Integrative Immune Signature of Complementary Circulating and Tumoral Biomarkers Maximizes the Predictive Power of Adjuvant Immunotherapeutic Benefits in High-risk Melanoma.

Purpose: Ipilimumab (IPI) improved outcomes for patients with high-risk melanoma compared with IFN-α2b in E1609, a phase III adjuvant trial. We hypothesized that combining candidate immune biomarkers in both tumor and circulating blood could generate a superior predictive biomarker signature.

Experimental Design: We conducted gene expression profiling on baseline tumors of patients treated with IPI and IFN. We also performed multicolor flow cytometry to compare cellular marker expression on thawed peripheral blood mononuclear cells and Luminex multiplex assay to measure serum biomarkers. We tested the expression levels of 31 genes and 40 circulating biomarkers in relation to survival outcomes. We then developed two separate multivariate Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression models followed by integrative modeling of risk prediction using the prioritized biomarkers.

Results: In blood, enriched populations of CXCR3+CD4+ T cells, CXCR3+CD8+ T cells, CTLA4+IFN-γ+CD8+ T cells, and higher levels of CCL3 and CXCL11 were associated with significantly improved overall survival and relapse-free survival, whereas high levels of CTLA4+ regulatory T cells (CD3+CD4+CD25hi+CD152+) and monocytic myeloid-derived suppressor cells (Lin-CD33+HLA-DrloCD14+CD15+) correlated with worse overall survival and relapse-free survival. In tumor, CXCL9, CD8A, CXCL10, and inositol polyphosphate-5-phosphatase D were identified as tier-1 (P < 0.05) and indoleamine 2, 3-dioxygenase 1, Igκ constant, and IL2RB as tier-2 (P < 0.1) biomarkers of survival. Multivariate survival analysis identified that ∼50% of the risk groups were defined by circulating and tumor biomarker models, indicating complementary features of defining risk groups in IPI-treated but not in IFN-treated patients.

Conclusions: Integrating candidate blood and tumor immune-related biomarkers generated a baseline signature that maximizes the prediction of immunotherapeutic benefits in reference to the compartmental biomarker signatures.