Targeting myeloid-derived suppressor cells in combination with tumor cell vaccination predicts anti-tumor immunity and breast cancer dormancy: an in silico experiment.

Among the different breast cancer subsets, triple-negative breast cancer (TNBC) has the worst prognosis and limited options for targeted therapies. Immunotherapies are emerging as novel treatment opportunities for TNBC. However, the surging immune response elicited by immunotherapies to eradicate cancer cells can select resistant cancer cells, which may result in immune escape and tumor evolution and progression. Alternatively, maintaining the equilibrium phase of the immune response may be advantageous for keeping a long-term immune response in the presence of a small-size residual tumor. Myeloid-derived suppressor cells (MDSCs) are activated, expanded, and recruited to the tumor microenvironment by tumor-derived signals and can shape a pro-tumorigenic micro-environment by suppressing the innate and adaptive anti-tumor immune responses. We recently proposed a model describing immune-mediated breast cancer dormancy instigated by a vaccine consisting of dormant, immunogenic breast cancer cells derived from the murine 4T1 TNBC-like cell line. Strikingly, these 4T1-derived dormant cells recruited fewer MDSCs compared to aggressive 4T1 cells. Recent experimental studies demonstrated that inactivating MDSCs has a profound impact on reconstituting immune surveillance against the tumor. Here, we developed a deterministic mathematical model for simulating MDSCs depletion from mice bearing aggressive 4T1 tumors resulting in immunomodulation. Our computational simulations indicate that a vaccination strategy with a small number of tumor cells in combination with MDSC depletion can elicit an effective immune response suppressing the growth of a subsequent challenge with aggressive tumor cells, resulting in sustained tumor dormancy. The results predict a novel therapeutic opportunity based on the induction of effective anti-tumor immunity and tumor dormancy.

Pubmed ID: 37041172 RIS Download