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Effective preparation of a monoclonal antibody against human chromogranin A for immunohistochemical diagnosis

Overview of attention for article published in BMC Biotechnology, May 2018
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Title
Effective preparation of a monoclonal antibody against human chromogranin A for immunohistochemical diagnosis
Published in
BMC Biotechnology, May 2018
DOI 10.1186/s12896-018-0436-z
Pubmed ID
Authors

Danping Zhang, Chengjie Xie, Rongzhi Wang, Qinghai Yang, Huiling Chen, Sumei Ling, Shihua Wang, Kunzhi Jia

Abstract

Human chromogranin A (CgA) is a ~ 49 kDa secreted protein mainly from neuroendocrine cells and endocrine cells. The CgA values in the diagnosis of tumor, and in the potential role in prognostic and predictive tumor as a biomarker. The synthesized gene of CgA coding area was cloned and expressed as fusion protein CgA-His in procaryotic system. Then the purified CgA-His protein was mixed with QuickAntibody-Mouse5W adjuvant, and injected into mice. The CgA-His protein was also used as coating antigen to determine the antiserum titer. By screening, a stable cell line named 4E5, which can generate anti-CgA monoclonal antibody (mAb), was obtained. The isotype of 4E5 mAb was IgG2b, and the chromosome number was 102 ± 4. Anti-CgA mAb was purified from ascites fluid, and the affinity constant reached 9.23 × 109 L/mol. Furthermore, the specificity of the mAb was determined with ELISA, western blot and immunohistochemistry. Results indicated that the mAb 4E5 was able to detect chromogranin A specifically and sensitively. A sensitive and reliable method was successfully developed for rapid production of anti-CgA mAb for immunohistochemistry diagnosis in this study, and the current study also provides conclusive guidelines for preparation of mAbs and implements in immunohistochemistry diagnosis.

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The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 33%
Student > Master 1 17%
Unknown 3 50%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 17%
Psychology 1 17%
Engineering 1 17%
Unknown 3 50%