Identification of purity and prognosis-related gene signature by network analysis and survival analysis in brain lower grade glioma.

Tumour microenvironment of brain lower grade glioma (LGG) consists of non-tumour cells including stromal cells and immune cells mainly. These non-tumour cells dilute the purity of LGG and play pivotal roles in tumour growth and development, thereby affecting patient prognosis. Tumour purity is also associated with molecular subtypes of LGG. In this study, we discovered the most relevant module to purity by weighted gene co-expression network analysis (WGCNA) and afterwards performed consensus network analysis and survival analysis to filter 61 significant genes related to both purity and prognosis. In turn, we built a simplified model based on the calculation of purity score, and consensus measurement of purity estimation (CPE), with a satisfactory predictive performance by random forest regression. HLA-E, MSN, GNG-5, MYL12A, ITGB4, PDPN, AGTRAP, S100A4, PLSCR1, VAMP5 were selected as the most relevant genes correlating to both purity and prognosis. The risk score model based on the 10 genes could moderately predict patients' overall survival. These 10 genes, respectively, were positively correlated positively to immunosuppressive cells like macrophage M2, but negatively correlated to patient prognosis, which may explain partially the poor prognosis with low-purity group.

Multi-dimensional omics characterization in glioblastoma identifies the purity-associated pattern and prognostic gene signatures.

BACKGROUND: The presence of tumor-associated stroma and tumor-infiltrated immune cells have been largely reported across glioblastomas. Tumor purity, defined as the proportion of tumor cells in the tumor, was associated with the genomic and clinicopathologic features of the tumor and may alter the interpretation of glioblastoma biology. METHODS: We use an integrative approach to infer tumor purity based on multi-omic data and comprehensively evaluate the impact of tumor purity on glioblastoma (GBM) prognosis, genomic profiling, and the immune microenvironment in the Cancer Genome Atlas Consortium (TCGA) cohort. RESULTS: We found that low tumor purity was significantly associated with reduced survival time. Additionally, we established a purity-relevant 5-gene signature that was an independent prognostic biomarker and validated it in the TCGA, CGGA and GSE4412 cohort. Moreover, we correlated tumor purity with genomic characteristics and tumor microenvironment. We identified that gamma delta T cells in glioblastoma microenvironment were positively correlated with purity and served as a marker for favorable prognosis, which was validated in both TCGA and CGGA dataset. CONCLUSIONS: We observe the potential confounding effects of tumor purity on GBM clinical and molecular information interpretation. GBM microenvironment could be purity-dependent, which provides new insights into the clinical implications of glioblastoma.

Glioblastoma vaccines: past, present, and opportunities.

Glioblastoma (GBM) is one of the most lethal central nervous systems (CNS) tumours in adults. As supplements to standard of care (SOC), various immunotherapies improve the therapeutic effect in other cancers. Among them, tumour vaccines can serve as complementary monotherapy or boost the clinical efficacy with other immunotherapies, such as immune checkpoint blockade (ICB) and chimeric antigen receptor T cells (CAR-T) therapy. Previous studies in GBM therapeutic vaccines have suggested that few neoantigens could be targeted in GBM due to low mutation burden, and single-peptide therapeutic vaccination had limited efficacy in tumour control as monotherapy. Combining diverse antigens, including neoantigens, tumour-associated antigens (TAAs), and pathogen-derived antigens, and optimizing vaccine design or vaccination strategy may help with clinical efficacy improvement. In this review, we discussed current GBM therapeutic vaccine platforms, evaluated and potential antigenic targets, current challenges, and perspective opportunities for efficacy improvement.

ImmunoPET imaging of TIGIT in the glioma microenvironment.

Glioblastoma (GBM) is the most common primary malignant brain tumor. Currently, there are few effective treatment options for GBM beyond surgery and chemo-radiation, and even with these interventions, median patient survival remains poor. While immune checkpoint inhibitors (ICIs) have demonstrated therapeutic efficacy against non-central nervous system cancers, ICI trials for GBM have typically had poor outcomes. TIGIT is an immune checkpoint receptor that is expressed on activated T-cells and has a role in the suppression of T-cell and Natural Killer (NK) cell function. As TIGIT expression is reported as both prognostic and a biomarker for anti-TIGIT therapy, we constructed a molecular imaging agent, [89Zr]Zr-DFO-anti-TIGIT (89Zr-αTIGIT), to visualize TIGIT in preclinical GBM by immunoPET imaging. PET imaging and biodistribution analysis of 89Zr-αTIGIT demonstrated uptake in the tumor microenvironment of GBM-bearing mice. Blocking antibody and irrelevant antibody tracer studies demonstrated specificity of 89Zr-αTIGIT with significance at a late time point post-tracer injection. However, the magnitude of 89Zr-αTIGIT uptake in tumor, relative to the IgG tracer was minimal. These findings highlight the features and limitations of using 89Zr-αTIGIT to visualize TIGIT in the GBM microenvironment.

