HDAC4, a prognostic and chromosomal instability marker, refines the predictive value of MGMT promoter methylation

MEN1 Deficiency-Driven Activation of the β-Catenin-MGMT Axis Promotes Pancreatic Neuroendocrine Tumor Growth and Confers Temozolomide Resistance

O6-methylguanine DNA methyltransferase (MGMT) removes alkyl adducts from the guanine O6 position (O6-MG) and repairs DNA damage. High MGMT expression results in poor response to temozolomide (TMZ). However, the biological importance of MGMT and the mechanism underlying its high expression in pancreatic neuroendocrine tumors (PanNETs) remain elusive. Here, it is found that MGMT expression is highly elevated in PanNET tissues compared with paired normal tissues and negatively associated with progression-free survival (PFS) time in patients with PanNETs. Knocking out MGMT inhibits cancer cell growth in vitro and in vivo. Ectopic MEN1 expression suppresses MGMT transcription in a manner that depends on β-Catenin nuclear export and degradation. The Leucine 267 residue of MEN1 is crucial for regulating β-Catenin-MGMT axis activation and chemosensitivity to TMZ. Interference with β-Catenin re-sensitizes tumor cells to TMZ and significantly reduces the cytotoxic effects of high-dose TMZ treatment, and MGMT overexpression counteracts the effects of β-Catenin deficiency. This study reveals the biological importance of MGMT and a new mechanism by which MEN1 deficiency regulates its expression, thus providing a potential combinational strategy for treating patients with TMZ-resistant PanNETs.

Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors

Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.

MGMT in TMZ-based glioma therapy: Multifaceted insights and clinical trial perspectives

Temozolomide (TMZ) is the most preferred and approved chemotherapeutic drug for either first- or second-line chemotherapy for glioma patients across the globe. In glioma patients, resistance to treatment with alkylating drugs like TMZ is known to be conferred by exalted levels of MGMT gene expression. On the contrary, epigenetic silencing through MGMT gene promoter methylation leading to subsequent reduction in MGMT transcription and protein expression, is predicted to have a response favoring TMZ treatment. Thus, MGMT protein level in cancer cells is a crucial determining factor in indicating and predicting the choice of alkylating agents in chemotherapy or choosing glioma patients directly for a second line of treatment. Thus, in-depth research is necessary to achieve insights into MGMT gene regulation that has recently enticed a fascinating interest in epigenetic, transcriptional, post-transcriptional, and post-translational levels. Furthermore, MGMT promoter methylation, stability of MGMT protein, and related subsequent adaptive responses are also important contributors to strategic developments in glioma therapy. With applications to its identification as a prognostic biomarker, thus predicting response to advanced glioma therapy, this review aims to concentrate on the mechanistic role and regulation of MGMT gene expression at epigenetic, transcriptional, post-transcriptional, and post-translational levels functioning under the control of multiple signaling dynamics.

Noninvasive radiomics model reveals macrophage infiltration in glioma

Preoperative MRI is an essential diagnostic and therapeutic reference for gliomas. This study aims to evaluate the prognostic aspect of a radiomics biomarker for glioma and further investigate its relationship with tumor microenvironment and macrophage infiltration. We covered preoperative MRI of 664 glioma patients from three independent datasets: Jiangsu Province Hospital (JSPH, n = 338), The Cancer Genome Atlas dataset (TCGA, n = 252), and Repository of Molecular Brain Neoplasia Data (REMBRANDT, n = 74). Incorporating a multistep post-processing workflow, 20 radiomics features (Rads) were selected and a radiomics survival biomarker (RadSurv) was developed, proving highly efficient in risk stratification of gliomas (cut-off = 1.06), as well as lower-grade gliomas (cut-off = 0.64) and glioblastomas (cut-off = 1.80) through three fixed cut-off values. Through immune infiltration analysis, we found a positive correlation between RadSurv and macrophage infiltration (RMΦ = 0.297, p < 0.001; RM2Φ = 0.241, p < 0.001), further confirmed by immunohistochemical-staining (glioblastomas, n = 32) and single-cell sequencing (multifocal glioblastomas, n = 2). In conclusion, RadSurv acts as a strong prognostic biomarker for gliomas, exhibiting a non-negligible positive correlation with macrophage infiltration, especially with M2 macrophage, which strongly suggests the promise of radiomics-based models as a preoperative alternative to conventional genomics for predicting tumor macrophage infiltration and provides clinical guidance for immunotherapy.

Differences of macrophages in the tumor microenvironment as an underlying key factor in glioma patients

BACKGROUND

Macrophages, the major immune cells in glioma microenvironment, are closely related to tumor prognosis. Further studies are needed to investigate macrophages, which will be helpful to fully understand the role of it and early achieve clinical translation.

METHODS

A total of 1334 glioma cases were enrolled in this study from 3 databases. In our works, the single cell cohorts from GSE89567, GSE84465, and the Chinese Glioma Genome Atlas (CGGA) datasets were used to analyze the key genes of macrophage. The bulk sequencing data from the Cancer Genome Atlas (TCGA) and CGGA datasets were respectively divided into the training set and validation set to test prognostic value of the key genes from single cell analysis.

RESULTS

Quantitative and functional differences significantly emerge in macrophage clusters between LGG and GBM. Firstly, we used the Seurat R package to identify 281 genes differentially expressed genes in macrophage clusters between LGG and GBM. Furthermore, based on these genes, we developed a predictive risk model to predict prognosis and reflect the immune microenvironment in glioma. The risk score calculation formula was yielded as follows: Risk score = (0.11 × EXPMACC1) + (-0.31 × EXPOTUD1) + (-0.09 × EXPTCHH) + (0.26 × EXPADPRH) + (-0.40× EXPABCG2) + (0.21 × EXPPLBD1) + (0.12 × EXPANG) + (0.29 × EXPQPCT). The risk score was independently related to prognosis. Further, significant differences existed in immunological characteristics between the low- and high-risk score groups. What is more, mutation analysis found different genomic patterns associated with the risk score.

