Moskov Mikaela, Hedlund Lindberg Julia, Lycke Maria, Ivansson Emma, Gyllensten Ulf, Sundfeldt Karin, Stålberg Karin, Enroth Stefan
Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, Uppsala, Sweden.
Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden.
Commun Med (Lond). 2025 Jun 12;5(1):230. doi: 10.1038/s43856-025-00945-0.
Ovarian cancer has the highest mortality of all gynecological cancers and surgery is commonly used as final diagnostic. Available literature indicates that women with benign tumors could often be conservatively managed, but accurate molecular tests are needed for triaging when gold-standard imaging techniques are inconclusive or lacking.
Here, we analyzed 5416 plasma proteins in two independent cohorts (N = 171, N = 233) with women surgically diagnosed with benign or malignant tumors. Using one cohort as discovery, we compared protein levels of benign tumors with early stage (I-II), late stage (III-IV) or any stage (I-IV) ovarian cancer and trained risk-score reporting multivariate models including a fixed cut-off for malignancy. Associations and model performance was then evaluated in the replication cohort.
We identify 327 biomarker associations, corresponding to 191 unique proteins, and replicate 326 (99.7%). By comparing the 191 proteins with their corresponding tumor gene expression we find that only 11% (21/191) have significant correlation. Through analyzes of protein-protein correlation networks, we find that 62 of the 191 proteins have high correlation with at least one other protein, suggesting that many of the associations are secondary effects. In the replication cohort, our model has areas under the curve (AUC = 0.96) corresponding to 97% sensitivity at 68% specificity. For early-stage tumors, we estimate the sensitivity to 91% at a specificity of 68% as compared to 85% and 54% for CA-125 alone.
Our results indicates that up to one third of benign cases can be identified by molecular measures thereby reducing the need for diagnostic surgery.
卵巢癌是所有妇科癌症中死亡率最高的，手术通常用作最终诊断方法。现有文献表明，患有良性肿瘤的女性通常可以采用保守治疗，但当金标准成像技术无法得出结论或不存在时，需要准确的分子检测来进行分类。
在此，我们分析了两个独立队列（N = 171，N = 233）中5416种血浆蛋白，这些队列中的女性经手术诊断患有良性或恶性肿瘤。我们将其中一个队列用作发现队列，比较了良性肿瘤与早期（I-II期）、晚期（III-IV期）或任何阶段（I-IV期）卵巢癌的蛋白水平，并训练了风险评分报告多变量模型，包括恶性肿瘤的固定临界值。然后在复制队列中评估关联和模型性能。
我们确定了327种生物标志物关联，对应191种独特蛋白，并复制了326种（99.7%）。通过将这191种蛋白与其相应的肿瘤基因表达进行比较，我们发现只有11%（21/191）具有显著相关性。通过分析蛋白质-蛋白质相关网络，我们发现191种蛋白中有62种与至少一种其他蛋白具有高度相关性，这表明许多关联是次要效应。在复制队列中，我们的模型的曲线下面积（AUC = 0.96）对应于在68%特异性时97%的敏感性。对于早期肿瘤，我们估计在68%特异性下敏感性为91%，而单独的CA-125分别为85%和54%。
我们的结果表明，高达三分之一的良性病例可以通过分子检测来识别，从而减少诊断性手术的需求。
