Detection of Aggregation-Prone Behavior in Mutant P53 V157F Breast Cancer Cells Using Multipoint Thioflavin T Fluorescence

The tumor suppressor p53, encoded by the TP53 gene, plays a central role in maintaining genomic stability. TP53 mutations, particularly hotspot variants, are found in approximately 50% of human cancers and may lead to the loss of tumor-suppressive functions or the acquisition of gain-of-function properties, including aggregation into prion-like structures. In this study, we assessed the aggregation tendency of the p53 V157F mutation in Hs578T breast cancer cells compared to MCF7 cells expressing wild-type p53. Protein aggregation was evaluated using Thioflavin T (ThT) staining followed by fluorescence quantification in 96-well plate assays. Cells were stained with a ThT/Hoechst solution, washed, and analyzed using a microplate reader under defined excitation/emission parameters. Quantitative analysis using both single-point and four-point fluorescence readings revealed that Hs578T cells exhibited a 3.20- to 4.26-fold increase in ThT fluorescence intensity relative to MCF7, indicating significantly elevated levels of β-sheet-rich or amyloid-like aggregates. Multipoint measurements confirmed the widespread and consistent presence of protein aggregates across the well surface. These findings support the use of multipoint plate-reading to accurately detect protein aggregation in cell-based assays.

Authors

Institutions

Publication Details

Journal
Journal of Visualized Experiments
Published
2025-12-30
DOI
https://doi.org/10.3791/68921
Primary Topic
Advanced Fluorescence Microscopy Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detection of Aggregation-Prone Behavior in Mutant P53 V157F Breast Cancer Cells Using Multipoint Thioflavin T Fluorescence

Kuan-Yo Wu, Jing-yan Chen, Sih-Tong Chen, Hsiao-Hsuan Wang et al.
Journal of Visualized Experiments
Advanced Fluorescence Microscopy Techniques
article

Detection of Aggregation-Prone Behavior in Mutant P53 V157F Breast Cancer Cells Using Multipoint Thioflavin T Fluorescence

Kuan-Yo Wu, Jing-yan Chen, Sih-Tong Chen, Hsiao-Hsuan Wang, Bi-He Cai, Chia-Chi Chen, Shao-I Chin, Zi-Min Zeng, Kuan-Yu Lin, Yi-Ting Cheng
article en

Abstract

The tumor suppressor p53, encoded by the TP53 gene, plays a central role in maintaining genomic stability. TP53 mutations, particularly hotspot variants, are found in approximately 50% of human cancers and may lead to the loss of tumor-suppressive functions or the acquisition of gain-of-function properties, including aggregation into prion-like structures. In this study, we assessed the aggregation tendency of the p53 V157F mutation in Hs578T breast cancer cells compared to MCF7 cells expressing wild-type p53. Protein aggregation was evaluated using Thioflavin T (ThT) staining followed by fluorescence quantification in 96-well plate assays. Cells were stained with a ThT/Hoechst solution, washed, and analyzed using a microplate reader under defined excitation/emission parameters. Quantitative analysis using both single-point and four-point fluorescence readings revealed that Hs578T cells exhibited a 3.20- to 4.26-fold increase in ThT fluorescence intensity relative to MCF7, indicating significantly elevated levels of β-sheet-rich or amyloid-like aggregates. Multipoint measurements confirmed the widespread and consistent presence of protein aggregates across the well surface. These findings support the use of multipoint plate-reading to accurately detect protein aggregation in cell-based assays.

Journal of Visualized Experiments(226)
I-Shou University (TW)
Quality Education
Openalex Percentile: Top 20%
Advanced Fluorescence Microscopy Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.