HMGB2 is a biomarker associated with poor prognosis promoting radioresistance in glioma by targeting base excision repair pathway.

BACKGROUND: High mobility group box 2 (HMGB2) is considered as a biomarker of poor prognosis in various cancers.This study aims to investigate the effect and mechanism of HMGB2 in gliomas. METHODS: With the glioma related on-line and our local hospital databases, the expression differences of HMGB2,Kaplan-Meier survival analysis and COX regression analysis were performed.The correlation analysis between the clinicopathological features and imaging parameters with the HMGB2 expression had been done. Then GSEA and PPI networks were carried out to find out the most significant pathway. The pathway inhibitor was applied to verify HMGB2's participation. CCK8,EDU assays,γ-H2AX immunofluorescence staining and colony formation assay were conducted to observe effects on glioma cells. RESULTS: Available datasets showed that HMGB2 was highly expressed in glioma and patients with high expression of HMGB2 had poorer prognosis and molecular characteristics. Protein level evidence of western blot and immunohistochemistry from our center supported the conclusions above. Analysis on imaging features suggested that HMGB2 expression level had an inverse association with ADCmean but positively with the thickness of enhancing margin. Results from GSEA and PPI network analysis exhibited that HMGB2 was involved in base excision repair (BER) signaling pathway. Experimental evidence demonstrated that the overexpression of HMGB2 promoted the proliferation of glioma cells and enhanced the radio-resistance. CONCLUSIONS: HMGB2 could promote glioma development and enhance the radioresistance of glioma cells, potentially related to the BER pathway, suggesting it may serve as an underlying biomarker for patients with glioma.

IDH1R132H mutation increases radiotherapy efficacy and a 4-gene radiotherapy-related signature of WHO grade 4 gliomas.

The prognosis for the WHO grade 4 IDH-mutant astrocytoma is better than IDH-wildtype glioblastoma (GBM) patients. The purpose of this study is to explore the potential mechanism of how IDH1 mutation can increase the efficacy of radiotherapy and to establish a risk-score model to predict the efficacy of radiotherapy in WHO grade 4 gliomas. First, we conducted experimental study on the effect of IDH1R132H mutation on glioma cells in vitro. Radiosensitivity of glioma cells was detected by γ-H2AX after 5 Gy radiation. Cell proliferation, migration and invasion were determined respectively by CCK-8, EDU, monolayer cell migration scratch assay and Transwell assay. Then we analyzed IDH1 gene status and the survival of WHO grade 4 glioma patients received radiotherapy in our center and verified our results by analyzing CGGA and TCGA database. For the risk-score model, we use CGGA data to find genetic differences between WHO grade 4 IDH-mutant astrocytoma and IDH-wildtype GBM patients, and determined a 4-gene radiotherapy-related signature through survival analysis by R software. Evaluation and verification through different glioma validation sets and different statistical methods. For in vitro experiments, we established glioma cells stably overexpressing IDH1 wild-type and IDH1-mutant proteins. γ-H2AX assay showed that IDH1-mutant glioma cells had higher radiosensitivity than wild-type. CCK-8 and EDU assay showed that proliferation capacity of IDH1-mutant glioma cells declined. Transwell assay and monolayer cell migration scratch assay also showed that IDH1-mutant glioma cells reduced migration and invasion capabilities. Among the 83 WHO grade 4 glioma patients who received radiotherapy in our center, WHO grade 4 IDH-mutant astrocytoma patients had longer OS and PFS versus IDH-wildtype GBM (P = 0.0336, P = 0.0324, respectively). TCGA and CGGA database analysis had the similar results. Through complex analysis of CGGA and TCGA databases, we established a risk-model that can predict the efficacy of radiotherapy for WHO grade 4 glioma patients. The 4-gene radiotherapy-related signature including ADD3, GRHPR, RHBDL1 and SLC9A9. Patients in the high-risk group had worse OS compared to low-risk group (P = 0.0001). High- and low-risk groups of patients receiving radiotherapy have significant survival differences, while patients who did not receive radiotherapy have no survival difference both in CGGA and TCGA databases. WHO grade 4 IDH-mutant astrocytoma is more radiosensitive than IDH-wildtype GBM patients. Our 4-gene radiotherapy-related signature can predict the radiation efficacy of WHO grade 4 glioma patients, and it may provide some reference for clinical treatment options.

The study of an anoikis-related signature to predict glioma prognosis and immune infiltration.

