Comprehensive Analysis of HDAC Family Identifies HDAC1 as a Prognostic and Immune Infiltration Indicator and HDAC1-Related Signature for Prognosis in Glioma

HAS2 facilitates glioma cell malignancy and suppresses ferroptosis in an FZD7-dependent manner

Glioma is the most common malignant tumor in the central nervous system, and it is crucial to uncover the factors that influence prognosis. In this study, we utilized Mfuzz to identify a gene set that showed a negative correlation with overall survival in patients with glioma. Gene Ontology (GO) enrichment analyses were then undertaken to gain insights into the functional characteristics and pathways associated with these genes. The expression distribution of Hyaluronan Synthase 2 (HAS2) was explored across multiple datasets, revealing its expression patterns. In vitro and in vivo experiments were carried out through gene knockdown and overexpression to validate the functionality of HAS2. Potential upstream transcription factors of HAS2 were predicted using transcriptional regulatory databases, and these predictions were experimentally validated using ChIP-PCR and dual-luciferase reporter gene assays. The results showed that elevated expression of HAS2 in glioma indicates poor prognosis. HAS2 was found to play a role in activating an antiferroptosis pathway in glioma cells. Inhibiting HAS2 significantly increased cellular sensitivity to ferroptosis-inducing agents. Finally, we determined that the oncogenic effect of HAS2 is mediated by the key receptor of the WNT pathway, FZD7.

A pancancer analysis of histone deacetylase 3 in human tumors

Background

Histone deacetylase 3 (HDAC3) is known to be an important role in various kinds of cancer, but its effect has not been examined on the pancancer level. Thus, a systematic pancancer analysis was conducted to explore its potential role in pancancer diagnosis, prognosis, and immune correlation research.

Methods

We used a series of databases including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) Project, The University of Alabama at Birmingham Cancer data analysis portal (UALCAN), Tumor Immune Estimation Resource (TIMER), and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), among others, to analyze the relationship between the expression of HDAC3 and the diagnosis and prognosis of cancer, the tumor microenvironment (TME), immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) system using various bioinformatics methods. Downstream pathways of HDAC3 were identified by gene set enrichment analysis (GSEA). Furthermore, the protein expression of HDAC3 in tumor tissues and normal tissues of 17 patients with gliomas was analyzed via western blotting.

Results

The expression of HDAC3 changed in most types of tumors, which was closely related to most tumor diagnoses and negatively related to some patients' overall survival (OS) and recurrence-free survival (RFS). The pan-cancer analysis demonstrated that it was tightly correlated to DNA methylation and RNA methylation modifications and associated with TMB and MSI. The expression level of HDAC3 was positively correlated with many immune checkpoint molecules and regulators and positively associated with the infiltration levels of immune cells in the TME in most tumor types. Furthermore, enrichment analysis revealed that transcriptional misregulation in cancer and RNA splicing functions were involved in the functional mechanism of HDAC3-related genes. Experimental research showed that the protein expression of HDAC3 was elevated in tumor tissues of patients with glioma.

Conclusions

Through our comprehensive bioinformatics analysis, we evaluated the role of HDAC3 in pancancer, and our findings suggest that it may be an indicator for some cancer diagnoses and influence immune balance.

Emerging trends in post-translational modification: Shedding light on Glioblastoma multiforme

Recent multi-omics studies, including proteomics, transcriptomics, genomics, and metabolomics have revealed the critical role of post-translational modifications (PTMs) in the progression and pathogenesis of Glioblastoma multiforme (GBM). Further, PTMs alter the oncogenic signaling events and offer a novel avenue in GBM therapeutics research through PTM enzymes as potential biomarkers for drug targeting. In addition, PTMs are critical regulators of chromatin architecture, gene expression, and tumor microenvironment (TME), that play a crucial function in tumorigenesis. Moreover, the implementation of artificial intelligence and machine learning algorithms enhances GBM therapeutics research through the identification of novel PTM enzymes and residues. Herein, we briefly explain the mechanism of protein modifications in GBM etiology, and in altering the biologics of GBM cells through chromatin remodeling, modulation of the TME, and signaling pathways. In addition, we highlighted the importance of PTM enzymes as therapeutic biomarkers and the role of artificial intelligence and machine learning in protein PTM prediction.