CONCLUSION

This study further confirms that the proportion of macrophage infiltration is not only significantly different, but the function of them is also different. The signature, identified from the differentially expressed macrophage-related genes impacts poor prognosis and short overall survival and may act as therapeutic targets in the future.

A Prognostic Model for Brain Glioma Patients Based on 9 Signature Glycolytic Genes

Objective

To screen glycolytic genes linked to the glioma prognosis and construct the prognostic model.

Methods

The relevant data of glioma were downloaded from TCGA and GTEx databases. GSEA of glycolysis-related pathways was carried out, and enriched differential genes were extracted. Screening out prognostic-related genes with conspicuous significance and construction of the prognostic model were conducted by multivariate Cox regression analysis and Lasso regression analysis. The model was evaluated, and cBioPortal was used to analyze the mutation of the model gene. The expression of the model gene in tumor and normal colon tissue was analyzed. The model was used to evaluate the prognosis of patients in different groups to verify the applicability of the model.

Results

339 differentially glycolytic-related genes were enriched in REACTOME_GLYCOLYSIS, GLYCOLYTIC_PROCESS, HALLMARK_GLYCOLYSIS, and other pathways. We obtained 9 key prognostic genes and constructed the prognostic evaluation model. The 3-year AUC values of the ROC curve display model are greater than 0.75, which indicates that the accuracy of the model is good. The relation of age and risk score to prognosis is shown by univariate and multivariate Cox analysis. The expression of SRD5A3, MDH2, and B3GAT3 genes was significantly upregulated in the tumor tissues, while the HDAC4 and G6PC2 genes were downregulated. The mutation rate of MDH2 and HDAC4 genes was the highest. This model could effectively distinguish the risk of poor prognosis of patients in any age stage.

Conclusion

The prognostic assessment models based on glycolysis-related nine-gene signature could accurately predict the prognosis of patients with GBM.

Potential new targets and drugs related to histone modifications in glioma treatment

Glioma accounts for 40-50% of craniocerebral tumors, whose outcome rarely improves after standard treatment. The development of new therapeutic targets for glioma treatment has important clinical significance. With the deepening of research on gliomas, recent researchers have found that the occurrence and development of gliomas is closely associated with histone modifications, including methylation, acetylation, phosphorylation, and ubiquitination. Additionally, evidence has confirmed the close relationship between histone modifications and temozolomide (TMZ) resistance. Therefore, histone modification-related proteins have been widely recognized as new therapeutic targets for glioma treatment. In this review, we summarize the potential histone modification-associated targets and related drugs for glioma treatment. We have further clarified how histone modifications regulate the pathogenesis of gliomas and the mechanism of drug action, providing novel insights for the current clinical glioma treatment. Herein, we have also highlighted the limitations of current clinical therapies and have suggested future research directions and expected advances in potential areas of disease prognosis. Due to the complicated glioma pathogenesis, in the present review, we have acknowledged the limitations of histone modification applications in the related clinical treatment.

Identification of a Novel Epithelial-Mesenchymal Transition Gene Signature Predicting Survival in Patients With HNSCC

Head and neck squamous cell cancer (HNSCC) is one of the most common types of cancer worldwide. There have been many reports suggesting that biomarkers explored via database mining plays a critical role in predicting HNSCC prognosis. However, a single biomarker for prognostic analysis is not adequate. Additionally, there is growing evidence indicating that gene signature could be a better choice for HNSCC prognosis. We performed a comprehensive analysis of mRNA expression profiles using clinical information of HNSCC patients from The Cancer Genome Atlas (TCGA). Gene Set Enrichment Analysis (GSEA) was performed, and we found that a set of genes involved in epithelial mesenchymal transition (EMT) contributed to HNSCC. Cox proportional regression model was used to identify a four-gene (WIPF1, PPIB, BASP1, PLOD2) signature that were significantly associated with overall survival (OS), and all the four genes were significantly upregulated in tumor tissues. We successfully classified the patients with HNSCC into high-risk and low-risk groups, where in high-risk indicated poorer patient prognosis, indicating that this gene signature might be a novel potential biomarker for the prognosis of HNSCC. The prognostic ability of the gene signature was further validated in an independent cohort from the Gene Expression Omnibus (GEO) database. In conclusion, we identified a four-EMT-based gene signature which provides the potentiality to serve as novel independent biomarkers for predicting survival in HNSCC patients, as well as a new possibility for individualized treatment of HNSCC.

Prognostic value of test(s) for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation for predicting overall survival in people with glioblastoma treated with temozolomide

BACKGROUND

Glioblastoma is an aggressive form of brain cancer. Approximately five in 100 people with glioblastoma survive for five years past diagnosis. Glioblastomas that have a particular modification to their DNA (called methylation) in a particular region (the O6-methylguanine-DNA methyltransferase (MGMT) promoter) respond better to treatment with chemotherapy using a drug called temozolomide.

OBJECTIVES

To determine which method for assessing MGMT methylation status best predicts overall survival in people diagnosed with glioblastoma who are treated with temozolomide.

SEARCH METHODS

We searched MEDLINE, Embase, BIOSIS, Web of Science Conference Proceedings Citation Index to December 2018, and examined reference lists. For economic evaluation studies, we additionally searched NHS Economic Evaluation Database (EED) up to December 2014.

SELECTION CRITERIA

Eligible studies were longitudinal (cohort) studies of adults with diagnosed glioblastoma treated with temozolomide with/without radiotherapy/surgery. Studies had to have related MGMT status in tumour tissue (assessed by one or more method) with overall survival and presented results as hazard ratios or with sufficient information (e.g. Kaplan-Meier curves) for us to estimate hazard ratios. We focused mainly on studies comparing two or more methods, and listed brief details of articles that examined a single method of measuring MGMT promoter methylation. We also sought economic evaluations conducted alongside trials, modelling studies and cost analysis.

