Zhou Xu, Xue Fei, Li Tingmiao, Xue Jiangshan, Yue Siqi, Zhao Shujie, Lu Hezhen, He Chengyan
Department of Laboratory Medicine, China-Japan Union Hospital of Jilin University, Changchun, China.
Department of Laboratory Medicine, Changchun Infectious Diseases Hospital, Changchun, China.
Front Oncol. 2024 Feb 12;14:1309842. doi: 10.3389/fonc.2024.1309842. eCollection 2024.
Bladder cancer is a common malignant tumor of the urinary system. The progression of the condition is associated with a poor prognosis, so it is necessary to identify new biomarkers to improve the diagnostic rate of bladder cancer.
In this study, 338 urine samples (144 bladder cancer, 123 healthy control, 32 cystitis, and 39 upper urinary tract cancer samples) were collected, among which 238 samples (discovery group) were analyzed by LC-MS. The urinary proteome characteristics of each group were compared with those of bladder cancer, and the differential proteins were defined by bioinformatics analysis. The pathways and functional enrichments were annotated. The selected proteins with the highest AUC score were used to construct a diagnostic panel. One hundred samples (validation group) were used to test the effect of the panel by ELISA.
Compared with the healthy control, cystitis and upper urinary tract cancer samples, the number of differential proteins in the bladder cancer samples was 325, 158 and 473, respectively. The differentially expressed proteins were mainly related to lipid metabolism and iron metabolism and were involved in the proliferation, metabolism and necrosis of bladder cancer cells. The AUC of the panel of APOL1 and ITIH3 was 0.96 in the discovery group. ELISA detection showed an AUC of 0.92 in the validation group.
This study showed that urinary proteins can reflect the pathophysiological changes in bladder cancer and that important molecules can be used as biomarkers for bladder cancer screening. These findings will benefit the application of the urine proteome in clinical research.
膀胱癌是泌尿系统常见的恶性肿瘤。病情进展与预后不良相关，因此有必要识别新的生物标志物以提高膀胱癌的诊断率。
本研究收集了338份尿液样本（144份膀胱癌样本、123份健康对照样本、32份膀胱炎样本和39份上尿路癌样本），其中238份样本（发现组）通过液相色谱-质谱联用仪进行分析。将每组的尿液蛋白质组特征与膀胱癌组进行比较，并通过生物信息学分析确定差异蛋白。对通路和功能富集进行注释。使用曲线下面积（AUC）得分最高的选定蛋白质构建诊断模型。使用100份样本（验证组）通过酶联免疫吸附测定（ELISA）检测该模型的效果。
与健康对照、膀胱炎和上尿路癌样本相比，膀胱癌样本中的差异蛋白数量分别为325、158和473种。差异表达蛋白主要与脂质代谢和铁代谢相关，并参与膀胱癌细胞的增殖、代谢和坏死。在发现组中，载脂蛋白L1（APOL1）和富含组氨酸的糖蛋白3（ITIH3）诊断模型的AUC为0.96。ELISA检测显示验证组的AUC为0.92。
本研究表明尿液蛋白质可反映膀胱癌的病理生理变化，重要分子可作为膀胱癌筛查的生物标志物。这些发现将有利于尿液蛋白质组在临床研究中的应用。
