Recent years have seen several exciting advancements in the development of active immunotherapy for the treatment of cancer. Sipuleucel-T, an active immunotherapy comprised of autologous dendritic cells (DC) pulsed with a fusion protein composed of granulocyte macrophage colony-stimulating factor (GM-CSF) and prostatic acid phosphatase (PAP), was shown to provide a significant increase in overall survival in patients with metastatic prostate cancer (Kantoff et al., 2010
). Additionally, ipilimumab, an antibody blocking cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) that facilitates T cell activation, was found to provide a benefit in overall survival in individuals with metastatic melanoma (Hodi et al., 2010
). While the success these agents had in Phase III clinical trials represented a ground shift in our understanding of the potential of anti-tumor immunity, the results from these trials also illuminated challenges with the clinical evaluation of immunotherapies. As opposed to therapies with direct cytotoxic effects, like chemotherapy or radiation therapy, immune-modulating therapies require time to activate the immune system and induce T-cell proliferation to sufficient levels where it can achieve clinical benefit, a process which may take place over weeks to months. As such, while randomized trials evaluating sipuleucel-T and ipilimumab both achieved the clinical endpoint of increased overall survival, they were not able to meet interim markers of efficacy such as increased time to disease progression. This emphasizes the importance of identifying short-term markers of efficacy that can be used to identify individuals who are responding to therapy, or those who would benefit from moving on to alternative treatments.
As one of the central goals of tumor immunotherapy is to elicit and/or augment cytotoxic T-cell responses that can recognize and lyse tumor cells, the development of interim biomarkers of immunotherapeutic efficacy have largely focused on assays that measure these inflammatory, Th1-type anti-tumor responses. This has led to the near universal use of assays such as enzyme-linked immunosorbent spot (ELISPOT) assays, intracellular cytokine staining (ICCS), and HLA-peptide multimer analysis. However, as our understanding of the nature of the relationship between the tumor and immune response has matured, tumor immunologists have come to appreciate that these effector responses are only one aspect of the immune system that can impact anti-tumor immunity. The immune system (and the tumor itself) is also able to mount suppressive immune responses that target effector responses and can lead to the amelioration of anti-tumor responses. These suppressive immune responses are predominantly composed of regulatory T cells, myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAM), which are able to survey the tumor microenvironment for effector immune responses to inhibit, which leads to the avoidance of anti-tumor immunity and further tumor growth. The monitoring of changes in regulatory immune responses, consequently, could theoretically serve as an additional biomarker of response to immune therapies, particular in the case of immune-modulating therapies or whole tumor vaccines where a specific antigenic target is unknown.
While there has been interest in monitoring suppressive immune responses following immunotherapeutic intervention, this has been a challenge given the difficulty in defining a set of cellular surface markers that can be used to easily identify and quantify regulatory immune responses. Furthermore, when evaluating antigen-specific vaccine approaches, there has been a noticeable paucity in the evaluation of antigen-specific regulatory responses following immunization. In addition, the intrinsic plasticity in regulatory immune function further complicates this analysis, as data in preclinical models indicates that immune responses can gain and lose suppressive activity depending on the microenvironment, which is particular important in the case of lymphocytes that infiltrate the suppressive tumor microenvironment. In this review, we will describe these regulatory cell populations, how they can suppress anti-tumor immune responses, how they have been used in the immune monitoring of clinical trials, and challenges associated with the implementation of regulatory cell detection into clinical trial immune monitoring.