Histone deacetylase-mediated tumor microenvironment characteristics and synergistic immunotherapy in gastric cancer

Background: Studies have shown that the expression of histone deacetylases (HDACs) is significantly related to the tumor microenvironment (TME) in gastric cancer. However, the expression of a single molecule or several molecules does not accurately reflect the TME characteristics or guide immunotherapy in gastric cancer. Methods: We constructed an HDAC score (HDS) based on the expression level of HDACs. The single-cell transcriptome was used to analyze the underlying factors contributing to differences in immune infiltration between patients with a high and low HDS. In vitro and in vivo experiments validated the strategy of transforming cold tumors into hot tumors to guide immunotherapy. Results: According to the expression characteristics of HDACs, we constructed an HDS model to characterize the TME. We found that patients with a high HDS had stronger immunogenicity and could benefit more from immunotherapy than those with a low score. The AUC value of the HDS combined with the combined positive score (CPS)for predicting the efficacy of immunotherapy was as high as 0.96. By single-cell and paired bulk transcriptome sequencing analysis, we found that the infiltration levels of CD4+ T cells, CD8+ T cells and NK cells were significantly decreased in the low HDS group, which may be induced by MYH11+ fibroblasts, CD234+ endothelial cells and CCL17+ pDCs via the MIF signaling pathway. Inhibition of the MIF signaling pathway was confirmed to potentially enhance immune infiltration. In addition, our analysis revealed that GPX4 inhibitors might be effective for patients with a low HDS. GPX4 knockout significantly inhibited PD-L1 expression and promoted the infiltration and activation of CD8+ T cells. Conclusion: We constructed an HDS model based on the HDAC expression characteristics of gastric cancer. This model was used to evaluate TME characteristics and predict immunotherapy efficacy. Inhibition of the MIF signaling pathway in the TME and GPX4 expression in tumor cells may be an important strategy for cold tumor synergistic immunotherapy for gastric cancer.

Integrating Multi-Omics Analysis for Enhanced Diagnosis and Treatment of Glioblastoma: A Comprehensive Data-Driven Approach

The most aggressive primary malignant brain tumor in adults is glioblastoma (GBM), which has poor overall survival (OS). There is a high relapse rate among patients with GBM despite maximally safe surgery, radiation therapy, temozolomide (TMZ), and aggressive treatment. Hence, there is an urgent and unmet clinical need for new approaches to managing GBM. The current study identified modules (MYC, EGFR, PIK3CA, SUZ12, and SPRK2) involved in GBM disease through the NeDRex plugin. Furthermore, hub genes were identified in a comprehensive interaction network containing 7560 proteins related to GBM disease and 3860 proteins associated with signaling pathways involved in GBM. By integrating the results of the analyses mentioned above and again performing centrality analysis, eleven key genes involved in GBM disease were identified. ProteomicsDB and Gliovis databases were used for determining the gene expression in normal and tumor brain tissue. The NetworkAnalyst and the mGWAS-Explorer tools identified miRNAs, SNPs, and metabolites associated with these 11 genes. Moreover, a literature review of recent studies revealed other lists of metabolites related to GBM disease. The enrichment analysis of identified genes, miRNAs, and metabolites associated with GBM disease was performed using ExpressAnalyst, miEAA, and MetaboAnalyst tools. Further investigation of metabolite roles in GBM was performed using pathway, joint pathway, and network analyses. The results of this study allowed us to identify 11 genes (UBC, HDAC1, CTNNB1, TRIM28, CSNK2A1, RBBP4, TP53, APP, DAB1, PINK1, and RELN), five miRNAs (hsa-mir-221-3p, hsa-mir-30a-5p, hsa-mir-15a-5p, hsa-mir-130a-3p, and hsa-let-7b-5p), six metabolites (HDL, N6-acetyl-L-lysine, cholesterol, formate, N, N-dimethylglycine/xylose, and X2. piperidinone) and 15 distinct signaling pathways that play an indispensable role in GBM disease development. The identified top genes, miRNAs, and metabolite signatures can be targeted to establish early diagnostic methods and plan personalized GBM treatment strategies.

