Real-Time Functional Stratification of Tumor Cell Lines Using a Non-Cytotoxic Phospholipoproteomic Platform: A...

Area of Science:

• Solid tumor immunotherapy
• Immuno-oncology drug development
• Ex vivo functional assays

Background:

• Assessing tumor response to immunotherapy is crucial but challenging.
• Current methods often rely on cytotoxicity or complex co-culture systems.
• Scalable, non-invasive tools are needed for evaluating immunoformulations.

Purpose of the Study:

• To introduce a real-time, ex vivo functional system for classifying tumor cell responses.
• To enable phenotypic screening without cytotoxicity, co-culture, or molecular profiling.
• To develop a quantitative method for evaluating immunoformulations in solid tumors.

Main Methods:

• Utilized IncuCyte® S3 real-time imaging to monitor tumor cell behavior ex vivo.
• Captured proliferative rates, cell death, and secretomic profiles of eight human tumor lines.
• Developed a structured decision-tree logic and computed a Functional Stratification Index (FSI) for classification.

Main Results:

• Classified tumor lines into stimulatory, inhibitory, or neutral response categories.
• Identified distinct patterns for inhibitory (high IFN-γ/IL-10) and stimulatory (proliferative gain) lines.
• Demonstrated reproducible results across independent batches, validating the system's reliability.

Conclusions:

• The developed system provides a quantitative, marker-free platform for functional evaluation of immunoformulations.
• This approach, codified as STIP (Structured Traceability and Immunophenotypic Platform), supports upstream validation in immuno-oncology.
• Enables adaptable, reproducible phenotypic screening for early-stage drug development and regulatory documentation.