肿瘤细胞治疗研究
英文原题：Dissecting the Tumor Microenvironment to Identify Biomarkers of Outcome to Anti-PD-1 Therapy in Clear-Cell Renal Cell Carcinoma: Analyses of the HCRN GU16-260 Trial.
肾透明细胞癌微环境中的各免疫细胞群体与一线抗 PD-1 治疗的应答/耐药相关。
目的：本研究在 II 期、非随机 HCRN GU16-260 试验中，考察免疫肿瘤微环境组分能否预测转移性透明细胞肾细胞癌（ccRCC）患者接受一线 nivolumab 抗 PD-1 治疗后的临床结局。 实验设计：对 72 名患者治疗前原发 ccRCC 组织进行多重免疫荧光和图像分析，评估非终末耗竭 CD8⁺PD-1⁺TIM-3⁻LAG-3⁻TIL（肿瘤浸润淋巴细胞）、PD-1⁺调节性 T 细胞（Treg）、总及瘤周三级淋巴结构（TLS）和 CD163⁺肿瘤相关巨噬细胞（TAM）。临床终点包括客观缓解率（ORR）和无进展生存期（PFS）。 结果：将这些细胞密度作为连续变量分析时，CD8⁺PD-1⁺TIM-3⁻LAG-3⁻ TIL、总及瘤周 TLS、CD163⁺ TAM 密度均与 ORR 提高相关（优势比：TIL 1.54［1.10–2.16］；总 TLS 1.18［1.02–1.37］；瘤周 TLS 1.10［1.02–1.18］；TAM 2.21［1.33–3.69］），也与 PFS 延长相关（风险比：TIL 0.79［0.67–0.95］；总 TLS 0.92［0.85–0.99］；瘤周 TLS 0.94［0.90–0.98］；TAM 0.77［0.61–0.97］）。将 PD-1⁺ Treg 百分比作为连续变量时，其与结局无关联；但按最佳截点分组后，PD-1⁺ Treg 比例高者 ORR 有较低趋势（12.5% 对 43.6%，P=0.093），且 PFS 更短（3.4 对 10.9 个月，P<0.001）。各生物标志物之间相关性不强，将其整合进多标志物模型可进一步区分结局。 结论：ccRCC 微环境中的不同免疫细胞群与一线抗 PD-1 治疗的应答/耐药相关。研究结果支持开发组合免疫标志物模型，以识别结局不同的患者。
PURPOSE: We investigated components of the immune tumor microenvironment as determinants of clinical outcome to anti-PD-1 therapy in patients with metastatic clear-cell renal cell carcinoma (ccRCC) treated with first-line nivolumab in the phase II, nonrandomized HCRN GU16-260 trial. EXPERIMENTAL DESIGN: Pretreatment primary ccRCCs from 72 patients were analyzed via multiplex immunofluorescence and image analysis to assess nonterminally exhausted CD8+ (CD8+PD-1+TIM-3-LAG-3-) tumor-infiltrating lymphocytes (TIL), PD-1+ regulatory T cells (Treg), total and peritumoral tertiary lymphoid structures (TLS), and CD163+ tumor-associated macrophages (TAM). Clinical endpoints included objective response rate (ORR) and progression-free survival (PFS). RESULTS: The densities of CD8+PD-1+TIM-3-LAG-3- TILs, total and peritumoral TLSs, and CD163+ TAMs, as continuous variables, were associated with improved ORR [odds ratio: 1.54 (1.10-2.16) for TILs; 1.18 (1.02-1.37) for total TLSs; 1.10 (1.02-1.18) for peritumoral TLSs; and 2.21 (1.33-3.69) for TAMs] and longer PFS [hazard ratio: 0.79 (0.67-0.95) for TILs; 0.92 (0.85-0.99) for total TLSs; 0.94 (0.90-0.98) for peritumoral TLSs; and 0.77 (0.61-0.97) for TAMs]. Although the percentage of PD-1+ Tregs as a continuous variable was not associated with outcomes, at an optimal cutoff, a high percentage of PD-1+ Tregs tended to be associated with lower ORR (12.5% vs. 43.6%, P = 0.093) and was associated with shorter PFS (3.4 vs. 10.9 months, P < 0.001). The biomarkers were not strongly correlated with each other, and their integration in multibiomarker models further stratified outcomes. CONCLUSIONS: Individual immune cell populations within the ccRCC microenvironment are associated with response/resistance to first-line anti-PD-1 therapy. Our findings support the development of combined immune marker models to identify patients with divergent outcomes.
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