Mathematical model of a personalized neoantigen cancer vaccine and the human immune system.
Marisabel Rodriguez MessanOsman N YogurtcuJoseph R McGillUjwani NukalaZuben E SaunaHong YangPublished in: PLoS computational biology (2021)
Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4+ and CD8+ T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient's immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient's major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.
Keyphrases
- papillary thyroid
- immune response
- squamous cell
- endothelial cells
- induced apoptosis
- case report
- lymph node metastasis
- squamous cell carcinoma
- childhood cancer
- early stage
- oxidative stress
- clinical trial
- end stage renal disease
- inflammatory response
- prognostic factors
- molecular dynamics
- endoplasmic reticulum stress
- cell death
- artificial intelligence
- skin cancer