Prediction of progression of chronic atrophic gastritis with Helicobacter pylori and poor prognosis of gastric cancer by CYP3A4

Coding RNA expression profile and transcription factor analysis of H.pylori-associated chronic atrophic gastritis

PURPOSE

Atrophic gastritis, one of the processes leading to gastric cancer (GC), is closely related to Helicobacter pylori (HP) infection. This study aimed to understand how HP causes chronic inflammation that leads to ulcers and stomach problems.

METHODS

Twenty-eight CAG patients were included in the study (9 HP-infected and 19 HP-uninfected). Endoscopy, histopathology, and high-throughput mRNA sequencing were performed. Differentially expressed genes (DEGs) were validated via qRT-PCR.

RESULTS

Principal component analysis (PCA) results showed that more than 88.9 ​% of the samples were classified into the HP (+) group. A total of 157 DEGs were identified, of which 38 were up-regulated and 119 were down-regulated. The DEGs were mainly enriched in the biological process (BP) terms associated with immune system process, adaptive immune response, G protein-coupled receptor signaling pathway, as well as point to numerous key pathways, including fat digestion and absorption, retinol metabolism, steroid hormone biosynthesis, ascorbate and aldarate metabolism, and chemical carcinogenesis. APOA1, APOA4, FOXP3, NR1H4, ABCG5, ACTA1, CCL19, CCR7, CYP3A4, and PDCD had the highest degrees in protein-protein interaction network as the hub genes; they were also included into the transcription factor (TF)-target network except for PDCD. APOA1 and CYP3A4 were extremely significantly up-regulated in HP (+) CAG patients compared with the HP (-) CAG patients, while FOXP3, CCR7 and CCL19 were significantly down-regulated.

CONCLUSION

The expression of APOA1, CYP3A4, FOXP3, CCR7, and CCL19 are the potential indicators for CAG to GC development, being the biomarkers to predict progression of CAG and poor prognosis of GC.

GADD45B regulates the carcinogenesis process of chronic atrophic gastritis and the metabolic pathways of gastric cancer

Background

Gastric cancer continues to be a significant global healthcare challenge, and its burden remains substantial. The development of gastric cancer (GC) is closely linked to chronic atrophic gastritis (CAG), yet there is a scarcity of research exploring the underlying mechanisms of CAG-induced carcinogenesis.

Methods

In this study, we conducted a comprehensive investigation into the oncogenes involved in CAG using both bulk transcriptome and single-cell transcriptome data. Our approach employed hdWGCNA to identify pathogenic genes specific to CAG, with non-atrophic gastritis (NAG) serving as the control group. Additionally, we compared CAG with GC, using normal gastric tissue as the control group in the single-cell transcriptome analysis. By intersecting the identified pathogenic genes, we pinpointed key network molecules through protein interaction network analysis. To further refine the gene selection, we applied LASSO, SVM-RFE, and RF techniques, which resulted in a set of cancer-related genes (CRGs) associated with CAG. To identify CRGs potentially linked to gastric cancer progression, we performed a univariate COX regression analysis on the gene set. Subsequently, we explored the relationship between CRGs and immune infiltration, drug sensitivity, and clinical characteristics in gastric cancer patients. We employed GSVA to investigate how CRGs regulated signaling pathways in gastric cancer cells, while an analysis of cell communication shed light on the impact of CRGs on signal transmission within the gastric cancer tumor microenvironment. Lastly, we analyzed changes in metabolic pathways throughout the progression of gastric cancer.

