Gamma-glutamyl Hydrolase Research Articles

Functional characterization of a novel Chlamydomonas reinhardtii hydrolase involved in biotransformation of chloramphenicol

Microalgae-based biotechnology is one of the most promising alternatives to conventional methods for the removal of antibiotic contaminants from diverse water matrices. However, current knowledge regarding the biochemical mechanisms and catabolic enzymes involved in microalgal biodegradation of antibiotics is scant, which limits the development of enhancement strategies to increase their engineering feasibility. In this study, we investigated the removal dynamics of amphenicols (chloramphenicol, thiamphenicol, and florfenicol), which are widely used in aquaculture, by Chlamydomonas reinhardtii under different growth modes (autotrophy, heterotrophy, and mixotrophy). We found C. reinhardtii removed >92 % chloramphenicol (CLP) in mixotrophic conditions. Intriguingly, gamma-glutamyl hydrolase (GGH) in C. reinhardtii was most significantly upregulated according to the comparative proteomics, and we demonstrated that GGH can directly bind to CLP at the Pro77 site to induce acetylation of the hydroxyl group at C3 position, which generated CLP 3-acetate. This identified role of microalgal GGH is mechanistically distinct from that of animal counterparts. Our results provide a valuable enzyme toolbox for biocatalysis and reveal a new enzymatic function of microalgal GGH. As proof of concept, we also analyzed the occurrence of these three amphenicols and their degradation intermediate worldwide, which showed a frequent distribution of the investigated chemicals at a global scale. This study describes a novel catalytic enzyme to improve the engineering feasibility of microalgae-based biotechnologies. It also raises issues regarding the different microalgal enzymatic transformations of emerging contaminants because these enzymes might function differently from their counterparts in animals.

Multi-Gene Single Nucleotide Polymorphism Detection in Gastric Cancer Based on Ion Semiconductor Sequencing Platform.

Gastric cancer is a common heterogeneous tumor. Most patients have advanced gastric cancer at the time of diagnosis and often need chemotherapy. Although 5-fluorouracil (5-FU) is widely used for treatment, its therapeutic sensitivity and drug tolerance still need to be determined, which emphasizes the importance of individualized administration. Pharmacogenetics can guide the clinical implementation of individualized treatment. Single nucleotide polymorphisms (SNPs), as a genetic marker, contribute to the selection of appropriate chemotherapy regimens and dosages. Some SNPs are associated with folate metabolism, the therapeutic target of 5-FU. Methylenetetrahydrofolate reductase (MTHFR) rs1801131 and rs1801133, dihydrofolate reductase (DHFR) rs1650697 and rs442767, methionine synthase (MTR) rs1805087, gamma-glutamyl hydrolase (GGH) rs11545078 and solute carrier family 19 member 1 (SLC19A1) rs1051298 have been investigated in different kinds of cancers and antifolate antitumor drugs, which have potential forecasting and guiding significance for application of 5-FU. The ion torrent next-generation semiconductor sequencing technology can rapidly detect gastric cancer-related SNPs. Each time a base is extended in a DNA chain, an H+ will be released, causing local pH changes. The ionic sensor detects pH changes and converts chemical signals into digital signals, achieving sequencing by synthesis. This technique has low sample requirement, simple operation, low cost, and fast sequencing speed, which is beneficial for guiding individualized chemotherapy by SNPs.

The Identification of Gamma-Glutamyl Hydrolase in Uterine Corpus Endometrial Carcinoma: a Predictive Model and Machine Learning.

Poor neoplastic differentiation contributes to the rapid progression of uterine corpus endometrial carcinoma (UCEC). Thus, it is essential to identify candidate genes, clarifying the carcinogenesis and progression of UCEC. We screened genes that affect differentiation and prognosis in UCEC. Least absolute selection and shrinkage operator (LASSO) regression, univariate Cox, and multivariate Cox proportional risk regression analyses were performed to screen out γ-glutamyl hydrolase (GGH) as the candidate gene. The clinical value of GGH on prognosis was evaluated. The relationship between GGH and immune infiltration was assessed by CIBERSORT, EPIC, ssGSEA, unsupervised clustering and immunohistochemistry (IHC). Additionally, we investigated the effect of GGH knockdown in vitro. Among the GGH, CDKN2A, and SIX1 genes, the impact of GGH was predominant on immune infiltration in UCEC. A nomogram containing GGH and other clinical features showed good predictive performance via curve analysis (DCA). In the functional analysis, GGH affected differentiation, tumour proliferation, and immune regulation. The immunosuppressive components were enriched in the GGH-high group, with poor immunotherapy efficacy. The study suggests that GGH may influence the progression of UCEC by regulating the glycolytic process. GGH is closely associated with various immune cell infiltrations. Our study demonstrates the prognostic role of GGH in carcinogenesis in UCEC.

