一组新的蛋白质生物标志物预测多发性骨髓瘤患者对含硼替佐米诱导方案的反应

Kay Reen Ting , Michael Henry , Justine Meiller , Annemarie Larkin , Martin Clynes , Paula Meleady , Despina Bazou , Paul Dowling , Peter O'Gorman
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引用次数: 18

摘要

背景:多发性骨髓瘤(MM)是一种复杂的异质性疾病。已经推荐了各种风险分层模型,包括细胞遗传学和FISH分析,以确定可能从新治疗中受益的高危患者,但这些设施尚未广泛使用。使用β -2微球蛋白和白蛋白的国际评分系统(ISS)在许多临床实践中仍然是广泛使用的预后评分系统;然而,它并不能预测MM患者对治疗的反应。本研究的目的是确定临床有用的生物标志物,以预测患者对硼替佐米治疗的反应。方法17 MM患者血清样本(9例有应答者/8例无应答者)用于发现阶段(无标记质谱法),另外20 MM患者血清样本用于基于elisa的验证阶段(14例有应答者/6例无应答者)。结果应答组clu和ANG平均水平较高,补体C1q浓度较低。所有标准生物标志物(白蛋白、β -2-微球蛋白(ß2M)、副蛋白和kappa/lambda (K/L)比)的组合AUC值为0.71,分类正确率为65%;新候选蛋白生物标志物与标准生物标志物的整体组合AUC值为0.89,分类正确率为85.3%。结论CLU、ANG、C1Q、白蛋白、ß2M、副蛋白和K/L比值组成的新生物标志物与标准生物标志物联合使用可能成为预测MM对硼替佐米治疗反应的新生物标志物。使用这种生物标志物面板可以促进更个性化的治疗方法,并最大限度地减少无效药物的不必要副作用。
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Novel panel of protein biomarkers to predict response to bortezomib-containing induction regimens in multiple myeloma patients

Background

Multiple myeloma (MM) is a complex heterogeneous disease. Various risk stratification models have been recommended including cytogenetic and FISH analysis to identify high-risk patients who may benefit from novel treatments, but such facilities are not widely available. The International Scoring System (ISS) using beta-2-microglobulin and albumin remains a widely used prognostic scoring system in many clinical practices; however it is not useful in predicting response to treatment in MM. The aim of this study is to identify clinically useful biomarkers to predict response to treatment containing bortezomib.

Methods

17 MM patient serum samples (9 responders/8 non-responders) were used for the discovery phase (label-free mass spectrometry) and an additional 20 MM patient serum samples were used for the ELISA-based validation phase (14 responders/6 non-responders).

Results

CLU and ANG mean levels were higher in the responders group, while Complement C1q had lower concentrations. The combination of all standard biomarkers (albumin, beta-2-microglobulin (ß2M), paraprotein and kappa/lambda (K/L) ratio) had an AUC value of 0.71 with 65% correct classification, while an overall combination of new candidate protein biomarkers with standard biomarkers had an AUC value of 0.89 with 85.3% correct classification.

Conclusions

A combination of new and standard biomarkers consisting of CLU, ANG, C1Q, albumin, ß2M, paraprotein and K/L ratio may have potential as a novel panel of biomarkers to predict MM response to treatment containing bortezomib.

General significance

Use of this biomarker panel could facilitate a more personalized therapy approach and to minimize unnecessary side effects from ineffective drugs.

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