Qin Yi, Wo Yang, Han Fengyi, Zhao Yandong, Wang Yawei
Qingdao University, Qingdao, China.
Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Jiangsu Road No.19, Qingdao, Shandong, China.
Discov Oncol. 2025 Apr 16;16(1):536. doi: 10.1007/s12672-025-02148-4.
Limited studies have investigated the metabolic heterogeneity of patients with clinical early-stage non-small cell lung cancer (NSCLC). Consensus clustering analysis has the potential to reveal distinct metabolic subgroups within clinical early-stage NSCLC patients. A total of 3324 clinical early-stage NSCLC patients who underwent surgery were included in this comprehensive evaluation. The evaluation encompassed 26 serum assessments related to metabolism and histopathological examination of the lymph nodes. By utilizing consensus clustering analysis, three clusters were identified based on various measurements, including blood glucose levels, blood uric acid, blood lipids, renal and liver function, and tumor markers. The differences in characteristics and lymph node metastasis (LNM) prevalence between the clusters were investigated and compared. The patients were classified into three distinct clusters that exhibited different patterns defined by the highest or lowest levels of metabolic feature variables. NSCLC cluster 1 had the lowest rates of LNM, while cluster 3 showed a significantly higher prevalence of LNM (1.6-fold increase, 95% CI: 1.21, 2.13) compared to cluster 1. Moreover, cluster 2 had the highest odds ratio (OR) of 1.78 (95% CI: 1.37, 2.33) for LNM prevalence. In subsequent sensitivity analysis, metabolic heterogeneity was observed among patients with a tumor measuring less than 2 cm in the long axis, along with similar differences in the prevalence of lymph node metastasis. This present study successfully categorized clinical early-stage NSCLC into three distinct subgroups, each with unique characteristics that reflect metabolic heterogeneity and significant disparities in the prevalence of LNM. Such an approach holds potential implications for clinical early-stage interventions targeting risk factors.
仅有有限的研究对临床早期非小细胞肺癌（NSCLC）患者的代谢异质性进行了调查。共识聚类分析有潜力揭示临床早期NSCLC患者中不同的代谢亚组。本综合评估纳入了总共3324例接受手术的临床早期NSCLC患者。评估涵盖了26项与代谢相关的血清检测以及淋巴结的组织病理学检查。通过使用共识聚类分析，基于包括血糖水平、血尿酸、血脂、肾功能和肝功能以及肿瘤标志物在内的各种测量指标，识别出了三个聚类。对各聚类之间的特征差异和淋巴结转移（LNM）发生率进行了调查和比较。患者被分为三个不同的聚类，这些聚类呈现出由代谢特征变量的最高或最低水平所定义的不同模式。NSCLC聚类1的LNM发生率最低，而聚类3的LNM发生率相较于聚类1显著更高（增加了1.6倍，95%置信区间：1.21，2.13）。此外，聚类2的LNM发生率的优势比（OR）最高，为1.78（95%置信区间：1.37，2.33）。在随后的敏感性分析中，在长轴小于2 cm的肿瘤患者中观察到了代谢异质性，同时淋巴结转移发生率也存在类似差异。本研究成功地将临床早期NSCLC分为三个不同的亚组，每个亚组都有独特的特征，反映了代谢异质性以及LNM发生率的显著差异。这种方法对针对风险因素的临床早期干预具有潜在意义。
