利用HER2阳性乳腺癌活检组织中的激酶组活性谱预测治疗结果。
Predicting treatment outcome using kinome activity profiling in HER2+ breast cancer biopsies.
作者信息
Debets Donna O, de Graaf Erik L, Liefaard Marte C, Sonke Gabe S, Lips Esther H, Ressa Anna, Altelaar Maarten
机构信息
Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, 3584 CH Utrecht, the Netherlands.
Pepscope B.V, Nieuwe Kanaal 7, 6709 PA Wageningen, the Netherlands.
出版信息
iScience. 2024 Apr 30;27(6):109858. doi: 10.1016/j.isci.2024.109858. eCollection 2024 Jun 21.
In this study, we measured the kinase activity profiles of 32 pre-treatment tumor biopsies of HER2-positive breast cancer patients. The aim of this study was to assess the prognostic potential of kinase activity levels, to identify potential mechanisms of resistance and to predict treatment success of HER2-targeted therapy combined with chemotherapy. Indeed, our system-wide kinase activity analysis allowed us to link kinase activity to treatment response. Overall, high kinase activity in the HER2-pathway was associated with good treatment outcome. We found eleven kinases differentially regulated between treatment outcome groups, including well-known players in therapy resistance, such as p38a, ERK, and FAK, and an unreported one, namely MARK1. Lastly, we defined an optimal signature of four kinases in a multiple logistic regression diagnostic test for prediction of treatment outcome (AUC = 0.926). This kinase signature showed high sensitivity and specificity, indicating its potential as predictive biomarker for treatment success of HER2-targeted therapy.
在本研究中,我们测量了32例HER2阳性乳腺癌患者治疗前肿瘤活检样本的激酶活性谱。本研究的目的是评估激酶活性水平的预后潜力,确定潜在的耐药机制,并预测HER2靶向治疗联合化疗的治疗效果。事实上,我们的全系统激酶活性分析使我们能够将激酶活性与治疗反应联系起来。总体而言,HER2通路中的高激酶活性与良好的治疗结果相关。我们发现治疗结果组之间有11种激酶存在差异调节,包括治疗耐药中的知名参与者,如p38a、ERK和FAK,以及一种未报道的激酶,即MARK1。最后,我们在多元逻辑回归诊断试验中定义了一个由四种激酶组成的最佳特征,用于预测治疗结果(AUC = 0.926)。这种激酶特征显示出高敏感性和特异性,表明其作为HER2靶向治疗成功预测生物标志物的潜力。
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