Intracranial pressure monitoring in neurosurgery: the present situation and prospects.

Intracranial pressure (ICP) is one of the most important indexes in neurosurgery. It is essential for doctors to determine the numeric value and changes of ICP, whether before or after an operation. Although external ventricular drainage (EVD) is the gold standard for monitoring ICP, more and more novel monitoring methods are being applied clinically.Invasive wired ICP monitoring is still the most commonly used in practice. Meanwhile, with the rise and development of various novel technologies, non-invasive types and invasive wireless types are gradually being used clinically or in the testing phase, as a complimentary approach of ICP management. By choosing appropriate monitoring methods, clinical neurosurgeons are able to obtain ICP values safely and effectively under particular conditions.This article introduces diverse monitoring methods and compares the advantages and disadvantages of different monitoring methods. Moreover, this review may enable clinical neurosurgeons to have a broader view of ICP monitoring.

Immuno-PET Imaging of CD69 Visualizes T-Cell Activation and Predicts Survival Following Immunotherapy in Murine Glioblastoma.

Glioblastoma (GBM) is the most common and malignant primary brain tumor in adults. Immunotherapy may be promising for the treatment of some patients with GBM; however, there is a need for noninvasive neuroimaging techniques to predict immunotherapeutic responses. The effectiveness of most immunotherapeutic strategies requires T-cell activation. Therefore, we aimed to evaluate an early marker of T-cell activation, CD69, for its use as an imaging biomarker of response to immunotherapy for GBM. Herein, we performed CD69 immunostaining on human and mouse T cells following in vitro activation and post immune checkpoint inhibitors (ICI) in an orthotopic syngeneic mouse glioma model. CD69 expression on tumor-infiltrating leukocytes was assessed using single-cell RNA sequencing (scRNA-seq) data from patients with recurrent GBM receiving ICI. Radiolabeled CD69 Ab PET/CT imaging (CD69 immuno-PET) was performed on GBM-bearing mice longitudinally to quantify CD69 and its association with survival following immunotherapy. We show CD69 expression is upregulated upon T-cell activation and on tumor-infiltrating lymphocytes (TIL) in response to immunotherapy. Similarly, scRNA-seq data demonstrated elevated CD69 on TILs from patients with ICI-treated recurrent GBM as compared with TILs from control cohorts. CD69 immuno-PET studies showed a significantly higher tracer uptake in the tumors of ICI-treated mice compared with controls. Importantly, we observed a positive correlation between survival and CD69 immuno-PET signals in immunotherapy-treated animals and established a trajectory of T-cell activation by virtue of CD69-immuno-PET measurements. Our study supports the potential use of CD69 immuno-PET as an immunotherapy response assessment imaging tool for patients with GBM. Significance: Immunotherapy may hold promise for the treatment of some patients with GBM. There is a need to assess therapy responsiveness to allow the continuation of effective treatment in responders and to avoid ineffective treatment with potential adverse effects in the nonresponders. We demonstrate that noninvasive PET/CT imaging of CD69 may allow early detection of immunotherapy responsiveness in patients with GBM.

Cerebral Intraparenchymal Hemorrhage Changes Patients' Gut Bacteria Composition and Function.

Gut bacteria consists of 150 times more genes than humans that are vital for health. Several studies revealed that gut bacteria are associated with disease status and influence human behavior and mentality. Whether human brain injury alters the gut bacteria is yet unclear, we tested 20 fecal samples from patients with cerebral intraparenchymal hemorrhage and corresponding healthy controls through metagenomic shotgun sequencing. The composition of patients' gut bacteria changed significantly at the phylum level; Verrucomicrobiota was the specific phylum colonized in the patients' gut. The functional alteration was observed in the patients' gut bacteria, including high metabolic activity for nutrients or neuroactive compounds, strong antibiotic resistance, and less virulence factor diversity. The changes in the transcription and metabolism of differential species were more evident than those of the non-differential species between groups, which is the primary factor contributing to the functional alteration of patients with cerebral intraparenchymal hemorrhage.

