Literature DB >> 29214870

Advances in cell-free protein array methods.

Xiaobo Yu1, Brianne Petritis2, Hu Duan1, Danke Xu3, Joshua LaBaer2.   

Abstract

INTRODUCTION: Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

Entities:  

Keywords:  Cell-free; biomarker; protein array; proteomics; translational research

Mesh:

Year:  2017        PMID: 29214870     DOI: 10.1080/14789450.2018.1415146

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  3 in total

1.  PAWER: protein array web exploreR.

Authors:  Dmytro Fishman; Ivan Kuzmin; Priit Adler; Jaak Vilo; Hedi Peterson
Journal:  BMC Bioinformatics       Date:  2020-09-17       Impact factor: 3.169

2.  In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine.

Authors:  Meng Xu; Jingwen Deng; Kaikun Xu; Tiansheng Zhu; Ling Han; Yuhong Yan; Danni Yao; Hao Deng; Dan Wang; Yaoting Sun; Cheng Chang; Xiaomei Zhang; Jiayu Dai; Liang Yue; Qiushi Zhang; Xue Cai; Yi Zhu; Hu Duan; Yuan Liu; Dong Li; Yunping Zhu; Timothy R D J Radstake; Deepak M W Balak; Danke Xu; Tiannan Guo; Chuanjian Lu; Xiaobo Yu
Journal:  Theranostics       Date:  2019-04-13       Impact factor: 11.556

3.  Autoantibody profiling identifies predictive biomarkers of response to anti-PD1 therapy in cancer patients.

Authors:  Qiaoyun Tan; Dan Wang; Jianliang Yang; Puyuan Xing; Sheng Yang; Yang Li; Yan Qin; Xiaohui He; Yutao Liu; Shengyu Zhou; Hu Duan; Te Liang; Haoyu Wang; Yanrong Wang; Shiyu Jiang; Fengyi Zhao; Qiaofeng Zhong; Yu Zhou; Shasha Wang; Jiayu Dai; Jiarui Yao; Di Wu; Zhishang Zhang; Yan Sun; Xiaohong Han; Xiaobo Yu; Yuankai Shi
Journal:  Theranostics       Date:  2020-05-16       Impact factor: 11.556

  3 in total

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