Variants in <i><scp>CCK</scp></i> and <i><scp>CCKAR</scp></i> genes to susceptibility to biliary tract cancers and stones: A population‐based study in <scp>S</scp>hanghai, <scp>C</scp>hina

Xu, Hongmin; Hsing, Ann W.; Vogtmann, Emily; Chu, Lisa W.; Cheng, Jiulong; Gao, Jing; Tan, Yuting; Wang, Bingsheng; Shen, Ming-Chang; Gao, Yu‐Tang

doi:10.1111/jgh.12278

Cited by 13 publications

(8 citation statements)

References 22 publications

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“…Our study first described the upregulation of KNG1 and CCKAR in prostate cancer. Previous studies have described the presence of KNG1 and CCKAR as biomarkers of various types of cancer, such as thyroid cancer [36,37], liver cancer [38], ovarian cancer [39], and cholangiocarcinoma [40]. In different stages of PCa development and progression, especially in the process of hormone-sensitive PCa progressing to castration-resistant PCa, the proteomic alterations and transcriptomic data have significant differences in changes [41].…”

Section: Discussionmentioning

confidence: 99%

Construction of Potential Gene Expression and Regulation Networks in Prostate Cancer Using Bioinformatics Tools

Liu

et al. 2021

Oxidative Medicine and Cellular Longevity

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Objective. To identify the key genes involved in prostate cancer and their regulatory network. Methods. The dataset of mRNA/miRNA transcriptome sequencing was downloaded from The Cancer Genome Atlas/the Gene Expression Omnibus database for analysis. The “edgeR” package in the R environment was used to normalize and analyze differentially expressed genes (DEGs) and miRNAs (DEmiRNAs). First, the PANTHER online tool was used to analyze the function enrichment of DEGs. Next, a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape tools. Finally, miRNA-gene regulatory networks were constructed using the miRTarBase. Results. We identified 4339 important DEGs, of which 2145 were upregulated (Up-DEGs) and 2194 were downregulated (Down-DEGs). Functional enrichment analysis showed that the Up-DEGs were related to the immune system and the cell cycle in prostate cancer, whereas the Down-DEGs were related to the nucleic acid metabolic process and metabolism pathways. Twelve core protein clusters were found in the PPI network. Further, the constructed miRNA-gene interaction network showed that 11 downregulated miRNAs regulated 16 Up-DEGs and 22 upregulated miRNAs regulated 22 Down-DEGs. Conclusion. We identified 4339 genes and 70 miRNAs that may be involved in immune response, cell cycle, and other key pathways of the prostate cancer regulatory network. Genes such as BUB1B, ANX1A1, F5, HTR4, and MUC4 can be used as biomarkers to assist in the diagnosis and prognosis of prostate cancer.

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Section: Discussionmentioning

confidence: 99%

Construction of Potential Gene Expression and Regulation Networks in Prostate Cancer Using Bioinformatics Tools

Liu

et al. 2021

Oxidative Medicine and Cellular Longevity

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“…The gallstone connection has largely been recognized in highly unusual kindreds, in which this receptor was found to be misprocessed and defective (32). Of note, the vast majority of patients with gallstones, including those with cholesterol gallstones, have normal CCK1R and CCK (33,50).…”

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confidence: 99%

Impact of ursodeoxycholic acid on a CCK1R cholesterol-binding site may contribute to its positive effects in digestive function