Identification of the novel prognostic biomarker, MLLT11, reveals its relationship with immune checkpoint markers in glioma.

Aim: This study aimed to explore the expression pattern of MLLT11 under different pathological features, evaluate its prognostic value for glioma patients, reveal the relationship between MLLT11 mRNA expression and immune cell infiltration in the tumor microenvironment (TME), and provide more evidence for the molecular diagnosis of glioma and immunotherapy. Methods: Using large-scale bioinformatic approach and RNA sequencing (RNA-seq) data from public databases The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and The Gene Expression Omnibus (GEO)), we investigated the relationship between MLLT11 mRNA levels and pathologic characteristics. The distribution in the different subtypes was observed based on Verhaak bulk and Neftel single-cell classification. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used for bioinformatic analysis. Kaplan-Meier survival analysis and Cox regression analysis were used for survival analysis. Correlation analyses were performed between MLLT11 expression and 22 immune cells and immune checkpoints in the TME. Results: We found that MLLT11 expression is decreased in high-grade glioma tissues; we further verified this result by RT-PCR, Western blotting, and immunohistochemistry using our clinical samples. According to the Verhaak classification, high MLLT11 expression is mostly clustered in pro-neutral (PN) and neutral (NE) subtypes, while in the Neftel classification, MLLT11 mainly clustered in neural progenitor-like (NPC-like) neoplastic cells. Survival analysis revealed that low levels of MLLT11 expression are associated with a poorer prognosis; MLLT11 was identified as an independent prognostic factor in multivariate Cox regression analyses. Functional enrichment analyses of MLLT11 with correlated expression indicated that low MLLT11 expression is associated with the biological process related to the extracellular matrix, and the high expression group is related to the synaptic structure. Correlation analyses suggest that declined MLLT11 expression is associated with increased macrophage infiltration in glioma, especially M2 macrophage, and verified by RT-PCR, Western blotting, and immunohistochemistry using our clinical glioma samples. MLLT11 had a highly negative correlation with immune checkpoint inhibitor (ICI) genes including PDCD1, PD-L1, TIM3(HAVCR2), and PD-L2 (PDCD1LG2). Conclusion: MLLT11 plays a crucial role in the progression of glioma and has the potential to be a new prognostic marker for glioma.

Clinical characteristics, surgical management, and prognostic factors for supratentorial hemangioblastoma: A retrospective study.

Background: Supratentorial hemangioblastoma is an extremely rare neoplasm. The aim of this study is to delineate the clinical features among cystic and solid supratentorial hemangioblastoma patients and evaluate the risk factors for progression-free survival (PFS). Methods: We conducted a literature search in PubMed for histopathologically identified supratentorial hemangioblastoma between 1947 and 2021 and extracted and collected the clinical features of patients treated at our own institute. The rate of PFS was determined using Kaplan-Meier analysis. Differences in categorical factors, such as the location of tumor and diagnosis of von Hippel-Lindau disease, were analyzed using the Pearson χ 2 test. A Cox regression analysis was performed to evaluate the association between various variates and survival outcomes. Results: A total of 237 cases of supratentorial hemangioblastoma were identified from 169 studies. A survival analysis found that patients with cystic tumors had a significantly better prognosis than those with solid tumors (log-rank, p = 0.0122). Cox regression analysis suggested that cystic hemangioblastoma (hazard ratio (HR): 0.186, 95% CI: 0.043-0.803, p < 0.05) and gross total resection (GTR) (HR: 0.126, 95% CI: 0.049-0.323, p < 0.001) were significant predictors of longer survival (PFS) for supratentorial hemangioblastoma. Following an analysis of 13 supratentorial hemangioblastoma cases from our institute, we validated that cystic tumor had improved prognosis than solid tumor (log-rank, p = 0.0096) and GTR was superior to subtotal resection (log-rank, p = 0.0029). Conclusions: Cystic hemangioblastoma vs. solid hemangioblastoma may be two tumoral statuses with different clinical features, and a specific treatment strategy should be considered.