Evaluation of the influence of polymorphisms of the transporter genes (<i>RFC1</i>, <i>MDR1</i>) and <i>GGH</i> on the efficacy of methotrexate in rheumatoid arthritis

The efficacy of methotrexate (MT) in patients with rheumatoid arthritis (RA) may be determined by genetic factors.Objective: to evaluate the isolated and combined effects of single nucleotide polymorphisms (SNPs) of membrane transporter proteins (RFC1 80G>A and MDR1 3435C>T) and the GGH -401C>T gamma-glutamyl hydrolase enzyme genes on the efficacy of MT in patients with RA.Material and methods. The study group consisted of 85 patients with a confirmed diagnosis of RA, who received therapy with MT starting at 10 mg/week and increasing in dose to a maximum of 25 mg/week. Efficacy was assessed after six months of treatment using the dynamics of the DAS28 index, identifying patients who responded and those who did not respond to MT therapy.Genotyping of RFC1, MDR1 and GGH gene polymorphisms was performed by real-time polymerase chain reaction. Three different approaches were used to analyze the results: 1) analysis for each of the genes; 2) logistic regression; and 3) multifactor dimensionality reduction (MDR).Results and discussion. Single gene analysis was used to determine the most likely predictors of non-response to therapy: 1) for GGH-401C>T, TT genotype (odds ratio, OR 5.09; 95% confidence interval, C11.11—23.3); 2) forMDR13435C>T, the TT genotype (OR 2.38; 95% CI0.89-6.37); 3) for RFC180G>A, not - AA genotype (OR 1.87; 95% CI 0.93-3.76).The logistic regression model showed a significant effect of homozygous genotype GGH -401TT on the efficacy of MT with low sensitivity of the method. The multifactorial dimensionality reduction results show a significant synergistic effect of the MT transport genes (MDR1, RFC1) and the GGH enzyme encoding the conversion of MT to the elimination form.Conclusion. Using various statistical methods, the following results were obtained: Single gene analysis revealed the most likely predictors of nonresponse to MT therapy: GGH -401C>T - TT genotype, MDR1 3435C>T - TT genotype, RFC1 80G>A - not-AA genotype; the method of multiple logistic regression allowed to determine the significant effect of GGH -401ТТ genotype on the effect of the drug with a low sensitivity of the method; the isolated effect of polymorphisms is probably less pronounced than their combined effect on the effectiveness of MT. SNP synergism is a major contributor to the development of treatment resistance. MDR is a promising method that can be used in the future to assess the impact of SNPs.

Evaluation of Intracellular Metabolism of Methotrexate in Hepatocytes and Embryonic Kidney Cells based on Folylpolyglutamate Synthetase and Gamma-Glutamyl Hydrolase Expression.

Methotrexate (MTX) is a common folic acid antagonist in clinical medicine, easily inducing a common adverse side effect of liver and kidney injury. It has been found that the expression of Folylpolyglutamate Synthetase (FPGS) and gamma-Glutamyl Hydrolase (GGH) may be closely related to that of related proteins to affect the intracellular metabolism of MTX. The relationship between FPGS/GGH and MTXPGs accumulation in liver and kidney cells was explored by adjusting the expression of FPGS and GGH in cells using UPLC-MS/MS quantitative technology. Based on UPLC-MS/MS quantitative techniques, the relationship between MTXPGs accumulation and FPGS/GGH in hepatocytes and embryonic kidney cells was explored by adjusting the expression of FPGS and GGH, and the effect of FPGS/GGH on the intracellular toxicity of MTX was comprehensively analyzed. The results showed that the difference in methotrexate polyglutamates (MTXPGs) accumulation in liver and kidney cells was related to the difference in FPGS and GGH expression. The expression of FPGS interacted with that of GGH. These results suggest that the protein abundance ratio of FPGS to GGH (FPGS/GGH) has more potential to be used as a predictor of MTX efficacy than the FPGS or GGH single protein index. This can effectively avoid liver and kidney damage caused by MTX and guides the rational use of drugs in MTX. The results prove that there is a positive correlation between the FPGS/GGH and the accumulation of MTXPGS in liver and kidney cells. Summarily, the FPGS/GGH is expected to be a predictor for MTXPGs accumulation and provides an effective method to evaluate the toxicity caused by MTX.

