Department of Obstetrics and Gynecology, Skåne University Hospital, Lund, Sweden;
Clinical Studies Sweden-Forum South, Skåne University Hospital, Lund, Sweden.
Cancer Genomics Proteomics. 2023 May-Jun;20(3):273-280. doi: 10.21873/cgp.20380.
BACKGROUND/AIM: Epithelial ovarian cancer (EOC) is usually diagnosed in advanced stages and has a high mortality rate. In this study, we used the proximity extension assay from Olink Proteomics to search for new plasma protein biomarkers to predict overall survival (OS) in patients with EOC.
Peripheral blood samples were obtained preoperatively from 116 EOC patients undergoing primary debulking surgery: 28 early EOC cases (FIGO stage I-II) and 88 advanced EOC cases (FIGO stage III-IV). Proteins were measured using the Olink Oncology II and Inflammation panels. In total, 177 unique protein biomarkers were analysed. Cross-validation and LASSO regression were combined to select prediction models for OS.
The model including age and the three-biomarker combination of neurotrophin-3 (NT-3)+transmembrane glycoprotein NMB (GPNMB)+mesothelin (MSLN) predicted worse OS with AUC=0.79 (p=0.004). Adding cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) to the model further improved performance (AUC=0.83; p=0.003). In a postoperative model including age and stage (III+IV vs. I+II), the three-biomarker panel of chemokine (C-C motif) ligand 28 (CCL28)+T-cell leukaemia/lymphoma protein 1A (TCL1A)+GPNMB improved the prediction of OS (from AUC=0.83 to AUC=0.90; p=0.05). In the postoperative model including age and dichotomized stage (III vs. I+II), the biomarkers CCL28 and GPNMB1 improved the prediction of OS (AUC=0.86; p<0.001). The combination of high levels of both CA125 and HE4 predicted worse survival (p=0.05).
In this explorative study evaluating the performance of plasma protein biomarkers in predicting OS, we found that adding biomarkers, especially NT-3, to the panel improved the prediction of OS.
背景/目的:上皮性卵巢癌(EOC)通常在晚期诊断,死亡率较高。本研究采用 Olink 蛋白质组学邻近延伸分析技术,寻找新的血浆蛋白生物标志物,预测上皮性卵巢癌患者的总生存期(OS)。
对 116 例行初次肿瘤细胞减灭术的上皮性卵巢癌患者(28 例早期 EOC 患者,FIGO Ⅰ-Ⅱ期;88 例晚期 EOC 患者,FIGO Ⅲ-Ⅳ期)术前采集外周血样本。采用 Olink Oncology II 和 Inflammation 面板进行蛋白检测。共分析了 177 种独特的蛋白生物标志物。采用交叉验证和 LASSO 回归相结合的方法选择用于 OS 预测的模型。
包含年龄和神经生长因子-3(NT-3)+跨膜糖蛋白 NMB(GPNMB)+间皮素(MSLN)这三个生物标志物组合的模型预测 OS 较差,AUC=0.79(p=0.004)。在该模型中加入癌抗原 125(CA125)和人附睾蛋白 4(HE4)可进一步提高模型性能(AUC=0.83,p=0.003)。在包含年龄和分期(Ⅲ+Ⅳ期与Ⅰ+Ⅱ期)的术后模型中,趋化因子(C-C 基序)配体 28(CCL28)+T 细胞白血病/淋巴瘤蛋白 1A(TCL1A)+GPNMB 这三个生物标志物组合可改善 OS 的预测(AUC 从 0.83 提高至 0.90,p=0.05)。在包含年龄和二分类分期(Ⅲ期与Ⅰ+Ⅱ期)的术后模型中,CCL28 和 GPNMB1 标志物可改善 OS 的预测(AUC=0.86,p<0.001)。同时高水平的 CA125 和 HE4 组合预测生存率更差(p=0.05)。
在本项评估预测上皮性卵巢癌患者 OS 的血浆蛋白生物标志物性能的探索性研究中,我们发现将生物标志物,特别是 NT-3,添加到面板中可改善 OS 预测。