Literature DB >> 30277755

Polymer-Ligand-Based ELISA for Robust, High-Throughput, Quantitative Detection of p53 Aggregates.

Elisabeth Maritschnegg1, Nicole Heinzl1, Stuart Wilson2, Simon Deycmar1, Markus Niebuhr1, Lukas Klameth1, Barbara Holzer1, Katarzyna Koziel3, Nicole Concin3, Robert Zeillinger1.   

Abstract

A growing number of diseases are being linked to protein misfolding and amyloid formation. Recently, p53 was also shown to associate into amyloid aggregates, raising the question of whether cancer development is associated with protein aggregation as well. However, a lack of suitable tools has hampered the evaluation of their clinical relevance. Herein, we report an enzyme-linked-immunosorbent-assay (ELISA) system based on a polyionic, high-molecular-weight ligand that specifically captures aggregated oligomers and amyloid proteins. We proved that naturally occurring tetramers of p53 are not bound, but high-molecular-weight aggregates are bound and subsequently detected. For the first time, this assay allows the quantitative detection of p53 aggregates from cell lysates, which was demonstrated using 22 ovarian-cancer cell lines as well as 7 patient-derived tumor tissues. The levels of p53 aggregates within the missense-mutated tissue samples varied more than 12-fold. This simple, robust method allows studying the abundance and clinical relevance of protein aggregates. This could help our understanding of the role of protein misfolding in cancer or even in predicting therapy responses to aggregation-targeting drugs.

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Year:  2018        PMID: 30277755     DOI: 10.1021/acs.analchem.8b02373

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  2 in total

1.  A Gold Nanoparticle Bouquet held on plasma membrane: An ultrasensitive dark-field imaging approach for Cancer Cell Analysis.

Authors:  Yue Cao; Jie Wang; Qiao-Yan Jiang; Li Hu; You-Jia Yu; Yan-Fang Yu; Feng Chen
Journal:  Nanotheranostics       Date:  2020-06-20

2.  A comparison of four technologies for detecting p53 aggregates in ovarian cancer.

Authors:  Nicole Heinzl; Katarzyna Koziel; Elisabeth Maritschnegg; Astrid Berger; Elisabeth Pechriggl; Heidi Fiegl; Alain G Zeimet; Christian Marth; Robert Zeillinger; Nicole Concin
Journal:  Front Oncol       Date:  2022-09-08       Impact factor: 5.738

  2 in total

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