Department of Minimally Invasive Interventional Therapy, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou China.
Department of Medical Oncology, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Artificial Intelligence Laboratory of Sun Yat-Sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Oncoimmunology. 2021 Apr 2;10(1):1908010. doi: 10.1080/2162402X.2021.1908010.
Currently, a significant proportion of cancer patients do not benefit from programmed cell death-1 (PD-1)-targeted therapy. Overcoming drug resistance remains a challenge. In this study, single-cell RNA sequencing and bulk RNA sequencing data from samples collected before and after anti-PD-1 therapy were analyzed. Cell-cell interaction analyses were performed to determine the differences between pretreatment responders and nonresponders and the relative differences in changes from pretreatment to posttreatment status between responders and nonresponders to ultimately investigate the specific mechanisms underlying response and resistance to anti-PD-1 therapy. Bulk-RNA sequencing data were used to validate our results. Furthermore, we analyzed the evolutionary trajectory of ligands/receptors in specific cell types in responders and nonresponders. Based on pretreatment data from responders and nonresponders, we identified several different cell-cell interactions, like WNT5A-PTPRK, EGFR-AREG, AXL-GAS6 and ACKR3-CXCL12. Furthermore, relative differences in the changes from pretreatment to posttreatment status between responders and nonresponders existed in SELE-PSGL-1, CXCR3-CCL19, CCL4-SLC7A1, CXCL12-CXCR3, EGFR-AREG, THBS1-a3b1 complex, TNF-TNFRSF1A, TNF-FAS and TNFSF10-TNFRSF10D interactions. In trajectory analyses of tumor-specific exhausted CD8 T cells using ligand/receptor genes, we identified a cluster of T cells that presented a distinct pattern of ligand/receptor expression. They highly expressed suppressive genes like HAVCR2 and KLRC1, cytotoxic genes like GZMB and FASLG and the tissue-residence-related gene CCL5. These cells had increased expression of survival-related and tissue-residence-related genes, like heat shock protein genes and the interleukin-7 receptor (IL-7R), CACYBP and IFITM3 genes, after anti-PD-1 therapy. These results reveal the mechanisms underlying anti-PD-1 therapy response and offer abundant clues for potential strategies to improve immunotherapy.
目前，相当一部分癌症患者无法从程序性细胞死亡蛋白 1（PD-1）靶向治疗中获益。克服耐药性仍然是一个挑战。在这项研究中，分析了接受抗 PD-1 治疗前后采集的样本的单细胞 RNA 测序和批量 RNA 测序数据。进行细胞间相互作用分析，以确定治疗前应答者和无应答者之间的差异，以及应答者和无应答者从治疗前到治疗后状态变化的相对差异，最终研究抗 PD-1 治疗应答和耐药的具体机制。使用批量 RNA 测序数据验证了我们的结果。此外，我们分析了应答者和无应答者中特定细胞类型中配体/受体的进化轨迹。基于应答者和无应答者的预处理数据，我们确定了几种不同的细胞间相互作用，如 WNT5A-PTPRK、EGFR-AREG、AXL-GAS6 和 ACKR3-CXCL12。此外，应答者和无应答者从治疗前到治疗后状态变化的相对差异存在于 SELE-PSGL-1、CXCR3-CCL19、CCL4-SLC7A1、CXCL12-CXCR3、EGFR-AREG、THBS1-a3b1 复合物、TNF-TNFRSF1A、TNF-FAS 和 TNFSF10-TNFRSF10D 相互作用中。在使用配体/受体基因对肿瘤特异性耗竭 CD8 T 细胞进行轨迹分析时，我们鉴定了一群呈现独特配体/受体表达模式的 T 细胞。它们高度表达抑制性基因，如 HAVCR2 和 KLRC1、细胞毒性基因，如 GZMB 和 FASLG 和组织驻留相关基因 CCL5。这些细胞在接受抗 PD-1 治疗后，表达与存活和组织驻留相关的基因增加，如热休克蛋白基因和白细胞介素 7 受体（IL-7R）、CACYBP 和 IFITM3 基因。这些结果揭示了抗 PD-1 治疗应答的机制，并为潜在的改善免疫治疗策略提供了丰富的线索。