Proteomic profiling of cerebrospinal fluid in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease

BackgroundMyelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is an autoimmune demyelinating disorder of the central nervous system.MethodsExtracted proteins from 34 cerebrospinal fluid (CSF) samples [patients with MOGAD (MOG group, n = 12); healthy controls (HC group, n = 12); patients with MOG seronegative and metagenomics next-generation sequencing-negative inflammatory neurological diseases (IND group, n = 10)] were processed and subjected to label-free quantitative proteomics. Supervised partial least squares-discriminant analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA) models were also performed based on proteomics data. Functional analysis of differentially expressed proteins (DEPs) was performed using Gene Ontology, InterPro, and Kyoto Encyclopedia Genes and Genomes. An enzyme-linked immunosorbent assay was used to determine the complement levels in serum from patients with MOGAD.ResultsFour hundred and twenty-nine DEPs (149 upregulated and 280 downregulated proteins) were identified in the MOG group compared to the HC group according to the P value and fold change (FC). Using the O-PLS-DA model, 872 differentially abundant proteins were identified with variable importance projection (VIP) scores > 1. Five proteins (gamma-glutamyl hydrolase, cathepsin F, interalpha-trypsin inhibitor heavy chain 5, latent transforming growth factor beta-binding protein 4 and leukocyte-associated immunoglobulin-like receptor 1) overlapping between the top 30 DEPs with top-ranked P value and FC and top 30 proteins in PLS-DA VIP lists were acquired. Functional analysis revealed that the dysregulated proteins in the MOG group were primarily involved in complement and coagulation cascades, cell adhesion, axon guidance, and glycosphingolipid biosynthesis compared to the HC group.ConclusionThe proteomic alterations in CSF samples from children with MOGAD identified in the current study might provide opportunities for developing novel biomarker candidates.

Interaction between glycolysis‒cholesterol synthesis axis and tumor microenvironment reveal that gamma-glutamyl hydrolase suppresses glycolysis in colon cancer.

Metabolic reprogramming is a feature of cancer. However, colon cancer subtypes based on the glycolysis‒cholesterol synthesis axis have not been identified, and little is known about connections between metabolic features and the tumor microenvironment. Data for 430 colon cancer cases were extracted from The Cancer Genome Atlas, including transcriptome data, clinical information, and survival outcomes. Glycolysis and cholesterol synthesis-related gene sets were obtained from the Molecular Signatures Database for a gene set variation analysis. The relationship between the genomic landscape and immune landscape were investigated among four metabolic subtypes. Hub genes were determined. The clinical significance of candidate hub gene was evaluated in 264 clinical samples and potential functions were validated in vitro and in vivo. Colon cancer cases were clustered into four metabolic subtypes: quiescent, glycolytic, cholesterogenic, and mixed. The metabolic subtypes differed with respect to the immune score, stromal score, and estimate score using the ESTIMATE algorithm, cancer-immunity cycle, immunomodulator signatures, and signatures of immunotherapy responses. Patients in the cholesterogenic group had better survival outcomes than those for other subtypes, especially glycolytic. The glycolytic subtype was related to unfavorable clinical characteristics, including high mutation rates in TTN, APC, and TP53, high mutation burden, vascular invasion, right colon cancer, and low-frequency microsatellite instability. GGH, CACNG4, MME, SLC30A2, CKMT2, SYN3, and SLC22A31 were identified as differentially expressed both in glycolytic-cholesterogenic subgroups as well as between colon cancers and healthy samples, and were involved in glycolysis‒cholesterol synthesis. GGH was upregulated in colon cancer; its high expression was correlated with CD4+ T cell infiltration and longer overall survival and it was identified as a favorable independent prognostic factor. The overexpression of GGH in colon cancer-derived cell lines (SW48 and SW480) inhibited PKM, GLUT1, and LDHA expression and decreased the extracellular lactate content and intracellular ATP level. The opposite effects were obtained by GGH silencing. The phenotype associated with GGH was also validated in a xenograft nude mouse model. Our results provide insight into the connection between metabolism and the tumor microenvironment in colon cancer and provides preliminary evidence for the role of GGH, providing a basis for subsequent studies.

