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find Keyword "enrichment" 5 results
  • Exploring The Mechanism of Postoperative Recurrence of Hepatocellular Carcinoma and Predicting The Candidate Drugs

    ObjectiveTo explore the mechanism of postoperative recurrence of hepatocellular carcinoma(HCC) and predicting the candidate drug. MethodsThe differently expressed genes of the human gene expression profiles with 35 postoperative recurrence of HCC tissues and 41 no recurrence of HCC tissues were identified. Then enriched these genes with gene ontology(GO) terms and KEGG pathway, and predicting the candidate drugs for suppress the postoperative recurrence using Connectivity Map(cmap) database. ResultsSeveral pathways such as Focal adhesion and MAPK signaling pathway were found involve in postoperative recurrence of HCC. Moreover, two candidate small molecule drugs(bambuterol and lovastatin) were found may suppress and postoperative recurrence of HCC. ConclusionFocal adhesion and MAPK signaling pathway may involve in the postoperative recurrence of HCC, bambuterol and lovastatin may candidate drugs for treat postoperative recurrence of HCC.

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  • Screening of nucleic acid aptamer of lung cancer cells based on cell exponential enrichment ligand system evolution and its application in tumor diagnosis and treatment

    Nucleic acid aptamer is an oligonucleotide sequence screened by the exponential enrichment ligand system evolution technology (SELEX). Previous studies have shown that nucleic acid aptamer has a good application prospect in tumor diagnosis and treatment. Therefore, we reviewed the selection and identification of nucleic acid aptamer of lung cancer cells in recent years, and discussed the effect of aptamer as targeting drugs and targeting vectors on the diagnosis of tumors, which provide a new idea for early diagnosis and treatment of tumor.

    Release date:2019-02-18 02:31 Export PDF Favorites Scan
  • Progress of enrichment technology of circulating tumor cells in primary liver cancer

    ObjectiveTo understand the latest progress of enrichment technology of circulating tumor cells (CTCs), and summarize the principle, advantages and disadvantages of various enrichment technologies and their applications in primary liver cancer (PLC). MethodThe literature relevant to the enrichment methods of CTCs in the PLC was reviewed and summarized. ResultsThe clinical significances of CTCs in the early diagnosis and staging, hierarchical diagnosis and treatment, and efficacy monitoring of patients with PLC had been recognized. There were many separation and enrichment technologies for CTC, which were mainly based on the differences of physical and biochemical characteristics, as well as the combination of enrichment methods with various principles. Each enrichment method had corresponding advantages and disadvantages, and few enrichment methods for CTC was applied to PLC. ConclusionsAlthough many problems need to be solved in enrichment method of CTCs at present, it is believed that the existing problems will be solved one by one with continuous improvement of technology. And CTC detection is expected to apply in clinical, so as to provide more efficient diagnosis and treatment methods for patients with PLC.

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  • Response of circulating tumor cells and circulating tumor endothelial cells to treatment modalities of nasopharyngeal carcinoma and its significance

    Objective To investigate the relationships between circulating tumor cells (CTCs), circulating tumor endothelial cells (CTECs) and treatment methods in patients with nasopharyngeal carcinoma (NPC) at different stages of treatment. Methods The data of NPC patients at different treatment periods in West China Hospital of Sichuan University from March 2016 to November 2019 were retrospectively collected. The patients received CTCs test and part of those patients received CTECs test, by subtraction enrichment-immunostaining-fluorescence in situ hybridization. The relationships of CTCs and CTECs with radiotherapy and chemotherapy, and the correlations between CTCs and CTECs in NPC patients were analyzed. Results A total of 191 patients were included. Among them, there were 66 cases before initial treatment, 38 cases after induction chemotherapy, and 87 cases after concurrent chemoradiotherapy. A total of 127 patients received CTECs test, including 41 cases before initial treatment, 29 cases after induction chemotherapy, and 57 cases after concurrent chemoradiotherapy. The positive rates of CTCs were 89.4%, 81.6% and 69.0% respectively in the three stages of treatment, and the difference was statistically significant only between the pre-treatment group and the post-concurrent chemoradiotherapy group (P=0.003). The number of CTCs in the post-concurrent chemoradiotherapy group was lower than that in the pre-treatment group and the post-induction chemotherapy group (P<0.001, P=0.002). The number of triploid CTCs in the post-concurrent chemoradiotherapy group was significantly different from that in the pre-treatment group and the post-induction chemotherapy group (P=0.009, P=0.013). The number of tetraploid CTCs in the post-concurrent chemoradiotherapy group was significantly different from that in the post-induction chemotherapy group (P=0.007). The number of polyploidy (pentaploid or > 5 copies of chromosome 8) CTCs in the post-concurrent chemoradiotherapy group was significantly different from that in the pre-treatment group (P<0.001). The positive rates of CTECs were 70.7%, 82.8% and 64.9% respectively in the three stages of treatment, and the difference was not statistically significant (P>0.05). The number of CTECs in the post-concurrent chemoradiotherapy group was only lower than that in the post-induction chemotherapy group (P=0.009). There was no significant difference in the number of triploid or tetraploid CTECs among the three groups (P=0.265, P=0.088). The number of polyploid CTECs was statistically different only between the post-concurrent chemoradiotherapy group and the post-induction chemotherapy group (P=0.007). Spearman correlation analysis showed that there was a significant positive correlation between CTCs and CTECs (rs=0.437, P<0.001). Conclusions Concurrent chemoradiotherapy plays a decisive role in reducing the number of CTCs in the blood of NPC patients, while induction chemotherapy does not appear to directly cause changes in the number of CTCs. In NPC patients, different types of CTCs have different responses to different treatments. There is a significant positive correlation between CTECs level and CTCs level in NPC.

    Release date:2024-02-29 12:03 Export PDF Favorites Scan
  • Analysis of transcriptomic differences of duodenal neuroendocrine tumor accompanied by liver and lymph node metastases

    ObjectiveTo explore the key genes and potential molecular mechanisms of liver and lymph node metastases relevant to duodenal neuroendocrine tumors (DNET). MethodsThe tissues of paracancerous duodenal epithelial, primary lesion, liver metastasis lesion, and lymph node metastasis lesion of a rare DNET accompanied by liver and lymph node metastases were sequenced and analyzed. The differentially expressed genes (DEGs) were screened for different tissues and the functional enrichment analysis was performed. ResultsThe tissues of paracancerous duodenal epithelial was used as the control, a total of 2 053 DEGs expressed only in the liver metastases lesion tissues and 742 DEGs expressed only in the lymph node metastases lesion tissues were screened out, and the top 5 genes expressed in the liver metastases lesion tissues were ORM1, C4BPA, AHSG, C9, and LBP, which in the lymph node metastases lesion tissues were ABHD12B, AC100850.1, HOXC9, AC083967.1, and HOXC8. Kyoto Encyclopedia of Genes and Genomes enrichment analysis found that the DEGs were mainly enriched in the phosphatidylinosiol 3 kinase / protein kinase B pathway, mitogen-activated protein kinase pathway, human papillomavirus infection, etc. ConclusionMultiple DEGs and pathways in metastatic lesions are found in this patient with DNET accompanied by liver metastasis and lymph node metastasis, which provides a new direction for treatment and prophylaxis of DNET.

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