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人工耳蜗植入后言语可懂度良好和不佳患者的蛋白质组图谱:外淋巴液蛋白能否预测性能?

Proteome profile of patients with excellent and poor speech intelligibility after cochlear implantation: Can perilymph proteins predict performance?

机构信息

Department of Otolaryngology, Hannover Medical School, Hannover, Germany.

Core Facility Proteomics, Hannover Medical School, Hannover, Germany.

出版信息

PLoS One. 2022 Mar 3;17(3):e0263765. doi: 10.1371/journal.pone.0263765. eCollection 2022.

Abstract

Modern proteomic analysis and reliable surgical access to gain liquid inner ear biopsies have enabled in depth molecular characterization of the cochlea microenvironment. In order to clarify whether the protein composition of the perilymph can provide new insights into individual hearing performance after cochlear implantation (CI), computational analysis in correlation to clinical performance after CI were performed based on the proteome profile derived from perilymph samples (liquid biopsies). Perilymph samples from cochlear implant recipients have been analyzed by mass spectrometry (MS). The proteins were identified using the shot-gun proteomics method and quantified and analyzed using Max Quant, Perseus and IPA software. A total of 75 perilymph samples from 68 (adults and children) patients were included in the analysis. Speech perception data one year after implantation were available for 45 patients and these were used for subsequent analysis. According to their hearing performance, patients with excellent (n = 22) and poor (n = 14) performance one year after CI were identified and used for further analysis. The protein composition and statistically significant differences in the two groups were detected by relative quantification of the perilymph proteins. With this procedure, a selection of 287 proteins were identified in at least eight samples in both groups. In the perilymph of the patients with excellent and poor performance, five and six significantly elevated proteins were identified respectively. These proteins seem to be involved in different immunological processes in excellent and poor performer. Further analysis on the role of specific proteins as predictors for poor or excellent performance among CI recipients are mandatory. Combinatory analysis of molecular inner ear profiles and clinical performance data using bioinformatics analysis may open up new possibilities for patient stratification. The impact of such prediction algorithms on diagnosis and treatment needs to be established in further studies.

摘要

现代蛋白质组学分析和可靠的手术入路获取内耳液活检,使我们能够深入研究耳蜗微环境的分子特征。为了阐明外淋巴液的蛋白质组成是否能为人工耳蜗植入(CI)后个体听力表现提供新的见解,我们基于外淋巴液样本(液活检)的蛋白质组谱,进行了与 CI 后临床性能相关的计算分析。通过质谱分析(MS)分析了接受人工耳蜗植入者的外淋巴液样本。使用shot-gun 蛋白质组学方法鉴定蛋白质,使用 Max Quant、Perseus 和 IPA 软件进行定量和分析。共纳入 68 例(成人和儿童)患者的 75 例外淋巴液样本进行分析。有 45 例患者在植入后 1 年获得了言语感知数据,并对这些数据进行了后续分析。根据他们的听力表现,确定了植入后 1 年听力效果好(n=22)和差(n=14)的患者,并进行了进一步分析。通过相对定量分析外淋巴液蛋白,检测到两组的蛋白质组成和统计学上的显著差异。通过该程序,在两组的至少 8 个样本中鉴定出 287 种蛋白质。在听力效果好和差的患者的外淋巴液中,分别鉴定出 5 种和 6 种显著升高的蛋白质。这些蛋白质似乎参与了听力效果好和差的患者不同的免疫过程。需要进一步分析特定蛋白质作为 CI 接受者中听力效果差或好的预测因子的作用。使用生物信息学分析对内耳分子谱和临床性能数据进行组合分析,可能为患者分层开辟新的可能性。需要进一步的研究来确定此类预测算法对诊断和治疗的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/761b/8893673/d632eac9f5de/pone.0263765.g001.jpg

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