Results

Using hdWGCNA, we have identified a total of 143 pathogenic genes that were shared by CAG and GC. To further investigate the underlying mechanisms, we conducted protein interaction network analysis and employed machine learning screening techniques. As a result, we have identified 15 oncogenes that are specifically associated with chronic atrophic gastritis. By performing ROC reanalysis and prognostic analysis, we have determined that GADD45B is the most significant gene involved in the carcinogenesis of CAG. Immunohistochemical staining and differential analysis have revealed that GADD45B expression was low in GC tissues while high in normal gastric tissues. Moreover, based on prognostic analysis, high expression of GADD45B has been correlated with poor prognosis in GC patients. Additionally, an analysis of immune infiltration has shown a relationship between GADD45B and the infiltration of various immune cells. By correlating GADD45B with clinical characteristics, we have found that it primarily affects the depth of invasion in GC. Through cell communication analysis, we have discovered that the CD99 signaling pathway network and the CDH signaling pathway network are the main communication pathways that significantly alter the microenvironment of gastric tissue during the development of chronic atrophic gastritis. Specifically, GADD45B-low GC cells were predominantly involved in the network communication of the CDH signaling pathway, while GADD45B-high GC cells played a crucial role in both signaling pathways. Furthermore, we have identified several metabolic pathways, including D-Glutamine and D-glutamate metabolism and N-Glycan biosynthesis, among others, that played important roles in the occurrence and progression of GC, in addition to the six other metabolic pathways. In summary, our study highlighted the discovery of 143 pathogenic genes shared by CAG and GC, with a specific focus on 15 oncogenes associated with CAG. We have identified GADD45B as the most important gene in the carcinogenesis of CAG, which exhibited differential expression in GC tissues compared to normal gastric tissues. Moreover, GADD45B expression was correlated with patient prognosis and is associated with immune cell infiltration. Our findings also emphasized the impact of the CD99 and CDH signaling pathway networks on the microenvironment of gastric tissue during the development of CAG. Additionally, we have identified key metabolic pathways involved in GC progression.

Conclusion

GADD45B, an oncogene implicated in chronic atrophic gastritis, played a critical role in GC development. Decreased expression of GADD45B was associated with the onset of GC. Moreover, GADD45B expression levels were closely tied to poor prognosis in GC patients, influencing the infiltration patterns of various cells within the tumor microenvironment, as well as impacting the metabolic pathways involved in GC progression.

Therapeutic Effect of Curcumol on Chronic Atrophic Gastritis (CAG) and Gastric Cancer Is Achieved by Downregulating SDF-1α/CXCR4/VEGF Expression

CAG is an essential procession of the transformation from gastritis into gastric cancer. A series of timely moves of diagnosis, treatment, and monitoring towards CAG to anticipate the potential population at risk of gastric cancer is an effective means to prevent gastric cancer occurrence. The main active monomer in Fuzheng Huowei Decoction is Curcumol, which is an indispensable ingredient in the treatment to CAG and gastric cancer. In this study, the CAG model, in vitro cultured gastric cancer cells, and participating nude mice were treated with Curcumol, and alterations in SDF-1α/CXCR4/VEGF expression were estimated using the assays of immunohistochemistry and Western blot. MTT, flow cytometry, transwell, HE staining, and tumor volume determination were applied for the verification of the regulatory effects of Curcumol on CAG and gastric cancer cells. The results showed that the expressions of VEGF, SDF-1α, CXCR4, and CD34 decreased in our CAG model with Curcumol treatment. Curcumol is in procession of an inhibitory effect toward the activity, migration, and invasion of gastric cancer cells, and it would also result in gastric cancer cells' apoptosis. We subsequently added SDF-1α overexpressing lentivirus to the Curcumol-treated group and found that the expressions of SDF-1α, CXCR4, and VEGF protein increased, and the inhibitory effect of Curcumol on gastric cancer cells was withdrawn. Our nude mouse experiment showed that Curcumol + SDF-1α group ended up with the largest tumor volume, while Fuzheng Huowei + NC group was with the smallest tumor volume. In conclusion, Curcumol is able to effectively protect the gastric tissue and suppress gastric cancer cells' viability. Curcumol functions as a therapeutic factor in chronic atrophic gastritis and gastric cancer by downregulating SDF-1α/CXCR4/VEGF expression.

The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics

Objective

Gastric cancer is among the most common malignant tumors of the digestive system. This study explored the molecular mechanisms and potential therapeutic targets for gastric cancer occurrence and progression using bioinformatics.

Methods

The gastric cancer microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. The R package was used for data mining and screening differentially expressed genes (DEGs). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Based on the protein-protein interaction (PPI) network analysis, core targets and core subsets were screened. Then, the relationship between the expression level of the core genes and the prognosis of gastric cancer patients was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) database.

