Department of Surgery, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
Department of Neurology, Neuro-Oncology Laboratory/Clinical and Cancer Proteomics, Erasmus University Medical Center, 3000 CA Rotterdam, The Netherlands.
Int J Mol Sci. 2022 Oct 17;23(20):12399. doi: 10.3390/ijms232012399.
The prospective, multicenter TESTBREAST study was initiated with the aim of identifying a novel panel of blood-based protein biomarkers to enable early breast cancer detection for moderate-to-high-risk women. Serum samples were collected every (half) year up until diagnosis. Protein levels were longitudinally measured to determine intrapatient and interpatient variabilities. To this end, protein cluster patterns were evaluated to form a conceptual basis for further clinical analyses. Using a mass spectrometry-based bottom-up proteomics strategy, the protein abundance of 30 samples was analyzed: five sequential serum samples from six high-risk women; three who developed a breast malignancy (cases) and three who did not (controls). Serum samples were chromatographically fractionated and an in-depth serum proteome was acquired. Cluster analyses were applied to indicate differences between and within protein levels in serum samples of individuals. Statistical analyses were performed using ANOVA to select proteins with a high level of clustering. Cluster analyses on 30 serum samples revealed unique patterns of protein clustering for each patient, indicating a greater interpatient than intrapatient variability in protein levels of the longitudinally acquired samples. Moreover, the most distinctive proteins in the cluster analysis were identified. Strong clustering patterns within longitudinal intrapatient samples have demonstrated the importance of identifying small changes in protein levels for individuals over time. This underlines the significance of longitudinal serum measurements, that patients can serve as their own controls, and the relevance of the current study set-up for early detection. The TESTBREAST study will continue its pursuit toward establishing a protein panel for early breast cancer detection.
前瞻性、多中心的 TESTBREAST 研究旨在确定一组新的基于血液的蛋白质生物标志物,以实现中高危女性的早期乳腺癌检测。在诊断前,每隔(半)年收集一次血清样本。对蛋白质水平进行纵向测量,以确定患者内和患者间的变异性。为此,评估了蛋白质聚类模式,为进一步的临床分析奠定了概念基础。使用基于质谱的自上而下的蛋白质组学策略,分析了 30 个样本的蛋白质丰度:来自 6 名高风险女性的 5 个连续血清样本;其中 3 人发生乳腺癌(病例),3 人未发生(对照)。血清样本经色谱分离,获得深度血清蛋白质组。应用聚类分析来指示个体血清样本中蛋白质水平之间和内部的差异。使用 ANOVA 进行统计分析,以选择聚类水平高的蛋白质。对 30 个血清样本的聚类分析显示了每个患者独特的蛋白质聚类模式,表明患者间的蛋白质水平变异性大于患者内的变异性。此外,还确定了聚类分析中最具特征性的蛋白质。纵向患者内样本中的强聚类模式表明,随着时间的推移,识别个体蛋白质水平的微小变化非常重要。这突显了纵向血清测量的重要性,即患者可以作为自己的对照,以及当前研究设计在早期检测中的相关性。TESTBREAST 研究将继续致力于建立用于早期乳腺癌检测的蛋白质组。