DATA COLLECTION AND ANALYSIS

Two review authors independently undertook all steps of the identification and data extraction process for multiple-method studies. We assessed risk of bias and applicability using our own modified and extended version of the QUality In Prognosis Studies (QUIPS) tool. We compared different techniques, exact promoter regions (5'-cytosine-phosphate-guanine-3' (CpG) sites) and thresholds for interpretation within studies by examining hazard ratios. We performed meta-analyses for comparisons of the three most commonly examined methods (immunohistochemistry (IHC), methylation-specific polymerase chain reaction (MSP) and pyrosequencing (PSQ)), with ratios of hazard ratios (RHR), using an imputed value of the correlation between results based on the same individuals.

MAIN RESULTS

We included 32 independent cohorts involving 3474 people that compared two or more methods. We found evidence that MSP (CpG sites 76 to 80 and 84 to 87) is more prognostic than IHC for MGMT protein at varying thresholds (RHR 1.31, 95% confidence interval (CI) 1.01 to 1.71). We also found evidence that PSQ is more prognostic than IHC for MGMT protein at various thresholds (RHR 1.36, 95% CI 1.01 to 1.84). The data suggest that PSQ (mainly at CpG sites 74 to 78, using various thresholds) is slightly more prognostic than MSP at sites 76 to 80 and 84 to 87 (RHR 1.14, 95% CI 0.87 to 1.48). Many variants of PSQ have been compared, although we did not see any strong and consistent messages from the results. Targeting multiple CpG sites is likely to be more prognostic than targeting just one. In addition, we identified and summarised 190 articles describing a single method for measuring MGMT promoter methylation status.

AUTHORS' CONCLUSIONS

PSQ and MSP appear more prognostic for overall survival than IHC. Strong evidence is not available to draw conclusions with confidence about the best CpG sites or thresholds for quantitative methods. MSP has been studied mainly for CpG sites 76 to 80 and 84 to 87 and PSQ at CpG sites ranging from 72 to 95. A threshold of 9% for CpG sites 74 to 78 performed better than higher thresholds of 28% or 29% in two of three good-quality studies making such comparisons.

Identification and validation of potential novel prognostic biomarkers for patients with glioma based on a gene co-expression network

BACKGROUND

Glioma is widely regarded as one of most lethal and challenging diseases of the nervous system. The aim of this study was to identify novel biomarkers that offer better prognosis prediction for Chinese patients with glioma.

METHODS

By using systematic approaches, the co-expression modules were identified from the Chinese Glioma Genome Atlas (CGGA) database through weighted gene co-expression network analysis and functional enrichment of essential modules of Kyoto Encyclopedia of Genes and Genomes terms. The co-expression modules were validated using The Cancer Genome Atlas database and the protein-protein interaction (PPI) network.

RESULTS

For network construction, 5,374 among 21,494 genes were selected, and an increasing genetic variance was associated with the prognosis of glioma. By using functional enrichment analysis, the involvement of multiple vital processes, including metabolism of fatty acids, was correlated with the patient prognosis. Notably, five hub genes (KCNB1, UST, SOX8, KLHL42, and HDAC4) were identified for these processes. Accordingly, using the Kaplan-Meier method, there was enhanced expression of these genes in patients with significantly lower overall survival rates, especially those from the CGGA database.

CONCLUSIONS

This study not only revealed the essential co-expression gene modules in patients with glioma, but it also unraveled the potential signaling pathways underlying these functional processes.

Identification of a nine-gene prognostic signature for gastric carcinoma using integrated bioinformatics analyses

BACKGROUND

Gastric carcinoma (GC) is one of the most aggressive primary digestive cancers. It has unsatisfactory therapeutic outcomes and is difficult to diagnose early.

AIM

To identify prognostic biomarkers for GC patients using comprehensive bioinformatics analyses.

METHODS

Differentially expressed genes (DEGs) were screened using gene expression data from The Cancer Genome Atlas and Gene Expression Omnibus databases for GC. Overlapping DEGs were analyzed using univariate and multivariate Cox regression analyses. A risk score model was then constructed and its prognostic value was validated utilizing an independent Gene Expression Omnibus dataset (GSE15459). Multiple databases were used to analyze each gene in the risk score model. High-risk score-associated pathways and therapeutic small molecule drugs were analyzed and predicted, respectively.

RESULTS

A total of 95 overlapping DEGs were found and a nine-gene signature (COL8A1, CTHRC1, COL5A2, AADAC, MAMDC2, SERPINE1, MAOA, COL1A2, and FNDC1) was constructed for the GC prognosis prediction. Receiver operating characteristic curve performance in the training dataset (The Cancer Genome Atlas-stomach adenocarcinoma) and validation dataset (GSE15459) demonstrated a robust prognostic value of the risk score model. Multiple database analyses for each gene provided evidence to further understand the nine-gene signature. Gene set enrichment analysis showed that the high-risk group was enriched in multiple cancer-related pathways. Moreover, several new small molecule drugs for potential treatment of GC were identified.

CONCLUSION

The nine-gene signature-derived risk score allows to predict GC prognosis and might prove useful for guiding therapeutic strategies for GC patients.

Genomic characteristics and drug screening among organoids derived from non-small cell lung cancer patients

BACKGROUND

Patient-derived organoid (PDO) models are highly valuable and have potentially widespread clinical applications. However, limited information is available regarding organoid models of non-small cell lung cancer (NSCLC). This study aimed to characterize the consistency between primary tumors in NSCLC and PDOs and to explore the applications of PDOs as preclinical models to understand and predict treatment response during lung cancer.