Results

Using the GSE19826 and GSE54129 datasets, a total of 550 DEGs were identified, including 248 upregulated and 302 downregulated genes. GO and KEGG analyses showed that the upregulated DEGs were mainly enriched in the extracellular matrix (ECM) organization of the biological process (BP), the collagen-containing ECM of cellular component (CC), and the ECM structural constituent of molecular function (MF). DEGs were also enriched in human papillomavirus infections, the focal adhesion pathway, PI3K-Akt signaling pathway, and among others. The downregulated DEGs were mainly enriched in digestion, basal part of the cell, and aldo-keto reductase (NADP) activity. And the above pathways were enriched primarily in the metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450, and retinol metabolism. Five core genes, including COL1A2, COL3A1, BGN, FN1, and VCAN, were significantly highly expressed in gastric cancer patients and were associated with poor prognosis.

Conclusion

This study identified new potential molecular targets closely related to gastric cancer occurrence and development via mining public data using bioinformatics analysis methods.

Identifying the Mechanisms of Rosa Roxburghii Tratt on Treating Gastric Cancer: Combining the Targetable Screening From the Cancer Genome Atlas With Network Pharmacology

The Chinese herbal medicine Rosa roxburghii Tratt (RRT) is widely used in the treatment of malignant tumors, including gastric cancer (GC), but its pharmacological mechanism remains unclear. The purpose of this research was to identify the mechanisms of RRT on treating GC by using network pharmacology and molecular docking, combined with the analysis of differential expressed genes in GEO gene chips and TCGA database. We first defined the effective components of RRT and their potential targets for the treatment of GC, and identified core targets according to the topology analysis by constructing a protein-protein interaction network. Furthermore, molecular docking was used to verify the docking between the core active ingredients and the key targets. The results showed that the effect of RRT may be closely associated with multiple signal pathways, including pathways in cancer, phosphatidylinositol 3-kinase-AKT serine/threonine kinase (PI3K-Akt), tumor necrosis factor (TNF), hypoxia-inducible factor 1 (HIF-1), and mitogen-activated protein kinase (MAPK). It is suggested that RRT may play an effect by regulating hypoxia, improving the tumor microenvironment, inhibiting inflammatory reactions and promoting apoptosis. The mechanism of RRT in the treatment of GC is revealed here for the first time based on network pharmacology analysis, which may provide a new direction for further exploration of the mechanisms of RRT in the treatment of GC and a new perspective for research on anti-tumor drugs.

Exploring the Molecular Mechanism of Astragali Radix-Curcumae Rhizoma against Gastric Intraepithelial Neoplasia by Network Pharmacology and Molecular Docking

Background

Astragali Radix-Curcumae Rhizoma (ARCR), a classic drug pair, has been widely used for the treatment of gastric intraepithelial neoplasia (GIN) in China. However, the underlying mechanisms of this drug pair are still unknown. Thus, elucidating the molecular mechanism of ARCR for treating GIN is imperative.

Methods

The active components and targets of ARCR were determined from the TCMSP database, and the differentially expressed genes related to GIN were identified from the GSE130823 dataset. The protein-protein interaction (PPI) network and ARCR-active component-target-pathway network were constructed by STRING 11.0 and Cytoscape 3.7.2, respectively. In addition, a receiver operating characteristic curve (ROC) was conducted to verify the key targets, and enrichment analyses were performed using R software. Molecular docking was carried out to test the binding capacity between core active components and key targets.

Results

31 active components were obtained from ARCR, among which 22 were hit by the 51 targets associated with GIN. Gene Ontology (GO) functional enrichment analysis showed that biological process (BP), molecular function (MF), and cellular component (CC) were most significantly enriched in response to a drug, catecholamine binding, and apical part of the cell, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated ARCR against GIN through regulation of neuroactive ligand-receptor interaction, nitrogen metabolism, calcium signaling pathway, chemical carcinogenesis-receptor activation, drug metabolism, gap junction, and cancers. In the PPI network, 15 potential targets were identified, of which nine key targets were proven to have higher diagnostic values in ROC. Molecular docking revealed a good binding affinity of active components (quercetin, bisdemethoxycurcumin, and kaempferol) with the corresponding targets (CYP3A4, CYP1A1, HMOX1, DRD2, DPP4, ADRA2A, ADRA2C, NR1I2, and LGALS4).

