Development of prognostic indicator based on NAD+ metabolism related genes in glioma.

Background: Studies have shown that Nicotinamide adenine dinucleotide (NAD+) metabolism can promote the occurrence and development of glioma. However, the specific effects and mechanisms of NAD+ metabolism in glioma are unclear and there were no systematic researches about NAD+ metabolism related genes to predict the survival of patients with glioma. Methods: The research was performed based on expression data of glioma cases in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Firstly, TCGA-glioma cases were classified into different subtypes based on 49 NAD+ metabolism-related genes (NMRGs) by consensus clustering. NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were gotten by intersecting the 49 NMRGs and differentially expressed genes (DEGs) between normal and glioma samples. Then a risk model was built by Cox analysis and the least shrinkage and selection operator (LASSO) regression analysis. The validity of the model was verified by survival curves and receiver operating characteristic (ROC) curves. In addition, independent prognostic analysis of the risk model was performed by Cox analysis. Then, we also identified different immune cells, HLA family genes and immune checkpoints between high and low risk groups. Finally, the functions of model genes at single-cell level were also explored. Results: Consensus clustering classified glioma patients into two subtypes, and the overall survival (OS) of the two subtypes differed. A total of 11 NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were screened by overlapping 5,995 differentially expressed genes (DEGs) and 49 NAD+ metabolism-related genes (NMRGs). Next, four model genes, PARP9, BST1, NMNAT2, and CD38, were obtained by Cox regression and least absolute shrinkage and selection operator (Lasso) regression analyses and to construct a risk model. The OS of high-risk group was lower. And the area under curves (AUCs) of Receiver operating characteristic (ROC) curves were >0.7 at 1, 3, and 5 years. Cox analysis showed that age, grade G3, grade G4, IDH status, ATRX status, BCR status, and risk Scores were reliable independent prognostic factors. In addition, three different immune cells, Mast cells activated, NK cells activated and B cells naive, 24 different HLA family genes, such as HLA-DPA1 and HLA-H, and 8 different immune checkpoints, such as ICOS, LAG3, and CD274, were found between the high and low risk groups. The model genes were significantly relevant with proliferation, cell differentiation, and apoptosis. Conclusion: The four genes, PARP9, BST1, NMNAT2, and CD38, might be important molecular biomarkers and therapeutic targets for glioma patients.

A Novel Multi-Omics Analysis Model for Diagnosis and Survival Prediction of Lower-Grade Glioma Patients.

Background: Lower-grade gliomas (LGGs) are characterized by remarkable genetic heterogeneity and different clinical outcomes. Classification of LGGs is improved by the development of molecular stratification markers including IDH mutation and 1p/19q chromosomal integrity, which are used as a hallmark of survival and therapy sensitivity of LGG patients. However, the reproducibility and sensitivity of the current classification remain ambiguous. This study aimed to construct more accurate risk-stratification approaches. Methods: According to bioinformatics, the sequencing profiles of methylation and transcription and imaging data derived from LGG patients were analyzed and developed predictable risk score and radiomics score. Moreover, the performance of predictable models was further validated. Results: In this study, we determined a cluster of 6 genes that were correlated with IDH mutation/1p19q co-deletion status. Risk score model was calculated based on 6 genes and showed gratifying sensitivity and specificity for survival prediction and therapy response of LGG patients. Furthermore, a radiomics risk score model was established to noninvasively assist judgment of risk score in pre-surgery. Taken together, a predictable nomogram that combined transcriptional signatures and clinical characteristics was established and validated to be preferable to the histopathological classification. Our novel multi-omics nomograms showed a satisfying performance. To establish a user-friendly application, the nomogram was further developed into a web-based platform: https://drw576223193.shinyapps.io/Nomo/, which could be used as a supporting method in addition to the current histopathological-based classification of gliomas. Conclusions: Our novel multi-omics nomograms showed the satisfying performance of LGG patients and assisted clinicians to draw up individualized clinical management.

A Novel Risk Score Model Based on Eleven Extracellular Matrix-Related Genes for Predicting Overall Survival of Glioma Patients.