Overexpression of gamma glutamyl hydrolase predicts extranodal extension in squamous cell carcinoma of the oral cavity

Extranodal extension (ENE) is an important prognostic factor in oral squamous cell carcinoma (OSCC). However, ENE is only confirmed postoperatively by histologic assessment of the lymph nodes after neck dissection. Accurate identification of ENE preoperatively would help in management of OSCC. We determined the expression of molecular markers gamma glutamyl hydrolase (GGH), cyclin-dependent kinase inhibitor-3 (CDKN3), and chromobox homolog-7 (CBX7) using immunohistochemistry in OSCC clinical samples (n=35). The intensity of staining was scored using a semiquantitative index (HSCORE). The association between clinicopathologic parameters and expression of molecular markers with ENE status was analyzed using chi-square test. The number of positive nodes and the highest anatomic level of nodal involvement significantly correlated with ENE (P < .05). High GGH expression was significantly associated with ENE (P < .05), with an increased risk for ENE (odds ratio [OR] 9.9, 95% CI 1.08-91.47, P=.04), whereas no significant association was seen for CDKN3 and CBX7 expression with ENE. However, a trend toward significance was observed with a high level of CDKN3 and a low level of CBX7 expression with ENE. Gamma glutamyl hydrolase offers potential as a predictor for ENE in OSCC, whereas the role of CDKN3 and CBX7 need to be validated in a larger sample.

Plasma proteome profiling of healthy individuals across the life span in a Sicilian cohort with long-lived individuals.

The study of healthy human aging is important for shedding light on the molecular mechanisms behind aging to promote well‐being and to possibly predict and/or avoid the development of age‐related disorders such as atherosclerosis and diabetes. Herein, we have employed an untargeted mass spectrometry‐based approach to study age‐related protein changes in a healthy Sicilian plasma cohort including long‐lived individuals. This approach confirmed some of the previously known proteins correlated with age including fibulin‐1, dystroglycan, and gamma‐glutamyl hydrolase. Furthermore, our findings include novel proteins that correlate with age and/or with location and uric acid, which could represent a unique signature for healthy aging.

Elevated Expression of Gamma-Glutamyl Hydrolase Is Associated With Poor Prognosis and Altered Immune Signature in Uterine Corpus Endometrial Carcinoma.

Uterine corpus endometrial carcinoma (UCEC) is a common malignant tumor of the female reproductive system with poor prognosis in advanced, recurrent, and metastatic cases. Identification of reliable molecular markers will help in the development of clinical strategies for early detection, diagnosis, and intervention. Gamma-glutamyl hydrolase (GGH) is a key enzyme in folate metabolism pathway. High expression of GGH is associated with severe clinicopathological features and poor prognosis of several cancers. High GGH expression is also related to cell resistance to antifolate drugs such as methotrexate. In this study we focused on the prognostic value of immunohistochemical GGH expression level in UCEC tissue and RNA-seq data from The Cancer Genome Atlas to establish associations with clinical features and outcomes. Further, we conducted comprehensive bioinformatics analyses to identify and functionally annotate differentially expressed genes (DEGs) associated with UCEC upregulation and assessed the effects of upregulation on immune infiltration. Both GGH mRNA and protein expression levels were elevated in tumor tissues, and higher expression was significantly associated with advanced clinicopathological features and poor prognosis by univariate analysis. Further multivariate analysis identified elevated GGH expression as an independent risk factor for poor outcome. Nomograms including GGH expression yielded a c-index for disease-specific survival prediction of 0.884 (95% confidence interval: 0.861–0.907). A total of 520 DEGs (111 upregulated and 409 downregulated) were identified between high and low GGH expression groups. Analysis using Gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway, Gene set enrichment analysis, and protein‒protein interaction indicated significant associations of altered GGH expression with cell proliferation, immune response, and the occurrence and development of UCEC tumors. Finally, GGH expression level was associated with high Th2 cell and low natural killer CD56bright cell infiltration. Collectively, these findings indicate that GGH drives UCEC progression and could be a useful biomarker for survival prediction as well as a therapeutic target.

Identification of Key Genes Associated with Changes in the Host Response to Severe Burn Shock: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database.

