Literature DB >> 25644017

Expression and characterization of bifunctional fusion proteins possessing antitumor and thrombolytic function for targeting therapy.

Jing Hui1, Jia-shuai Lin1, Ying Hu1, Hui Li1, Feng-qing Hu1.   

Abstract

It is a usual clinical phenomenon that cancer patients are prone to thrombosis. Until now, there have been no efficient methods or appropriate drugs to prevent and cure tumor thrombus. ΔSEC2, N-terminal deletion of 17 amino acids and C-terminal deletion of 132 amino acids, retained antitumor activity of SEC2. ΔSak, N-terminal deletion of 10 amino acids, had thrombolytic activity and specificity advantages. By utilizing bioactivities of ΔSEC2 and ΔSak, ΔSEC2Sak and ΔSakSEC2 were constructed. Octreotide is a tumor targeting peptide and it can be combined with somatostatin (SST) receptors of tumor surface in ligand-receptor binding way. It can be used to increase specificity for tumor therapy. Based on previous studies, DNA sequence encoding octreotide gene was inserted into plasmid pET-28a-Δsec2sak and pET-28a-Δsaksec2. After expression and purification, fusion proteins could significantly stimulate proliferation of mouse spleen lymphocyte, obviously inhibit the growth of human gastric carcinoma BGC-823, and have thrombolytic activity, indicating that fusion proteins retained bioactivities of staphylococcal enterotoxin C2 and Sak. Furthermore, tumor binding capacity of fusion protein was confirmed through the coimmunoprecipitation method. The result showed that they could bind SST receptor 2 antibody, indicating that fusion proteins could be specifically targeted to tumor surface. It has important significance and may be used for targeted therapy.
© 2015 International Union of Biochemistry and Molecular Biology, Inc.

Entities:  

Keywords:  antitumor; octreotide; staphylococcal enterotoxin (SE); targeted therapy

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Year:  2015        PMID: 25644017     DOI: 10.1002/bab.1356

Source DB:  PubMed          Journal:  Biotechnol Appl Biochem        ISSN: 0885-4513            Impact factor:   2.431


  1 in total

1.  Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment.

Authors:  Xing Liu; Abai Xu; Jingwen Huang; Haiyan Shen; Yazhen Liu
Journal:  J Int Med Res       Date:  2022-01       Impact factor: 1.671

  1 in total

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