背景:第9版肺癌TNM分类将M1c分为两个亚类:M1c1(单个器官系统内的多个胸腔外病变)和M1c2(涉及多个器官系统的多个胸腔外病变)。现有研究表明,与M1c2期相比,M1c1期肺癌患者的总体生存率更高。晚期非小细胞肺癌(NSCLC)患者的一线治疗,缺乏驱动基因突变,涉及使用免疫检查点抑制剂(ICIs)联合化疗。然而,缺乏证据表明接受一线免疫化疗的M1c1和M1c2非小细胞肺癌患者之间存在潜在的生存差异,预测治疗结果的可靠生物标志物难以捉摸.血清代谢谱可能阐明不同的预后机制,需要在接受联合治疗的M1c1和M1c2中鉴定不同的代谢物。这项研究旨在仔细检查各种转移模式(M1c1和M1c2)之间的生存差异,以及与接受一线ICIs联合化疗的NSCLC患者治疗结果相关的精确代谢物。
方法:在本研究中,根据第9版TNM分类,33例诊断为M1c1缺乏驱动基因突变的NSCLC患者,22例类似诊断为M1c2,已注册。这些患者接受了一线PD-1抑制剂加化疗。使用单变量和多变量Cox回归模型分析接受联合治疗的患者的转移模式与无进展生存期(PFS)之间的关系。在治疗开始前从所有患者获得血清样本,用于非靶向代谢组学分析,旨在鉴定差异代谢物。
结果:在PFS的单变量分析中,接受一线PD-1抑制剂加化疗的M1c1NSCLC患者表现出延长的PFS(HR=0.49,95%CI,0.27-0.88,p=0.017)。在多变量PFS分析中,这些接受一线PD-1抑制剂+化疗的M1c1患者的PFS也延长(HR=0.45,95%CI,0.22~0.92,p=0.028).接受一线PD-1抑制剂加化疗的M1c1和M1c2的血清代谢谱显示出明显的差异。与M1c1患者相比,M1c2患者在各种途径预处理中表现出改变,包括血小板活化,亚油酸代谢,和VEGF信号通路。脂质相关代谢物水平降低(二酰基甘油,鞘磷脂)与不良结局相关。
结论:NSCLC患者M1c1,无驱动基因突变,接受一线PD-1抑制剂联合化疗,与M1c2患者相比,经历了更好的结局。此外,代谢组学与这些患者的预后密切相关,预后不良的M1c2患者在治疗前表现出明显的代谢途径变化。这些变化主要涉及脂质代谢的改变,如减少二酰甘油和鞘磷脂,这可能会影响肿瘤的迁移和侵袭。
BACKGROUND: The 9th edition of the TNM Classification for lung cancer delineates M1c into two subcategories: M1c1 (Multiple extrathoracic lesions within a single organ system) and M1c2 (Multiple extrathoracic lesions involving multiple organ systems). Existing research indicates that patients with lung cancer in stage M1c1 exhibit superior overall survival compared to those in stage M1c2. The primary frontline therapy for patients with advanced non-small cell lung cancer (NSCLC), lacking driver gene mutations, involves the use of immune checkpoint inhibitors (ICIs) combined with chemotherapy. Nevertheless, a dearth of evidence exists regarding potential survival disparities between NSCLC patients with M1c1 and M1c2 undergoing first-line immune-chemotherapy, and reliable biomarkers for predicting treatment outcomes are elusive. Serum metabolic profiles may elucidate distinct prognostic mechanisms, necessitating the identification of divergent metabolites in M1c1 and M1c2 undergoing combination therapy. This study seeks to scrutinize survival discrepancies between various metastatic patterns (M1c1 and M1c2) and pinpoint metabolites associated with treatment outcomes in NSCLC patients undergoing first-line ICIs combined with chemotherapy.
METHODS: In this study, 33 NSCLC patients lacking driver gene mutations diagnosed with M1c1, and 22 similarly diagnosed with M1c2 according to the 9th edition of TNM Classification, were enrolled. These patients received first-line PD-1 inhibitor plus chemotherapy. The relationship between metastatic patterns and progression-free survival (PFS) in patients undergoing combination therapy was analyzed using univariate and multivariate Cox regression models. Serum samples were obtained from all patients before treatment initiation for untargeted metabolomics analysis, aiming to identify differential metabolites.
RESULTS: In the univariate analysis of PFS, NSCLC patients in M1c1 receiving first-line PD-1 inhibitor plus chemotherapy exhibited an extended PFS (HR = 0.49, 95% CI, 0.27-0.88, p = 0.017). In multivariate PFS analyses, these M1c1 patients receiving first-line PD-1 inhibitor plus chemotherapy also demonstrated prolonged PFS (HR = 0.45, 95% CI, 0.22-0.92, p = 0.028). The serum metabolic profiles of M1c1 and M1c2 undergoing first-line PD-1 inhibitors plus chemotherapy displayed notable distinctions. In comparison to M1c1 patients, M1c2 patients exhibited alterations in various pathways pretreatment, including platelet activation, linoleic acid metabolism, and the VEGF signaling pathway. Diminished levels of lipid-associated metabolites (diacylglycerol, sphingomyelin) were correlated with adverse outcomes.
CONCLUSIONS: NSCLC patients in M1c1, devoid of driver gene mutations, receiving first-line PD-1 inhibitors combined with chemotherapy, experienced superior outcomes compared to M1c2 patients. Moreover, metabolomic profiles strongly correlated with the prognosis of these patients, and M1c2 patients with unfavorable outcomes manifested distinct changes in metabolic pathways before treatment. These changes predominantly involved alterations in lipid metabolism, such as decreased diacylglycerol and sphingomyelin, which may impact tumor migration and invasion.