CA19-9 Level to Serum γ-Glutamyltransferase as a Potential Prognostic Biomarker in Patients with Pancreatic Head Carcinoma

GGT5 facilitates migration and invasion through the induction of epithelial-mesenchymal transformation in gastric cancer

BACKGROUND

Gamma-glutamyltransferase 5 (GGT5), one of the two members in the GGT family (GGT1 and GGT5), plays a crucial role in oxidative regulation, inflammation promotion, and drug metabolism. Particularly in the tumorigenesis of various cancers, its significance has been recognized. Nevertheless, GGT5's role in gastric cancer (GC) remains ambiguous. This study delves into the function and prognostic significance of GGT5 in GC through a series of in vitro experiments.

METHODS

Employing online bioinformatics analysis tools such as The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Kaplan-Meier plotter, and cBioPortal, we explored GGT5 characteristics and functions in GC. This encompassed aberrant expression, prognostic value, genomic alterations and mutations, immune cell infiltration, and associated signaling pathways. Immunohistochemistry was conducted to assess GGT5 expression in GC and adjacent normal tissues. Subsequently, univariate and multivariate logistic regression analyses were applied to investigate the associations between GGT5 and clinical characteristics. CCK8, wound healing, and migration assays were utilized to evaluate the impact of GGT5 on cell viability and migration. Additionally, Gene Set Enrichment Analysis (GSEA) and Western blot analysis were performed to scrutinize the activity of the epithelial-mesenchymal transformation (EMT) signaling pathway under GGT5 regulation.

RESULTS

GGT5 exhibits upregulation in gastric cancer, with its overexpression significantly linked to histological differentiation in GC patients (P < 0.05). Multivariate analysis indicates that elevated GGT5 expression is an independent risk factor associated with poorer overall survival in gastric cancer patients (P < 0.05). In vitro experiments reveal that downregulation of GGT5 hampers the proliferation and migration of GC cell lines. Finally, GSEA using TCGA data highlights a significant correlation between GGT5 expression and genes associated with EMT, a finding further confirmed by Western blot analysis.

CONCLUSIONS

GGT5 emerges as a promising prognostic biomarker and potential therapeutic target for GC.

Predicting the unpredictable: a robust nomogram for predicting recurrence in patients with ampullary carcinoma

OBJECTIVE

To screen the risk factors affecting the recurrence risk of patients with ampullary carcinoma (AC)after radical resection, and then to construct a model for risk prediction based on Lasso-Cox regression and visualize it.

METHODS

Clinical data were collected from 162 patients that received pancreaticoduodenectomy treatment in Hebei Provincial Cancer Hospital from January 2011 to January 2022. Lasso regression was used in the training group to screen the risk factors for recurrence. The Lasso-Cox regression and Random Survival Forest (RSF) models were compared using Delong test to determine the optimum model based on the risk factors. Finally, the selected model was validated using clinical data from the validation group.

RESULTS

The patients were split into two groups, with a 7:3 ratio for training and validation. The variables screened by Lasso regression, such as CA19-9/GGT, AJCC 8th edition TNM staging, Lymph node invasion, Differentiation, Tumor size, CA19-9, Gender, GPR, PLR, Drinking history, and Complications, were used in modeling with the Lasso-Cox regression model (C-index = 0.845) and RSF model (C-index = 0.719) in the training group. According to the Delong test we chose the Lasso-Cox regression model (P = 0.019) and validated its performance with time-dependent receiver operating characteristics curves(tdROC), calibration curves, and decision curve analysis (DCA). The areas under the tdROC curves for 1, 3, and 5 years were 0.855, 0.888, and 0.924 in the training group and 0.841, 0.871, and 0.901 in the validation group, respectively. The calibration curves performed well, as well as the DCA showed higher net returns and a broader range of threshold probabilities using the predictive model. A nomogram visualization is used to display the results of the selected model.

CONCLUSION

The study established a nomogram based on the Lasso-Cox regression model for predicting recurrence in AC patients. Compared to a nomogram built via other methods, this one is more robust and accurate.