BACKGROUND: Gliomas are the most common highly aggressive primary malignant brain tumors in adults with different biological behaviors and clinically heterogeneous features. About the extremely poor prognosis of gliomas, the search for potential therapeutic modalities and targets is crucial. METHOD: We extracted the anoikis-related genes (ARG) from GeneCards and obtained differentially expressed genes in normal and glioma tissues from the GSE4290 dataset to obtain intersect differentially expressed ARG in gliomas by differential analysis. KEGG and GO analyses were used to evaluate the potential pathways and molecular processes of these genes. Based on The Cancer Genome Atlas (TCGA) training cohort, we performed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression to construct an ARG prognostic model and validated them in the TCGA testing cohort and the Chinese Glioma Genome Atlas (CGGA) validation cohort. Subsequently, we further explored the differences in clinical characteristics, tumor mutation burden (TMB), and the immune microenvironment in the high- and low-risk groups. Univariate and multifactorial regression analyses and nomogram construction were also performed. Moreover, we evaluated the expression levels of key genes via public databases, qPCR analysis and IHC staining, and further assessed the clinical prognostic value. RESULTS: The regulatory model based on quantitative ARG prognostic models showed that patients in the high-risk group were associated with poorer survival prognosis, poorer clinical characteristics, and higher TMB levels. Moreover, the high-risk group had high levels of immune infiltration and upregulated immune checkpoint gene expression. The ARG prognostic model and the Nomogram showed good predictive performance. Expression and survival analysis of five prognostic ARG signatures (ETV4, HMOX1, MYC, NFE2L2, and UBE2C) showed that these genes have potential prognostic value. CONCLUSION: Our constructed ARG prognostic risk model provides a potential therapeutic target and theoretical basis for predicting the prognosis of glioma patients and guiding individualized immunotherapy.

Identification of a novel immune landscape signature as effective diagnostic markers related to immune cell infiltration in diabetic nephropathy.

Background: The study aimed to identify core biomarkers related to diagnosis and immune microenvironment regulation and explore the immune molecular mechanism of diabetic nephropathy (DN) through bioinformatics analysis. Methods: GSE30529, GSE99325, and GSE104954 were merged with removing batch effects, and different expression genes (DEGs) were screened at a criterion |log2FC| >0.5 and adjusted P <0.05. KEGG, GO, and GSEA analyses were performed. Hub genes were screened by conducting PPI networks and calculating node genes using five algorithms with CytoHubba, followed by LASSO and ROC analysis to accurately identify diagnostic biomarkers. In addition, two different GEO datasets, GSE175759 and GSE47184, and an experiment cohort with 30 controls and 40 DN patients detected by IHC, were used to validate the biomarkers. Moreover, ssGSEA was performed to analyze the immune microenvironment in DN. Wilcoxon test and LASSO regression were used to determine the core immune signatures. The correlation between biomarkers and crucial immune signatures was calculated by Spearman analysis. Finally, cMap was used to explore potential drugs treating renal tubule injury in DN patients. Results: A total of 509 DEGs, including 338 upregulated and 171 downregulated genes, were screened out. "chemokine signaling pathway" and "cell adhesion molecules" were enriched in both GSEA and KEGG analysis. CCR2, CX3CR1, and SELP, especially for the combination model of the three genes, were identified as core biomarkers with high diagnostic capabilities with striking AUC, sensitivity, and specificity in both merged and validated datasets and IHC validation. Immune infiltration analysis showed a notable infiltration advantage for APC co-stimulation, CD8+ T cells, checkpoint, cytolytic activity, macrophages, MHC class I, and parainflammation in the DN group. In addition, the correlation analysis showed that CCR2, CX3CR1, and SELP were strongly and positively correlated with checkpoint, cytolytic activity, macrophages, MHC class I, and parainflammation in the DN group. Finally, dilazep was screened out as an underlying compound for DN analyzed by CMap. Conclusions: CCR2, CX3CR1, and SELP are underlying diagnostic biomarkers for DN, especially in their combination. APC co-stimulation, CD8+ T cells, checkpoint, cytolytic activity, macrophages, MHC class I, and parainflammation may participate in the occurrence and development of DN. At last, dilazep may be a promising drug for treating DN.

A Model for Predicting Clinical Prognosis in Patients with WHO Grade 2 Glioma.

Objectives: Although patients with grade 2 glioma have a relatively better prognosis and longer survival than those with high-grade glioma, there are still a number of patients with disappointing outcomes. In order to accurately predict the prognosis of patients, relevant risk factors were included in the analysis to establish a clinical prediction model so as to provide a basis for clinically individualized treatment. Methods: A retrospective study was conducted in patients diagnosed with grade 2 glioma. Data including clinical features, pathological type, molecular classification, neuroimaging examination, treatment, and survival were collected. The data sets were randomly assigned, with 80% of the data used for model building and 20% for validation. Cox proportional hazard regression analysis was used to construct the model using important risk factors and present it in the form of a nomogram. The nomogram was evaluated a using C-index and calibration chart. Results: A total of 160 patients were enrolled in this analysis, including 128 in the training group and 32 in the validation group. In the training group, eight important risk factors including preoperative KPS, the first presenting symptom, the extent of resection, the gross tumor size, 1p19q, IDH, radiotherapy, and chemotherapy were identified to construct the model. The C-index of the training group and the validation group was 0.832 and 0.801, respectively, indicating that the model had good prediction ability. The calibration charts of the two groups were drawn respectively, which showed that the calibration line and the standard line had a good consistency, which suggested that the model-predicted risk had a good consistency with the actual risk. Conclusions: Based on the data of our center, a nomogram prediction model with eight variables has been established as an off-the-rack tool and verified its accuracy, which can guide clinical work and provide consultation for patients.

