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Real-Time Functional Stratification of Tumor Cell Lines Using a Non-Cytotoxic Phospholipoproteomic Platform: A Label-Free Ex Vivo Model
by
,
Ramón Gutiérrez-Sandoval
1,*,†
,
Francisco Gutiérrez-Castro
2,†, 
Natalia Muñoz-Godoy
2,
Ider Rivadeneira
3,
Adolay Sobarzo
4,
Jordan Iturra
3,
Ignacio Muñoz
3,
Cristián Peña-Vargas
1,
Matías Vidal
1 and
Francisco Krakowiak
5 1
Department of Oncopathology, OGRD Alliance, Lewes, DE 19958, USA
2
Cancer Research Department, Flowinmunocell-Bioexocell Group, 08028 Barcelona, Spain
3
Outreach and Engagement Programs Department for the OGRD Consortium, Charlestown KN0802, Saint Kitts and Nevis
4
Departamento de Ciencias Biológicas y Químicas, Facultad de Ciencias, Universidad San Sebastián, Lientur 1457, Concepción 4080871, Chile
5
Department of Molecular Oncopathology, Bioclas, Concepción 4030000, Chile
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Biology 2025, 14(8), 953; https://doi.org/10.3390/biology14080953
Submission received: 13 June 2025
/
Revised: 22 July 2025
/
Accepted: 27 July 2025
/
Published: 28 July 2025
(This article belongs to the Section Cancer Biology)
Simple Summary
Functional profiling of a tumor’s response to non-toxic phospholipoproteomic platforms is a growing field in oncology. Unlike traditional drug models, which rely on killing cells or tracking receptor inhibition, this study presents a real-time, label-free system to classify tumor phenotypes based on their kinetic and secretomic behavior. By avoiding cytotoxic endpoints or genetic manipulation, we captured functional compatibility between human tumors and structurally active phospholipoproteomic formulations. This platform supports the standardized classification of tumor responses into stimulatory, inhibitory, or neutral profiles, providing a reproducible and non-invasive tool for selecting candidates in preclinical cancer immunotherapy programs.
Abstract
The development of scalable, non-invasive tools to assess tumor responsiveness to structurally active immunoformulations remains a critical unmet need in solid tumor immunotherapy. Here, we introduce a real-time, ex vivo functional system to classify tumor cell lines exposed to a phospholipoproteomic platform, without relying on cytotoxicity, co-culture systems, or molecular profiling. Tumor cells were monitored using IncuCyte® S3 (Sartorius) real-time imaging under ex vivo neutral conditions. No dendritic cell components or immune co-cultures were used in this mode. All results are derived from direct tumor cell responses to structurally active formulations. Using eight human tumor lines, we captured proliferative behavior, cell death rates, and secretomic profiles to assign each case into stimulatory, inhibitory, or neutral categories. A structured decision-tree logic supported the classification, and a Functional Stratification Index (FSI) was computed to quantify the response magnitude. Inhibitory lines showed early divergence and high IFN-γ/IL-10 ratios; stimulatory ones exhibited a proliferative gain under balanced immune signaling. The results were reproducible across independent batches. This system enables quantitative phenotypic screening under standardized, marker-free conditions and offers an adaptable platform for functional evaluation in immuno-oncology pipelines where traditional cytotoxic endpoints are insufficient. This approach has been codified into the STIP (Structured Traceability and Immunophenotypic Platform), supporting reproducible documentation across tumor models. This platform contributes to upstream validation logic in immuno-oncology workflows and supports early-stage regulatory documentation.