BackgroundPatients with severe burns continue to display a high mortality rate during the initial shock period. The precise molecular mechanism underlying the change in host response during severe burn shock remains unknown. This study aimed to identify key genes leading to the change in host response during burn shock.MethodsThe GSE77791 dataset, which was utilized in a previous study that compared hydrocortisone administration to placebo (NaCl 0.9%) in the inflammatory reaction of severe burn shock, was downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs). Functional enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed. The protein–protein interaction (PPI) network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and then visualized in Cytoscape. In addition, important modules in this network were selected using the Molecular Complex Detection (MCODE) algorithm, and hub genes were identified in cytoHubba, a Cytoscape plugin.ResultsA total of 1059 DEGs (508 downregulated genes and 551 upregulated genes) were identified from the dataset. The DEGs enriched in GO terms and KEGG pathways were related to immune response. The PPI network contained 439 nodes and 2430 protein pairs. Finally, important modules and hub genes were identified using the different Cytoscape plugins. The key genes in burn shock were identified as arginase 1 (ARG1), cytoskeleton-associated protein (CKAP4), complement C3a receptor (C3AR1), neutrophil elastase (ELANE), gamma-glutamyl hydrolase (GGH), orosomucoid (ORM1), and quiescin sulfhydryl (QSOX1).ConclusionThe DEGs, functional terms and pathways, and hub genes identified in the present study can help shed light on the molecular mechanism underlying the changes in host response during burn shock and provide potential targets for early detection and treatment of burn shock.

Identification of genes involved in inbreeding depression of reproduction in Langshan chickens.

ObjectiveInbreeding depression of reproduction is a major concern in the conservation of native chicken genetic resources. Here, based on the successful development of strongly inbred (Sinb) and weakly inbred (Winb) Langshan chickens, we aimed to evaluate inbreeding effects on reproductive traits and identify candidate genes involved in inbreeding depression of reproduction in Langshan chickens.MethodsA two-sample t-test was performed to estimate the differences in phenotypic values of reproductive traits between Sinb and Winb chicken groups. Three healthy chickens with reproductive trait values around the group mean values were selected from each of the groups. Differences in ovarian and hypothalamus transcriptomes between the two groups of chickens were analyzed by RNA sequencing (RNA-Seq).ResultsThe Sinb chicken group showed an obvious inbreeding depression in reproduction, especially for traits of age at the first egg and egg number at 300 days (p<0.01). Furthermore, 68 and 618 differentially expressed genes (DEGs) were obtained in the hypothalamus and ovary between the two chicken groups, respectively. In the hypothalamus, DEGs were mainly enriched in the pathways related to vitamin metabolism, signal transduction and development of the reproductive system, such as the riboflavin metabolism, Wnt signaling pathway, extracellular matrix-receptor interaction and focal adhesion pathways, including stimulated by retinoic acid 6, serpin family F member 1, secreted frizzled related protein 2, Wnt family member 6, and frizzled class receptor 4 genes. In the ovary, DEGs were significantly enriched in pathways associated with basic metabolism, including amino acid metabolism, oxidative phosphorylation, and glycosaminoglycan degradation. A series of key DEGs involved in folate biosynthesis (gamma-glutamyl hydrolase, guanosine triphosphate cyclohydrolase 1), oocyte meiosis and ovarian function (cytoplasmic polyadenylation element binding protein 1, structural maintenance of chromosomes 1B, and speedy/RINGO cell cycle regulator family member A), spermatogenesis and male fertility (prostaglandin D2 synthase 21 kDa), Mov10 RISC complex RNA helicase like 1, and deuterosome assembly protein 1) were identified, and these may play important roles in inbreeding depression in reproduction.ConclusionThe results improve our understanding of the regulatory mechanisms underlying inbreeding depression in chicken reproduction and provide a theoretical basis for the conservation of species resources.

The complexity of folate polyglutamylation in plants: Postharvest ripening and ethylene modulate polyglutamylated profiles in climacteric fruits plus systematic analysis of the glutamyl tail-editing enzymes

Folate derivatives exist in nature in a variety of polyglutamyl forms (Glun); the glutamyl tail is added to the folate molecule by folylpolyglutamate synthetase (FPGS), and removed by gamma-glutamyl hydrolase (GGH) isoforms in several compartments within the cell. Folate polyglutamylation affects the use of the folate cofactors and their transport in organisms, also impacting their bioavailability as vitamins in mammals; however, little is known about its regulation in plants. We explored the possible effect of genetic, developmental, and environmental factors on the Glun extent of the most prevalent folate in plants, 5-CH3-THF. We chose ripening and ethylene treatment in climacteric fruits, to assess developmental and environmental factors. Postharvest ripening increased short Glun tails, and ethylene gassing affected negatively long Glun tails. To evaluate genetic factors, we retrieved and compared the deduced FPGS and GGH sequences from 27 plants with known Glun profile and attempted to correlate their phylogenetic relation, number of isoforms, predicted localization, and primary sequence with the Glun profiles generated and gathered by this study. GGH sequences were quite conserved among plants, while FPGS diverged more. We postulate that the very long Glun tail found only in papaya is the result of very particular changes in one of the FPGS’s primary structure.