Systematic Analysis of 4-gene Prognostic Signature in Patients with Diffuse Gliomas Based on Gene Expression Profiles.

Background: Diffuse gliomas are a group of diseases that contain different degrees of malignancy and complex heterogeneity. Previous studies proposed biomarkers for certain grades of gliomas, but few of them have conducted a systematic analysis of different grades to search for molecular markers. Methods: WGCNA was used to find significant genes associated with malignant progression of diffuse glioma in TCGA glioma sequencing expression data and the GEO expression profile-merge meta dataset. Lasso regression was used for potential model building and the best model was selected by CPE, IDI, and C_index. Risk score model was used to evaluate the gene signature prognostic power. Multi-omics data, including CNV, methylation, clinical traits, and mutation, were used for model evaluation. Results: We found out 67 genes significantly associated with malignant progression of diffuse glioma by WGCNA. Next, we established a new 4 gene molecular marker (KDELR2, EMP3, TIMP1, and TAGLN2). Multivariate cox analysis identified the risk score of the 4 genes as an independent predictor of prognosis in patients with diffuse gliomas, and its predictive power was independent of the histopathological grades of glioma. Further, we had confirmed in five independent test datasets and the risk score remained good predictive power. The combination of the prognosis model with specific molecular characteristics possessed a better predictive power. Furthermore, we divided the low-risk group into three subtypes: LowRisk_IDH1wt, LowRisk_IDH1mut/ATRXmut, and LowRisk_IDH1mut/ATRXwt by combining IDH1 mutation with ATRX mutation, which possessed obvious survival difference. In further analysis, we found that the 4 gene prognosis model possessed multi-omics features. Conclusion: We established a malignant-related 4-gene molecular marker by glioma expression profile data from multiple microarrays and sequencing data. The four markers had good predictive power on the overall survival of glioma patients and were associated with gliomas' clinical and genetic backgrounds, including clinical features, gene mutation, methylation, CNV, signal pathways.

Hypoxia Contributes to Poor Prognosis in Primary IDH-wt GBM by Inducing Tumor Cells MES-Like Transformation Trend and Inhibiting Immune Cells Activity.

AIMS: To reveal the influence of hypoxia on tumor cells and immune cells in primary IDH-wt glioblastoma patients. METHODS: Single-cell RNA-seq data and bulk RNA-seq data were acquired from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, respectively. Hypoxia status and subtypes of tumor cells were identified based on single-sample Gene Set Enrichment Analysis (ssGSEA). Regulon network analysis of different subtypes under different conditions was conducted by SCENIC. Within tumor microenvironment, biological process activity analysis and cell-cell communication network were conducted to uncover the inner links between each cell subtype under different hypoxia status. RESULTS: Different types of tumor cell in GBM possessed different hypoxia status, and MES-like subtype was under a more severe hypoxia condition than other subtypes. Hypoxia also induced MES-like signature gene expression within each tumor cell, which could stimulate tumor cell proliferation and invasion by regulating cell-cell communication. Additionally, hypoxia inhibited immune cell activity in the tumor microenvironment by inducing macrophage phenotype polarization and upregulating immune-inhibited cell-cell interaction within immune cells. Interactions between tumor cells and immune cells under hypoxia status also promoted tumor progression. CONCLUSIONS: Hypoxia was a poor prognostic marker for primary IDH-wt GBM patients. Meanwhile, it could induce tumor cells' MES-like transformation trend and inhibit antitumor function of immune cells.

Multivariate Analysis and Validation of the Prognostic Factors for Skull Base Chordoma.

