Prognostic significance of GAD1 overexpression in patients with resected lung adenocarcinoma

A GAD1 inhibitor suppresses osteosarcoma growth through the Wnt/β-catenin signaling pathway

Background

As a marker of the GABAergic system, the expression of glutamate decarboxylase 1 (GAD1) is mainly restricted to the central nervous system. Emerging studies have shown that aberrant expression of GAD1 in tumor tissues may promote tumor cell growth. The role of GAD1 in the development of osteosarcoma (OS) remains unclear, so this study sought to investigate the expression status of GAD1 and the effect of its specific inhibitor 3-mercaptopropionic acid (3-MPA) on OS.

Methods

The R2 database was used to analyze the relationship between the expression of GAD1 and clinical prognosis in OS patients. Immunohistochemistry was used to compare the expression profile of GAD1 between OS and matched neighboring tissues. The potential antitumor effects of 3-MPA on cell viability, colony formation and the cell cycle were examined. Moreover, the in vivo effect of 3-MPA on tumor growth was investigated using tumor-bearing nude mice.

Results

The expression level of GAD1 was aberrantly upregulated in OS tissues, but almost no expression of GAD1 was found in matched neighboring tissues. Western blotting analyses showed upregulation of GAD1 in OS cells compared to human osteoblast cells. In vitro and in vivo, 3-MPA significantly suppressed the growth of OS. Regarding the mechanism, 3-MPA inhibited β-catenin and cyclin D1 in OS cells, thereby inactivating the Wnt/β-catenin pathway.

Conclusions

OS displays increased expression of the GABAergic neuronal marker GAD1, and 3-MPA significantly reduces OS growth by inhibiting the Wnt/β-catenin pathway.

Identification and validation of a metabolism-related gene signature for predicting the prognosis of paediatric medulloblastoma

Medulloblastoma (MB) is a malignant brain tumour that is highly common in children and has a tendency to spread to the brain and spinal cord. MB is thought to be a metabolically driven brain tumour. Understanding tumour cell metabolic patterns and characteristics can provide a promising foundation for understanding MB pathogenesis and developing treatments. Here, by analysing RNA-seq data of MB samples from the Gene Expression Omnibus (GEO) database, 12 differentially expressed metabolic-related genes (DE-MRGs) were chosen for the construction of a predictive risk score model for MB. This model demonstrated outstanding accuracy in predicting the outcomes of MB patients and served as a standalone predictor. An evaluation of functional enrichment revealed that the risk score showed enrichment in pathways related to cancer promotion and the immune response. In addition, a high risk score was an independent poor prognostic factor for MB in patients with different ages, sexes, metastasis stages and subgroups (SHH and Group 4). Consistently, the metabolic enzyme ornithine decarboxylase (ODC1) was upregulated in MB patients with poor survival time. Inhibition of ODC1 in primary and metastatic MB cell lines decreased cell proliferation, migration and invasion but increased immune infiltration. This study could aid in identifying metabolic targets for MB as well as optimizing risk stratification systems and individual treatment plans for MB patients via the use of a metabolism-related gene prognostic risk score signature.

Risk Stratification by Tissue GAD1 Expression Level in Curatively Resected Esophageal Squamous Cell Carcinoma

BACKGROUND/AIM

To improve patient management, new biomarkers are required that stratify prognosis. Here we focused on glutamic acid decarboxylase 1 (GAD1), which is associated with proliferation of lung cancer cells, and investigated its expression and function in esophageal squamous cell carcinoma (ESCC).

MATERIALS AND METHODS

We evaluated changes in the proliferative potential of ESCC cell lines using small interfering RNA-mediated GAD1 knockdown techniques. We analyzed GAD1 protein expression using a tissue microarray (TMA) and measured GAD1 mRNA expression to evaluate correlations between the expression level of each tissue and postoperative outcomes of two independent cohorts (the TMA and mRNA cohorts) of patients who underwent radical esophagectomy.

RESULTS

GAD1 knockdown reduced cell proliferation. In the TMA cohort, high GAD1 expression significantly correlated with lymph node metastasis and advanced stage. Disease-free survival was significantly shorter in the group with high GAD1 expression, as was overall survival. Multivariate analysis of overall survival showed that positivity for GAD1 was an independent prognostic factor for poor survival. In the mRNA cohort, GAD1 mRNA expression in ESCC tissues was significantly up-regulated compared with that in adjacent noncancerous mucosal tissues. When patients were divided into high- and low-expression groups according to the median GAD1 mRNA expression level in ESCC tissues, overall survival was significantly shortened in the high GAD1 expression group. The incidence of initial hematogenous recurrence was significantly higher in the group with high GAD1 expression.

