Immunological monitoring for prediction of clinical response to antitumor vaccine therapy

Abstract

Immunotherapy has shown promising results in a variety of cancers, including melanoma. However, the responses to therapy are usually heterogeneous, and understanding the factors affecting clinical outcome is still not achieved. Here, we show that immunological monitoring of the vaccine therapy for melanoma patients may help to predict the clinical course of the disease.We studied cytokine profile of cellular Th1 (IL-2, IL-12, IFN-γ) and humoral Th2 (IL-4, IL-10) immune response, vascular endothelial growth factor (VEGFA), transforming growth factor-β 2 (TGF-β 2), S100 protein (S100A1B and S100BB), adhesion molecule CD44 and serum cytokines β2-microglobulin to analyze different peripheral blood mononuclear cell subpopuations of patients treated with dendritic vaccines and/or cyclophosphamide in melanoma patients in the course of adjuvant treatment.The obtained data indicate predominance of cellular immunity in the first adjuvant group of patients with durable time to progression and shift to humoral with low cellular immunity in patients with short-term period to progression (increased levels of IL-4 and IL- 10). Beta-2 microglobulin was differentially expressed in adjuvant subgroups: its higher levels correlated with shorter progression-free survival and the total follow-up time. Immunoregulatory index was overall higher in patients with disease progression compared to the group of patients with no signs of disease progression.

Activation of interferon regulatory factor 3 by replication-competent vaccinia viruses improves antitumor efficacy mediated by T cell responses

“… 42 We based our strategy for improving antitumor T cell responses on the observation that poly(I:C), used as an adjuvant in cancer vaccination, leads to T helper 1 (Th1) polarization, 43 which directly correlates with robust antitumor immunity in the clinic. 44 As poly(I:C) selectively activates TLR3, we attempted to construct an oncolytic vector virus with the capacity to activate the TLR3-IRF3 pathway after infection.…”

Immuno-Metabolism and Microenvironment in Cancer: Key Players for Immunotherapy

“… Other predictive factors such as the genomic signatures and metabolic profiles associated with ICI resistance are under preclinical and clinical evaluation, and some of them have shown encouraging results [ 154 ]. The presence of mutations of Janus kinase 2 (JAK2), beta2-microglobulin and serine/threonine kinase 11 (STK11) are some of the alterations that have recently emerged as potential predictors of low responsiveness to ICIs [ 155 , 156 , 157 ]. Heterozygosity in the HLA class I genotype, a characteristic that facilitates the presentation of a broader set of tumor antigens to T cells, is another possible response biomarker that has been demonstrated to confer a higher responsivity to ICIs in cancer patients [ 158 , 159 ].…”

“…Other predictive factors such as the genomic signatures and metabolic profiles associated with ICI resistance are under preclinical and clinical evaluation, and some of them have shown encouraging results [ 154 ]. The presence of mutations of Janus kinase 2 (JAK2), beta2-microglobulin and serine/threonine kinase 11 (STK11) are some of the alterations that have recently emerged as potential predictors of low responsiveness to ICIs [ 155 , 156 , 157 ].…”