Background: Skull base chordoma is a rare tumor with low-grade malignancy and a high recurrence rate, the factors affecting the prognosis of patients need to be further studied. For that, we investigated prognostic factors of skull base chordoma through the database of the Surveillance, Epidemiology, and End Results (SEER) program, and validated in an independent data set from the Xiangya Hospital. Methods: Six hundred and forty-three patients diagnosed with skull base chordoma were obtained from the SEER database (606 patients) and the Xiangya Hospital (37 patients). Categorical variables were selected by Chi-square test with a statistical difference. Survival curves were constructed by Kaplan-Meier analysis and compared by log-rank test. Univariate and multivariate Cox regression analyses were used to explore the prognostic factors. Propensity score matching (PSM) analysis was undertaken to reduce the substantial bias between gross total resection (GTR) and subtotal resection (STR) groups. Furthermore, clinical data of 37 patients from the Xiangya Hospital were used as validation cohorts to check the survival impacts of the extent of resection and adjuvant radiotherapy on prognosis. Results: We found that age at diagnosis, primary site, disease stage, surgical treatment, and tumor size was significantly associated with the prognosis of skull base chordoma. PSM analysis revealed that there was no significant difference in the OS between GTR and STR (p = 0.157). Independent data set from the Xiangya Hospital proved no statistical difference in OS between GTR and STR groups (p = 0.16), but the GTR group was superior to the STR group for progression-free survival (PFS) (p = 0.048). Postoperative radiotherapy does not improve OS (p = 0.28), but it can prolong PFS (p = 0.0037). Nomograms predicting 5- and 10-year OS and DSS were constructed based on statistically significant factors identified by multivariate Cox analysis. Age, primary site, tumor size, surgical treatment, and disease stage were included as prognostic predictors in the nomograms with good performance. Conclusions: We identified age, tumor size, surgery, primary site, and tumor stage as main factors affecting the prognosis of the skull base chordoma. Resection of the tumor as much as possible while ensuring safety, combined with postoperative radiotherapy may be the optimum treatment for skull base chordoma.

Effect of intra- and inter-tumoral heterogeneity on molecular characteristics of primary IDH-wild type glioblastoma revealed by single-cell analysis.

AIMS: To reveal the effects of intra- and inter-tumoral heterogeneity on characteristics of primary IDH-wild type glioblastoma cells. METHODS: Single-cell RNA-seq data were acquired from the GEO database, and bulk sample transcriptome data were downloaded from the TCGA database with clinical information. Neoplastic subtype and glioma stem-like cells (GSCs) were identified by matching 5000 random virtual samples based on ssGSEA. CNV was inferred to compare the heterogeneity among patients and subtypes by infercnv. Transition direction was inferred by RNA velocity, and lineage trajectory was inferred by monocle. Regulon network of cells was analyzed by SCENIC, and cell communication was identified by CellPhoneDB. RESULTS: Glioblastoma (GBM) cells could be divided into four subtypes by Verhaak classifier. However, classification of three subtypes (except NE subtype) was more suitable for GBM cells, and Verhaak classifier has difficulty in distinguishing GSCs. GBM heterogeneity and GBM cells' regulon network were mainly influenced by inter-tumoral heterogeneity. Within the same patient, different subclones exist in the same subtype of cells whose transition direction could be predicted by regulon similarity. Apart from inter-tumoral heterogeneity, different subtype of cells share common subtype-specific cell-cell communications. CONCLUSIONS: Inter-tumoral heterogeneity contributes mainly to GBM heterogeneity and cell molecular characteristics. However, the same subtype of cells shared cell communication similarities.

Improved Prognostic Prediction of Glioblastoma using a PAS Detected from Single-cell RNA-seq.

Glioblastoma (GBM) is a common malignant brain tumor of the central nervous system with a poor prognosis. In order to identify the prognostic signatures of GBM, we screened differentially expressed genes (DEGs) that were based on a single-cell RNA sequencing (scRNA-seq) dataset. These genes characteristically represent the intra-tumor heterogenicity of glioblastoma. Moreover, we performed univariate analysis, log-rank test and multivariate Cox regression analyses to confirm a gene set that could be related to the overall survival (OS) among DEGs. Prognostic associated signatures (PAS) were utilized to construct a model for predicting OS in GBM patients. When considering either the training or the validation sets, time-dependent receiver operating characteristic (ROC) curves all indicated that our model displayed an excellent predictive ability. Additionally, we analyzed PAS at the single-cell level and found that the PAS score was associated with somatic mutations and clinical factors. Three factors, which included the PAS score, radiotherapy status, and age, were all used to establish a nomogram to predict the 6-month and 1-year survival probabilities. In conclusion, we constructed an optimal model that was derived from scRNA-seq to better predict the survival probability of GBM patients. These genes might also act as potential prognostic biomarkers and enable surgeons to develop individually therapeutic schedules and improve the prognosis of GBM patients.

Construction and Validation of a 13-Gene Signature for Prognosis Prediction in Medulloblastoma.