CONCLUSION

GAD1 expression mediates the proliferative potential of ESCC cells, and a high level may serve as a useful prognostic biomarker for patients with ESCC.

GABAergic signaling beyond synapses: an emerging target for cancer therapy

Traditionally, γ-aminobutyric acid (GABA) is best known for its role as a primary inhibitory neurotransmitter reducing neuronal excitability in the mammalian central nervous system (CNS), thereby producing calming effects. However, an emerging body of data now supports a function for GABA beyond neurotransmission as a potent factor regulating cancer cell growth and metastasis, as well as the antitumor immune response, by shaping the tumor microenvironment (TME). Here, we review the current knowledge on GABA's effects on the function of tumor cells, tumor-immune interactions, and the underlying molecular mechanisms. Since altered GABAergic signaling is now recognized as a feature of certain types of solid tumors, we also discuss the potential of repurposing existing GABAergic agents as a new class of anticancer therapy.

GABAergic signaling as a potential therapeutic target in cancers

GABA is the most common inhibitory neurotransmitter in the vertebrate central nervous system. Synthesized by glutamic acid decarboxylase, GABA could specifically bind with two GABA receptors to transmit inhibition signal stimuli into cells: GABAA receptor and GABAB receptor. In recent years, emerging studies revealed that GABAergic signaling not only participated in traditional neurotransmission but was involved in tumorigenesis as well as regulating tumor immunity. In this review, we summarize the existing knowledge of the GABAergic signaling pathway in tumor proliferation, metastasis, progression, stemness, and tumor microenvironment as well as the underlying molecular mechanism. We also discussed the therapeutical advances in targeting GABA receptors to provide the theoretical basis for pharmacological intervention of GABAergic signaling in cancer treatment especially immunotherapy.

Bodywide ecological interventions on cancer

Historically, cancer research and therapy have focused on malignant cells and their tumor microenvironment. However, the vascular, lymphatic and nervous systems establish long-range communication between the tumor and the host. This communication is mediated by metabolites generated by the host or the gut microbiota, as well by systemic neuroendocrine, pro-inflammatory and immune circuitries-all of which dictate the trajectory of malignant disease through molecularly defined biological mechanisms. Moreover, aging, co-morbidities and co-medications have a major impact on the development, progression and therapeutic response of patients with cancer. In this Perspective, we advocate for a whole-body 'ecological' exploration of malignant disease. We surmise that accumulating knowledge on the intricate relationship between the host and the tumor will shape rational strategies for systemic, bodywide interventions that will eventually improve tumor control, as well as quality of life, in patients with cancer.

Integrative Metabolomic and Lipidomic Profiling of Lung Squamous Cell Carcinoma for Characterization of Metabolites and Intact Lipid Species Related to the Metastatic Potential

SQCC is a major type of NSCLC, which is a major cause of cancer-related deaths, and there were no reports regarding the prediction of metastatic potential of lung SQCC by metabolomic and lipidomic profiling. In this study, metabolomic and lipidomic profiling of lung SQCC were performed to predict its metastatic potential and to suggest potential therapeutic targets for the inhibition of lung SQCC metastasis. Human bronchial epithelial cells and four lung SQCC cell lines with different metastatic potentials were analyzed using gas chromatography-mass spectrometry and direct infusion-mass spectrometry. Based on the obtained metabolic and lipidomic profiles, we constructed models to predict the metastatic potential of lung SQCC; glycerol, putrescine, β-alanine, hypoxanthine, inosine, myo-inositol, phosphatidylinositol (PI) 18:1/18:1, and PI 18:1/20:4 were suggested as characteristic metabolites and intact lipid species associated with lung SQCC metastatic potential. In this study, we established predictive models for the metastatic potential of lung SQCC; furthermore, we identified metabolites and intact lipid species relevant to lung SQCC metastatic potential that may serve as potential therapeutic targets for the inhibition of lung SQCC metastasis.