Gamma-glutamyltransferase-associated glycoprotein patterns in human seminal plasma of normozoospermic men: a new aspect of biomarker heterogeneity

BACKGROUND

Gamma-glutamyltransferase (GGT) is a well-known laboratory biomarker. In spite of high concentration and the possible biomedical importance of estimating GGT in human seminal plasma (hSP), it has not been widely explored in reproductive physiology. This study aimed to complement existing data on its diversity, previously obtained on seminal extracellular vesicles, by analyzing matched soluble fraction of hSP. The GGT-associated patterns of selected glycoproteins were analyzed in order to establish an adjunct referent parameter for differentiation between known high molecular mass forms of GGT. Getting insight into distinct GGT-associated glycoprotein patterns should contribute to define them together as possible multimarkers.

METHODS

GGT forms in soluble, membrane-free-fraction isolated form hSP of normozoospermic men were analyzed using gel filtration and lectin blotting using WGA (wheat germ agglutinin) and Con A (concanavalin A).

RESULTS

Widely distributed GGT (with two to three partially resolved peaks), which may correspond to high molecular mass aggregates, were detected. GGT-associated patterns of selected glycoproteins (at position of big, medium, and small-GGT) all comprised high molecular mass WGA-reactive smears, but differed in the presence of Con A-reactive glycans, as well as mucin-associated antigens CA19-9 and CA125.

CONCLUSIONS

GGT contributes to several molecular patterns that differ between the soluble and extracellular vesicle fractions of hSP. Their glycobiochemical heterogeneity is due to difference in the presence of distinct sialylated and mannosylated glycans. Moreover, GGT-associated glycoprotein patterns differentiate between high molecular mass forms of GGT in the soluble fraction of hSP. They hold promise as possible targets for increasing biomarker potential of GGT.

Identification of GGT5 as a Novel Prognostic Biomarker for Gastric Cancer and its Correlation With Immune Cell Infiltration

Gastric cancer (GC) is a common malignant tumor of the digestive system. Recent studies revealed that high gamma-glutamyl-transferase 5 (GGT5) expression was associated with a poor prognosis of gastric cancer patients. In the present study, we aimed to confirm the expression and prognostic value of GGT5 and its correlation with immune cell infiltration in gastric cancer. First, we compared the differential expression of GGT5 between gastric cancer tissues and normal gastric mucosa in the cancer genome atlas (TCGA) and GEO NCBI databases using the most widely available data. Then, the Kaplan-Meier method, Cox regression, and univariate logistic regression were applied to explore the relationships between GGT5 and clinical characteristics. We also investigated the correlation of GGT5 with immune cell infiltration, immune-related genes, and immune checkpoint genes. Finally, we estimated enrichment of gene ontologies categories and relevant signaling pathways using GO annotations, KEGG, and GSEA pathway data. The results showed that GGT5 was upregulated in gastric cancer tissues compared to normal tissues. High GGT5 expression was significantly associated with T stage, histological type, and histologic grade (p < 0.05). Moreover, gastric cancer patients with high GGT5 expression showed worse 10-years overall survival (p = 0.008) and progression-free intervals (p = 0.006) than those with low GGT5 expression. Multivariate analysis suggested that high expression of GGT5 was an independent risk factor related to the worse overall survival of gastric cancer patients. A nomogram model for predicting the overall survival of GC was constructed and computationally validated. GGT5 expression was positively correlated with the infiltration of natural killer cells, macrophages, and dendritic cells but negatively correlated with Th17 infiltration. Additionally, we found that GGT5 was positively co-expressed with immune-related genes and immune checkpoint genes. Functional analysis revealed that differentially expressed genes relative to GGT5 were mainly involved in the biological processes of immune and inflammatory responses. In conclusion, GGT5 may serve as a promising prognostic biomarker and a potential immunological therapeutic target for GC, since it is associated with immune cell infiltration in the tumor microenvironment.