Gliomas are the most common lethal primary brain tumors with variable survival outcomes for patients. The extracellular matrix (ECM) is linked with clinical prognosis of glioma patients, but it is not commonly used as a clinical indicator. Herein, we investigated changes in ECM-related genes (ECMRGs) via analyzing the transcriptional data of 938 gliomas from TCGA and CGGA datasets. Based on least absolute shrinkage and selection operator (LASSO) Cox regression analysis, a 11-ECMRG signature that is strongly linked with overall survival (OS) in glioma patients was identified. This signature was characterized by high-risk and low-risk score patterns. We found that the patients in the high-risk group are significantly linked with malignant molecular features and worse outcomes. Univariate and multivariate Cox regression analyses suggested that the signature is an independent indicator for glioma prognosis. The prediction accuracy of the signature was verified through time-dependent receiver operating characteristic (ROC) curves and calibration plots. Further bioinformatics analyses implied that the ECMRG signature is strongly associated with the activation of multiple oncogenic and metabolic pathways and immunosuppressive tumor microenvironment in gliomas. In addition, we confirmed that the high-risk score is an indicator for a therapy-resistant phenotype. In addition to bioinformatics analyses, we functionally verified the oncogenic role of bone morphogenetic protein 1 (BMP1) in gliomas in vitro.

A novel DNA damage and repair-related gene signature to improve predictive capacity of overall survival for patients with gliomas.

Gliomas, as the most lethal and malignant brain tumours in adults, remain a major challenge worldwide. DNA damage and repair-related genes (DDRRGs) appear to play a significant role in gliomas, but the studies of DDRRGs are still insufficient. Herein, we systematically explored and analysed 1547 DDRRGs in 938 glioma samples from TCGA and CGGA datasets. Using least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we identified a 16-DDRRG signature, characterized by high-risk and low-risk patterns. This risk model harbours robust predictive capability for overall survival of glioma patients. We found the high-risk score is strongly associated with well-known malignant features of gliomas, such as the mesenchymal subtype, IDH-wildtype, 1p/19q non-codeletion and MGMT promoter unmethylated status. In addition, we found that the high-risk score is also linked with multiple oncogenic pathways and therapeutic resistance. Significantly, we found the high-risk group has higher enrichment of immunosuppressive cells (M2-type macrophages, Tregs and MDSCs) and immune inhibition biomarkers (PD-1, PD-L1 and CTLA-4). Lastly, we proved that SMC4, which has the highest positive regression coefficient in our risk model, is strongly linked with malignant progression and TMZ resistance of gliomas in a E2F1-dependent manner.

CRB2 enhances malignancy of glioblastoma via activation of the NF-κB pathway.

Glioblastoma (GBM) is one of the most lethal types of primary brain tumors in adults with a median survival of less than 15 months. Although comprehensive clinical treatment strategies including surgical resection followed by radiotherapy and chemotherapy are widely applied, the prognosis for GBM patients remains dismal. The Nuclear Factor-κB (NF-κB) signaling pathway is a complex network linking extracellular stimuli to cell survival and proliferation, and aberrant activation of NF-κB signaling has been implicated in the propagation of a wide range of cancers. However, the underlying mechanism of NF-κB activation still requires further investigation. Here, we report that crumbs homolog 2 (CRB2) is markedly up-regulated in human GBM relative to non-tumor tissues or normal astrocytes. Clinically, enriched CRB2 could be observed in high grade glioma with IDH IDH wild-type and 1p19q co-deletion and implied poor outcome in GBM. Consistent with this, malignant characteristics of GBM cells including proliferation, migration, invasion and tumorigenesis were significantly suppressed by lentivirus knock-down of CRB2. Furthermore, exogenous overexpression of CRB2 enhanced the malignant biological signatures of GBM cells as well as therapy resistance to temozolomide (TMZ). To further investigate the molecular mechanisms responsible, bioinformatics analysis was performed using 3 public databases, with the result that CRB2 was found to correlate closely with tumor necrosis factor α (TNFα)-NF-κB signaling. Mechanistically, elevated CRB2 increased the phosphorylation of IκB-kinase α (IKKα), thus activating NF-κB via reduction of Ikß protein. Taken together, these data suggest that CRB2 might be a reliable prognostic biomarker and potential therapeutic target for GBM.

NEK2 enhances malignancies of glioblastoma via NIK/NF-κB pathway.

