PCaAnalyser

PCaAnalyser quantifies protein expression and biological parameters in three-dimensional (3D) cell culture models to support prostate cancer (PCa) research and high-throughput screening workflows.

Key Features:

• Implementation: Java-based program integrated into an automated high-content-analysis (HCA) system.
• High-Throughput Capability: Engineered for high-throughput screening (HTS) and supports batch processing as well as standalone analysis modules.
• Automated Quantification: Automates quantification of protein expression and other biological parameters from 3D cell cultures.
• Comprehensive Parameter Analysis: Quantifies nuclei count, predicts nuclei–spheroid membership, and classifies peripheral versus non-peripheral areas to measure biomarker expression and protein constituents associated with PCa progression.
• Signal-to-Noise Ratio Adaptability: Defines cellular objects reliably across varying signal-to-noise ratios.
• Novel Algorithms: Employs novel algorithms to achieve rapid and accurate quantification within 3D cultures.

Scientific Applications:

• 3D prostate cancer model analysis: Quantitative analysis of biomarkers and protein expression in 3D PCa models, including metastatic cell lines DU145 and PC3.
• Drug discovery and compound evaluation: Support for evaluation of compounds for potential therapeutic efficacy within HTS pipelines using 3D culture readouts.

Methodology:

Java-based implementation of novel algorithms within an automated HCA system to quantify protein expression and biological parameters in 3D cultures, including nuclei counting, nuclei–spheroid membership prediction, peripheral versus non-peripheral area classification, and object definition across variable signal-to-noise ratios.