Chapter 3 │ Page 80 the experiment, with criteria including tumor volumes exceeding 1500 mm³ or the onset of ulceration. Long-term survivors were defined as mice remaining alive 100 days after experimental onset. 2.10. Data Processing and Statistical Analysis Statistical di erences for spheroid viability, organoid kinetics, DAMP expression, and cytokine and chemokine release were determined with JMP Pro 17 (SAS Software, Belgium). The linear mixed model was used, with “treatment” designated as the fixed e ect, and the “di erent experimental repeats” and the “interaction between experiments and the date” as random e ects. Only after null hypothesis rejection in the Fixed E ect Test, statistical significance of the fixed e ect was determined, and a post hoc analysis for multiple comparisons was performed. When comparing data to untreated controls, Dunnett’s correction for multiple testing was performed, while Tukey’s correction was used for all pairwise comparisons. For in vivo experiments, survival di erences between groups were evaluated using the Log-Rank (Mantel-Cox) test, while Cox Proportional Hazards (CoxPH) Model was used to determine hazard ratios (protection e ect) compared to untreated controls (Python). Di erences in mouse tumor kinetics were assessed using Mixed Model ANOVA in R. P values equal to or less than 0.05 were considered as statistically significant. Visual representations (graphs and heatmaps) were created with GraphPad Prism v10.4.1, while the spheroid kinetics synergy map was generated using the SynergyFinder tool. Unsupervised hierarchical clustering of cytokine and chemokine results was performed in Python. Data was first preprocessed through log₂ transformation and Z-score normalization, followed by calculating a correlation-based distance matrix. Agglomerative clustering using Ward’s method was applied, and the results were visualized via a heatmap with dendrograms using the incorporated Seaborn clustering tool.
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