MELK is a prognostic biomarker and correlated with immune infiltration in glioma.

Objective: Glioma accounts for the vast majority of primary brain tumors with inevitable recurrence and poor prognosis. Maternal embryonic leucine zipper kinase (MELK) is overexpressed in multiple human tumors and could activate a variety of oncogenic-associated signal pathways. However, its role in the glioma microenvironment is still largely unknown. Methods: We collected the RNA sequence data and clinical information of gliomas from the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases, and investigated MELK expression and its correlation with clinicopathologic features and prognosis in glioma. Moreover, the relationship between MELK expression and immune cell infiltration in the tumor microenvironment of gliomas was explored through single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. In addition, gene set enrichment analysis (GSEA) and Metascape online analysis were performed to find out signaling pathways enriched by differentially expressed genes (DEGs) between high- and low-MELK expression groups. Finally, immunohistochemistry was performed to validate our findings. Results: Data analysis of CGGA and GEO datasets showed that MELK was significantly upregulated in gliomas than in normal brain tissues, and MELK expression was obviously correlated with clinicopathologic features, including age, WHO grade, histological subtype, IDH mutant status, 1p19q codeletion status, and PRS type. Stratified analysis, Cox regression analysis, and nomogram model revealed that high expression of MELK predicted poor survival; hence, MELK could serve as an independent prognostic biomarker for glioma. Moreover, results from enrichment pathway analysis indicated that the immune system process, angiogenesis, apoptosis, cell cycle, and other oncogenic-related signal pathways were significantly enriched between high- and low-MELK expression groups. Immune infiltration analysis demonstrated that increased MELK expression was significantly correlated with higher immune scores, higher fractions of immunocytes (T cells, NK cells resting, macrophages, resting mast cells, and neutrophils), and higher expression levels of immune checkpoints (B7-H3, CTLA4, LAG3, PD-1, PD-L1, and TIM3). Finally, immunohistochemistry analysis validated our findings that high expression of MELK relates to increased malignancy and poor prognosis of glioma. Conclusion: Our findings identified that MELK could act as an independent prognostic indicator and potential immunotherapy target for glioma. In conclusion, these findings suggested that DDOST mediated the immunosuppressive microenvironment of gliomas and could be an important biomarker in diagnosing and treating gliomas.

Blocking REDD1/TXNIP Complex Ameliorates HG-Induced Renal Tubular Epithelial Cell Apoptosis and EMT through Repressing Oxidative Stress.

Diabetic nephropathy (DN) has become the most common secondary kidney disease causing end-stage renal disease (ESRD). Nevertheless, the underlying mechanisms responsible for DN remain largely unknown. Regulated in development and DNA damage response 1 (REDD1) is a prooxidative molecule known to contribute to diabetes mellitus and its complications. However, it has not been previously examined whether and how REDD1 can further drive renal tubular epithelial cell (RTEC) apoptosis and epithelial-to-mesenchymal transition in DN. The expression of REDD1 was elevated in the kidneys of DN patients and diabetic mice in this study. By generating the DN model in REDD1 knockout mice, we demonstrated that REDD1 deficiency significantly improved apoptosis and EMT in diabetic mice. In vitro experiments showed that REDD1 generation was induced by high glucose (HG) in HK-2 cells. Similarly, the transfection of REDD1 siRNA plasmid also suppressed HG-induced apoptosis and EMT. Furthermore, we discovered that the inhibition of REDD1 suppressed the expression of Nox4-induced HG and reactive oxygen species (ROS) synthesis in HK-2 cells. In addition, HG could induce endogenous REDD1 and TXNIP to form a powerful complex. In summary, our findings demonstrate that blocking the REDD1/TXNIP complex can prevent HG-induced apoptosis and EMT by inhibiting ROS production, highlighting REDD1 as a valuable therapeutic priority site for DN.

TOP2A correlates with poor prognosis and affects radioresistance of medulloblastoma.