Expression, Significance, and Correlation of Histone Deacetylase 1/RE-1 Silencing Transcription Factor and Neuronal Markers in Glioma

BACKGROUND

Inducing the differentiation of glioma cells into neuron-like cells may be an effective strategy to combat glioma. The histone deacetylase 1/RE-1 silencing transcription factor (HDAC1/REST) complex regulates the expression of multiple neuronal genes. In this study, we analyzed the presence and significance of this regulatory effect in glioma based on bioinformatics methods.

METHODS

The Human Protein Atlas database was used to obtain immunohistochemical staining images. The Gene Expression Profiling Interactive Analysis and Chinese Glioma Genome Atlas databases were used to analyze the expression of HDAC1/REST and neuronal markers in glioma, their effects on survival, and the association between HDAC1/REST and the expression of neuronal markers and stem cell markers. The differentially expressed genes between the high and low HDAC1/REST groups were explored. The Database for Annotation, Visualization and Integrated Discovery database was used for gene ontology and kyoto encyclopedia of genes and genomes pathway enrichment analysis.

RESULTS

The results showed that the expression of HDAC1 and REST increased with the grade of glioma, while the expression of neuronal markers decreased with the grade of glioma. High expression of HDAC1/REST and low expression of neuronal markers were associated with poor prognosis. HDAC1/REST expression was negatively correlated with the expression of neuronal markers, and positively correlated with the expression of neural stem cell markers. The genes up-regulated in the high HDAC1/REST group were mainly related to extracellular matrix and inflammation, and the down-regulated genes were mainly related to synapsis.

CONCLUSIONS

This study suggested that HDAC1/REST may be involved in maintaining the malignant phenotype of glioma cells and the stem cell status of glioma stem cells by inhibiting the expression of neuronal markers, which promote the progression of glioma.

Systematic analysis identifies REST as an oncogenic and immunological biomarker in glioma

The repressor element 1 silencing transcription factor (REST) has been proposed to function as a transcription factor to silence gene transcription by binding to repressor element 1 (RE1), a highly conserved DNA motif. The functions of REST in various tumors have been studied, but its role and correlation with immune cell infiltration remains uncertain in gliomas. REST expression was analyzed in datasets of The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) and validated by the Gene Expression Omnibus and Human Protein Atlas databases. The clinical prognosis of REST was evaluated by clinical survival data of TCGA cohort and validated by Chinese Glioma Genome Atlas cohort. MicroRNAs (miRNAs) contributing to REST overexpression in glioma were identified by a combination of a series of in silico analyses, including expression analysis, correlation analysis, and survival analysis. The correlations between immune cell infiltration level and REST expression were analyzed by TIMER2 and GEPIA2 tools. Enrichment analysis of REST was performed using STRING and Metascape tools. The expression and function of predicted upstream miRNAs at REST and their association with glioma malignancy and migration were also confirmed in glioma cell lines. REST was highly expressed and associated with poorer overall survival and disease-specific survival in glioma and some other tumors. MiR-105-5p and miR-9-5p were identified as the most potential upstream miRNAs of REST in glioma patient cohort and experiments in vitro. REST expression was positively correlated with infiltration of immune cells and the expression of immune checkpoints such as PD1/PD-L1 and CTLA-4 in glioma. Furthermore, histone deacetylase 1 (HDAC1) was a potential REST-related gene in glioma. Enrichment analysis of REST found chromatin organization and histone modification were the most significant enriched terms, and Hedgehog-Gli pathway might be involved in the effect of REST on the pathogenesis of glioma. Our study suggests REST to be an oncogenic gene and the biomarker of poor prognosis in glioma. High REST expression might affect the tumor microenvironment of glioma. More basic experiments and large clinical trials aimed at the carcinogenetic study of REST in glioma will be needed in the future.