METHODS

Fresh tumor samples were harvested for organoid culture. Primary tumor samples and PDOs were analyzed via whole-exome sequencing. Paired samples were subjected to immunohistochemical analysis. There were 26 antineoplastic drugs tested in the PDOs. Cell viability was assessed using the Cell Titer Glo assay 7-10 days after drug treatment. A heatmap of log-transformed values of the half-maximal inhibitory concentrations was generated on the basis of drug responses of PDOs through nonlinear regression (curve fit). A total of 12 patients (stages I-III) were enrolled, and 7 paired surgical tumors and PDOs were analyzed.

RESULTS

PDOs retained the histological and genetic characteristics of the primary tumors. The concordance between tumors and PDOs in mutations in the top 20 NSCLC-related genes was >80% in five patients. Sample purity was significantly and positively associated with variant allele frequency (Pearson r = 0.82, P = 0.0005) and chromosome stability. The in vitro response to drug screening with PDOs revealed high correlation with the mutation profiles in the primary tumors.

CONCLUSIONS

PDOs are highly credible models for detecting NSCLC and for prospective prediction of the treatment response for personalized precision medicine.

KEY POINTS

Lung cancer organoid models could save precious time of drug testing on patients, and accurately select anticancer drugs according to the drug sensitivity results, so as to provide a powerful supplement and verification for the gene sequencing.

Expression and prognostic value of mRNAs in lower grade glioma with MGMT promoter methylated

Due to the varied overall survival (OS), limited studies focus on the factors that affect the prognosis for lower grade glioma patients (LGGs) with MGMT promoter methylated. A total of 579 samples (TCGA LGGs 456; CGGA LGGs 123) were included to identify potential genes for LGGs with MGMT promoter methylated. All bioinformatics analyses were conducted using SPSS software and GraphPad Prism 6. Based on COX regression analysis, we established a four-gene signature (ALDOC, APOBEC3C, ANXA1 and ARPP21) and divided LGGs into two groups based on median risk score. The OS of LGGs in high risk group was shorter than low risk group (P < 0.0001). Furthermore, the OS in high risk group were shorter than low risk group in Grade II and III, respectively (P = 0.0003; P = 0.0104). It showed that the signature was an independent prognosis factor on multivariate Cox regression analysis (P = 0.033). Patients in high group tended to displayed high grade (GIII), IDH1 wild type and mesenchymal subtype preference. Four-gene signature was discovered for LGGs with MGMT promoter methylated. Our findings suggested that the four genes could serve as prognostic biomarkers.

Dp44mT, an iron chelator, suppresses growth and induces apoptosis via RORA-mediated NDRG2-IL6/JAK2/STAT3 signaling in glioma

PURPOSE

The iron-chelating agent di-2-pyridylketone 4,4-dimethyl-3-thiosemicarbazone (Dp44mT) has been found to inhibit cell growth and to induce apoptosis in several human cancers. However, its effects and mechanism of action in glioma are unknown.

METHODS

Human glioma cell line LN229 and patient-derived glioma stem cells GSC-42 were applied for both in vitro and in vivo xenograft nude mouse experiments. The anti-tumor effects of Dp44mT were assessed using MTS, EdU, TUNEL, Western blotting, qRT-PCR, luciferase reporter, chromatin immunoprecipitation and immunohistochemical assays.

RESULTS

We found that Dp44mT can upregulate the expression of the anti-oncogene N-myc downstream-regulated gene (NDRG)2 by directly binding to and activating the RAR-related orphan receptor (ROR)A. In addition, we found that NDRG2 overexpression suppressed inflammation via activation of interleukin (IL)-6/Janus kinase (JAK)2/signal transducer and activator of transcription (STAT)3 signaling.

CONCLUSIONS

Our data indicate that Dp44mT may serve as an effective drug for the treatment of glioma by targeting RORA and enhancing NDRG2-mediated IL-6/JAK2/STAT3 signaling.

IFI30 Is a Novel Immune-Related Target with Predicting Value of Prognosis and Treatment Response in Glioblastoma

Purpose

As a crucial part of anti-tumor immunotherapy, interferon-α/β (IFN-α/β) treatment has been broadly applied to clinical trials of glioma. However, less is known about implement of interferon-γ (IFN-γ) in glioma. Further investigating the valuable hub molecular of IFN-γ family might provide us a novel guidance for glioma therapy.

Methods

This study carried out an analysis on glioma patients from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) cohorts. The analyses were performed by GraphPad Prism 8 and R language. All the validated experiments were performed three times independently.

Results

We identified IFI30 as the most stable independent prognostic gene among 20 classical IFN-γ stimulated genes (ISGs) in glioma patients. Furthermore, we found that IFI30 highly expressed in malignant subtypes of glioma and associated with chemotherapy response. We also found IFI30 could activate IL6-STAT6 signal pathway to decline the glioma cells' chemotherapy sensitivity by performing experiments. Gene ontology (GO) analysis showed IFI30 associated with enhanced leucocyte mediated immune and inflammatory response. Microenvironment analysis referred that high IFI30 expression accompanied with more infiltration of M2 type macrophages.

Conclusion

IFI30 is involved in the malignant progression and chemotherapy response of glioblastoma, which can be a potential target for treatment in glioblastoma patients.