Radiotherapy remains the standard treatment for medulloblastoma (MB), and the radioresistance contributes to tumor recurrence and poor clinical outcomes. Nuclear DNA topoisomerase II-alpha (TOP2A) is a key catalytic enzyme that initiates DNA replication, and studies have shown that TOP2A is closely related to the therapeutic effects of radiation. In this study, we found that TOP2A was significantly upregulated in MB, and high expression of TOP2A related to poor prognosis of MB patients. Knockdown of TOP2A inhibited MB cell proliferation, migration, and invasion, whereas overexpression of TOP2A enhanced the proliferative and invasive ability of MB cells. Moreover, si-TOP2A transfection in combination with irradiation (IR) significantly reduced the tumorigenicity of MB cells, compared with those transfected with si-TOP2A alone. Cell survival curve analysis revealed that the survival fraction of MB cells was significantly reduced upon TOP2A downregulation and that si-TOP2A-transfected cells had decreased D0, Dq, and SF2 values, indicating that TOP2A knockdown suppresses the resistance to radiotherapy in MB cells. In addition, western blot analysis demonstrated that the activity of Wnt/ß-catenin signaling pathway was inhibited after TOP2A downregulation alone or in combination with IR treatment, whereas overexpression of TOP2A exhibited the opposite effects. Gene set enrichment analysis also revealed that Wnt/ß-catenin signaling pathway is enriched in TOP2A high-expression phenotypes. Collectively, these data indicate that high expression of TOP2A leads to poor prognosis of MB, and downregulation of TOP2A inhibits the malignant behaviour as well as the radioresistance of MB cells. The Wnt/ß-catenin signaling pathway may be involved in the molecular mechanisms of TOP2A mediated reduced tumorigenicity and radioresistance of MB cells.

Identification of FABP7 as a Potential Biomarker for Predicting Prognosis and Antiangiogenic Drug Efficacy of Glioma.

Objective: Glioma is a common malignant tumor of the central nervous system with extremely poor prognosis. An efficient molecular marker for diagnosis and treatment is urgently needed. Fatty acid binding protein 7(FABP7), which regulates intracellular lipid metabolism, is highly expressed in nervous system tumors, but its prognostic value remains undetermined. The present study investigated the relationship between FABP7 expression and prognosis in glioma patients by bioinformatics analysis, as well as immunohistochemically evaluating the effect of FABP7 expression on the efficacy of antiangiogenic drugs. Methods: Gene expression and clinical data on patients with glioma were collected from the China Glioma Genome Atlas (CGGA) database, The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases. Levels of FABP7 expression and their association with the clinicopathologic characteristics of glioma patients were analyzed in the CGGA database. The relationships between FABP7 expression and clinical findings, such as survival and prognostic, were determined and used for nomogram construction. Mechanisms of action of FABP7 were assessed using GSEA software. FABP7 expression in the tissues of glioma patients treated with apatinib was evaluated immunohistochemically. Results: FABP7 was highly expressed in glioma samples, with higher FABP7 expression associated with poorer patient prognosis and more advanced clinicopathological features. Bioinformatics analysis, including survival, receiver operating characteristic curve, and univariate and multivariate Cox analyses, showed that FABP7 was independently prognostic of outcomes in glioma patients. GSEA analysis showed that FABP7 was associated with angiogenesis, with FABP7 having correlation coefficients > 0.4 with seven factors in the angiogenic pathway, POSTN, TIMP1, PDGFA, FGFR1, S100A4, COL5A2, and STC1, and the expression of these factors related to patient prognosis. Immunohistochemistry showed that FABP7 expression was higher in glioma patients with poor survival after apatinib treatment. Conclusions: High FABP7 expression is associated with poor prognosis in glioma patients. FABP7, which is important for glioma angiogenesis, may serve as an independent prognostic predictor in glioma patients.

Meta of classical chemotherapy compared with high-dose chemotherapy and autologous stem cell rescue in newly diagnosed medulloblastoma after radiotherapy.

BACKGROUND: High-dose chemotherapy combined with autologous stem cell rescue (HDCT + ASCR) has been used to treat newly diagnosed medulloblastoma, but there was no high-level evidence to support its efficacy. METHODS: Databases were retrieved, and patients were divided into 2 groups: group A was radiotherapy combined with HCDT + ASCR, and group B was classical radiotherapy and chemotherapy. The clinical benefit rate, progression-free survival (PFS), overall survival (OS) and toxicities data were extracted. RESULTS: 22 clinical trials met the inclusion criteria, 416 in group A and 2331 in group B. There was no difference in CBR between 2 groups (80.0% vs 71.5%, P.262). The 3-year PFS (3-y PFS) of group A was significantly better than group B (79.0% vs 69.5%, P = .004). The analysis found that there was no difference between the 2 groups of the standard risk group or the high-risk group. In the standard risk group, the 5-y PFS of group A was significantly better than group B (83.6% vs75.6%, P = .004). Comparison of 3-y OS and 5-y OS between 2 groups of all MB patients showed no difference (P = .086; P = .507), stratified analysis was the same result. The gastrointestinal toxicity in group A was significantly higher than that in group B (P = .016), and the level 3/4 ototoxicity in high-risk group A was higher than that in group B (P = .001). CONCLUSIONS: HDCT + ASCR can prolong 3-year PFS significantly, and prolong 5-y PFS significantly in the standard risk group, but increase gastrointestinal toxicity significantly for newly diagnosed medulloblastoma.