Gamma-glutamyl hydrolase gene polymorphisms – another way to predict methotrexate efficacy in rheumatoid arthritis

The current treatment strategy for rheumatoid arthritis has been formulated within the framework of the European League Against Rheumatism (EULAR) concept “Treatment to achieve the goal”. Methotrexate prescribed as soon as possible after verifying rheumatoid arthritis is recognized as a first-line drug that allows to achieve disease remission and prevent destructive changes in the joints. Long-term clinical experience of using methotrexate allowed to conclude that almost 30% patients with rheumatoid arthritis turn out to be resistant to such treatment, enforcing to change the basal anti-inflammatory therapy, shift to using targeted or genetically engineered biological drugs, so that timeframe to prevent disease progression can be irreversibly lost. In the last decade, genetic testing for drug therapy effectiveness has been gaining momentum based on individual features in functioning of enzyme systems which regulate various stages of drug biotransformation. To date, a personalized approach to treatment of rheumatoid arthritis may be implemented after examining more than a dozen of single nucleotide polymorphisms (SNPs) within the folate cycle genes responsible for metabolizing methotrexate as well as its mechanism of action. In our work, we attempted to test a relationship between therapeutic response (efficacy and resistance) to methotrexate and -401CT (rs 3758149) SNP in the GGH (gamma-glutamyl hydrolase) gene, which coordinates the processes of extracellular methotrexate transport. A groups patients consisted of 85 basic anti-inflammatory therapy-naïve patients diagnosed with rheumatoid arthritis, who were initially treated with methotrexate at a dose of 10 to 17.5 mg per week, with subsequently assessed therapeutic efficacy 6 months after the treatment onset based on dynamics in DAS28 index that allowed to identify groups of “responders” and “non-responders”. Next, all patients from select groups underwent molecular genetic typing for GGH-401CT SNP by using real-time polymerase chain reaction. Our study allowed to find that prevalence of the TT homozygous genotype (OR = 5.09; 95% CI 1.11- 23.3; p = 0.037) dominated in “methotrexate non-responders”, whereas “methotrexate responders” tended to have higher C allele frequency (OR = 0.54; 95% CI 0.27-1.01; p = 0.087), which allowed to identify them by genetic predictors of methotrexate therapeutic response in rheumatoid arthritis.

Novel circulating protein biomarkers for thyroid cancer determined through data-independent acquisition mass spectrometry.

BackgroundDistinguishing between different types of thyroid cancers (TC) remains challenging in clinical laboratories. As different tumor types require different clinical interventions, it is necessary to establish new methods for accurate diagnosis of TC.MethodsProteomic analysis of the human serum was performed through data-independent acquisition mass spectrometry for 29 patients with TC (stages I–IV): 13 cases of papillary TC (PTC), 10 cases of medullary TC (MTC), and six cases follicular TC (FTC). In addition, 15 patients with benign thyroid nodules (TNs) and 10 healthy controls (HCs) were included in this study. Subsequently, 17 differentially expressed proteins were identified in 291 patients with TC, including 247 with PTC, 38 with MTC, and six with FTC, and 69 patients with benign TNs and 176 with HC, using enzyme-linked immunosorbent assays.ResultsIn total, 517 proteins were detected in the serum samples using an Orbitrap Q-Exactive-plus mass spectrometer. The amyloid beta A4 protein, apolipoprotein A-IV, gelsolin, contactin-1, gamma-glutamyl hydrolase, and complement factor H-related protein 1 (CFHR1) were selected for further analysis. The median serum CFHR1 levels were significantly higher in the MTC and FTC groups than in the PTC and control groups (P < 0.001). CFHR1 exhibited higher diagnostic performance in distinguishing patients with MTC from those with PTC (P < 0.001), with a sensitivity of 100.0%, specificity of 85.08%, area under the curve of 0.93, and detection cut-off of 0.92 ng/mL.ConclusionCFHR1 may serve as a novel biomarker to distinguish PTC from MTC with high sensitivity and specificity.