Glycolysis gene expression profilings screen for prognostic risk signature of hepatocellular carcinoma

Metabolic changes are the markers of cancer and have attracted wide attention in recent years. One of the main metabolic features of tumor cells is the high level of glycolysis, even if there is oxygen. The transformation and preference of metabolic pathways is usually regulated by specific gene expression. The aim of this study is to develop a glycolysis-related risk signature as a biomarker via four common cancer types. Only hepatocellular carcinoma was shown the strong relationship with glycolysis. The mRNA sequencing and chip data of hepatocellular carcinoma, breast invasive carcinoma, renal clear cell carcinoma, colorectal adenocarcinoma were included in the study. Gene set enrichment analysis was performed, profiling three glycolysis-related gene sets, it revealed genes associated with the biological process. Univariate and multivariate Cox proportional regression models were used to screen out prognostic-related gene signature. We identified six mRNAs (DPYSL4, HOMER1, ABCB6, CENPA, CDK1, STMN1) significantly associated with overall survival in the Cox proportional regression model for hepatocellular carcinoma. Based on this gene signature, we were able to divide patients into high-risk and low-risk subgroups. Multivariate Cox regression analysis showed that prognostic power of this six gene signature is independent of clinical variables. Further, we validated this data in our own 55 paired hepatocellular carcinoma and adjacent tissues. The results showed that these proteins were highly expressed in hepatocellular carcinoma tissues compared with adjacent tissue. The survival time of high-risk group was significantly shorter than that of low-risk group, indicating that high-risk group had poor prognosis. We calculated the correlation coefficients between six proteins and found that these six proteins were independent of each other. In conclusions, we developed a glycolysis-related gene signature that could predict survival in hepatocellular carcinoma patients. Our findings provide novel insight to the mechanisms of glycolysis and it is useful for identifying patients with hepatocellular carcinoma with poor prognoses.

CD48 is a key molecule of immunomodulation affecting prognosis in glioma

Purpose: Glioma is a refractory disease associated with immune cell infiltration, and the effectiveness of checkpoint blockade remains suboptimal. As an adhesion and costimulatory molecule, CD48 plays a significant role in immunomodulation. As such, studying CD48 may provide additional understanding of the immune and inflammation response of glioma. Methods: Using R language and GraphPad Prism 7, RNA sequencing data of 946 patients from Chinese Glioma Genome Atlas and The Cancer Genome Atlas cohorts were analyzed. Results: CD48 was highly expressed in the malignant progression of glioma. As an independent risk factor, high-CD48 patients were associated with poor prognosis. CD48 influenced glioma purity and the local immune cell subpopulation. CD48 was closely related to immune function in glioma. Patients with an enhanced immune phenotype, high CD48, were associated with immune suppressive molecules and checkpoints. In addition, CD48 correlated with the immune and inflammatory response. A checkpoint risk score including CD48, SLAMF8 and PD-L1 was used to assess the role of checkpoints. Risk score was particularly high in a malignant subtype of glioma and was an independent predictive indicator of unfavorable outcome. Additionally, age, IDH subtype and MGMT promoter status influenced the predictive significance of checkpoint risk score. Conclusion: CD48 exhibits a crucial role in reduced survival and immunomodulation in glioma. In addition, we found that checkpoints play a greater role in patients older than 40 years old with IDH wild-type and MGMT methylated status. These findings suggest that combining CD48 blockade with PD-L1 may be a promising approach to glioma immunotherapy for specific subpopulations of patients.

Clinicopathological features and prediction values of HDAC1, HDAC2, HDAC3, and HDAC11 in classical Hodgkin lymphoma

Histone deacetylases (HDACs) are involved in multiple physical and pathological processes in classical Hodgkin lymphoma (cHL). The prognostic value of HDACs in cHL patients has not been discussed. The aim of the current study is to investigate the HDAC1, HDAC2, HDAC3, and HDAC11 expressions, and to evaluate the correlation of HDAC1, HDAC2, HDAC3, and HDAC11 expressions with the survival rate in cHL patients. We retrospectively analyzed clinicopathological data of 28 patients who were diagnosed with cHL between August 2002 and March 2010. Immunohistochemistry was used to detect the expression of HDAC1, HDAC2, HDAC3, and HDAC11 in these patients. The results showed that HDAC1, HDAC3, and HDAC11 were expressed at a higher level in Hodgkin Reed-Sternberg cells, whereas HDAC2 was expressed at a lower level in Hodgkin Reed-Sternberg cells. The expression of HDAC2 had a relationship with pathological type (P=0.012). There was also a correlation between the expression of HDAC11 and the erythrocyte sedimentation rate (P=0.054). Other clinicopathological parameters had no significant correlation with the expression of HDAC1, HDAC2, HDAC3, and HDAC11 in terms of survival (P>0.05). The 10-year total survival rate by Cox multivariate analysis, after taking into account all clinical and pathologic factors, showed that bulky disease retained significance (P=0.028). Higher expression of HDAC1 predicted shorter progression-free survival and overall survival (OS) in cHL patients (P<0.05, in both cases), and higher expression of HDAC11 might be correlated with lower OS (P=0.05). The study showed that the expressions of HDAC2 and HDAC11 have a particular relationship with the pathologic subtype. Increased expression of HDAC1 was correlated negatively with progression-free survival and OS, and increased expression of HDAC11 had a borderline relationship with the OS rate in patients with cHL.

Identification of a novel cell cycle-related gene signature predicting survival in patients with gastric cancer

Gastric cancer (GC) is one of the most fatal cancers in the world. Thousands of biomarkers have been explored that might be related to survival and prognosis via database mining. However, the prediction effect of single gene biomarkers is not specific enough. Increasing evidence suggests that gene signatures are emerging as a possible better alternative. We aimed to develop a novel gene signature to improve the prognosis prediction of GC. Using the messenger RNA (mRNA)-mining approach, we performed mRNA expression profiling in a large GC cohort (n = 375) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and we recovered genes related to the G2/M checkpoint, which we identified with a Cox proportional regression model. We identified a set of five genes (MARCKS, CCNF, MAPK14, INCENP, and CHAF1A), which were significantly associated with overall survival (OS) in the test series. Based on this five-gene signature, the test series patients could be classified into high-risk or low-risk subgroups. Multivariate Cox regression analysis indicated that the prognostic power of this five-gene signature was independent of clinical features. In conclusion, we developed a five-gene signature related to the cell cycle that can predict survival for GC. Our findings provide novel insight that is useful for understanding cell cycle mechanisms and for identifying patients with GC with poor prognoses.

