Aims: Immunotherapy is a rising alternative to traditional treatment in breast cancer (BC) patients in order to transform cold into hot immune enriched tumours and improve responses and outcome. A computational modelling approach was applied to quantify modulation effects of immunotherapy and chemotherapy response on tumour shrinkage and progression-free survival (PFS) in naïve BC patients.
Methods: Eighty-three Her2-negative BC patients were recruited for neoadjuvant chemotherapy with or without immunotherapy based on dendritic cell vaccination. Sequential tumour size measurements were modelled using nonlinear mixed effects modelling and linked to PFS. Data from another set of patients (n = 111) were used to validate the model.
Results: Tumour size profiles over time were linked to biomarker dynamics and PFS. The immunotherapy effect was related to tumour shrinkage (P < .05), with the shrinkage 17% (95% confidence interval: 2-23%) being higher in vaccinated patients, confirmed by the finding that pathological complete response rates in the breast were higher in the vaccinated compared to the control group (25.6% vs 13.6%; P = .04). The whole tumour shrinkage time profile was the major prognostic factor associated to PFS (P < .05), and therefore, immunotherapy influences indirectly on PFS, showing a trend in decreasing the probability of progression with increased vaccine effects. Tumour subtype was also associated with PFS (P < .05), showing that luminal A BC patients have better prognosis.
Conclusions: Dendritic cell-based immunotherapy is effective in decreasing tumour size. The semi-mechanistic validated model presented allows the quantification of the immunotherapy treatment effects on tumour shrinkage and establishes the relationship between the dynamics of tumour size and PFS.
Keywords: computational modelling; dendritic cell vaccines; neoadjuvant scenario; pharmacodynamics; pharmacometrics.