GADD45B regulates the carcinogenesis process of chronic atrophic gastritis and the metabolic pathways of gastric cancer.
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ABSTRACT:
SUBMITTER: Xu W
PROVIDER: S-EPMC10441793 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature
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GADD45B regulates the carcinogenesis process of chronic atrophic gastritis and the metabolic pathways of gastric cancer.
Xu Wei W Jiang Tianxiao T Shen Kanger K Zhao Dongxu D Zhang Man M Zhu Wenxin W Liu Yunfei Y Xu Chunfang C
Frontiers in endocrinology 20230807
<h4>Background</h4>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.<h4>Methods</h4>In this study, we conducted a comprehensive investigation into the oncogenes involved in CAG using both bulk transcriptome and single-cell transcriptome data. ...[more]
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Project description:BackgroundGastric cancer (GC) is categorized as diffuse- and intestinal-type adenocarcinoma. Intestinal-type GC is associated with chronic gastritis, atrophic gastritis (AG), and intestinal metaplasia (IM), precursors of dysplastic changes. Diffuse-type GC is generally known to undergo de novo carcinogenesis and is not associated with chronic mucosal changes. However, clinically, AG and IM are frequently observed surrounding diffuse-type GC. This study aimed to evaluate the role of AG and IM in diffuse-type GC.MethodsWe retrospectively reviewed the data of patients undergoing surgery for early GC. We divided patients with diffuse-type GC into two groups according to the presence of AG and IM based on Kyoto classification of gastritis. The clinicopathological characteristics were compared between the groups.ResultsAmong patients with diffuse-type GC, 52.5% patients had AG and 18.4% had severe AG. With regard to IM, 42.1% patients had IM and 17.1% had severe IM. Diffuse-type GC combined with severe AG or IM showed larger tumor size and higher submucosal invasion rate than that without severe AG or IM. However, the lymph node metastasis (LNM) rate was not significantly different between the two groups. In multivariate analysis, severe AG or IM was not an independent risk factor for LNM.ConclusionsSevere AG or IM surrounding diffuse-type gastric cancer suggests a collapse of normal mucosal barriers and leads to the spread of cancer cells. Although the association between chronic mucosal changes and LNM is unclear, more caution is needed during endoscopy especially for complete resection of diffuse-type GC with these features.
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Project description:Gastric cancer is an important health problem because it is difficult to diagnose and treat in advanced stage. This makes that the prognosis of gastric cancer patients remains scarce. Currently it is known that the cause of gastric cancer is attributed to chronic infection with Helicobacter pylori. Its persistent infection leads to development of chronic atrophic gastritis that is considered as a predecessor stage of intestinal-type gastric cancer. The understanding of the alteration of molecular mechanisms during the early stages of the development of gastric cancer, and the identification of their potential biomarkers can allow a rapid diagnosis that leads to an improvement diagnosis and increase the patient’s prognosis. We analyzed gene expression profiles of patients with chronic atrophic gastritis and gastric cancer through microarray analysis, functional enrichment analysis and validation of gene expression by quantitative PCR. Gene expression profiles in patients with chronic atrophic gastritis showed molecular changes of the gastric mucosa, which leads to intestinal metaplasia and subsequently, gastric cancer. In gastric cancer the gene expression profile showed the stage of tumor progression, the product of these genes are potential biomarkers of early stages of cancer that can be potential therapeutic targets. Accordingly, the transcriptome analysis revealed several gene groups are related to development of chronic atrophic gastritis, some of which were inhibited in gastric cancer patients. The increased expression of CLDN1, CLDN7, OLFM4, c-Myc and MMP-9 genes in chronic atrophic gastritis and gastric cancer point outs to their use as promising biomarkers for the early diagnosis of gastric cancer.
