scholarly journals miRNA and mRNA expression profiles in gastric cancer patients and the relationship with circRNA

Neoplasma ◽  
2019 ◽  
Vol 66 (06) ◽  
pp. 879-886 ◽  
Author(s):  
F. Jiang ◽  
X. B. Shen
Keyword(s):  
Gastric Cancer ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Expression Profiles ◽  
Gastric Cancer Patients ◽  
The Relationship

scholarly journals Significance of aquaporins’ expression in the prognosis of gastric cancer

2018 ◽  
Vol 38 (3) ◽  
Author(s):  
Saroj Thapa ◽  
Mandika Chetry ◽  
Kaiyu Huang ◽  
Yangpei Peng ◽  
Jinsheng Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Cancer Biomarker ◽  
Clinicopathological Features ◽  
Her2 Status ◽  
Aberrant Expression ◽  
Gastric Cancer Patients

Gastric carcinoma is one of the most lethal malignancy at present with leading cause of cancer-related deaths worldwide. Aquaporins (AQPs) are a family of small, integral membrane proteins, which have been evidenced to play a crucial role in cell migration and proliferation of different cancer cells including gastric cancers. However, the aberrant expression of specific AQPs and its correlation to detect predictive and prognostic significance in gastric cancer remains elusive. In the present study, we comprehensively explored immunohistochemistry based map of protein expression profiles in normal tissues, cancer and cell lines from publicly available Human Protein Atlas (HPA) database. Moreover, to improve our understanding of general gastric biology and guide to find novel predictive prognostic gastric cancer biomarker, we also retrieved ‘The Kaplan–Meier plotter’ (KM plotter) online database with specific AQPs mRNA to overall survival (OS) in different clinicopathological features. We revealed that ubiquitous expression of AQPs protein can be effective tools to generate gastric cancer biomarker. Furthermore, high level AQP3, AQP9, and AQP11 mRNA expression were correlated with better OS in all gastric patients, whereas AQP0, AQP1, AQP4, AQP5, AQP6, AQP8, and AQP10 mRNA expression were associated with poor OS. With regard to the clinicopathological features including Laurens classification, clinical stage, human epidermal growth factor receptor 2 (HER2) status, and different treatment strategy, we could illustrate significant role of individual AQP mRNA expression in the prognosis of gastric cancer patients. Thus, our results indicated that AQP’s protein and mRNA expression in gastric cancer patients provide effective role to predict prognosis and act as an essential agent to therapeutic strategy.

DETERMINATION OF P53 GENE CODON 72 POLYMORPHISMS IN PATIENTS WITH GASTRIC CANCER

2013 ◽  
pp. 11-17
Author(s):  
Thi Tuy Ha Nguyen ◽  
Thi Minh Thi Ha
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
P53 Gene ◽  
Diffuse Gastric Cancer ◽  
Codon 72 ◽  
Cancer Group ◽  
Pcr Rflp ◽  
Gastric Cancer Patients ◽  
The Relationship

Background: The role of p53 gene in the gastric cancer is still controversial. This study is aimed at determining the rate of the p53 gene codon 72 polymorphisms in gastric cancer patients and evaluating the relationship between these polymorphisms and endoscopic and histopathological features of gastric cancer. Patients and methods: Sixty eight patients with gastric cancer (cases) and one hundred and thirty six patients without gastric cancer (controls) were enrolled. p53 gene codon 72 polymorphisms were determined by PCR-RFLP technique with DNA extracted from samples of gastric tissue. Results: In the group of gastric cancer, Arginine/Argnine, Arginine/Proline and Proline/Proline genotypes were found in 29.4%, 42.7% and 27.9%, respectively. The differences of rates were not statistically significant between cases and controls (p > 0,05). In males, the Proline/Proline genotype was found in 38.1% in patients with gastric cancer and more frequent in patients without gastric cancer (15.7%, p = 0,01). An analysis of ROC curve showed that the cut-off was the age of 52 in the Proline/Proline genotype, but it was 65 years old in the Arginine/Proline genotype. The Proline/Proline genotype was found in 41.9% in Borrmann III/IV gastric cancer, this rate was higher than Borrmann I/II gastric cancer (16.2%, p = 0.037) and also higher than controls (18.4%, p = 0,01). The rate of Proline/Proline genotype was 41.7% in the diffuse gastric cancer, it was higher than in controls (p = 0,023). Conclusion: No significative difference of rate was found in genotypes between gastric cancer group and controls. However, there was the relationship between Proline/Proline genotype and gastric cancer in males, Borrmann types of gastric cancer, the diffuse gastric cancer. Key words: polymorphism, codon 72, p53 gene, PCR - RFLP, gastric cancer.

scholarly journals Prognostic significance of IL-17 mRNA expression in peritoneal lavage in gastric cancer patients who underwent curative resection

2013 ◽  
Vol 31 (2) ◽  
pp. 605-612 ◽  
Author(s):  
TAKESHI IIDA ◽  
MAKOTO IWAHASHI ◽  
MASAHIRO KATSUDA ◽  
KOICHIRO ISHIDA ◽  
MIKIHITO NAKAMORI ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Curative Resection ◽  
Peritoneal Lavage ◽  
Prognostic Significance ◽  
Gastric Cancer Patients

scholarly journals Serum leptin levels in gastric cancer patients and the relationship with insulin resistance