GAD1 expression and its methylation as indicators of malignant behavior in thymic epithelial tumors

Thymic epithelial tumors (TETs) comprise thymomas and thymic carcinoma (TC). TC has more aggressive features and a poorer prognosis than thymomas. Genetic and epigenetic alterations in thymomas and TC have been investigated in an attempt to identify novel target molecules for TC. In the present study, genome-wide screening was performed on aberrantly methylated CpG islands in thymomas and TC, and the glutamate decarboxylase 1 gene (GAD1) was identified as the 4th significantly hypermethylated CpG island in TC compared with thymomas. GAD1 catalyzes the production of γ-aminobutyric acid from L-glutamic acid. GAD1 expression is abundant in the brain but rare in other tissues, including the thymus. A total of 73 thymomas and 17 TC tissues were obtained from 90 patients who underwent surgery or biopsy at Tokushima University Hospital between 1990 and 2017. DNA methylation was examined by bisulfite pyrosequencing, and the mRNA and protein expression levels of GAD1 were analyzed using reverse transcription-quantitative PCR and immunohistochemistry, respectively. The DNA methylation levels of GAD1 were significantly higher in TC tissues than in the normal thymus and thymoma tissues, and GAD1 methylation exhibited high sensitivity and specificity for discriminating between TC and thymoma. The mRNA and protein expression levels of GAD1 were significantly higher in TC tissues than in thymomas. Patients with TET with high GAD1 DNA hypermethylation and high mRNA and protein expression levels had significantly shorter relapse-free survival rates than those with low levels. In conclusion, significantly more epigenetic alterations were observed in TC tissues compared with in thymomas, which may contribute to the clinical features and prognosis of patients.

Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer

Oxidative stress (OS) reactions are reported to be associated with oncogenesis and tumor progression. However, little is known about the potential diagnostic value of OS in gastric cancer (GC). This study identified hub OS genes associated with the prognosis and progression of GC and illustrated the underlying mechanisms. The transcriptome data and corresponding GC clinical information were collected from The Cancer Genome Atlas (TCGA) database. Aberrantly expressed OS genes between tumors and adjacent normal tissues were screened, and 11 prognosis-associated genes were identified with a series of bioinformatic analyses and used to construct a prognostic model. These genes were validated in the Gene Expression Omnibus (GEO) database. Furthermore, weighted gene co-expression network analysis (WGCNA) was subsequently conducted to identify the most significant hub genes for the prediction of GC progression. Analysis revealed that a good prognostic model was constructed with a better diagnostic accuracy than other clinicopathological characteristics in both TCGA and GEO cohorts. The model was also significantly associated with the overall survival of patients with GC. Meanwhile, a nomogram based on the risk score was established, which displayed a favorable discriminating ability for GC. In the WGCNA analysis, 13 progression-associated hub OS genes were identified that were also significantly associated with the progression of GC. Furthermore, functional and gene ontology (GO) analyses were performed to reveal potential pathways enriched with these genes. These results provide novel insights into the potential applications of OS-associated genes in patients with GC.

DNA methylation patterns-based subtype distinction and identification of soft tissue sarcoma prognosis

Soft tissue sarcomas (STSs) are heterogeneous at the clinical with a variable tendency of aggressive behavior. In this study, we constructed a specific DNA methylation-based classification to identify the distinct prognosis-subtypes of STSs based on the DNA methylation spectrum from the TCGA database. Eventually, samples were clustered into 4 subgroups, and their survival curves were distinct from each other. Meanwhile, the samples in each subgroup reflected differentially in several clinical features. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was also conducted on the genes of the corresponding promoter regions of the above-described specific methylation sites, revealing that these genes were mainly concentrated in certain cancer-associated biological functions and pathways. In addition, we calculated the differences among clustered methylation sites and performed the specific methylation sites with LASSO algorithm. The selection operator algorithm was employed to derive a risk signature model, and a prognostic signature based on these methylation sites performed well for risk stratification in STSs patients. At last, a nomogram consisted of clinical features and risk score was developed for the survival prediction. This study declares that DNA methylation-based STSs subtype classification is highly relevant for future development of personalized therapy as it identifies the prediction value of patient prognosis.

Deep neural network improves the estimation of polygenic risk scores for breast cancer

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. In this study, we compared a series of computational models for estimation of breast cancer PRS. A deep neural network (DNN) was found to outperform alternative machine learning techniques and established statistical algorithms, including BLUP, BayesA, and LDpred. In the test cohort with 50% prevalence, the Area Under the receiver operating characteristic Curve (AUC) were 67.4% for DNN, 64.2% for BLUP, 64.5% for BayesA, and 62.4% for LDpred. BLUP, BayesA, and LPpred all generated PRS that followed a normal distribution in the case population. However, the PRS generated by DNN in the case population followed a bimodal distribution composed of two normal distributions with distinctly different means. This suggests that DNN was able to separate the case population into a high-genetic-risk case subpopulation with an average PRS significantly higher than the control population and a normal-genetic-risk case subpopulation with an average PRS similar to the control population. This allowed DNN to achieve 18.8% recall at 90% precision in the test cohort with 50% prevalence, which can be extrapolated to 65.4% recall at 20% precision in a general population with 12% prevalence. Interpretation of the DNN model identified salient variants that were assigned insignificant p values by association studies, but were important for DNN prediction. These variants may be associated with the phenotype through nonlinear relationships.