Glioblastoma (GBM) is one of the most lethal primary brain tumor with a poor median survival less than 15 months. Despite the development of the clinical strategies over the decades, the outcomes for GBM patients remain dismal due to the strong proliferation and invasion ability and the acquired resistance to radiotherapy and chemotherapy. Therefore, developing new biomarkers and therapeutic strategies targeting GBM is in urgent need. In this study, gene expression datasets and relevant clinical information were extracted from public cancers/glioma datasets, including TCGA, GRAVENDEEL, REMBRANDT, and GILL datasets. Differentially expressed genes were analyzed and NEK2 was picked as a candidate gene for subsequent validation. Human tissue samples and corresponding data were collected from our center and detected by immunohistochemistry analysis. Molecular biological assays and in vivo xenograft transplantation were performed to confirm the bioinformatic findings. High-throughput RNA sequencing, followed by KEGG analysis, GSEA analysis and GO analysis were conducted to identify potential signaling pathways related to NEK2 expression. Subsequent mechanism assays were used to verify the relationship between NEK2 and NF-κB signaling. Overall, we identified that NEK2 is significantly upregulated in GBM and the higher expression of NEK2 exhibited a poorer prognosis. Functionally, NEK2 knockdown attenuated cell proliferation, migration, invasion, and tumorigenesis of GBM while NEK2 overexpression promoted the GBM progression. Furthermore, High-throughput RNA sequencing and bioinformatics analysis indicated that NEK2 was positively related to the NF-κB signaling pathway in GBM. Mechanically, NEK2 activated the noncanonical NF-κB signaling pathway by phosphorylating NIK and increasing the activity and stability of NIK. In conclusion, NEK2 promoted the progression of GBM through activation of noncanonical NF-κB signaling, indicating that NEK2- NF-κB axis could be a potential drug target for GBM.

Retinol binding protein 1-dependent activation of NF- κB signaling enhances the malignancy of non-glioblastomatous diffuse gliomas.

Nonglioblastomatous diffuse glioma (non-GDG) is a heterogeneous neuroepithelial tumor that exhibits a varied survival range from 4 to 13 years based on the diverse subtypes. Recent studies demonstrated novel molecular markers can predict prognosis for non-GDG patients; however, these findings as well as pathological classification strategies show obvious limitations on malignant transition due to the heterogeneity among non-GDGs. Therefore, developing reliable prognostic biomarkers and therapeutic targets have become an urgent need for precisely distinguishing non-GDG subtypes, illuminating the underlying mechanism. Nuclear factor κß (NF-κB) has been proved to be a significant nuclear transcriptional regulator with specific DNA-binding sequences to participate in multiple pathophysiological processes. However, the underlying mechanism of NF-κB activation still needs to be further investigated. Herein, our results indicated retinol-binding protein 1 (RBP1) was significantly upregulated in the IDHWT and 1p19qNon co-del non-GDG subtypes and enriched RBP1 expression was markedly correlated with more severe outcomes. Additionally, malignant signatures of the non-GDG cells including proliferation, migration, invasion, and self-renewal were significantly suppressed by lentiviral knockdown of RBP1. To further explore the underlying molecular mechanism, bioinformatics analysis was performed using databases, and the results demonstrated RBP1 was strongly correlated with tumor necrosis factor α (TNFα)-NF-κB signaling. Moreover, exogenous silencing of RBP1 reduced phosphorylation of IkB-kinase α (IKKα) and thus decreased NF-κB expression via decreasing the degradation of the IκBα protein. Altogether, these data suggested RBP1-dependent activation of NF-κB signaling promoted malignancy of non-GDG, indicating that RBP1 could be a reliable prognostic biomarker and potential therapeutic target for non-GDG.

FABP5 enhances malignancies of lower-grade gliomas via canonical activation of NF-κB signaling.

Low-grade gliomas (LGGs) are grade III gliomas based on the WHO classification with significant genetic heterogeneity and clinical properties. Traditional histological classification of gliomas has been challenged by the improvement of molecular stratification; however, the reproducibility and diagnostic accuracy of LGGs classification still remain poor. Herein, we identified fatty acid binding protein 5 (FABP5) as one of the most enriched genes in malignant LGGs and elevated FABP5 revealed severe outcomes in LGGs. Functionally, lentiviral suppression of FABP5 reduced malignant characters including proliferation, cloning formation, immigration, invasion and TMZ resistance, contrarily, the malignancies of LGGs were enhanced by exogenous overexpression of FABP5. Mechanistically, epithelial-mesenchymal transition (EMT) was correlated to FABP5 expression in LGGs and tumour necrosis factor α (TNFα)-dependent NF-κB signalling was involved in this process. Furthermore, FABP5 induced phosphorylation of inhibitor of nuclear factor kappa-B kinase α (IKKα) thus activated nuclear factor kappa-B (NF-κB) signalling. Taken together, our study indicated that FABP5 enhances malignancies of LGGs through canonical activation of NF-κB signalling, which could be used as individualized prognostic biomarker and potential therapeutic target of LGGs.

