Literature DB >> 21901605

Recombinant antibodies for the generation of antibody arrays.

Carl A K Borrebaeck1, Christer Wingren.   

Abstract

Affinity proteomics, mainly represented by antibody microarrays, has in recent years been established as a powerful tool for high-throughput (disease) proteomics. The technology can be used to generate detailed protein expression profiles, or protein maps, of focused set of proteins in crude proteomes and potentially even high-resolution portraits of entire proteomes. The technology provides unique opportunities, for example biomarker discovery, disease diagnostics, patient stratification and monitoring of disease, and taking the next steps toward personalized medicine. However, the process of designing high-performing, high-density antibody micro- and nanoarrays has proven to be challenging, requiring truly cross-disciplinary efforts to be adopted. In this mini-review, we address one of these key technological issues, namely, the choice of probe format, and focus on the use of recombinant antibodies vs. polyclonal and monoclonal antibodies for the generation of antibody arrays.

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Year:  2011        PMID: 21901605     DOI: 10.1007/978-1-61779-286-1_17

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  12 in total

Review 1.  Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

Authors:  Carl A K Borrebaeck
Journal:  Nat Rev Cancer       Date:  2017-02-03       Impact factor: 60.716

2.  Human anti-EGFL7 recombinant full-length antibodies selected from a mammalian cell-based antibody display library.

Authors:  Feng Li; Yan-Hong Liu; Yan-Wen Li; Qian Ju; Lin Chen; Ping-Li Xie; Yue-Hui Li; Guan-Cheng Li
Journal:  Mol Cell Biochem       Date:  2012-06       Impact factor: 3.396

Review 3.  Recombinant antibodies and their use in biosensors.

Authors:  Xiangqun Zeng; Zhihong Shen; Ray Mernaugh
Journal:  Anal Bioanal Chem       Date:  2011-12-13       Impact factor: 4.142

4.  Plasma protein profiling in a stage defined pancreatic cancer cohort - Implications for early diagnosis.

Authors:  Anna Sandström Gerdtsson; Christer Wingren; Helena Persson; Payam Delfani; Malin Nordström; He Ren; Xin Wen; Ulrika Ringdahl; Carl A K Borrebaeck; Jihui Hao
Journal:  Mol Oncol       Date:  2016-07-12       Impact factor: 6.603

5.  Identification of plasma protein profiles associated with risk groups of prostate cancer patients.

Authors:  Malin Nordström; Christer Wingren; Carsten Rose; Anders Bjartell; Charlotte Becker; Hans Lilja; Carl A K Borrebaeck
Journal:  Proteomics Clin Appl       Date:  2014-10-22       Impact factor: 3.494

6.  Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model.

Authors:  Bernet S Kato; George Nicholson; Maja Neiman; Mattias Rantalainen; Chris C Holmes; Amy Barrett; Mathias Uhlén; Peter Nilsson; Tim D Spector; Jochen M Schwenk
Journal:  Proteome Sci       Date:  2011-11-17       Impact factor: 2.480

7.  Identification of a serum biomarker signature associated with metastatic prostate cancer.

Authors:  Venera Kuci Emruli; Leena Liljedahl; Ulrika Axelsson; Corinna Richter; Lisa Theorin; Anders Bjartell; Hans Lilja; Jenny Donovan; David Neal; Freddie C Hamdy; Carl A K Borrebaeck
Journal:  Proteomics Clin Appl       Date:  2021-05-04       Impact factor: 3.603

8.  Technical Advances of the Recombinant Antibody Microarray Technology Platform for Clinical Immunoproteomics.

Authors:  Payam Delfani; Linda Dexlin Mellby; Malin Nordström; Andreas Holmér; Mattias Ohlsson; Carl A K Borrebaeck; Christer Wingren
Journal:  PLoS One       Date:  2016-07-14       Impact factor: 3.240

9.  Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays.

Authors:  Anna S Gerdtsson; Linda Dexlin-Mellby; Payam Delfani; Erica Berglund; Carl A K Borrebaeck; Christer Wingren
Journal:  Microarrays (Basel)       Date:  2016-06-08

10.  Can glycoprofiling be helpful in detecting prostate cancer?

Authors:  Štefan Belický; Jan Tkac
Journal:  Chem Zvesti       Date:  2014-11-28       Impact factor: 2.097

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