Searching for New Biomarkers and the Use of Multivariate Analysis in Gastric Cancer Diagnostics
Language English Country Greece Media print
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
27069188
PII: 36/4/1967
Knihovny.cz E-resources
- Keywords
- Gastric cancer, biomarkers, gastric cancer index, tumor markers,
- MeSH
- Antigens, Tumor-Associated, Carbohydrate blood MeSH
- Adult MeSH
- Helicobacter pylori immunology MeSH
- Immunoglobulin G blood MeSH
- Helicobacter Infections immunology MeSH
- Carcinoembryonic Antigen blood MeSH
- Middle Aged MeSH
- Humans MeSH
- Matrix Metalloproteinase 7 blood MeSH
- Multivariate Analysis MeSH
- Biomarkers, Tumor blood MeSH
- Stomach Neoplasms blood diagnosis MeSH
- Pepsinogen A blood MeSH
- Antibodies, Bacterial blood MeSH
- Risk Factors MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Models, Theoretical * MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Antigens, Tumor-Associated, Carbohydrate MeSH
- CA-72-4 antigen MeSH Browser
- Immunoglobulin G MeSH
- Carcinoembryonic Antigen MeSH
- Matrix Metalloproteinase 7 MeSH
- MMP7 protein, human MeSH Browser
- Biomarkers, Tumor MeSH
- Pepsinogen A MeSH
- Antibodies, Bacterial MeSH
AIM: The first aim of this study was to search for new biomarkers to be used in gastric cancer diagnostics. The second aim was to verify the findings presented in literature on a sample of the local population and investigate the risk of gastric cancer in that population using a multivariant statistical analysis. PATIENTS AND METHODS: We assessed a group of 36 patients with gastric cancer and 69 healthy individuals. We determined carcinoembryonic antigen, cancer antigen 19-9, cancer antigen 72-4, matrix metalloproteinases (-1, -2, -7, -8 and -9), osteoprotegerin, osteopontin, prothrombin induced by vitamin K absence-II, pepsinogen I, pepsinogen II, gastrin and Helicobacter pylori for each sample. RESULTS: The multivariate stepwise logistic regression identified the following biomarkers as the best gastric cancer predictors: CEA, CA72-4, pepsinogen I, Helicobacter pylori presence and MMP7. CONCLUSION: CEA and CA72-4 remain the best markers for gastric cancer diagnostics. We suggest a mathematical model for the assessment of risk of gastric cancer.