Conclusion

This study revealed the active components and molecular mechanism by which ARCR treatment is effective against GIN through regulating multipathway, such as neuroactive ligand-receptor interaction, nitrogen metabolism, and calcium signaling pathway.

Construction and Validation of a Novel Prognostic Signature for Intestinal Type of Gastric Cancer

Background

Intestinal type of gastric cancer (IGC) is the largest subtype of gastric cancer (GC) by Lauren classification. The purpose of this present study was to construct a prognostic signature for IGC patients, based on the high-grade dysplasia (HGD) and IGC tissues, to improve and enhance the prognostic accuracy.

Methods

The microarray datasets and associated clinical characteristics of HGD and IGC were obtained from the Gene Expression Omnibus (GEO) database. Based on the differential expression analysis between HGD and IGC, the prognostic-related differential expression genes (DEGs) were identified in a training set by univariate COX regression analysis. The least absolute shrinkage and selection operator (LASSO) regression was used to construct an optimal prognostic signature. The enrichment analysis was performed by using Gene Set Enrichment Analysis (GSEA). The performance of the nomogram was assessed by the calibration curve and concordance index (C-index). The results were validated by using a testing set.

Results

We identified 35 prognostic-related DGEs in the training set. The nine-gene signature was established by LASSO analysis. The nine-gene signature was an independent risk factor in both the training and testing sets. The areas under the curve (AUC) values of receiver operating characteristic (ROC) analysis were 0.733 and 0.700 for the training and testing sets, respectively. In GSEA analysis, the gene expression in high-risk group was enriched in hedgehog signaling, epithelial mesenchymal transition, and angiogenesis. The nomogram for IGC showed good performance with C-index of 0.81 (95% CI: 0.76-0.86) and 0.70 (95% CI: 0.63-0.77) in the training and testing sets, respectively.

Conclusion

We identified and verified a nine-gene signature for the prognostic prediction of IGC patients, which might identify subgroups of IGC patients and select more suitable therapeutic options.

Extrahepatic cytochrome P450 epoxygenases: pathophysiology and clinical significance in human gastrointestinal cancers

Cytochrome P450 (CYP) epoxygenases, a multi-gene superfamily of heme-containing enzymes, are commonly known to metabolize endogenous arachidonic acid (AA) to epoxyeicosatrienoic acids (EETs). The role of CYPs is mostly studied in liver drugs metabolism, cardiac pathophysiology, and hypertension fields. Particularly, the biological functions of these enzymes have increasingly attracted a growing interest in cancer biology. Most published studies on CYPs in cancer have been limited to their role as drug metabolizing systems. The activity of these enzymes may affect drug pharmacokinetics and bioavailability as well as exogenous compounds turnover. Some CYP isoforms are selectively highly expressed in tumors, suggesting a potential mechanistic role in promoting resistance to chemotherapy. Majority of drugs elicit their effects in extrahepatic tissues whereby their metabolism can significantly determine treatment outcome. Nonetheless, the role of extrahepatic CYPs is not fully understood and targeting these enzymes as effective anti-cancer therapies are yet to be developed. This review article summarizes an up-to-date body of information from published studies on CYP enzymes expression levels and pathophysiological functions in human normal and malignant gastrointestinal (GI) tract tissues. Specifically, we reviewed and discussed the current research initiatives by emphasizing on the clinical significance and the pathological implication of CYPs in GI malignancies of esophagus, stomach, and colon.

