Chang Zhenglin, Chen Bingsen, Wang Suilin, Chen Kaipai, Huang Linliang, Yang Yi, Wu Haojie, Jian Wenhua, Cheng Zhangkai J, Han Xiujing, Sun Baoqing
Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China.
Guangzhou National Laboratory, Guangzhou International Bio Island, XingDaoHuanBei Road, Guangzhou, 510005, Guangdong Province, China.
BMC Cancer. 2025 May 1;25(1):820. doi: 10.1186/s12885-025-14225-6.
Cancer biomarker discovery is essential for early detection and monitoring, yet there is a lack of comprehensive studies examining organ-specific biomarkers across various cancer types. In this study, we analyzed clinical data from 59,184 cancer patients diagnosed between 2013 and 2023, focusing on 11 major cancer systems. We used propensity score matching with 55,010 healthy controls to create balanced comparison groups. Serum biomarker profiles were assessed through principal component analysis, differential expression analysis, and ROC curve analysis. Our findings revealed organ-specific biomarker patterns, such as decreased CA724, ferritin, and β2-microglobulin in thoracic cancer, reduced serum phosphorus in neurological cancer, and elevated cystatin C and creatinine in urinary system cancer. Further analysis across 22 cancer types uncovered additional biomarkers, including elevated ALT in hepatobiliary cancer, altered coagulation factors in laryngeal cancer, increased monocytes in pancreatic cancer, and reduced complement C3 in intestinal cancer. These results provide valuable insights into the unique biomarker signatures for different cancers, contributing to the potential development of more targeted and efficient screening methods.
癌症生物标志物的发现对于早期检测和监测至关重要，但目前缺乏全面研究各种癌症类型中器官特异性生物标志物的研究。在本研究中，我们分析了2013年至2023年间确诊的59184例癌症患者的临床数据，重点关注11个主要癌症系统。我们使用倾向评分匹配法与55010名健康对照创建了平衡的比较组。通过主成分分析、差异表达分析和ROC曲线分析评估血清生物标志物谱。我们的研究结果揭示了器官特异性生物标志物模式，如胸段癌中CA724、铁蛋白和β2-微球蛋白降低，神经癌中血清磷降低，泌尿系统癌中胱抑素C和肌酐升高。对22种癌症类型的进一步分析发现了其他生物标志物，包括肝胆癌中ALT升高、喉癌中凝血因子改变、胰腺癌中单核细胞增加以及肠癌中补体C3降低。这些结果为不同癌症的独特生物标志物特征提供了有价值的见解，有助于开发更具针对性和高效的筛查方法。