ANXA1: An Important Independent Prognostic Factor and Molecular Target in Glioma.

Objective: The expression, prognosis, and related mechanisms of ANXA1 are investigated in glioma, with the objective to find potential therapeutic molecular targets for glioma. Methods: We analyzed the gene expression of ANXA1 using glioma-related databases, including the Chinese Glioma Genome Atlas (CGGA) database, The Cancer Genome Atlas (TCGA) database, and the Gene Expression Omnibus (GEO) database. Moreover, we collected the sample tissues and corresponding paracancerous tissues of 23 glioma patients and then conducted a Western blot experiment to verify the expression and correlate survival of ANXA1. Moreover, we generated survival ROC curves, performing univariate and multivariate Cox analyses and the construction of the nomogram. Differential expression analysis was conducted by high and low grouping based on the median of the ANXA1 gene expression values. We conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Set Enrichment Analysis (GSEA) to explore possible mechanisms, and gene co-expression analysis was also performed. Results: The results showed that the ANXA1 expression level was higher in gliomas than in normal tissues, and a high expression level of ANXA1 in gliomas was associated with poorer prognosis. The independent prognosis analysis showed that the ANXA1 gene was an independent prognostic factor of glioma. In the analysis of KEGG and Gene Set Enrichment Analysis (GSEA), it is shown that ANXA1 may play an important role in glioma patients by affecting extracellular matrix (ECM)-receptor interaction and the focal adhesion signal pathway. The core genes, including COL1A1, COL1A2, FN1, ITGA1, and ITGB1, were screened for gene correlation and prognosis analysis. The expression level of the five genes was verified by qPCR in glioma. We concluded that these five core genes and ANXA1 could play a synergistic role in gliomas. Conclusion: The results indicated that a high expression level of ANXA1 leads to worse prognosis and ANXA1 is an independent prognostic factor and a potentially important target for the treatment of gliomas.

Integrated Analysis of Multiple Microarray Studies to Identify Core Gene-Expression Signatures Involved in Tubulointerstitial Injury in Diabetic Nephropathy.

Diabetic nephropathy is a leading cause of end-stage renal disease in both developed and developing countries. It is lack of specific diagnosis, and the pathogenesis remains unclarified in diabetic nephropathy, following the unsatisfactory effects of existing treatments. Therefore, it is very meaningful to find biomarkers with high specificity and potential targets. Two datasets, GSE30529 and GSE47184 from GEO based on diabetic nephropathy tubular samples, were downloaded and merged after batch effect removal. A total of 545 different expression genes screened with log2FC > 0.5 were weighted gene coexpression correlation network analysis, and green module and blue module were identified. The results of KEGG analyses both in green module and GSEA analysis showed the same two enriched pathway, focal adhesion and viral myocarditis. Based on the intersection among WGCNA focal adhesion/Viral myocarditis, GSEA focal adhesion/viral myocarditis, and PPI network, 17 core genes, ACTN1, CAV1, PRKCB, PDGFRA, COL1A2, COL6A3, RHOA, VWF, FN1, HLA-F, HLA-DPB1, ITGB2, HLA-DRA, HLA-DMA, HLA-DPA1, HLA-B, and HLA-DMB, were identified as potential biomarkers in diabetic tubulointerstitial injury and were further validated externally for expression at GSE99325 and GSE104954 and clinical feature at nephroseq V5 online platform. CMap analysis suggested that two compounds, LY-294002 and bufexamac, may be new insights for therapeutics of diabetic tubulointerstitial injury. Conclusively, it was raised that a series of core genes may be as potential biomarkers for diagnosis and two prospective compounds.

NRAGE Confers Radiation Resistance in 2D and 3D Cell Culture and Poor Outcome in Patients With Esophageal Squamous Cell Carcinoma.