Vitamin D receptor gene methylation in patients with hand, foot, and mouth disease caused by enterovirus 71

To evaluate the epigenetic regulation of the VDR gene in enterovirus 71 (EV71)-associated severe hand, foot, and mouth disease (HFMD), a total of 116 patients with EV71-HFMD, including 58 with mild EV71-HFMD and 58 with severe EV71-HFMD, as well as 60 healthy controls, were enrolled in this study. Quantitative real-time PCR was used to measure the relative levels of VDR mRNA expression, and the methylation status of the VDR promoter was assessed using a MethylTarget™ assay. The DNA methylation levels of the VDR promoter in children with EV71-associated severe HFMD were lower than those in the healthy controls and in children with mild HFMD (P < 0.05). Hypomethylation at CpG site 133 and hypermethylation at the CpG 42 sites and 68 downregulated VDR expression. Moreover, the methylation level of VDR could be used for differential diagnosis of mild and severe EV71-associated HFMD (AUC₅₆, 0.73; AUC₆₈, 0.699; AUC₄₂, 0.694; AUC₆₆, 0.693). VDR expression and promoter methylation were associated with the progression of EV71 infection. Determining the VDR promoter status might help clinicians initiate the appropriate strategy for treatment of EV71-associated HFMD.

Patients with Cholangiocarcinoma Present Specific RNA Profiles in Serum and Urine Extracellular Vesicles Mirroring the Tumor Expression: Novel Liquid Biopsy Biomarkers for Disease Diagnosis

Cholangiocarcinoma (CCA) comprises a group of heterogeneous biliary cancers with dismal prognosis. The etiologies of most CCAs are unknown, but primary sclerosing cholangitis (PSC) is a risk factor. Non-invasive diagnosis of CCA is challenging and accurate biomarkers are lacking. We aimed to characterize the transcriptomic profile of serum and urine extracellular vesicles (EVs) from patients with CCA, PSC, ulcerative colitis (UC), and healthy individuals. Serum and urine EVs were isolated by serial ultracentrifugations and characterized by nanoparticle tracking analysis, transmission electron microscopy, and immunoblotting. EVs transcriptome was determined by Illumina gene expression array [messenger RNAs (mRNA) and non-coding RNAs (ncRNAs)]. Differential RNA profiles were found in serum and urine EVs from patients with CCA compared to control groups (disease and healthy), showing high diagnostic capacity. The comparison of the mRNA profiles of serum or urine EVs from patients with CCA with the transcriptome of tumor tissues from two cohorts of patients, CCA cells in vitro, and CCA cells-derived EVs, identified 105 and 39 commonly-altered transcripts, respectively. Gene ontology analysis indicated that most commonly-altered mRNAs participate in carcinogenic steps. Overall, patients with CCA present specific RNA profiles in EVs mirroring the tumor, and constituting novel promising liquid biopsy biomarkers.

Prognostic significance of GAD1 overexpression in patients with resected lung adenocarcinoma

BACKGROUND AND OBJECTIVES

In a previous genome-wide screening, we identified hypermethylated CpG islands around glutamate decarboxylase 1 (GAD1) in lung adenocarcinoma (LADC). In this study, we aimed to investigate the methylation and expression status of GAD1 and its prognostic value in patients with LADC.

METHODS

GAD1 methylation and mRNA expression status were analyzed using 33 tumorous and paired non-tumorous LADC samples and publicly available datasets. The prognostic value of GAD1 overexpression was investigated using publicly available datasets of mRNA levels and 162 cases of LADC by immunohistochemistry.

RESULTS

The methylation and mRNA expression levels of GAD1, each having a positive correlation, were significantly higher in LADC tumors than in paired non-tumorous tissues. LADC patients with higher GAD1 mRNA expression showed significantly poorer prognosis for overall survival in publicly available datasets. Higher immunoreactivity of GAD1 was significantly associated with the pathological stage, pleural invasion, lymph vessel invasion, and poorer prognosis for cancer-specific and disease-free survival. Multivariate analysis revealed that GAD1 protein overexpression is an independent prognosticator for disease-free survival.

CONCLUSIONS

GAD1 mRNA and protein expression levels were significant prognostic factors in LADC, suggesting that they might be useful biomarkers to stratify patients with worse clinical outcomes after resection.