2019-12-18 | GSE116312 | GEO
Project description:Chronic atrophic gastritis (CAG) is a very common gastritis and one of the major precursor lesions of gastric cancer, one of the most common cancers worldwide. The molecular mechanism underlying CAG is unclear, but its elucidation is essential for the prevention and early detection of gastric cancer and appropriate intervention. A combination of two-dimensional gel electrophoresis and mass spectrometry was used in the present study to analyze the differentially expressed proteins. Samples from 21 patients (9 females and 12 males; mean age: 61.8 years) were used. We identified 18 differentially expressed proteins in CAG compared with matched normal mucosa. Eight proteins were up-regulated and 10 down-regulated in CAG when compared with the same amounts of proteins in individually matched normal gastric mucosa. Two novel proteins, proteasome activator subunit 1 (PSME1), which was down-regulated in CAG, and ribosomal protein S12 (RPS12), which was up-regulated in CAG, were further investigated. Their expression was validated by Western blot and RT-PCR in 15 CAG samples matched with normal mucosa. The expression level of RPS12 was significantly higher in CAG than in matched normal gastric mucosa (P < 0.05). In contrast, the expression level of PSME1 in CAG was significantly lower than in matched normal gastric mucosa (P < 0.05). This study clearly demonstrated that there are some changes in protein expression between CAG and normal mucosa. In these changes, down-regulation of PSME1 and up-regulation of RPS12 could be involved in the development of CAG. Thus, the differentially expressed proteins might play important roles in CAG as functional molecules.
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Project description:BackgroundScreening for chronic atrophic gastritis (CAG) is crucial for the prevention and early detection of gastric cancer. Endoscopy is the main method of CAG diagnosis, with high training requirements and limited accuracy, making it difficult to popularize. The study attempts to improve the positive rate and accuracy of CAG screening through non-invasive testing.MethodsA total of 2564 patients who underwent gastroscopy were included in this study. The results of gastroscopic evaluation, histological biopsy results (including H. pylori biopsy), urea breath test (UBT) results, serum pepsinogen, and testosterone were statistically analyzed.ResultsWe found significant differences in the diagnosis of CAG between endoscopy and histological biopsy. Pepsinogen II and pepsinogen I/II ratio were more useful for the diagnosis of CAG compared with pepsinogen I. The risk of CAG was increased when pepsinogen II exceeded 11.05 μg/L, and the pepsinogen I/II ratio was less than 3.75. CAG positivity was higher in patients with positive H. pylori infection on UBT screening. In addition, higher levels of testosterone, SHBG and HSD17B2, and lower level of GNRH1 were found in CAG mucosa. Patients with high serum testosterone had a higher risk of CAG.ConclusionCAG screening should be combined with endoscopic evaluation, biopsy, and other non-invasive tests. Non-invasive tests include the combination of serum pepsinogen II protein and pepsinogen I/II ratio and high level of serum testosterone. UBT combined with serum pepsinogen testing may improve the positive rate of CAG and reduce gastric mucosal damage from multiple biopsies.
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Project description:BackgroundChronic atrophic gastritis (CAG) is a precancerous condition. It is not easy to detect CAG in endoscopy. Improving the detection rate of CAG under endoscopy is essential to reduce or interrupt the occurrence of gastric cancer. This study aimed to construct a deep learning (DL) model for CAG recognition based on endoscopic images to improve the CAG detection rate during endoscopy.MethodsWe collected 10,961 endoscopic images and 118 video clips from 4,050 patients. For model training and testing, we divided them into two groups based on the pathological results: CAG and chronic non-atrophic gastritis (CNAG). We compared the performance of four state-of-the-art (SOTA) DL networks for CAG recognition and selected one of them for further improvement. The improved network was called GAM-EfficientNet. Finally, we compared GAM-EfficientNet with three endoscopists and analyzed the decision basis of the network in the form of heatmaps.ResultsAfter fine-tuning and transfer learning, the sensitivity, specificity, and accuracy of GAM-EfficientNet reached 93%, 94%, and 93.5% in the external test set and 96.23%, 89.23%, and 92.37% in the video test set, respectively, which were higher than those of the three endoscopists.ConclusionsThe CAG recognition model based on deep learning has high sensitivity and accuracy, and its performance is higher than that of endoscopists.
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