Costimulatory checkpoint SLAMF8 is an independent prognosis factor in glioma

AIMS

Immune checkpoint blockade has made breakthroughs in immunotherapy for glioma. However, current immunotherapy has therapeutic benefits only in a subset of patients and accompanied by immune-related side effects. SLAMF8 is a costimulatory molecule that affects the activation of macrophages in inflammation. The study of SLAMF8 may provide new information for immunological research and treatment of glioma.

METHODS

CGGA and TCGA cohorts of 946 patients with RNA sequencing data and full clinical information were analyzed using R language and GraphPad Prism 7.

RESULTS

SLAMF8 was overexpressed along with malignancy progression and was a biomarker of mesenchymal subtype. As an independent prognostic factor, high SLAMF8 conferred reduced overall survival and chemotherapy resistance. SLAMF8 implied lower proportion of cancer cells along with increasing enrichment of monocytic lineage, myeloid dendritic cells. Functional analysis showed higher SLAMF8 indicated activation of antigen processing and presenting and the IFN-γ/TNF/TLR-mediated signaling. Meanwhile, coexpressing with classical checkpoint SLAMF8 aggravated immunosuppression and enhanced inflammation response.

CONCLUSION

Our study highlighted the important role of SLAMF8 in malignancy progression, shortened survival, and immune disorders. Further research on SLAMF8 in immunosuppression and inflammation response to glioma cells could aid immunotherapy for glioma.

Long noncoding RNA LINC00152 is a potential prognostic biomarker in patients with high-grade glioma

AIMS

To investigate the role of LINC00152 in high-grade glioma (HGG).

METHODS

We collected data from the Chinese Glioma Genome Atlas (CGGA) microarray, CGGA RNA sequencing, and GSE16011 datasets to evaluate the expression and prognostic relationship of LINC00152 in patients with HGGs. A knockdown assay was performed to determine the function of LINC00152 in glioma development and progression in vitro and in vivo.

RESULTS

The expression of LINC00152 was increased with glioma grade, especially in the mesenchymal TCGA subtype. LINC00152 was independently associated with poor prognosis, and the overall survival (OS) of the high expression group was shorter than the low expression group (median OS 14.77 vs 9.65 months; P = 0.0216) in the CGGA microarray dataset. The results were validated in the other 2 datasets. Based on the expression of LINC00152, 4288 (2519 positively; 1769 negatively) probes were extracted to perform a biological process analysis using the Database for Annotation, Visualization, and Integrated Discovery. Positively regulated genes were enriched in immune response, apoptotic process, cell adhesion, and regulation of cell proliferation. The clinical and molecular features of HGG patients indicated that patients in the LINC00152 high expression group tended to display the mesenchymal type, older (≥46 years), isocitrate dehydrogenase1 wild-type, O(6)-methylguanine DNA methyltransferase unmethylated, nonchemotherapy, and low karnofsky performance status. Functionally, knockdown of LINC00152 inhibited cell proliferation, migration, and invasion and increased the sensitivity of chemotherapy in vitro.

CONCLUSION

Our results indicate that knockdown of LINC00152 could inhibit tumor growth in vivo. LINC00152 could serve as a potential prognostic biomarker in patients with HGG.

Personalized anticancer therapy selection using molecular landscape topology and thermodynamics

Personalized anticancer therapy requires continuous consolidation of emerging bioinformatics data into meaningful and accurate information streams. The use of novel mathematical and physical approaches, namely topology and thermodynamics can enable merging differing data types for improved accuracy in selecting therapeutic targets. We describe a method that uses chemical thermodynamics and two topology measures to link RNA-seq data from individual patients with academically curated protein-protein interaction networks to select clinically relevant targets for treatment of low-grade glioma (LGG). We show that while these three histologically distinct tumor types (astrocytoma, oligoastrocytoma, and oligodendroglioma) may share potential therapeutic targets, the majority of patients would benefit from more individualized therapies. The method involves computing Gibbs free energy of the protein-protein interaction network and applying a topological filtration on the energy landscape to produce a subnetwork known as persistent homology. We then determine the most likely best target for therapeutic intervention using a topological measure of the network known as Betti number. We describe the algorithm and discuss its application to several patients.

Is the prognostic significance of O6-methylguanine- DNA methyltransferase promoter methylation equally important in glioblastomas of patients from different continents? A systematic review with meta-analysis

BACKGROUND

O6-methylguanine-DNA methyltransferase (MGMT) is an independent predictor of therapeutic response and potential prognosis in patients with glioblastoma multiforme (GBM). However, its significance of clinical prognosis in different continents still needs to be explored.

PATIENTS AND METHODS

To explore the effects of MGMT promoter methylation on both progression-free survival (PFS) and overall survival (OS) among GBM patients from different continents, a systematic review of published studies was conducted.

RESULTS

A total of 5103 patients from 53 studies were involved in the systematic review and the total percentage of MGMT promoter methylation was 45.53%. Of these studies, 16 studies performed univariate analyses and 17 performed multivariate analyses of MGMT promoter methylation on PFS. The pooled hazard ratio (HR) estimated for PFS was 0.55 (95% CI 0.50, 0.60) by univariate analysis and 0.43 (95% CI 0.38, 0.48) by multivariate analysis. The effect of MGMT promoter methylation on OS was explored in 30 studies by univariate analysis and in 30 studies by multivariate analysis. The combined HR was 0.48 (95% CI 0.44, 0.52) and 0.42 (95% CI 0.38, 0.45), respectively.