2015 ◽  
Vol 2 ◽  
pp. 346-352 ◽  
Author(s):  
Huseyin Begenik ◽  
Mehmet Aslan ◽  
Ahmet Cumhur Dulger ◽  
Habib Emre ◽  
Ahu Kemik ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Insulin Resistance ◽  
Cancer Patients ◽  
Serum Leptin ◽  
Gastric Cancer Patients ◽  
The Relationship

Application of serum proteomic patterns by ProteinChip SELDI system in diagnosis of gastric cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 10559-10559
Author(s):  
J. Lim ◽  
J. Cho ◽  
Y. Paik ◽  
Y. Chang ◽  
H. Kim
Keyword(s):  
Gastric Cancer ◽  
Decision Tree ◽  
Cancer Patients ◽  
Expression Profiles ◽  
Protein Profiling ◽  
Healthy Individuals ◽  
Protein Biomarker ◽  
Biomarker Pattern ◽  
Gastric Cancer Patients ◽  
Tof Ms

10559 Background: Gastric cancer is one of the most common malignancy in the world and one of the leading causes of cancer related death in Korea. Most treatments for advanced gastric cancer have limited efficacy. So early detection of gastric cancer could have profound impact on the successful treatment. Application of multiple biomarkers may improve the diagnostic prediction to distinguish cancer from non-cancer. ProteinChip Surface-Enhanced Laser Desorption/Ionization Time-of-flight Mass Spectrometry (SELDI-TOF-MS) system is one of the currently used techniques to identify biomarkers for cancers. In this study, we have explored whether the serum proteomic patterns by ProteinChip SELDI system can differentiate gastric cancers from non-cancer cohorts. Methods: We have screened protein profiles of 100 serum samples obtained from 60 gastric cancer patients and 40 healthy individuals. Protein expression profiles were expressed on ProteinChip Array and analyzed by PreoteinChip Reader. Peak intensities were normalized by total ion currency and analyzed by the Biomarker Wizard Software to identify the peaks showing significantly different intensities between normal and cancer groups. Classification analysis and construction of decision trees were done with the Biomarker Pattern Software. Results: SELDI -TOF-MS by averaging 50 laser spots collected at a laser intensity setting of 160, a detector sensitivity of 6, and mean mass range of 30 kDa. Seventeen protein peaks shown significant differences between two groups were chosen to make a protein biomarker pattern. The decision tree which gives the highest discrimination included four peaks at 5,919, 8,583, 10,286, and 13,758 as splitters. The sensitivity and the specificity for classification of with the decision tree giving the highest discrimination were 96.7% (58/60) and 97.5% (39/40), respectively. When the protein biomarker pattern was tested with the blinded test set including 30 gastric cancer patients and 20 healthy individuals and, it yielded a sensitivity of 93.3% (28/30) and a specificity of 90% (18/20). Conclusions: These results suggest that serum-protein profiling pattern by SELDI system may distinguish gastric cancer patients from normal counterparts with relatively high sensitivity and specificity. No significant financial relationships to disclose.

scholarly journals Study on the Relationship between Expression of LGR5 and Clinicopathological Characteristics in Gastric Cancer Patients

Health ◽  
2018 ◽  
Vol 10 (01) ◽  
pp. 159-169
Author(s):  
Xiulian Xu ◽  
Qijun Lv ◽  
Ping Xie ◽  
Shoujiang Wei ◽  
Chongshu Wang
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
Clinicopathological Characteristics ◽  
Gastric Cancer Patients ◽  
The Relationship

scholarly journals Gastric Microbiome Diversities in Gastric Cancer Patients from Europe and Asia Mimic the Human Population Structure and Are Partly Driven by Microbiome Quantitative Trait Loci

2020 ◽  
Vol 8 (8) ◽  
pp. 1196
Author(s):  
Bruno Cavadas ◽  
Rui Camacho ◽  
Joana C. Ferreira ◽  
Rui M. Ferreira ◽  
Ceu Figueiredo ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Population Structure ◽  
Quantitative Trait Loci ◽  
Cancer Patients ◽  
Quantitative Trait ◽  
Expression Profiles ◽  
European Ancestry ◽  
Microbiome Diversity ◽  
Trait Loci ◽  
Gastric Cancer Patients

The human gastrointestinal tract harbors approximately 100 trillion microorganisms with different microbial compositions across geographic locations. In this work, we used RNASeq data from stomach samples of non-disease (164 individuals from European ancestry) and gastric cancer patients (137 from Europe and Asia) from public databases. Although these data were intended to characterize the human expression profiles, they allowed for a reliable inference of the microbiome composition, as confirmed from measures such as the genus coverage, richness and evenness. The microbiome diversity (weighted UniFrac distances) in gastric cancer mimics host diversity across the world, with European gastric microbiome profiles clustering together, distinct from Asian ones. Despite the confirmed loss of microbiome diversity from a healthy status to a cancer status, the structured profile was still recognized in the disease condition. In concordance with the parallel host-bacteria population structure, we found 16 human loci (non-synonymous variants) in the European-descendent cohorts that were significantly associated with specific genera abundance. These microbiome quantitative trait loci display heterogeneity between population groups, being mainly linked to the immune system or cellular features that may play a role in enabling microbe colonization and inflammation.

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