■静脉内平滑肌瘤病(IVL)是一种罕见的内分泌相关肿瘤,具有血管内浸润的独特特征。这项研究旨在确定可靠的生物标志物,以在预测的背景下监督IVL的发展或复发,预防性,和个性化医疗(PPPM/3PM)。
■共招募60例,以检测IVL患者血清样本中的差异表达蛋白(DEPs)。这些病例包括复发性IVL,非复发性IVL,子宫肌瘤,和没有子宫肌瘤的健康个体,每个类别有15个案例。然后,加权基因共表达网络分析(WGCNA),套索惩罚Cox回归分析(Lasso),趋势聚类,和广义线性回归模型(GLM)用于筛选参与IVL进展的hub蛋白。
■首先,从2582种可识别蛋白中确定了93种差异表达蛋白(DEP),在IVL组中增加了54种蛋白质,剩下的蛋白质下降了。这些蛋白质富含对免疫环境的调节,主要通过激活B细胞的功能。在上述综合分析之后,建立了基于4种蛋白质(A0A5C2FUE5,A0A5C2GPQ1,A0A5C2GNC7和A0A5C2GBR3)的模型,以有效确定IVL病变进展的潜力.在这些蛋白质中,我们的结果表明,危险因素A0A5C2FUE5与IVL进展相关(OR=2.64).相反,A0A5C2GPQ1,A0A5C2GNC7和A0A5C2GBR3可能以保护性方式起作用并防止疾病发展(OR分别为0.32,0.60,0.53),多类接收机算子特征曲线分析进一步支持了这一点。
■基于整合的生物信息学分析最终鉴定了四种hub蛋白。这项研究通过3PM方法增强了这些新型生物标志物在预测IVL的预后或进展方面的有希望的应用。
■在线版本包含补充材料,可在10.1007/s13167-023-00338-0获得。
UNASSIGNED: Intravenous leiomyomatosis (IVL) is a rare endocrine-associated tumor with unique characteristics of intravascular invasion. This
study aimed to identify reliable biomarkers to supervise the development or recurrence of IVL in the context of predictive, preventive, and personalized medicine (PPPM/3PM).
UNASSIGNED: A total of 60 cases were recruited to detect differentially expressed proteins (DEPs) in serum samples from IVL patients. These cases included those with recurrent IVL, non-recurrent IVL, uterine myoma, and healthy individuals without uterine myoma, with 15 cases in each category. Then, weighted gene co-expression network analysis (WGCNA), lasso-penalized Cox regression analysis (Lasso), trend clustering, and a generalized linear regression model (GLM) were utilized to screen the hub proteins involved in IVL progression.
UNASSIGNED: First, 93 differentially expressed proteins (DEPs) were determined from 2582 recognizable proteins, with 54 proteins augmented in the IVL group, and the remaining proteins declined. These proteins were enriched in the modulation of the immune environment, mainly by activating the function of B cells. After the integrated analyses mentioned above, a model based on four proteins (A0A5C2FUE5, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3) was developed to efficiently determine the potential of IVL lesions to progress. Among these featured proteins, our results demonstrated that the risk factor A0A5C2FUE5 was associated with IVL progression (OR = 2.64). Conversely, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3 might act in a protective manner and prevent disease development (OR = 0.32, 0.60, 0.53, respectively), which was further supported by the multi-class receiver operator characteristic curve analysis.
UNASSIGNED: Four hub proteins were eventually identified based on the integrated bioinformatics analyses. This
study potentiates the promising application of these novel biomarkers to predict the prognosis or progression of IVL by a 3PM approach.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13167-023-00338-0.