Objective: The purpose of the study is to explore the mechanism of NRAGE enhancing radioresistance of esophageal squamous cell carcinoma (ESCC) in 2D and 3D levels. Methods: Stably NRAGE-overexpressed ESCC cells and 3D-printing models for ESCC cells were established. Then, cellular malignancy indexes, such as cell morphology, proliferation, radioresistance, motility, apoptosis, cell cycle, and proteins of the Wnt/ß-catenin pathway, were compared between radioresistant and its parental cells in 2D and 3D levels. Additionally, 44 paraffin ESCC specimens with radical radiotherapy were selected to examine NRAGE and ß-catenin protein expression and analyze the clinical correlation. Results: Experiments in 2D culture showed that morphology of the Eca109/NRAGE cells was more irregular, elongated spindle-shaped and disappeared polarity. It obtained faster growth ability, stronger resistance to irradiation, enhanced motility, reduced apoptosis ratio and cell cycle rearrangement. Moreover, Western blot results showed ß-catenin, p-Gsk-3ß and CyclinD1 expressions were induced, while p-ß-catenin and Gsk-3ß expressions decreased in Eca109/NRAGE cells. Experiments in the 3D-printing model showed Eca109/NRAGE cell-laden 3D scaffolds had the advantage on growth and spheroiding according to the brightfield observation, scanning electron microscopy and Ki-67 IHC staining, and higher expression at the ß-catenin protein. Clinical analysis showed that NRAGE expression was higher in tumor tissues than in control tissues of ESCC patients from the Public DataBase. Compared with radiotherapy effective group, both NRAGE total and nuclear and ß-catenin nuclear expressions were significantly upregulated from ESCC specimens in invalid group. Further analysis showed a positive and linear correlation between NRAGE nuclear and ß-catenin nuclear expressions. Additionally, results from univariate and multivariate analyses revealed NRAGE nuclear expression could serve as a risk factor for ESCC patients receiving radical radiotherapy. Conclusion: ESCC cells with NRAGE nuclear accumulation demonstrated greater radioresistance, which may be related to the activation of the Wnt/ß-catenin signaling pathway. It indicated that NRAGE nuclear expression was a potential biomarker for monitoring radiotherapeutic response.

Identification of MCM4 as a Prognostic Marker of Hepatocellular Carcinoma.

METHODS: MCM4 expression difference in HCC were analyzed from TCGA and GEO data and verified by real-time PCR and western blot. ROC curve was used to analyze the diagnostic value of MCM4 and AFP. Additionally, the relationship between MCM4 and stage or nodal metastasis status or grade or age in TCGA cohort with HCC was observed from the UALCAN website. The univariate and multivariate Cox and functional analyses were done to explore the prognostic value of MCM4 in TCGA cohort. RESULTS: It was found that MCM4 was significantly highly expressed in HCC tissues from TCGA, GEO, and experimental data. Furthermore, ROC curve analysis showed that MCM4 was superior to be a diagnostic biomarker than AFP from TCGA (AUCMCM4 = 0.9461, AUCAFP = 0.7056) and GEO (GSE19665: AUCMCM4 = 0.8800, AUCAFP = 0.5100; GSE64041 AUCMCM4 = 0.8038, AUCAFP = 0.6304). AUC of MCM4 from real-time PCR result in 60 pairs of HCC and adjacent tissues was 0.7172, demonstrating the prediction value of MCM4. Besides, different expression tendencies of MCM4 among different stages or nodal metastasis status or grade or age were observed from the UALCAN website. In addition, multiROC analysis showed the advantage of MCM4 as a survival prediction at 1, 3, and 5 years with the higher AUC at 0.69 of 1 year, 0.65 of 3 years, and 0.61 of 5 years. It was shown that MCM4 was independently associated with OS in univariate and multivariate Cox analysis. And GSEA displayed that MCM4 was highly enriched in KEGG_CELL_CYCLE signaling pathway following higher correlation positively with CDC6, PLK1, CRC1, and BUB1B in HCC. CONCLUSION: MCM4 might be a potential biomarker in guiding the prognostic status of HCC patients.

Upregulated Expression of Cancer-Derived Immunoglobulin G Is Associated With Progression in Glioma.

OBJECTIVE: Gliomas are the most aggressive intracranial tumors accounting for the vast majority of brain tumors with very poor prognosis and overall survival (OS). Cancer-derived immunoglobulin G (cancer-IgG) has been found to be widely expressed in several malignancies such as breast cancer, colorectal cancer, and lung cancer. Cancer-IgG could promote tumorigenesis and progression. However, its role in glioma has not been revealed yet. METHODS: We mined open databases including the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) to study the role of IGHG1, which encodes cancer-IgG in glioma. Examination of the differential expression of IGHG1 was carried out in the GEO and TCGA databases. Furthermore, its expression in different molecular subtypes was analyzed. Stratified analysis was performed with clinical features. Subsequently, immune infiltration analysis was conducted using single-sample gene set enrichment analysis (ssGSEA). GSEA was performed to reveal the mechanisms of IGHG1. Lastly, immunohistochemistry was processed to validate our findings. RESULTS: In this study, we found that the expression of IGHG1 was higher in glioma and molecular subtypes with poor prognosis. The overall survival of patients with a high expression of IGHG1 was worse in the stratified analysis. Immune infiltration analysis indicated that the expression level of IGHG1 was positively correlated with the stromal score, ESTIMATE score, and immune score and negatively correlated with tumor purity. Results from the GSEA and DAVID demonstrated that IGHG1 may function in phagosome, antigen processing and presentation, extracellular matrix structural constituent, antigen binding, and collagen-containing extracellular matrix. Finally, immunohistochemistry assay validated our findings that patients with a high expression of cancer-IgG had poor OS and disease-free survival (DFS). CONCLUSION: Cancer-IgG is a promising biomarker of diagnosis and treatment for patients with glioma.

