Gutiérrez-Sandoval Ramón, Gutiérrez-Castro Francisco, Muñoz-Godoy Natalia, Rivadeneira Ider, Sobarzo Adolay, Iturra Jordan, Muñoz Ignacio, Peña-Vargas Cristián, Vidal Matías, Krakowiak Francisco
Department of Oncopathology, OGRD Alliance, Lewes, DE 19958, USA.
Cancer Research Department, Flowinmunocell-Bioexocell Group, 08028 Barcelona, Spain.
Biology (Basel). 2025 Jul 28;14(8):953. doi: 10.3390/biology14080953.
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.
开发可扩展的非侵入性工具来评估肿瘤对结构活性免疫制剂的反应性,仍然是实体瘤免疫治疗中一个关键的未满足需求。在此,我们引入了一种实时离体功能系统,用于对暴露于磷脂蛋白质组学平台的肿瘤细胞系进行分类,而不依赖细胞毒性、共培养系统或分子谱分析。在离体中性条件下,使用IncuCyte S3(赛多利斯公司)实时成像监测肿瘤细胞。此模式下不使用树突状细胞成分或免疫共培养。所有结果均源自肿瘤细胞对结构活性制剂的直接反应。我们使用8种人类肿瘤细胞系,捕捉增殖行为、细胞死亡率和分泌组图谱,将每个病例分为刺激、抑制或中性类别。结构化的决策树逻辑支持分类,并计算功能分层指数(FSI)以量化反应强度。抑制性细胞系显示出早期分化和高IFN-γ/IL-10比率;刺激性细胞系在平衡的免疫信号传导下表现出增殖增加。结果在独立批次间具有可重复性。该系统能够在标准化、无标记条件下进行定量表型筛选,并为免疫肿瘤学流程中的功能评估提供了一个可适应的平台,其中传统的细胞毒性终点是不够的。这种方法已被编入STIP(结构化可追溯性和免疫表型平台),支持跨肿瘤模型的可重复记录。该平台有助于免疫肿瘤学工作流程中的上游验证逻辑,并支持早期监管文件编制。