CONCLUSION

In each subgroup divided by areas, the prognostic significance still remained highly significant. The proportion of methylation in each group was in inverse proportion to the corresponding HR in the univariate and multivariate analyses of PFS. However, from the perspective of OS, compared with data from Europe and the US, higher methylation rates in Asia did not bring better returns.

Tumor Purity as an Underlying Key Factor in Glioma

Purpose: Glioma tissues consist of not only glioma cells but also glioma-associated nontumor cells, such as stromal cells and immune cells. These nontumor cells dilute the purity of glioma cells and play important roles in glioma biology. Currently, the implications of variation in glioma purity are not sufficiently clarified.Experimental Design: Here, tumor purity was inferred for 2,249 gliomas and 29 normal brain tissues from 5 cohorts. Based on the transcriptomic profiling method, we classified CGGA and TCGA-RNAseq cohorts as the RNAseq set for discovery. Cases from TCGA-microarray, REMBRANDT, and GSE16011 cohorts were grouped as a microarray set for validation. Tissues from the CGGA cohort were reviewed for histopathologic validation.Results: We found that glioma purity was highly associated with major clinical and molecular features. Low purity cases were more likely to be diagnosed as malignant entities and independently correlated with reduced survival time. Integrating glioma purity into prognostic nomogram significantly improved the predictive validity. Moreover, most recognized prognostic indicators were no longer significantly effective under different purity conditions. These results highlighted the clinical importance of glioma purity. Further analyses found distinct genomic patterns associated with glioma purity. Low purity cases were distinguished by enhanced immune phenotypes. Macrophages, microglia, and neutrophils were mutually associated and enriched in low purity gliomas, whereas only macrophages and neutrophils served as robust indicators for poor prognosis.Conclusions: Glioma purity and relevant nontumor cells within microenvironment confer important clinical, genomic, and biological implications, which should be fully valued for precise classification and clinical prediction. Clin Cancer Res; 23(20); 6279-91. ©2017 AACR.

The multifaceted influence of histone deacetylases on DNA damage signalling and DNA repair

Histone/protein deacetylases play multiple roles in regulating gene expression and protein activation and stability. Their deregulation during cancer initiation and progression cause resistance to therapy. Here, we review the role of histone deacetylases (HDACs) and the NAD+ dependent sirtuins (SIRTs) in the DNA damage response (DDR). These lysine deacetylases contribute to DNA repair by base excision repair (BER), nucleotide excision repair (NER), mismatch repair (MMR), non-homologous end joining (NHEJ), homologous recombination (HR) and interstrand crosslink (ICL) repair. Furthermore, we discuss possible mechanisms whereby these histone/protein deacetylases facilitate the switch between DNA double-strand break (DSB) repair pathways, how SIRTs play a central role in the crosstalk between DNA repair and cell death pathways due to their dependence on NAD+, and the influence of small molecule HDAC inhibitors (HDACi) on cancer cell resistance to genotoxin based therapies. Throughout the review, we endeavor to identify the specific HDAC targeted by HDACi leading to therapy sensitization.

Gene Expression Profiling Stratifies IDH1-Mutant Glioma with Distinct Prognoses

Isocitrate dehydrogenase (IDH)1 mutation is one of the most important genetic aberrations in glioma. Even several genetic events have refined its prognostic value, the genome-wide expression alteration has not been systematically profiled. In this work, RNA-seq expression data from 310 patients in the Chinese Glioma Genome Atlas database were included as training set, while another 297 patients with microarray data were used as internal validation set. An independent cohort of GSE16011 (n = 205) constituted an external validation set. Approximately one fifth of the genes were differentially expressed in LGG according to IDH1 mutation status, yielding distinct gene expression profiles. A six-gene risk signature was established for IDH1-mutant LGG to distinguish low- from high-risk cases, which had distinct prognoses. The six-gene signature was an independent prognostic factor for IDH1-mutant LGG and had superior predictive value as compared to traditional clinicopathologic factors. Moreover, we depicted the differential expression pattern in GBM attributing to various IDH1 status, which was similar to that of LGG. It suggested that the effect of IDH1 mutation is conserved across histological classifications. The six-gene signature had equal prognostic value for IDH1-mutant GBM. By combining glioma grade, IDH1 status, and the six-gene signature, all glioma patients could be classified into six subgroups. These six subgroups could be further summarized into three sets with distinct prognosis. Taken together, a gene expression profile associated with IDH1 status was identified in LGG and GBM; a risk signature based on six genes was developed with equal prognostic value for IDH1-mutant LGG and GBM. When combined with clinicopathologic factors, the six-gene signature is a tool that enables precise risk stratification and can improve clinical management.

A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients

Although O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation status is an important marker for glioblastoma multiforme (GBM), there is considerable variability in the clinical outcome of patients with similar methylation profiles. The present study aimed to refine the prognostic and predictive value of MGMT promoter status in GBM by identifying a micro (mi)RNA risk signature. Data from The Cancer Genome Atlas was used for this study, with MGMT promoter-methylated samples randomly divided into training and internal validation sets. Data from The Chinese Glioma Genome Atlas was used for independent validation. A five miRNA-based risk signature was established for MGMT promoter-methylated GBM to distinguish cases as high- or low-risk with distinct prognoses, which was confirmed using internal and external validation sets. Importantly, the prognostic value of the signature was significant in different cohorts stratified by clinicopathologic factors and alkylating chemotherapy, and a multivariate Cox analysis found it to be an independent prognostic marker along with age and chemotherapy. Based on these three factors, we developed a quantitative model with greater accuracy for predicting the 1-year survival of patients with MGMT promoter-methylated GBM. These results indicate that the five-miRNA signature is an independent risk predictor for GBM with MGMT promoter methylation and can be used to identify patients at high risk of unfavorable outcome and resistant to alkylating chemotherapy, underscoring its potential for personalized GBM management.