Impact of epigenetic reprogramming on antitumor immune responses in glioma

Epigenetic remodeling is a molecular hallmark of gliomas, and it has been identified as a key mediator of glioma progression. Epigenetic dysregulation contributes to gliomagenesis, tumor progression, and responses to immunotherapies, as well as determining clinical features. This epigenetic remodeling includes changes in histone modifications, chromatin structure, and DNA methylation, all of which are driven by mutations in genes such as histone 3 genes (H3C1 and H3F3A), isocitrate dehydrogenase 1/2 (IDH1/2), α-thalassemia/mental retardation, X-linked (ATRX), and additional chromatin remodelers. Although much of the initial research primarily identified how the epigenetic aberrations impacted glioma progression by solely examining the glioma cells, recent studies have aimed at establishing the role of epigenetic alterations in shaping the tumor microenvironment (TME). In this review, we discuss the mechanisms by which these epigenetic phenomena in glioma remodel the TME and how current therapies targeting epigenetic dysregulation affect the glioma immune response and therapeutic outcomes. Understanding the link between epigenetic remodeling and the glioma TME provides insights into the implementation of epigenetic-targeting therapies to improve the antitumor immune response.

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Background: Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma.

Methods: RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. Via consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores.

Results: We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. SPP1 was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells.

Conclusion: In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

Comprehensive analysis of histone deacetylases genes in the prognosis and immune infiltration of glioma patients

The occurrence and development of tumors are closely related to histone deacetylases (HDACs). However, their relationship with the overall biology and prognosis of glioma is still unknown. In the present study, we developed and validated a prognostic model for glioma based on HDAC genes. Glioma patients can be divided into two subclasses based on eleven HDAC genes, and patients from the two subclasses had markedly different survival outcomes. Then, using six HDAC genes (HDAC1, HDAC3, HDAC4, HDAC5, HDAC7, and HDAC9), we established a prognostic model for glioma patients, and this prognostic model was validated in an independent cohort. Furthermore, the calculated risk score from six HDACA genes expression was found to be an independent prognostic factor that could predict the five-year overall survival of glioma patients well. High-risk patients have changes in multiple complex functions and molecular signaling pathways, and the gene alterations of high- and low-risk patients were significantly different. We also found that the different survival outcomes of high- and low-risk patients could be related to the differences in immune filtration levels and the tumor microenvironment. Subsequently, we identified several small molecular compounds that could be favorable for glioma patient treatment. Finally, the expression levels of HDAC genes from the prognostic model were validated in glioma and nontumor tissue samples. Our results revealed the clinical utility and potential molecular mechanisms of HDAC genes in glioma. A model based on six HDAC genes can predict the overall survival of glioma patients well, and these genes are potential therapeutic targets.

Histone deacetylase (HDAC) 11 inhibits matrix metalloproteinase (MMP) 3 expression to suppress colorectal cancer metastasis

Emerging evidence has implicated invasion and metastasis are the major common reason of treatment failure and the leading cause of death in colorectal cancer (CRC). Many members of the HDAC family have been reported to be key factors in the genesis and progression of cancer. Until now, few research focused on the actual expression patterns of HDAC11 in most malignancies. In the current study, we found that the expression of HDAC11 is decreased in mouse colitis tissues and colitis-associated cancer (CAC) tissue compared with normal colon tissue. Clinically HDAC11 expression is significantly lower in colorectal cancer tissues of patients and correlated with lymph node metastasis. Additionally, HDAC11 is downregulated in the relative high metastatic potential colorectal cancer cells. We also found HDAC11 inhibits the migration and invasion of colorectal cancer cell by downregulating Mmp3 expression. At the molecular level, the expression of HDAC11 inversely correlated with the level of histone H3K9 and H3K14 acetylation. In addition, analysis of chromatin-protein association by ChIP-qPCR demonstrated that the level of H3K9 acetylation correlated with the upregulation of Mmp3. Through a better understanding of this previously unknown role of HDAC11 in migration and invasion of colorectal cancer, HDAC11 may become a novel candidate for developing rational therapeutic strategies.

Identification of a novel histone phosphorylation prognostic signature in hepatocellular carcinoma based on bulk and single-cell RNA sequencing

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of death in the world, characterized by high morbidity, poor prognosis and high mortality. Histone modifications regulate intracellular gene expression at the post-transcriptional level, and disturbances in the regulatory pattern of histone modifications at individual locus or across the genome can lead to tumorigenesis of HCC. In this study, we constructed a prognosis-related histone phosphorylation regulated (HPR) genes signature and elucidated whether HPR genes can predict overall survival in HCC patients.