Preoperative Prediction Nomogram Based on Integrated Profiling for Glioblastoma Multiforme in Glioma Patients.

Introduction: Traditional classification that divided gliomas into glioblastoma multiformes (GBM) and lower grade gliomas (LGG) based on pathological morphology has been challenged over the past decade by improvements in molecular stratification, however, the reproducibility and diagnostic accuracy of glioma classification still remains poor. This study aimed to establish and validate a novel nomogram for the preoperative diagnosis of GBM by using integrated data combined with feasible baseline characteristics and preoperative tests. Material and method: The models were established in a primary cohort that included 259 glioma patients who had undergone surgical resection and were pathologically diagnosed from March 2014 to May 2016 in the First Affiliated Hospital of Xi'an Jiaotong University. The preoperative data were used to construct three models by the best subset regression, the forward stepwise regression, and the least absolute shrinkage and selection operator, and to furthermore establish the nomogram among those models. The assessment of nomogram was carried out by the discrimination and calibration in internal cohorts and external cohorts. Results and discussion: Out of all three models, model 2 contained eight clinical-related variables, which exhibited the minimum Akaike Information Criterion (173.71) and maximum concordance index (0.894). Compared with the other two models, the integrated discrimination index for model 2 was significantly improved, indicating that the nomogram obtained from model 2 was the most appropriate model. Likewise, the nomogram showed great calibration and significant clinical benefit according to calibration curves and the decision curve analysis. Conclusion: In conclusion, our study showed a novel preoperative model that incorporated clinically relevant variables and imaging features with laboratory data that could be used for preoperative prediction in glioma patients, thus providing more reliable evidence for surgical decision-making.

Loss of PLK2 induces acquired resistance to temozolomide in GBM via activation of notch signaling.

BACKGROUND: Glioblastoma (GBM) is a lethal type of primary brain tumor with a median survival less than 15 months. Despite the recent improvements of comprehensive strategies, the outcomes for GBM patients remain dismal. Accumulating evidence indicates that rapid acquired chemoresistance is the major cause of GBM recurrence thus leads to worse clinical outcomes. Therefore, developing novel biomarkers and therapeutic targets for chemoresistant GBM is crucial for long-term cures. METHODS: Transcriptomic profiles of glioblastoma were downloaded from gene expression omnibus (GEO) and TCGA database. Differentially expressed genes were analyzed and candidate gene PLK2 was selected for subsequent validation. Clinical samples and corresponding data were collected from our center and measured using immunohistochemistry analysis. Lentiviral transduction and in vivo xenograft transplantation were used to validate the bioinformatic findings. GSEA analyses were conducted to identify potential signaling pathways related to PLK2 expression and further confirmed by in vitro mechanistic assays. RESULTS: In this study, we identified PLK2 as an extremely suppressed kinase-encoding gene in GBM samples, particularly in therapy resistant GBM. Additionally, reduced PLK2 expression implied poor prognosis and TMZ resistance in GBM patients. Functionally, up-regulated PLK2 attenuated cell proliferation, migration, invasion, and tumorigenesis of GBM cells. Besides, exogenous overexpression of PLK2 reduced acquired TMZ resistance of GBM cells. Furthermore, bioinformatics analysis indicated that PLK2 was negatively correlated with Notch signaling pathway in GBM. Mechanically, loss of PLK2 activated Notch pathway through negative transcriptional regulation of HES1 and degradation of Notch1. CONCLUSION: Loss of PLK2 enhances aggressive biological behavior of GBM through activation of Notch signaling, indicating that PLK2 could be a prognostic biomarker and potential therapeutic target for chemoresistant GBM.

Elevation of CXCL1 indicates poor prognosis and radioresistance by inducing mesenchymal transition in glioblastoma.

