多重生物标志物测定提高了对上皮性卵巢癌存活的预测。

IF 2.6 4区 医学 Q2 GENETICS & HEREDITY Cancer Genomics & Proteomics Pub Date : 2023-05-01 DOI:10.21873/cgp.20380
Arturas Dobilas, Anna Åkesson, Pia Leandersson, Christer Borgfeldt
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引用次数: 0

摘要

背景/目的:上皮性卵巢癌(EOC)通常在晚期诊断出来,死亡率很高。在这项研究中,我们使用Olink蛋白质组学的接近延伸试验来寻找新的血浆蛋白生物标志物来预测EOC患者的总生存期(OS)。材料与方法:术前采集116例初诊减积EOC患者外周血标本,其中早期EOC 28例(FIGO分期I-II期),晚期EOC 88例(FIGO分期III-IV期)。使用Olink肿瘤学II和炎症面板测量蛋白质。总共分析了177个独特的蛋白质生物标志物。结合交叉验证和LASSO回归选择OS预测模型。结果:包括年龄和神经营养因子-3 (NT-3)+跨膜糖蛋白NMB (GPNMB)+间皮素(MSLN)三生物标志物组合的模型预测更差的OS, AUC=0.79 (p=0.004)。在模型中添加癌抗原125 (CA125)和人附睾蛋白4 (HE4)进一步提高了模型的性能(AUC=0.83;p = 0.003)。在包括年龄和分期(III+IV vs I+II)的术后模型中,趋化因子(C-C motif)配体28 (CCL28)+ t细胞白血病/淋巴瘤蛋白1A (TCL1A)+GPNMB的三生物标志物组合改善了OS的预测(从AUC=0.83到AUC=0.90;p = 0.05)。在术后模型中,包括年龄和二分分期(III期vs. I+II期),生物标志物CCL28和GPNMB1改善了OS的预测(AUC=0.86;结论:在这项评估血浆蛋白生物标志物预测OS性能的探索性研究中,我们发现在面板中添加生物标志物,特别是NT-3,可以提高OS的预测。
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A Multiplex Biomarker Assay Improves the Prediction of Survival in Epithelial Ovarian Cancer.

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.

Materials and methods: 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.

Results: 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).

Conclusion: 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.

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来源期刊
Cancer Genomics & Proteomics
Cancer Genomics & Proteomics ONCOLOGY-GENETICS & HEREDITY
CiteScore
5.00
自引率
8.00%
发文量
51
期刊介绍: Cancer Genomics & Proteomics (CGP) is an international peer-reviewed journal designed to publish rapidly high quality articles and reviews on the application of genomic and proteomic technology to basic, experimental and clinical cancer research. In this site you may find information concerning the editorial board, editorial policy, issue contents, subscriptions, submission of manuscripts and advertising. The first issue of CGP circulated in January 2004. Cancer Genomics & Proteomics is a journal of the International Institute of Anticancer Research. From January 2013 CGP is converted to an online-only open access journal. Cancer Genomics & Proteomics supports (a) the aims and the research projects of the INTERNATIONAL INSTITUTE OF ANTICANCER RESEARCH and (b) the organization of the INTERNATIONAL CONFERENCES OF ANTICANCER RESEARCH.
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