Department of Urology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Yantai Institute, China Agricultural University, Yantai, China.
Front Immunol. 2022 Aug 25;13:972227. doi: 10.3389/fimmu.2022.972227. eCollection 2022.
Most patients with clear cell renal cell carcinoma (ccRCC) have an impaired response to immune checkpoint blockade (ICB) therapy. Few biomarkers can predict responsiveness, and there is insufficient evidence to extend them to ccRCC clinical use. To explore subtypes and signatures of immunocytes with good predictive performance for ICB outcomes in the ccRCC context, we reanalyzed two ccRCC single-cell RNA sequencing (scRNA-seq) datasets from patients receiving ICB treatment. A subtype of proliferative CD4 T cells and regulatory T cells and a subtype of antigen-presenting monocytes that have good predictive capability and are correlated with ICB outcomes were identified. These findings were corroborated in independent ccRCC ICB pretreatment bulk RNA-seq datasets. By incorporating the cluster-specific marker genes of these three immunocyte subtypes, we developed a prediction model, which reached an AUC of 93% for the CheckMate cohort (172 samples). Our study shows that the ICB response prediction model can serve as a valuable clinical decision-making tool for guiding ICB treatment of ccRCC patients.
大多数透明细胞肾细胞癌 (ccRCC) 患者对免疫检查点阻断 (ICB) 治疗的反应受损。很少有生物标志物可以预测反应性，并且没有足够的证据将其扩展到 ccRCC 的临床应用。为了探索在 ccRCC 背景下对 ICB 结果具有良好预测性能的免疫细胞亚群和特征，我们重新分析了来自接受 ICB 治疗的患者的两个 ccRCC 单细胞 RNA 测序 (scRNA-seq) 数据集。鉴定出具有良好预测能力且与 ICB 结果相关的增殖性 CD4 T 细胞和调节性 T 细胞亚群以及具有良好预测能力且与 ICB 结果相关的抗原呈递单核细胞亚群。这些发现在独立的 ccRCC ICB 预处理批量 RNA-seq 数据集中得到了证实。通过整合这三种免疫细胞亚群的簇特异性标记基因，我们开发了一个预测模型，在 CheckMate 队列 (172 个样本) 中达到了 93%的 AUC。我们的研究表明，ICB 反应预测模型可以作为指导 ccRCC 患者 ICB 治疗的有价值的临床决策工具。
