tissue specimens by using a qRT‒PCR assay. RESULTS: GA-MSCs were successfully isolated from glioma tissues. Based on intracranial xenograft models and transcriptome microarray screening, 8 genes (MCM7, CDK6, ORC1, CCL20, TNFRSF12A, POLA1, TRAF1 and TIAM1) were selected for the construction of a GA-MSC-related gene prognostic index (GA-MSCRGPI). In both the training and validation cohorts, high GA-MSCRGPI patients showed an inferior survival outcome compared with low GA-MSCRGPI patients. A nomogram was established based on independent prognostic indicators (age, WHO grade and GA-MSCRGPI) and exhibited a strong forecasting ability for overall survival (OS). Moreover, we found that the GA-MSCRGPI could evaluate the prognosis of glioma patients undergoing chemoradiotherapy. The high GA-MSCRGPI group exhibited higher immune, stromal and ESTIMATE scores; lower tumor purity; higher infiltration of Tregs and M2-type macrophages; fewer activated NK cells; and higher expression of immune checkpoints. Tumor Immune Dysfunction and Exclusion (TIDE) showed that the high GA-MSCRGPI group had more responders to ICI therapy. The results of the genetic mutation profile and tumor mutation burden (TMB) in different GA-MSCRGPI subgroups further supplement GA-MSCRGPI-related mechanisms. Finally, the expression patterns of 8 selected GA-MSCRGs in GA-MSCRGPI were correlated with glioma WHO grades to a certain extent. CONCLUSION: The constructed GA-MSCRGPI could predict prognosis and guide individualized therapy in glioma patients.

A Risk Score Signature Consisting of Six Immune Genes Predicts Overall Survival in Patients with Lower-Grade Gliomas.

BACKGROUND: Lower-grade gliomas (LGGs) are less aggressive with a long overall survival (OS) time span. Because of individualized genomic features, a prognostic system incorporating molecular signatures can more accurately predict OS. METHODS: Differential expression analysis between LGGs and normal tissues was performed using the Gene Expression Omnibus (GEO) datasets (GSE4290 and GSE12657). Immune-related differentially expressed genes (ImmPort-DEGs) were analyzed for functional enrichment. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an immune risk score signature (IRSS). We extracted information from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) to establish and validate the model. The relationship of model gene sets with immune infiltration was analyzed based on gene set variation analysis (GSVA) scores. Patients were divided into low- and high-risk groups based on the median score. The time-dependent receiver-operating characteristic (ROC) curve and the Kaplan-Meier curve were used to evaluate the model. Then, a precise prognostic nomogram was established, and its efficacy was verified. RESULTS: A total of 18 related immune genes were identified, building a 6-gene IRSS (BMP2, F2R, FGF13, PCSK1, PRKCB, and PTGER3). DEGs were enriched in T cell and NK cell regulatory pathways. Immune infiltration analysis confirmed that the gene signature correlated with a decrease in innate immune cells. In terms of model evaluation, ROC curves at 1, 3, and 5 years showed moderate predictive ability of IRSS (AUC = 0.930, 0.797, and 0.728). The Cox regression analysis revealed that IRSS was an independent prognostic factor, and the nomogram model had good predictive ability (C - index = 0.828). Meanwhile, the predictive power of IRSS was also confirmed in the training cohort. The Kaplan-Meier results showed that the prognosis of the high-risk group was significantly worse in all cohorts. CONCLUSION: IRSS may serve as a novel survival prediction tool in the classification of LGG patients.

COL5A1 Serves as a Biomarker of Tumor Progression and Poor Prognosis and May Be a Potential Therapeutic Target in Gliomas.

Glioma is the most common malignancy of the central nervous system. Although advances in surgical resection, adjuvant radiotherapy, and chemotherapy have been achieved in the last decades, the prognosis of gliomas is still dismal. COL5A1 is one of the collagen members with minor content but prominent functions. The present study examined the biological functions, prognostic value, and gene-associated tumor-infiltrating immune cells of COL5A1 through experiments and bioinformatics analysis. We found that the overexpression of COL5A1 was positively correlated with the increasing tumor malignancies and indicated poor prognosis in gliomas. Moreover, downregulation of COL5A1 could inhibit proliferation and migration of glioma cells and enhance their temozolomide sensitivities in vitro. Further bioinformatic analysis revealed that COL5A1 and its co-expressed genes participated in a number of pathways and biological processes involved in glioma progression. Finally, we evaluated the tumor-infiltrating immune cells of gliomas depending on COL5A1 and found that the percentages of the dendritic cells, which were known as the central mediator of tumor microenvironment in gliomas, were positively associated with the expression levels of COL5A1. Taken together, COL5A1 is an important biomarker and potential therapeutic target of gliomas.

Neural Stem Cells Overexpressing Nerve Growth Factor Improve Functional Recovery in Rats Following Spinal Cord Injury via Modulating Microenvironment and Enhancing Endogenous Neurogenesis.

Spinal cord injury (SCI) is a devastating event characterized by severe motor, sensory, and autonomic dysfunction. Currently, there is no effective treatment. Previous studies showed neural growth factor (NGF) administration was a potential treatment for SCI. However, its targeted delivery is still challenging. In this study, neural stem cells (NSCs) were genetically modified to overexpress NGF, and we evaluated its therapeutic value following SCI. Four weeks after transplantation, we observed that NGF-NSCs significantly enhanced the motor function of hindlimbs after SCI and alleviated histopathological damage at the lesion epicenter. Notably, the survival NGF-NSCs at lesion core maintained high levels of NGF. Further immunochemical assays demonstrated the graft of NGF-NSCs modulated the microenvironment around lesion core via reduction of oligodendrocyte loss, attenuation of astrocytosis and demyelination, preservation of neurons, and increasing expression of multiple growth factors. More importantly, NGF-NSCs seemed to crosstalk with and activate resident NSCs, and high levels of NGF activated TrkA, upregulated cAMP-response element binding protein (CREB) and microRNA-132 around the lesion center. Taken together, the transplantation of NGF-NSCs in the subacute stage of traumatic SCI can facilitate functional recovery by modulating the microenvironment and enhancing endogenous neurogenesis in rats. And its neuroprotective effect may be mediated by activating TrkA, up-regulation of CREB, and microRNA-132.