A Focal Adhesion-Related Gene Signature Predicts Prognosis in Glioma and Correlates With Radiation Response and Immune Microenvironment.

BACKGROUND: Glioma is the most frequent brain malignancy presenting very poor prognosis and high recurrence rate. Focal adhesion complexes play pivotal roles in cell migration and act as hubs of several signaling pathways. METHODS: We used bioinformatic databases (CGGA, TCGA, and GEO) and identified a focal adhesion-related differential gene expression (FADG) signature by uniCox and LASSO regression analysis. We calculated the risk score of every patient using the regression coefficient value and expression of each gene. Survival analysis, receiver operating characteristic curve (ROC), principal component analysis (PCA), and stratified analysis were used to validate the FADG signature. Then, we conducted GSEA to identify the signaling pathways related to the FADG signature. Correlation analysis of risk scores between the immune checkpoint was performed. In addition, the correlation of risk scores and genes related with DNA repair was performed. CIBERSORT and ssGSEA were used to explore the tumor microenvironment (TME). A nomogram that involved our FADG signature was also constructed. RESULTS: In total, 1,726 (528 patients diagnosed with WHO II, 591 WHO III, and 603 WHO IV) cases and 23 normal samples were included in our study. We identified 29 prognosis-related genes in the LASSO analysis and constructed an eight FADG signature. The results from the survival analysis, stratified analysis, ROC curve, and univariate and multivariate regression analysis revealed that the prognosis of the high-risk group was significantly worse than the low-risk group. Correlation analysis between risk score and genes that related with DNA repair showed that the risk score was positively related with BRCA1, BRCA2, RAD51, TGFB1, and TP53. Besides, we found that the signature could predict the prognosis of patients who received radiation therapy. SsGSEA indicated that the high-risk score was positively correlated with the ESTIMATE, immune, and stromal scores but negatively correlated with tumor purity. Notably, patients in the high-risk group had a high infiltration of immunocytes. The correlation analysis revealed that the risk score was positively correlated with B7-H3, CTLA4, LAG3, PD-L1, and TIM3 but inversely correlated with PD-1. CONCLUSION: The FADG signature we constructed could provide a sensitive prognostic model for patients with glioma and contribute to improve immunotherapy management guidelines.

DNMT family induces down-regulation of NDRG1 via DNA methylation and clinicopathological significance in gastric cancer.

BACKGROUND: Aberrant DNA methylation of tumor suppressor genes is a common event in the development and progression of gastric cancer (GC). Our previous study showed NDRG1, which could suppress cell invasion and migration, was frequently down-regulated by DNA methylation of its promoter in GC. PURPOSE AND METHODS: To analyze the relationship between the expression and DNA methylation of NDRG1 and DNA methyltransferase (DNMT) family. We performed a comprehensive comparison analysis using 407 patients including sequencing analysis data of GC from TCGA. RESULTS: NDRG1 was down-regulated in GC, and was negatively correlative to DNMT1 (r = -0.11, p = 0.03), DNMT3A (r = -0.10, p = 0.01), DNMT3B (r = -0.01, p = 0.88), respectively, whereas the DNA methylation of NDRG1 was positively correlative to DNMT family (DNMT1 r = 0.20, p < 0.01; DNMT3A r = 0.26, p < 0.001; DNMT3B r = 0.03, p = 0.57, respectively). NDRG1 expression was significantly inverse correlated with invasion depth (p = 0.023), but DNMT1 was significantly positive correlated with invasion depth (p = 0.049). DNMT3B was significantly correlated with the degree of tumor cell differentiation (p = 0.030). However, there was no association between the expression of DNMT3A and clinicopathological features. The KM plotter showed that NDRG1 (HR = 0.95, 95% CI [0.8-1.12], p = 0.53) and DNMT1 (HR = 1.04, 95% CI [0.88-1.23], p = 0.67) had no association with prognosis of GC patients, while, DNMT3A (p = 0.0064) and DNMT3B (p = 0.00025) displayed significantly association. But the overall survival of high expression of NDRG1 tended to be prolonged. CONCLUSION: These data suggest that down-regulation of NDRG1expression in GC may be due to its promoter DNA methylation via DNMT family. The demethylating agent maybe a potential target drug for GC patients.