Prognostic Score-based Clinical Factors and Metabolism-related Biomarkers for Predicting the Progression of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor representing more than 90% of primary liver cancer. This study aimed to identify metabolism-related biomarkers with prognostic value by developing the novel prognostic score (PS) model. Transcriptomic profiles derived from TCGA and EBIArray databases were analyzed to identify differentially expressed genes (DEGs) in HCC tumor samples compared with normal samples. The overlapped genes between DEGs and metabolism-related genes (crucial genes) were screened and functionally analyzed. A novel PS model was constructed to identify optimal signature genes. Cox regression analysis was performed to identify independent clinical factors related to prognosis. Nomogram model was constructed to estimate the predictability of clinical factors. Finally, protein expression of crucial genes was explored in different cancer tissues and cell types from the Human Protein Atlas (HPA). We screened a total of 305 overlapped genes (differentially expressed metabolism-related genes). These genes were mainly involved in "oxidation reduction," "steroid hormone biosynthesis," "fatty acid metabolic process," and "linoleic acid metabolism." Furthermore, we screened ten optimal DEGs (CYP2C9, CYP3A4, and TKT, among others) by using the PS model. Two clinical factors of pathologic stage (P < .001, HR: 1.512 [1.219-1.875]) and PS status (P <.001, HR: 2.259 [1.522-3.354]) were independent prognostic predictors by cox regression analysis. Nomogram model showed a high predicted probability of overall survival time, and the AUC value was 0.837. The expression status of 7 proteins was frequently altered in normal or differential tumor tissues, such as liver cancer and stomach cancer samples.We have identified several metabolism-related biomarkers for prognosis prediction of HCC based on the PS model. Two clinical factors were independent prognostic predictors of pathologic stage and PS status (high/low risk). The prognosis prediction model described in this study is a useful and stable method for novel biomarker identification.

Glutathione Peroxidase 8 as a Prognostic Biomarker of Gastric Cancer: An Analysis of The Cancer Genome Atlas (TCGA) Data

Background

Glutathione peroxidase 8 (GPX8) has previously been shown to play a role in Keshan disease. In the present study, we explored the prognostic relevance of GPX8 expression in patients with gastric cancer (GC) based upon The Cancer Genome Atlas (TCGA) data.

Material/Methods

We assessed the relationship between the expression of GPX8 and clinicopathological findings in GC patients via logistic regression analyses, Kruskal-Wallis tests, and Wilcoxon signed-rank tests. We further assessed the prognostic relevance of specific variables using Kaplan-Meier and Cox regression analyses. We lastly conducted gene set enrichment analyses (GSEA).

Results

We detected a significant association between elevated GPX8 levels and more advanced GC tumor stage (OR=5.92 for I vs. IV), as well as more advanced T (OR=22.91 for T1 vs. T4) and N classification (OR=1.82 for N0 vs. N3). We found worse prognosis in patients expressing high levels of GPX8 relative to those with lower expression of this gene (P=0.021). In a univariate analysis, we found high GPX8 expression was strongly correlated with worse OS (hazard ratio [HR]: 1.05; 95% confidence interval [CI]: 1.01–1.08; P=0.018), and multivariate analysis confirmed that GPX8 expression independently predicts GC patient OS (HR: 1.04; CI: 1.00–1.08, P=0.041). GSEA revealed that elevated GPX8 expression was associated with enrichment of pathways consistent with MAPK signaling, JAK/STAT signaling, TGF-β signaling, melanoma, and basal cell carcinoma.

Conclusions

The expression of GPX8 may have prognostic relevance, being positively associated with worse OS in GC patients.

Screening of long non-coding RNAs markers in plasma of children with chronic gastritis

Objective

The study aimed to detect and analyze long non-coding RNAs (lncRNAs) in plasma of children diagnosed with chronic gastritis, and to explore its biological functions and involved signaling pathways.

Methods

The plasma samples were collected from six children that were diagnosed with chronic gastritis by physical examination, gastroscopy, and pathological examination and six healthy children. The plasma samples were assayed for determining the expression profiles of lncRNA based upon the gen chip detection. The specific expression of lcnRNA in plasma of children with chronic gastritis was analyzed and its biological functions were speculated.

Results

Five lncRNAs (RP11-697M17.1, RP11-388M20.9, AFAP1-AS1, BC062758, and XLOC001406) were significantly up-regulated, and five lncRNAs (UNQ697, BX571672.5, CYP4F35P, ANKRD20A5P, and AL832737) were observed to be significantly down-regulated. The lncRNAs RP11-697M17.1, and UNQ697 were detected with the highest up-regulation and down-regulation, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that the up-regulated lncRNAs were significantly enriched in 20 signaling pathways such as phosphoinositide-3-kinase–protein kinase B (PI3K-Akt) pathway, and the down-regulated lncRNAs target genes were significantly enriched in 20 signaling pathways such as the metabolic pathway.

Conclusion

The analysis of the lncRNA expression profiles in plasma of children with chronic gastritis revealed that the lncRNA RP11-697M17.1, and lncRNA UNQ697 may act as plasma markers for predicting chronic gastritis in children.