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A comparison of four technologies for detecting p53 aggregates in ovarian cancer
Nicole Heinzl1, Katarzyna Koziel2, Elisabeth Maritschnegg1
1Molecular Oncology Group, Department of Obstetrics and Gynecology, Comprehensive Cancer Center-Gynecologic Cancer Unit, Medical University of Vienna, Vienna, Austria.
Abstract:
The tumor suppressor protein p53 is mutated in half of all cancers and has been described to form amyloid-like structures, commonly known from key proteins in neurodegenerative diseases. Still, the clinical relevance of p53 aggregates remains largely unknown, which may be due to the lack of sensitive and specific detection methods. The aim of the present study was to compare the suitability of four different methodologies to specifically detect p53 aggregates: co-immunofluorescence (co-IF), proximity ligation assay (PLA), co-immunoprecipitation (co-IP), and the p53-Seprion-ELISA in cancer cell lines and epithelial ovarian cancer tissue samples. In 7 out of 10 (70%) cell lines, all applied techniques showed concordance. For the analysis of the tissue samples co-IF, co-IP, and p53-Seprion-ELISA were compared, resulting in 100% concordance in 23 out of 30 (76.7%) tissue samples. However, Co-IF lacked specificity as there were samples, which did not show p53 staining but abundant staining of amyloid proteins, highlighting that this method demonstrates that proteins share the same subcellular space, but does not specifically detect p53 aggregates. Overall, the PLA and the p53-Seprion-ELISA are the only two methods that allow the quantitative measurement of p53 aggregates. On the one hand, the PLA represents the ideal method for p53 aggregate detection in FFPE tissue, which is the gold-standard preservation method of clinical samples. On the other hand, when fresh-frozen tissue is available the p53-Seprion-ELISA should be preferred because of the shorter turnaround time and the possibility for high-throughput analysis. These methods may add to the understanding of amyloid-like p53 in cancer and could help stratify patients in future clinical trials targeting p53 aggregation.
Insights
Detecting tumor suppressor protein p53 aggregates, crucial in cancer, was compared using four methods. Proximity ligation assay (PLA) and p53-Seprion-ELISA are best for quantitative p53 aggregate detection.
Area of Science:
- Oncology
- Biochemistry
- Molecular Biology
Background:
- The tumor suppressor protein p53 is frequently mutated in human cancers.
- p53 can form amyloid-like aggregates, similar to proteins implicated in neurodegenerative diseases.
- The clinical significance of p53 aggregates is unclear due to a lack of specific detection methods.
Purpose of the Study:
- To evaluate and compare four methods for specifically detecting p53 aggregates.
- Assess the suitability of co-immunofluorescence (co-IF), proximity ligation assay (PLA), co-immunoprecipitation (co-IP), and p53-Seprion-ELISA.
- Determine the most effective methods for analyzing p53 aggregates in cancer cell lines and tissues.
Main Methods:
- Comparison of co-IF, PLA, co-IP, and p53-Seprion-ELISA in cancer cell lines.
- Evaluation of co-IF, co-IP, and p53-Seprion-ELISA in epithelial ovarian cancer tissue samples.
- Assessment of method specificity and quantitative capabilities for p53 aggregate detection.
Main Results:
- Co-IF showed a lack of specificity, detecting amyloid proteins without confirming p53 aggregates.
- PLA and p53-Seprion-ELISA were identified as the only methods capable of quantitative p53 aggregate measurement.
- High concordance was observed between methods in cell lines (70%) and tissue samples (76.7%), with co-IF, co-IP, and ELISA showing 100% concordance in a subset of tissues.
Conclusions:
- Proximity ligation assay (PLA) is ideal for p53 aggregate detection in formalin-fixed paraffin-embedded (FFPE) tissues.
- p53-Seprion-ELISA is preferred for fresh-frozen tissues, offering faster, high-throughput analysis.
- These validated methods can advance understanding of amyloid-like p53 in cancer and aid patient stratification for targeted therapies.
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