Desai

Dong

Harikumar

et al. 2015

American Journal of Physiology-Gastrointestinal and Liver Physi

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Dysfunction of the type 1 cholecystokinin (CCK) receptor (CCK1R) as a result of increased gallbladder muscularis membrane cholesterol has been implicated in the pathogenesis of cholesterol gallstones. Administration of ursodeoxycholic acid, which is structurally related to cholesterol, has been shown to have beneficial effects on gallstone formation. Our aims were to explore the possible direct effects and mechanism of action of bile acids on CCK receptor function. We studied the effects of structurally related hydrophobic chenodeoxycholic acid and hydrophilic ursodeoxycholic acid in vitro on CCK receptor function in the setting of normal and elevated membrane cholesterol. We also examined their effects on a cholesterol-insensitive CCK1R mutant (Y140A) disrupting a key site of cholesterol action. The results show that, similar to the impact of cholesterol on CCK receptors, bile acid effects were limited to CCK1R, with no effects on CCK2R. Chenodeoxycholic acid had a negative impact on CCK1R function, while ursodeoxycholic acid had no effect on CCK1R function in normal membranes but was protective against the negative impact of elevated cholesterol on this receptor. The cholesterol-insensitive CCK1R mutant Y140A was resistant to effects of both bile acids. These data suggest that bile acids compete with the action of cholesterol on CCK1R, probably by interacting at the same site, although the conformational impact of each bile acid appears to be different, with ursodeoxycholic acid capable of correcting the abnormal conformation of CCK1R in a high-cholesterol environment. This mechanism may contribute to the beneficial effect of ursodeoxycholic acid in reducing cholesterol gallstone formation.

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“…Cholecystokinin A receptor (CCKAR) is a G protein-coupled receptor that can be activated by cholecystokinin (CCK), whose mutation can affect the risk of gallbladder cancer in women. 27 Previous studies have found that the expression level of CCKAR in a gallbladder with gallstones was significantly lower than that in a gallbladder without gallstones. 28 In addition, CCKAR has been found to be associated with tumor suppression and is used as a candidate gene for studying ESCC.…”

Section: Discussionmentioning

confidence: 93%

Epigenetic Study of Esophageal Carcinoma Based on Methylation, Gene Integration and Weighted Correlation Network Analysis

Xu¹,

Wang²,

Liu

et al. 2021

OTT

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Purpose: Esophageal carcinoma is a common and highly metastatic malignant tumor of the digestive tract. The aim of the present study was to identify potential molecular markers of esophageal carcinoma that may help its diagnosis and treatment. Materials and Methods: First, mRNA and DNA methylation data were downloaded from The Cancer Genome Atlas (TCGA) database for the identification of differentially expressed genes (DEGs) and DNA methylation analysis. Secondly, Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify important modules and hub genes. In addition, correlation analysis between DNA methylation genes and DEGs was performed. Thirdly, the GSE45670 dataset was used to validate the expression of the diagnostic and survival ability analysis of genes in TCGA data. Finally, reverse transcription-quantitative PCR and immunohistochemical analysis of genes were performed. Results: A total of 2408 DEGs and 5134 differentially methylated sites were obtained. In the WGCNA analysis, the royal blue module was found to be the optimal module. In addition, hub genes in the module, including ESRRG, MFSD4, CCKBR, ATP4B, ESRRB, ATP4A, CCKAR and B3GAT1, were also differentially methylated genes and DEGs. It was found that CCKAR, MFSD4 and ESRRG may be diagnostic gene biomarkers for esophageal carcinoma. In addition, the high expression of MFSD4 was significantly correlated with patient survival. Immunohistochemistry analysis results showed that the gene expression levels of ATP4B, B3GAT1, CCKBR and ESRRG were decreased in esophageal carcinoma tissues, which was in line with the bioinformatics results. Conclusion: Therefore, these identified molecular markers may be helpful in the diagnosis and treatment of esophageal carcinoma.

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Variants in CCK and CCKAR genes to susceptibility to biliary tract cancers and stones: A population‐based study in Shanghai, China

Cited by 13 publications

References 22 publications

Construction of Potential Gene Expression and Regulation Networks in Prostate Cancer Using Bioinformatics Tools

Construction of Potential Gene Expression and Regulation Networks in Prostate Cancer Using Bioinformatics Tools

Impact of ursodeoxycholic acid on a CCK1R cholesterol-binding site may contribute to its positive effects in digestive function

Epigenetic Study of Esophageal Carcinoma Based on Methylation, Gene Integration and Weighted Correlation Network Analysis

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