Yang Yiren, Pang Qingyang, Hua Meimian, Huangfu Zhao, Yan Rui, Liu Wenqiang, Zhang Wei, Shi Xiaolei, Xu Yifan, Shi Jiazi
Department of Urology, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China.
Department of Urology, Changzheng Hospital, Naval Medical University (Second Military Medical University), Shanghai, China.
Front Oncol. 2023 May 16;13:1170567. doi: 10.3389/fonc.2023.1170567. eCollection 2023.
Clear cell renal cell carcinoma (ccRCC) is the most common pathology type in kidney cancer. However, the prognosis of advanced ccRCC is unsatisfactory. Thus, early diagnosis becomes one of the most important research priorities of ccRCC. However, currently available studies about ccRCC lack urine-related further studies. In this study, we applied proteomics to search urinary biomarkers to assist early diagnosis of ccRCC. In addition, we constructed a prognostic model to assist judge patients' prognosis.
Urine which was used to perform 4D label-free quantitative proteomics was collected from 12 ccRCC patients and 11 non-tumor patients with no urinary system diseases. The urine of 12 patients with ccRCC confirmed by pathological examination after surgery was collected before operatoin. Bioinformatics analysis was used to describe the urinary proteomics landscape of these patients with ccRCC. The top ten proteins with the highest expression content were selected as the basis for subsequent validation. Urine from 46 ccRCC patients and 45 control patients were collected to use for verification by enzyme linked immunosorbent assay (ELISA). In order to assess the prognostic value of urine proteomics, a prognostic model was constructed by COX regression analysis on the intersection of RNA-sequencing data in The Cancer Genome Atlas (TCGA) database and our urine proteomic data.
133 proteins differentially expressed in the urinary samples were found and 85 proteins (Fold Change, FC>1.5) were identified up-regulated while 48 down-regulated (FC<0.5). Top 10 proteins including S100A14, PKHD1L1, FABP4, ITIH2, C3, C8G, C2, ATF6, ANGPTL6, F13B were performed ELISA to verify. The results showed that PKHD1L1, ANGPTL6, FABP4 and C3 were statistically significant (<0.05). We performed multivariate logistic regression analysis and plotted a nomogram. Receiver operating characteristic (ROC) curve indicted that the diagnostic efficiency of combined indicators is satisfactory (Aare under curve, AUC=0.835). Furthermore, the prognostic value of the urine proteomics was explored through the intersection between urine proteomics and TCGA RNA-seq data. Thus, COX regression analysis showed that VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 were statistically significant (<0.05).
Our study indicated that the application of urine proteomics to explore diagnostic biomarkers and to construct prognostic models of renal clear cell carcinoma is of certain clinical value. PKHD1L1, ANGPTL6, FABP4 and C3 can assist to diagnose ccRCC. The prognostic model constituted of VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 can significantly predict the prognosis of ccRCC patients, but this still needs more clinical trials to verify.
透明细胞肾细胞癌（ccRCC）是肾癌中最常见的病理类型。然而，晚期ccRCC的预后并不理想。因此，早期诊断成为ccRCC最重要的研究重点之一。然而，目前关于ccRCC的现有研究缺乏与尿液相关的进一步研究。在本研究中，我们应用蛋白质组学来寻找尿液生物标志物以辅助ccRCC的早期诊断。此外，我们构建了一个预后模型以辅助判断患者的预后。
从12例ccRCC患者和11例无泌尿系统疾病的非肿瘤患者中收集用于进行4D无标记定量蛋白质组学分析的尿液。12例经手术病理检查确诊为ccRCC的患者的尿液在手术前收集。采用生物信息学分析来描述这些ccRCC患者的尿液蛋白质组学概况。选择表达含量最高的前10种蛋白质作为后续验证的基础。收集46例ccRCC患者和45例对照患者的尿液用于通过酶联免疫吸附测定（ELISA）进行验证。为了评估尿液蛋白质组学的预后价值，通过对癌症基因组图谱（TCGA）数据库中的RNA测序数据与我们的尿液蛋白质组数据的交集进行COX回归分析构建了一个预后模型。
在尿液样本中发现133种差异表达的蛋白质，其中85种蛋白质（倍数变化，FC>1.5）被鉴定为上调，48种下调（FC<0.5）。对包括S100A14、PKHD1L1、FABP4、ITIH2、C3、C8G、C2、ATF6、ANGPTL6、F13B在内的前10种蛋白质进行ELISA验证。结果显示PKHD1L1、ANGPTL6、FABP4和C3具有统计学意义（<0.05）。我们进行了多因素逻辑回归分析并绘制了列线图。受试者工作特征（ROC）曲线表明联合指标的诊断效率令人满意（曲线下面积，AUC=0.835）。此外，通过尿液蛋白质组学与TCGA RNA-seq数据的交集探索了尿液蛋白质组学的预后价值。因此，COX回归分析表明VSIG4、HLA-DRA、SERPINF1和IGLV2-23具有统计学意义（<0.05）。
我们的研究表明，应用尿液蛋白质组学探索肾透明细胞癌的诊断生物标志物并构建预后模型具有一定的临床价值。PKHD1L1、ANGPTL6、FABP4和C3可辅助诊断ccRCC。由VSIG4、HLA-DRA、SERPINF1和IGLV2-23构成的预后模型可显著预测ccRCC患者的预后，但这仍需要更多的临床试验来验证。