Background: Recent studies have identified several molecular subgroups of medulloblastoma associated with distinct clinical outcomes; however, no robust gene signature has been established for prognosis prediction. Our objective was to construct a robust gene signature-based model to predict the prognosis of patients with medulloblastoma. Methods: Expression data of medulloblastomas were acquired from the Gene Expression Omnibus (GSE85217, n = 763; GSE37418, n = 76). To identify genes associated with overall survival (OS), we performed univariate survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. A risk score model was constructed based on selected genes and was validated using multiple datasets. Differentially expressed genes (DEGs) between the risk groups were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and protein-protein interaction (PPI) analyses were performed. Network modules and hub genes were identified using Cytoscape. Furthermore, tumor microenvironment (TME) was evaluated using ESTIMATE algorithm. Tumor-infiltrating immune cells (TIICs) were inferred using CIBERSORTx. Results: A 13-gene model was constructed and validated. Patients classified as high-risk group had significantly worse OS than those as low-risk group (Training set: p < 0.0001; Validation set 1: p < 0.0001; Validation set 2: p = 0.00052). The area under the curve (AUC) of the receiver operating characteristic (ROC) analysis indicated a good performance in predicting 1-, 3-, and 5-year OS in all datasets. Multivariate analysis integrating clinical factors demonstrated that the risk score was an independent predictor for the OS (validation set 1: p = 0.001, validation set 2: p = 0.004). We then identified 265 DEGs between risk groups and PPI analysis predicted modules that were highly related to central nervous system and embryonic development. The risk score was significantly correlated with programmed death-ligand 1 (PD-L1) expression (p < 0.001), as well as immune score (p = 0.035), stromal score (p = 0.010), and tumor purity (p = 0.010) in Group 4 medulloblastomas. Correlations between the 13-gene signature and the TIICs in Sonic hedgehog and Group 4 medulloblastomas were revealed. Conclusion: Our study constructed and validated a robust 13-gene signature model estimating the prognosis of medulloblastoma patients. We also revealed genes and pathways that may be related to the development and prognosis of medulloblastoma, which might provide candidate targets for future investigation.

PTTG has a Dual Role of Promotion-Inhibition in the Development of Pituitary Adenomas.

Pituitary Tumor Transforming Gene (PTTG) of human is known as a checkpoint gene in the middle and late stages of mitosis, and is also a proto-oncogene that promotes cell cycle progression. In the nucleus, PTTG works as securin in controlling the mid-term segregation of sister chromatids. Overexpression of PTTG, entering the nucleus with the help of PBF in pituitary adenomas, participates in the regulation of cell cycle, interferes with DNA repair, induces genetic instability, transactivates FGF-2 and VEGF and promotes angiogenesis and tumor invasion. Simultaneously, overexpression of PTTG induces tumor cell senescence through the DNA damage pathway, making pituitary adenoma possessing the potential self-limiting ability. To elucidate the mechanism of PTTG in the regulation of pituitary adenomas, we focus on both the positive and negative function of PTTG and find out key factors interacted with PTTG in pituitary adenomas. Furthermore, we discuss other possible mechanisms correlate with PTTG in pituitary adenoma initiation and development and the potential value of PTTG in clinical treatment.

ACSS2-related autophagy has a dual impact on memory.

Autophagy is an intracellular degenerative pathway which is responsible for neuronal survival. Under the condition of nutrient deprivation, autophagy can lead to dysfunction in memory consolidation. AMPK/mTOR pathway is currently the most studied autophagy mechanism, while recently researchers have proved ACSS2 can also affect autophagy. ACSS2 is phosphorylated at Ser659 by AMPK and then forms a translocation complex with Importin α5 to translocate into the nucleus. This process interacts with TFEB, resulting in upregulated expression of lysosomal and autophagosomal genes. These upregulations inhibit synaptic plasticity and hence memory functions. On the other hand, ACSS2 is also recognized as a regulator of histone acetylation. After recruiting CBP/p300 and activating CBP's HAT activity in the nucleus, ACSS2 maintains the level of localized histone acetylation by recapturing acetate from histone deacetylation to reform acetyl-CoA, providing substrates for HAT. The increase of histone acetylation locally enhanced immediate early gene transcription, including Egr2, Fos, Nr2f2, Sgk1, and Arc, to benefit neuronal plasticity and memory in many ways.