Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina.
Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina.
Clin Cancer Res. 2022 Mar 15;28(6):1192-1202. doi: 10.1158/1078-0432.CCR-21-3114.
Immunotherapy with checkpoint inhibitors is improving the outcomes of several cancers. However, only a subset of patients respond. Therefore, predictive biomarkers are critically needed to guide treatment decisions and develop approaches to the treatment of therapeutic resistance.
We compared bioenergetics of circulating immune cells and metabolomic profiles of plasma obtained at baseline from patients with melanoma treated with anti-PD-1 therapy. We also performed single-cell RNA sequencing (scRNAseq) to correlate transcriptional changes associated with metabolic changes observed in peripheral blood mononuclear cells (PBMC) and patient plasma.
Pretreatment PBMC from responders had a higher reserve respiratory capacity and higher basal glycolytic activity compared with nonresponders. Metabolomic analysis revealed that responder and nonresponder patient samples cluster differently, suggesting differences in metabolic signatures at baseline. Differential levels of specific lipid, amino acid, and glycolytic pathway metabolites were observed by response. Further, scRNAseq analysis revealed upregulation of T-cell genes regulating glycolysis. Our analysis showed that SLC2A14 (Glut-14; a glucose transporter) was the most significant gene upregulated in responder patients' T-cell population. Flow cytometry analysis confirmed significantly elevated cell surface expression of the Glut-14 in CD3+, CD8+, and CD4+ circulating populations in responder patients. Moreover, LDHC was also upregulated in the responder population.
Our results suggest a glycolytic signature characterizes checkpoint inhibitor responders; consistently, both ECAR and lactate-to-pyruvate ratio were significantly associated with overall survival. Together, these findings support the use of blood bioenergetics and metabolomics as predictive biomarkers of patient response to immune checkpoint inhibitor therapy.
免疫检查点抑制剂的免疫疗法正在改善几种癌症的预后。然而，只有一部分患者有反应。因此，迫切需要预测性生物标志物来指导治疗决策，并制定治疗治疗耐药性的方法。
我们比较了接受抗 PD-1 治疗的黑色素瘤患者基线时循环免疫细胞的生物能量和血浆代谢组学特征。我们还进行了单细胞 RNA 测序（scRNAseq），以关联与外周血单核细胞（PBMC）和患者血浆中观察到的代谢变化相关的转录变化。
与无反应者相比，有反应者的预处理 PBMC 具有更高的储备呼吸能力和更高的基础糖酵解活性。代谢组学分析表明，应答者和无应答者患者样本聚类不同，提示基线时代谢特征存在差异。通过应答观察到特定脂质、氨基酸和糖酵解途径代谢物的差异水平。此外，scRNAseq 分析显示 T 细胞基因调节糖酵解的上调。我们的分析表明，SLC2A14（Glut-14；葡萄糖转运蛋白）是应答者患者 T 细胞群体中上调最显著的基因。流式细胞术分析证实应答者患者的 CD3+、CD8+和 CD4+循环群体中 Glut-14 的细胞表面表达显著升高。此外，LDHC 在应答者群体中也上调。
我们的结果表明，糖酵解特征可表征检查点抑制剂应答者；一致地，ECAR 和乳酸/丙酮酸比均与总生存期显著相关。这些发现共同支持将血液生物能量和代谢组学用作免疫检查点抑制剂治疗患者反应的预测性生物标志物。