Frequency distribution of five SNPs in human GGH gene and their effects on clinical outcomes of Chinese pediatric patients with acute lymphoblastic leukemia.

Methotrexate (MTX) is widely used in the treatment of childhood acute lymphoblastic leukemia (ALL). Gamma-glutamyl hydrolase (GGH) plays an important role in the disposition of MTX. The aim of this study was to investigate the frequency distribution of five SNPs in the human GGH gene and their effects on serum MTX concentrations and clinical outcomes in Chinese children with ALL. Genotyping of 149 pediatric patients for GGH rs11545078 C>T, rs11545077 G>A, rs1800909 T>C, rs11545076 T>G, and rs3758149 C>T was performed using the Sequenom MassARRAY system. Serum MTX concentrations were determined using a fluorescence polarization immunoassay. The five SNPs studied were in strong linkage. The minor allele frequencies for rs11545078, rs11545077, rs1800909, rs11545076, and rs3758149 were 5.3, 15.0, 14.3, 15.0, and 15.0%, respectively. Four haplotypes (CGTTC, CACGT, TACGT, and TATGT) were observed at frequencies of 84.9, 9.8, 4.5, and 0.8%, respectively. The median C/D ratios of serum MTX at 24 h and 42 h in children with variant haplotypes (12.30 and 0.08 μmol/L per g/m², respectively) were higher than those in wild haplotype carriers (11.85 and 0.07 μmol/L per g/m², respectively). The event-free survival of patients with variant haplotypes (89.2%) was significantly better than that of patients with wild haplotypes (71.9%, P < 0.05). The relapse rate in children with variant haplotypes (8.1%) was lower than that in children with wild haplotypes (15.6%). These findings have implications for the efficacious use of MTX in childhood ALL patients.

High gamma-glutamyl hydrolase and low folylpolyglutamate synthetase expression as prognostic biomarkers in patients with locally advanced gastric cancer who were administrated postoperative adjuvant chemotherapy with S-1

PurposeThe enzymes gamma-glutamyl hydrolase (GGH) and folylpolyglutamate synthetase (FPGS) regulate intracellular folate concentrations needed for cell proliferation, DNA synthesis, and repair. High GGH expression affects 5-FU thymidylate synthase (TS) inhibition and is a risk factor for various malignancies. Here, the clinical significance of GGH and FPGS expression was investigated in Stage II/III gastric cancer patients undergoing postoperative adjuvant chemotherapy with S-1.MethodsSurgical specimens of cancer tissue and adjacent normal mucosa, obtained from 253 patients with previously untreated gastric cancer, were examined. GGH and FPGS mRNA expression was measured by qPCR to evaluate their clinicopathological significance in gastric cancer patients after curative resection.ResultsWhile FPGS expression showed no significant differences between the cancerous and normal samples, GGH expression was higher in cancer tissue than in adjacent normal mucosa. High GGH expression was correlated with age, histological type, and vascular invasion. Overall survival (OS) of patients with high GGH mRNA expression was significantly poorer than of patients with low GGH expression. Multivariate analysis showed that high GGH expression was an independent prognostic factor of OS (HR: 2.58, 95% CI 1.29–5.16). Patients who received S-1 adjuvant treatment showed a significantly poor OS between high GGH/low FPGS and low GGH/high FPGS. Patients without adjuvant treatment showed no significant difference.ConclusionGGH expression was significantly higher in gastric cancer tissue than in adjacent normal mucosa. High GGH and low FPGS expression is a useful independent predictor of poor outcomes in stage II/III gastric cancer patients undergoing postoperative adjuvant chemotherapy with S-1.

Proteomic Changes in Human Sperm During Sequential in vitro Capacitation and Acrosome Reaction.