DNA methylation in adult diffuse gliomas

Adult diffuse gliomas account for the majority of primary malignant brain tumours, and are in most cases lethal. Current therapies are often only marginally effective, and improved options will almost certainly benefit from further insight into the various processes contributing to gliomagenesis and pathology. While molecular characterization of these tumours classifies them on the basis of genetic alterations and chromosomal abnormalities, DNA methylation patterns are increasingly understood to play a role in glioma pathogenesis. Indeed, a subset of gliomas associated with improved survival is characterized by the glioma CpG island methylator phenotype (G-CIMP), which can be induced by the expression of mutant isocitrate dehydrogenase (IDH1/2). Aberrant methylation of particular genes or regulatory elements, within the context of G-CIMP-positive and/or negative tumours, has also been shown to be associated with differential survival. In this review, we provide an overview of the current knowledge regarding the role of DNA methylation in adult diffuse gliomas. In particular, we discuss IDH mutations and G-CIMP, MGMT promoter methylation, DNA methylation-mediated microRNA regulation and aberrant methylation of specific genes or groups of genes.

Association between small heat shock protein B11 and the prognostic value of MGMT promoter methylation in patients with high-grade glioma

OBJECT This study investigated the role and prognostic value of heat shock proteins (HSPs) in glioma. METHODS Data from 3 large databases of glioma samples (Chinese Glioma Genome Atlas, Repository for Molecular Brain Neoplasia Data, and GSE16011), which contained whole-genome messenger RNA microarray expression data and patients' clinical data, were analyzed. Immunohistochemical analysis was performed to validate protein expression in another set of 50 glioma specimens. RESULTS Of 28 HSPs, 11 were overexpressed in high-grade glioma (HGG) compared with low-grade glioma. A univariate Cox analysis revealed that HSPB11 has significant prognostic value for each glioma grade, which was validated by a Kaplan-Meier survival analysis. HSPB11 expression was associated with poor prognosis and was independently correlated with overall survival (OS) in HGG. This study further explored the combined role of HSPB11 and other molecular markers in HGG, such as isocitrate dehydrogenase 1 (IDH1) mutation and O(6)-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. HSPB11 expression was able to refine the prognostic value of IDH1 mutation in patients with HGG. However, when combined with MGMT promoter methylation status, among patients with a methylated MGMT promoter, those with lower levels of HSPB11 expression had longer OS and progression-free survival than patients with higher levels of HSPB11 expression or with an unmethylated MGMT promoter. Moreover, within the MGMT promoter methylation group, patients with low levels of HSPB11 expression were more sensitive to combined radiochemotherapy than those with high levels of HSPB11 expression, which may explain why some patients with HGG with a methylated MGMT promoter show tolerance to radiochemotherapy. CONCLUSIONS HSPB11 was identified as a novel prognostic marker in patients with HGG. Together with MGMT promoter methylation status, HSPB11 expression can predict outcome for patients with HGG and identify those who would most benefit from combined radiochemotherapy.

Genetic and epigenetic characterization of low-grade gliomas reveals frequent methylation of the MLH3 gene

Diffuse astrocytomas and oligodendrogliomas (WHO grade II) are the most common histological subtypes of low-grade gliomas (LGGs). Several molecular and epigenetic markers have been identified that predict tumor progression. Our aim was in detail to investigate the genetic and epigenetic background of LGGs and to identify new markers that might play a role in tumor behavior. Twenty-three patients with oligodendroglioma or oligoastrocytoma (LGO) and 22 patients with diffuse astrocytoma (LGA) were investigated using several molecular-cytogenetic and molecular methods to assess their copy number variations, mutational status and level of promoter methylation. The most frequent findings were a 1p/19q codeletion in 83% of LGO and copy-neutral loss of heterozygosity (CN-LOH) of 17p in 72% of LGA. Somatic mutations in the isocitrate dehydrogenase 1 or 2 (IDH1/IDH2) genes were detected in 96% of LGO and 91% of LGA. The O-6-methylguanine-DNA-methyltransferase (MGMT) promoter was methylated in 83% of LGO and 59% of LGA. MutL homolog 3 (MLH3) promoter methylation was observed in 61% of LGO and 27% of LGA. Methylation of the MGMT promoter, 1p/19q codeletion, mutated IDH1, and CN-LOH of 17p were the most frequent genetic aberrations in LGGs. The findings were more diverse in LGA than in LGO. To the best of our knowledge, this is the first time description of methylation of the MLH3 gene promoter in LGGs. Further studies are required to determine the role of the methylated MLH3 promoter and the other aberrations detected.

Regulation of expression of O6-methylguanine-DNA methyltransferase and the treatment of glioblastoma (Review)

O-6-methylguanine-DNA methyltransferase (MGMT) is an abundantly expressed nuclear protein dealkylating O⁶-methylguanine (O⁶-MG) DNA residue, thus correcting the mismatches of O⁶-MG with a thymine residue during DNA replication. The dealkylating effect of MGMT is relevant not only in repairing DNA mismatches produced by environmental alkylating agents promoting tumor pathogenesis, but also when alkylating molecules are applied in the chemotherapy of different cancers, including glioma, the most common primary tumor of the central nervous system. Elevated MGMT gene expression is known to confer resistance to the treatment with the alkylating drug temozolomide in patients affected by gliomas and, on the contrary, methylation of MGMT gene promoter, which causes reduction of MGMT protein expression, is known to predict a favourable response to temozolomide. Thus, detecting expression levels of MGMT gene is crucial to indicate the option of alkylating agents or to select patients directly for a second line targeted therapy. Further study is required to gain insights into MGMT expression regulation, that has attracted growing interest recently in MGMT promoter methylation, histone acetylation and microRNAs expression. The review will focus on the epigenetic regulation of MGMT gene, with translational applications to the identification of biomarkers predicting response to therapy and prognosis.