AIM:To analyze the differences and relevance of Yes-associated protein (YAP) and survivin, and to explore the correlation and signifi cance of their expression in gastric carcinoma and precancerous lesions.METHODS: Th...AIM:To analyze the differences and relevance of Yes-associated protein (YAP) and survivin, and to explore the correlation and signifi cance of their expression in gastric carcinoma and precancerous lesions.METHODS: The PV9000 immunohistochemical method was used to detect the expression of YAP and survivin in 98 cases of normal gastric mucosa, 58 intestinal metaplasia (IM), 32 dysplasia and 98 gastric carcinoma.RESULTS: The positive rates of YAP in dysplasia (37.5%) and gastric carcinoma (48.0%) were significantly higher than that in normal gastric mucosa (13.3%), P<0.01. The positive rates of survivin in IM (53.4%), dysplasia (59.4%) and gastric carcinoma (65.3%) were significantly higher than in normal gastric mucosa (11.2%), P<0.01. Survivin expression gradually increased from 41.7% in well differentiated adenocarcinoma through 58.3% in moderately differentiated adenocarcinoma to 75.6% in poorly differentiated adenocarcinoma, with significant Rank correlation, rk=0.279, P<0.01. The positive rate of survivin in gastric carcinoma of diffused type (74.6%) was significantly higher than that in intestinal type (51.3%), P<0.05. In gastric carcinoma with lymph node metastasis (76.9%), the positive rate of survivin was signifi cantly higher than that in the group without lymph node metastasis (41.2%), P<0.01. In 98 cases of gastric carcinoma, the expression of YAP and of survivin were positively correlated, rk=0.246, P<0.01.CONCLUSION: YAP may play an important role as a carcinogenic factor and may induce survivin expression. Detecting both markers together may help in early diagnosis of gastric carcinoma.展开更多
Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine,because it may help to find new therapeutic opportunities for cancer treatment and cure in...Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine,because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches.One of the pathways known to be important for the development of neoplastic diseases and pathological processes is the Hedgehog signaling pathway that normally controls human embryonic development.Systematic accumulation of various types of biological data,including interactions between proteins,regulation of genes transcription,proteomics,and metabolomics experiments results,allows the application of computational analysis of these big data for identification of key molecular mechanisms of certain diseases and pathologies and promising therapeutic targets.The aim of this study is to develop a computational approach for revealing associations between human proteins and genes interacting with the Hedgehog pathway components,as well as for identifying their roles in the development of various types of tumors.We automatically collect sets of abstract texts from the NCBI PubMed bibliographic database.For recognition of the Hedgehog pathway proteins and genes and neoplastic diseases we use a dictionary-based named entity recognition approach,while for all other proteins and genes machine learning method is used.For association extraction,we develop a set of semantic rules.We complete the results of the text analysis with the gene set enrichment analysis.The identified key pathways that may influence the Hedgehog pathway and their roles in tumor development are then verified using the information in the literature.展开更多
基金Supported by National Natural Science Foundation of China,No.30371607
文摘AIM:To analyze the differences and relevance of Yes-associated protein (YAP) and survivin, and to explore the correlation and signifi cance of their expression in gastric carcinoma and precancerous lesions.METHODS: The PV9000 immunohistochemical method was used to detect the expression of YAP and survivin in 98 cases of normal gastric mucosa, 58 intestinal metaplasia (IM), 32 dysplasia and 98 gastric carcinoma.RESULTS: The positive rates of YAP in dysplasia (37.5%) and gastric carcinoma (48.0%) were significantly higher than that in normal gastric mucosa (13.3%), P<0.01. The positive rates of survivin in IM (53.4%), dysplasia (59.4%) and gastric carcinoma (65.3%) were significantly higher than in normal gastric mucosa (11.2%), P<0.01. Survivin expression gradually increased from 41.7% in well differentiated adenocarcinoma through 58.3% in moderately differentiated adenocarcinoma to 75.6% in poorly differentiated adenocarcinoma, with significant Rank correlation, rk=0.279, P<0.01. The positive rate of survivin in gastric carcinoma of diffused type (74.6%) was significantly higher than that in intestinal type (51.3%), P<0.05. In gastric carcinoma with lymph node metastasis (76.9%), the positive rate of survivin was signifi cantly higher than that in the group without lymph node metastasis (41.2%), P<0.01. In 98 cases of gastric carcinoma, the expression of YAP and of survivin were positively correlated, rk=0.246, P<0.01.CONCLUSION: YAP may play an important role as a carcinogenic factor and may induce survivin expression. Detecting both markers together may help in early diagnosis of gastric carcinoma.
基金This work was supported by the Ministry of Science and Higher Education of the Russian Federation within the framework of state support for the creation and development of World-Class Research Centers'Digital Biodesign and Personalized Healthcare'(No.75-15-2022-305).
文摘Analysis of molecular mechanisms that lead to the development of various types of tumors is essential for biology and medicine,because it may help to find new therapeutic opportunities for cancer treatment and cure including personalized treatment approaches.One of the pathways known to be important for the development of neoplastic diseases and pathological processes is the Hedgehog signaling pathway that normally controls human embryonic development.Systematic accumulation of various types of biological data,including interactions between proteins,regulation of genes transcription,proteomics,and metabolomics experiments results,allows the application of computational analysis of these big data for identification of key molecular mechanisms of certain diseases and pathologies and promising therapeutic targets.The aim of this study is to develop a computational approach for revealing associations between human proteins and genes interacting with the Hedgehog pathway components,as well as for identifying their roles in the development of various types of tumors.We automatically collect sets of abstract texts from the NCBI PubMed bibliographic database.For recognition of the Hedgehog pathway proteins and genes and neoplastic diseases we use a dictionary-based named entity recognition approach,while for all other proteins and genes machine learning method is used.For association extraction,we develop a set of semantic rules.We complete the results of the text analysis with the gene set enrichment analysis.The identified key pathways that may influence the Hedgehog pathway and their roles in tumor development are then verified using the information in the literature.