The male gamete is not completely mature after ejaculation and requires further events in the female genital tract to acquire fertilizing ability, including the processes of capacitation and acrosome reaction. In order to shed light on protein changes experienced by the sperm cell in preparation for fertilization, a comprehensive quantitative proteomic profiling based on isotopic peptide labeling and liquid chromatography followed by tandem mass spectrometry was performed on spermatozoa from three donors of proven fertility under three sequential conditions: purification with density gradient centrifugation, incubation with capacitation medium, and induction of acrosome reaction by exposure to the calcium ionophore A23187. After applying strict selection criteria for peptide quantification and for statistical analyses, 36 proteins with significant changes in their relative abundance within sperm protein extracts were detected. Moreover, the presence of peptide residues potentially harboring sites for post-translational modification was revealed, suggesting that protein modification may be an important mechanism in sperm maturation. In this regard, increased levels of proteins mainly involved in motility and signaling, both regulated by protein modifiers, were detected in sperm lysates following incubation with capacitation medium. In contrast, less abundant proteins in acrosome-reacted cell lysates did not contain potentially modifiable residues, suggesting the possibility that all those proteins might be relocated or released during the process. Protein-protein interaction analysis revealed a subset of proteins potentially involved in sperm maturation, including the proteins Erlin-2 (ERLIN2), Gamma-glutamyl hydrolase (GGH) and Transmembrane emp24 domain-containing protein 10 (TMED10). These results contribute to the current knowledge of the molecular basis of human fertilization. It should now be possible to further validate the potential role of the detected altered proteins as modulators of male infertility.

The role of transcription factor Sp1 in the regulation of gamma-glutamyl hydrolase gene expression by the rs3758149 polymorphism in CEM/C1 cells.

Gamma-Glutamyl hydrolase (GGH) plays an important role in the disposition of anti-folate analogs. Several studies noted the pharmacological relevance of rs3758149 C/T polymorphism located in the human GGH promoter. The present study aimed to investigate the role of rs3758149 C/T polymorphism and transcription factors in the regulation of GGH expression in human acute lymphoblastic leukemia (ALL) CEM/C1 cells. Compared with the rs3758149 T allele, the C allele showed significantly higher transcriptional activity in luciferase reporter assays, as well as a stronger binding affinity for the nuclear protein extracts in an electrophoretic mobility shift assay. Sp1 was identified as the target transcription factor that exhibited allele-specific binding to the location of rs3758149 C/T polymorphism in the chromatin immunoprecipitation assay. Overexpression of Sp1 led to enhanced GGH promoter activity and GGH mRNA expression in allele-specific manners. These findings suggested that Sp1 acted as a positive regulator of human GGH transcription through the rs3758149 polymorphism in CEM/C1 cells. This study contributed to the present understanding of the mechanisms underlying variable responses of ALL to anti-folates.

Rationale and preclinical development of LEAF-1401 and LEAF-1701: A novel class of potent next generation antifolates.

e14515 Background: Polyglutamation of antifolates by folylpolyglutamate synthase (FPGS) greatly enhances their activity, e.g. pentaglutamated pemetrexed is 80-fold more potent at inhibiting thymidylate synthase than pemetrexed. Polyglutamated antifolates however, do not readily cross the cell membrane, due to high negative charge and molecular mass. The resulting poor intracellular bioavailability greatly limits their therapeutic potential. Gamma glutamyl hydrolase (GGH) enzyme removes the glutamate residues from polyglutamates, which then are subject to efflux pumps. Resistance to pemetrexed has been linked to downregulation of both FPGS and folate transporters and upregulation of both GGH and the efflux pumps. We have been developing a novel class of nanoliposomal polyglutamated-antifolates including: LEAF-1401; nanoliposomal gamma-L pentaglutamated antifolate LEAF-1701; nanoliposomal alpha-L pentaglutamated antifolate These were designed to address key challenges of currently used antifolates namely: Bypassing the need for intracellular endogenous FPGS Direct delivery of the much more active polyglutamates through nanoliposome technology Minimizing toxicity to normal cells Mitigating against key antifolate resistance mechanisms such as downregulation of FPGS and folate transporters, and upregulation of GGH and efflux pumps Methods: In vitro testing in cell lines and in vivo testing in mice were performed using LEAF-1701 and LEAF-1401 in various tumor types. Results: Compared to pemetrexed: In vitro, LEAF-1701 and LEAF-1401 were more potent, in various cell lines while sparing normal neutrophils, colon and liver cells. In vivo, in H292 lung cancer xenografts, treatment with LEAF-1701 improved survival to 59 days vs 39 days for pemetrexed. In A549 lung cancer mouse orthotopic models, treatment with LEAF-1401 reduced metastatic tumor burden and prevented new metastases. In vivo, in mice doses of up to 80 mg/kg IV weekly were tolerated with little impact on blood counts and chemistry. Conclusions: LEAF-1701 and LEAF-1401 are innovative new chemical entities with promising preclinical activity and improved safety profiles and are now advancing to the clinic.