Table_3_A network approach to define the predictive role of immune profile on tumor response and toxicity of anti PD-1 single agent immunotherapy in patients with solid tumors.xlsx

BackgroundThe immune profile of each patient could be considered as a portrait of the fitness of his/her own immune system. The predictive role of the immune profile in immune-related toxicities (irAEs) development and tumour response to treatment was investigated.
MethodsA prospective, multicenter study evaluating, through a multiplex assay, the soluble immune profile at the baseline of 53 patients with advanced cancer, treated with immunotherapy as single agent was performed. Four connectivity heat maps and networks were obtained by calculating the Spearman correlation coefficients for each group: responder patients who developed cumulative toxicity (R-T), responders who did not develop cumulative toxicity (R-NT), non-responders who developed cumulative toxicity (NR-T), non-responders who did not develop cumulative toxicity (NR-NT).
ResultsA statistically significant up-regulation of IL-17A, sCTLA4, sCD80, I-CAM-1, sP-Selectin and sEselectin in NR-T was detected. A clear loss of connectivity of most of the soluble immune checkpoints and cytokines characterized the immune profile of patients with toxicity, while an inversion of the correlation for ICAM-1 and sP-selectin was observed in NR-T. Four connectivity networks were built for each group. The highest number of connections characterized the NR-T.
ConclusionsA connectivity network of immune dysregulation was defined for each subgroup of patients, regardless of tumor type. In patients with the worst prognosis (NR-T) the peculiar connectivity model could facilitate their early and timely identification, as well as the design of a personalized treatment approach to improve outcomes or prevent irAEs.

背景 每位患者的免疫谱可视为其自身免疫系统健康状态的画像。本研究探讨了免疫谱在免疫相关不良反应（immune-related adverse events, irAEs）发生及肿瘤治疗应答中的预测作用。
方法 本研究为一项前瞻性多中心研究，通过多重检测分析对53例接受单药免疫治疗的晚期癌症患者的基线可溶性免疫标志物谱进行评估。研究针对四组患者分别计算斯皮尔曼相关系数（Spearman correlation coefficients），以此生成四张关联热图与关联网络：发生累积毒性的治疗应答者（R-T）、未发生累积毒性的治疗应答者（R-NT）、发生累积毒性的无应答者（NR-T）、未发生累积毒性的无应答者（NR-NT）。
结果 研究在NR-T组中检测到白细胞介素17A（IL-17A）、可溶性细胞毒性T淋巴细胞相关抗原4（sCTLA4）、可溶性CD80（sCD80）、细胞间黏附分子1（I-CAM-1）、可溶性P选择素（sP-Selectin）以及可溶性E选择素（sE-selectin）的表达具有统计学意义的显著上调。存在毒性反应的患者的免疫谱特征为多数可溶性免疫检查点分子与细胞因子的关联网络出现明显连接缺失；而在NR-T组中，细胞间黏附分子1与可溶性P选择素的相关性发生反转。本研究为上述四组患者分别构建了关联网络，其中NR-T组的关联连接数量最多。
结论 本研究为各患者亚组构建了免疫失调关联网络，且该网络不受肿瘤类型的影响。在预后最差的NR-T组患者中，其独特的关联网络模型可助力实现早期及时识别，同时可为制定个性化治疗方案以改善预后或预防免疫相关不良反应提供指导。