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

experimental_design

We conducted gene expression profiling on baseline tumors of patients treated with IPI and IFN.

我们对接受IPI和IFN治疗的患者的基线肿瘤进行了基因表达谱分析。

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.

我们还进行了多色流式细胞术，以比较解冻的外周血单个核细胞上细胞标志物的表达，并使用Luminex多重检测法来测量血清生物标志物。

We tested the expression levels of 31 genes and 40 circulating biomarkers in relation to survival outcomes.

我们检测了31个基因和40种循环生物标志物的表达水平，并研究了它们与生存结果的关系。

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.

我们随后开发了两个独立的多变量最小绝对收缩和选择算子（LASSO）Cox回归模型，并使用优先级生物标志物进行了风险预测的综合建模。

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 survivaland 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 survivaland 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.

在血液中，CXCR3+CD4+ T细胞、CXCR3+CD8+ T细胞、CTLA4+IFN-γ+CD8+ T细胞的富集群体以及CCL3和CXCL11水平的升高与显著改善的总生存和无复发生存相关，而CTLA4+调节性T细胞（CD3+CD4+CD25hi+CD152+）和单核性髓源性抑制细胞（Lin-CD33+HLA-DrloCD14+CD15+）的高水平与较差的总生存和无复发生存相关。在肿瘤中，CXCL9、CD8A、CXCL10和肌醇多磷酸-5-磷酸酶D被识别为一级（P < 0.05）生存生物标志物，而吲哚胺2,3-双加氧酶1、Igκ恒定区和IL2RB被识别为二级（P < 0.1）生物标志物。多变量生存分析确定约50%的风险组是由循环和肿瘤生物标志物模型定义的，这表明在IPI治疗的患者中定义风险组具有互补特征，但在IFN治疗的患者中则没有。

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.

整合候选的血液和肿瘤免疫相关生物标志物，生成了一个基线签名，该签名最大化了对免疫治疗益处的预测，相对于分隔的生物标志物签名。