The current management of alveolar soft part sarcomas.

OBJECTIVE: Alveolar soft part sarcomas (ASPS) which has high potential ability of metastasis, is a rare and slowly growing malignant tumor, and mainly primary localized in limbs. To date, little is known about the best treatment of ASPS. This study aims to review the current management and advance of ASPS. METHODS: WANFANG MED ONLINE, CNKI, and NCBI PUBMED were used to search literature spanning from 1963 to 2020, and all cases of ASPS about "ASPS, diagnosis, treatment, surgery, radiotherapy, chemotherapy, target therapy or immune therapy" with detailed data were included. RESULTS: Complete surgical resection remained the standard management strategy, radiotherapy was reported to be used for the patients of micro- or macroscopical incomplete residue or the surgical margin was questionable. Chemotherapy was controversial. Some target drugs and immune checkpoint inhibitors had produced antitumor activity. CONCLUSION: Complete surgical resection is the cure treatment for ASPS, and adjuvant chemotherapy is not recommended excepted clinical trials. For the patients with micro- or macroscopical incomplete residue, radiotherapy should be appreciated. Furthermore, for recurrence, distant metastasis, and refractory of ASPS, combination therapy, especially combination with multiple target agents and/or immune checkpoint inhibitors may prolong survival time.

Circular RNA: A novel type of biomarker for glioma (Review).

With the rapid development of sequencing technologies, the characteristics and functions of circular RNAs (circRNAs) in different tissues, and their underlying pathophysiological mechanisms, have been identified. circRNAs are significantly enriched in the brain and are continually expressed from the embryonic stage to the adult stage in rats. Previous studies have reported that certain circRNAs are differentially expressed in glioma and regulate a number of biological processes, such as cell proliferation, metastasis and oncogenesis of glioma. Furthermore, certain circRNAs have been associated with tumor size, World Health Organization tumor grade and poor prognosis in patients with glioma. It has been hypothesized that circRNAs may be involved in the onset and progression of glioma through transcriptional regulation, protein translation and binding to microRNAs. These properties and functions suggest the potential of circRNAs as prognostic biomarkers and therapeutic targets for glioma. For the present review, published studies were examined from PubMed, Embase, Cochrane Central and the reference lists of the retrieved articles. The aim of the present review was to summarize the progress of circRNA research in glioma, discuss the potential diagnostic and prognostic values, and the roles of circRNAs in glioma, and provide a novel theoretical basis and research concepts for the prediction, diagnosis and treatment of glioma.

A Prognostic DNA Damage Repair Genes Signature and Its Impact on Immune Cell Infiltration in Glioma.

OBJECTIVE: Glioma is the most frequent type of malignant cerebral tumors. DNA damage repair genes (DDRGs) play a crucial role in the development of cancer. In this study, we constructed a DDRGs signature and investigated the potential mechanisms involved in this disease. METHODS: RNA sequence data, microarray data, and corresponding clinical information of gliomas were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO). Subsequently, we identified candidate genes by differential analysis and Cox regression analysis. The least absolute shrinkage and selection operator Cox regression model was utilized to construct a DDRGs signature using TCGA training dataset. According to this signature, patients with glioma were divided into low- and high-risk groups. The predictive ability of the signature was validated by prognostic analysis, receiver operating characteristic curves, principal component analysis, and stratification analysis in TCGA testing and CGGA verification datasets. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate the immune microenvironment of glioma. Moreover, we conducted GSEA to determine the functions and pathways in the low- and high-risk groups. Finally, a nomogram was constructed by combining the signature and other clinical features. RESULTS: A total of 1,431 samples of glioma (592 from TCGA, 686 from the CGGA, and 153 from the GEO) and 23 samples of normal brain tissue from the GEO were analyzed in this study. There were 51 prognostic differentially expressed DDRGs. Additionally, five DDRGs (CDK4、HMGB2、WEE1、SMC3 and GADD45G) were selected to construct a DDRGs signature for glioma, stratifying patients into low- and high-risk groups. The survival analysis showed that the DDRGs signature could differentiate the outcome of the low- and high-risk groups, showing that high-risk gliomas were associated with shorter overall survival. The immune microenvironment analysis revealed that more immunosuppressive cells, such as tumor associated macrophages and regulatory T cells, were recruited in the high-risk group. GSEA also showed that high-risk glioma was correlated with the immune and extracellular matrix pathways. CONCLUSION: The five DDRGs signature and its impact on the infiltration of immunosuppressive cells could precisely predict the prognosis and provide guidance on the treatment of glioma.