INTRODUCTION: Glioblastoma (GBM) is identified as a lethal malignant tumor derived from the nervous system. Despite the standard clinical strategy including maximum surgical resection, temozolomide (TMZ) chemotherapy, and radiotherapy, the median survival of GBM patients remains <15 months. Accumulating evidence indicates that rapid-acquired radioresistance is one of the most common reasons for GBM recurrence. Therefore, developing novel therapeutic targets for radioresistant GBM could yield long-term cures. AIMS: To investigate the functional role of CXCL1 in the acquired radioresistance and identify the molecular pathway correlated to CXCL1. RESULTS: In this study, we identified that CXCL1 is highly expressed in GBM and the elevation of CXCL1 is involved in radioresistance and poor prognosis in GBM patients. Additionally, silencing CXCL1 attenuated the proliferation and radioresistance of GBM cells. Furthermore, we demonstrated that CXCL1-overexpression induced radioresistance through mesenchymal transition of GBM via the activation of nuclear factor-kappa B (NF-κB) signaling. CONCLUSION: CXCL1 was highly enriched in GBM and positively correlated with poor prognosis in GBM patients. Additionally, elevated CXCL1 induced radioresistance in GBM through regulation of NF-κB signaling by promoting mesenchymal transition in GBM.

Cholangiocarcinoma-derived exosomes inhibit the antitumor activity of cytokine-induced killer cells by down-regulating the secretion of tumor necrosis factor-α and perforin.

OBJECTIVE: The aim of our study is to observe the impact of cholangiocarcinoma-derived exosomes on the antitumor activities of cytokine-induced killer (CIK) cells and then demonstrate the appropriate mechanism. METHODS: Tumor-derived exosomes (TEXs), which are derived from RBE cells (human cholangiocarcinoma line), were collected by ultracentrifugation. CIK cells induced from peripheral blood were stimulated by TEXs. Fluorescence-activated cell sorting (FACS) was performed to determine the phenotypes of TEX-CIK and N-CIK (normal CIK) cells. The concentrations of tumor necrosis factor-α (TNF-α) and perforin in the culture medium supernatant were examined by using an enzyme-linked immunosorbent assay (ELISA) kit. A CCK-8 kit was used to evaluate the cytotoxic activity of the CIK cells to the RBE cell line. RESULTS: The concentrations of TNF-α and perforin of the group TEX-CIK were 138.61 pg/ml and 2.41 ng/ml, respectively, lower than those of the group N-CIK 194.08 pg/ml (P<0.01) and 3.39 ng/ml (P<0.05). The killing rate of the group TEX-CIK was 33.35%, lower than that of the group N-CIK (47.35% (P<0.01)). The population of CD3(+), CD8(+), NK (CD56(+)), and CD3(+)CD56(+) cells decreased in the TEX-CIK group ((63.2±6.8)%, (2.5±1.0)%, (0.53±0.49)%, (0.45±0.42)%) compared with the N-CIK group ((90.3±7.3)%, (65.7±3.3)%, (4.2±1.2)%, (15.2±2.7)%), P<0.01. CONCLUSIONS: Our results suggest that RBE cells-derived exosomes inhibit the antitumor activity of CIK cells by down-regulating the population of CD3(+), CD8(+), NK (CD56(+)), and CD3(+)CD56(+) cells and the secretion of TNF-α and perforin. TEX may play an important role in cholangiocarcinoma immune escape.

Pancreatic cancer-derived exosomes transfer miRNAs to dendritic cells and inhibit RFXAP expression via miR-212-3p.

It has been reported tumor-derived exosomes can transfer miRNAs to recipient cells in the tumor microenvironment, promoting tumor invasion and metastasis. The present research aimed to explore how pancreatic cancer (PC) derived exosomal miRNAs inhibited mRNA expression of dendritic cells and induced immune tolerance. Our study revealed that 9 PC-related miRNAs were increased and 208 mRNAs were inhibited in exosome-stimulated dendritic cells (exo-iDCs) compared to immature dendritic cells (iDCs). A target prediction between the 9 miRNAs and 208 mRNAs was performed by bioinformatics database analysis. From the target prediction, it was predicted and validated that regulatory factor X-associated protein (RFXAP), an important transcription factor for MHC II, was inhibited by miR-212-3p transferred from PC-secreted exosomes, resulting in decreased MHC II expression. Moreover, a clinical study showed a negative correlation between miR-212-3p and RFXAP in PC tissue. From these data, we concluded that PC-related miRNAs can be transferred to dendritic cells via exosome and inhibit target mRNA expression. More importantly, PC-derived exosomes inhibit RFXAP expression via miR-212-3p, which decrease MHC II expression and induce immune tolerance of dendritic cells. RFXAP deficiency has never been reported in solid tumors. The functions and mechanisms of RFXAP in tumors deserve future explorations.