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基于基因表达的预测因子,用于预测接受双磷酸盐治疗的骨髓瘤患者发生骨病的高风险。

A gene expression-based predictor for myeloma patients at high risk of developing bone disease on bisphosphonate treatment.

机构信息

Section of Haemato-Oncology Research Unit, Division of Molecular Pathology, Institute of Cancer Research, Sutton, Surrey, United Kingdom.

出版信息

Clin Cancer Res. 2011 Oct 1;17(19):6347-55. doi: 10.1158/1078-0432.CCR-11-0994. Epub 2011 Aug 19.

Abstract

PURPOSE

Myeloma bone disease impairs quality of life and is associated with impaired survival. Even with effective bisphosphonate treatment, a significant proportion of patients still develop skeletal-related events (SRE). Identifying such patients at presentation would allow treatment modification.

EXPERIMENTAL DESIGN

To investigate the molecular basis of bone disease at presentation and to develop a predictive signature for patients at high risk of developing SREs on bisphosphonates, 261 presenting myeloma samples were analyzed by global gene expression profiling. The derived "SRE gene signature" was complemented by the integration of associated clinical parameters to generate an optimal predictor.

RESULTS

Fifty genes were significantly associated with presenting bone disease, including the WNT signaling antagonist DKK1 and genes involved in growth factor signaling and apoptosis. Higher serum calcium level and the presence of bone disease and hyperdiploidy at presentation were associated with high risk of SRE development. A gene signature derived from the fourteen genes overexpressed in the SRE group was able to identify patients at high risk of developing an SRE on treatment. These genes either belonged to the IFN-induced family or were involved in cell signaling and mitosis. Multivariate logistic model selection yielded an optimal SRE predictor comprising seven genes and calcium level, which was validated as an effective predictor in a further set of patients.

CONCLUSIONS

The simple expression-based SRE predictor can effectively identify individuals at high risk of developing bone disease while being on bisphosphonates. This predictor could assist with developing future trials on novel therapies aimed at reducing myeloma bone disease.

摘要

目的

骨髓瘤骨病降低生活质量,并与生存受损相关。即使接受了有效的双膦酸盐治疗,仍有相当一部分患者会发生骨骼相关事件(SRE)。在初诊时识别此类患者可进行治疗调整。

实验设计

为了研究初诊时骨病的分子基础,并为接受双膦酸盐治疗的患者开发一种发生 SRE 的高风险预测特征,对 261 例初诊骨髓瘤样本进行了全基因表达谱分析。通过整合相关的临床参数,对衍生的“SRE 基因特征”进行补充,以生成最佳预测因子。

结果

50 个基因与初诊骨病显著相关,包括 WNT 信号通路拮抗剂 DKK1 以及参与生长因子信号和细胞凋亡的基因。初诊时血清钙水平较高、存在骨病和超二倍体与 SRE 发展风险较高相关。从 SRE 组中 14 个高表达基因中得到的基因特征能够识别出在治疗过程中发生 SRE 的高风险患者。这些基因要么属于 IFN 诱导家族,要么参与细胞信号转导和有丝分裂。多变量逻辑模型选择产生了一个包含七个基因和钙水平的最佳 SRE 预测因子,在另一组患者中验证了其作为有效预测因子的能力。

结论

基于表达的简单 SRE 预测因子可有效识别在接受双膦酸盐治疗时发生骨病风险较高的个体。该预测因子可辅助设计旨在减少骨髓瘤骨病的新型治疗方法的未来试验。

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