METHODS

Differentially expressed genes were screened using TCGA, ICGC and GEO databases, and a new risk signature was constructed by univariate Cox regression and Lasso regression analysis. Predictive nomograms were established by multivariate Cox regression of risk scores and clinical parameters, calibration curve and decision curve analysis were used to evaluate the models. The ssGSEA methods were used to determine the effect of risk scores on the tumor immune microenvironment. Data for HCC single-cell RNA sequencing (scRNA-seq) have been downloaded from Gene Expression Omnibus (GEO) to understand the role of HPR genes in tumorigenesis.

RESULTS

Our analyses of nine HPR genes provided prognostic insights. Overall survival in the low-risk and high-risk groups was statistically higher, respectively (P<0.001). Cox regression analysis revealed that the risk score is a significant predictor of HCC outcomes (HR=2. 2.62, 95%CI: 1.248-5.514, P=0.011). In addition, a nomogram combining risk scores with TNM stages was constructed and tested from calibration curves and decision curves (AUC=0.780). MHC-class-I genes, iDCs, Macrophages, Tfh, Treg, Th2 were overexpressed in the high-risk group.

CONCLUSION

HPR genes risk score is closely related to the prognosis of HCC, tumor immune process and tumor cell progression.

High-dose dexamethasone injection disordered metabolism and multiple protein kinases expression in the mouse kidney

Glucocorticoids (GCs) have been widely used in clinical treatment as anti-inflammatory, anti-shock and immunosuppressive medicines. However, the effect of excessive GCs on immune response and metabolism of kidney remains unclear. Here, we profiled the gene expression of kidney from mice with high-dose dexamethasone (DEX) treatment. A total of 1193 differentially expressed genes (DEGs) were screened in DEX treatment group compared with the saline group, including 715 down- regulated and 478 up-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of these DEGs showed extracellular matrix (ECM)-receptor interaction, cell adhesion molecules signaling pathway were significantly enriched, and that the vast majority of DEGs were involved in monocarboxylic acid metabolism, leukocyte cell-cell adhesion and fatty acid metabolism. Gene set enrichment analysis (GSEA) revealed that DEGs were strongly associated with immune-response and cell adhesion gene sets, such as Fc γ R-mediated phagocytosis, leukocyte transendothelial migration, T-cell receptor signaling pathway, cell adhesion, ECM-receptor interaction and focal adhesion-associated pathways. KEGG pathway analysis of differentially expressed kinases (DEKs) showed T-cell receptor and forkhead box class O signaling pathway were enriched. Furthermore, we found multiple protein kinases expression were dysregulated greatly after dexamethasone treatment, including classical effector of GCs stimulation-serum and GC-regulated kinase. These protein kinases are involved in multiple signaling pathways in mice kidney, such as mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/Akt signaling pathway. We profiled the gene expression of the kidney from high-dose dexamethasone-treated mice and provided important information for further study the mechanism of side effects of GCs in clinical therapy.

PODNL1 Methylation Serves as a Prognostic Biomarker and Associates with Immune Cell Infiltration and Immune Checkpoint Blockade Response in Lower-Grade Glioma

Lower-grade glioma (LGG) is a diffuse infiltrative tumor of the central nervous system, which lacks targeted therapy. We investigated the role of Podocan-like 1 (PODNL1) methylation in LGG clinical outcomes using the TCGA-LGG transcriptomics dataset. We identified four PODNL1 CpG sites, cg07425555, cg26969888, cg18547299, and cg24354933, which were associated with unfavorable overall survival (OS) and disease-free survival (DFS) in univariate and multivariate analysis after adjusting for age, gender, tumor-grade, and IDH1-mutation. In multivariate analysis, the OS and DFS hazard ratios ranged from 0.44 to 0.58 (p < 0.001) and 0.62 to 0.72 (p < 0.001), respectively, for the four PODNL1 CpGs. Enrichment analysis of differential gene and protein expression and analysis of 24 infiltrating immune cell types showed significantly increased infiltration in LGGs and its histological subtypes with low-methylation levels of the PODNL1 CpGs. High PODNL1 expression and low-methylation subgroups of the PODNL1 CpG sites were associated with significantly increased PD-L1, PD-1, and CTLA4 expressions. PODNL1 methylation may thus be a potential indicator of immune checkpoint blockade response, and serve as a biomarker for determining prognosis and immune subtypes in LGG.