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基于基因表达谱的原发性中枢神经系统淋巴瘤患者预后风险评分。

Gene expression signature-based prognostic risk score in patients with primary central nervous system lymphoma.

机构信息

Biostatistics Center, Kurume University, Kurume, Fukuoka, Japan.

出版信息

Clin Cancer Res. 2012 Oct 15;18(20):5672-81. doi: 10.1158/1078-0432.CCR-12-0596. Epub 2012 Aug 20.

DOI:10.1158/1078-0432.CCR-12-0596
PMID:22908096
Abstract

PURPOSE

Better understanding of the underlying biology of primary central nervous system lymphomas (PCNSL) is critical for the development of early detection strategies, molecular markers, and new therapeutics. This study aimed to define genes associated with survival of patients with PCNSL.

EXPERIMENTAL DESIGN

Expression profiling was conducted on 32 PCNSLs. A gene classifier was developed using the random survival forests model. On the basis of this, prognosis prediction score (PPS) using immunohistochemical analysis is also developed and validated in another data set with 43 PCNSLs.

RESULTS

We identified 23 genes in which expressions were strongly and consistently related to patient survival. A PPS was developed for overall survival (OS) using a univariate Cox model. Survival analyses using the selected 23-gene classifiers revealed a prognostic value for high-dose methotrexate (HD-MTX) and HD-MTX-containing polychemotherapy regimen-treated patients. Patients predicted to have good outcomes by the PPS showed significantly longer survival than those with poor predicted outcomes (P < 0.0001). PPS using immunohistochemical analysis is also significant in test (P = 0.0004) and validation data set (P = 0.0281). The gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification (P < 0.0001). Among the genes, BRCA1 protein expressions were most strongly associated with patient survival.

CONCLUSION

We have identified gene expression signatures that can accurately predict survival in patients with PCNSL. These predictive genes should be useful as molecular biomarkers and they could provide novel targets for therapeutic interventions.

摘要

目的

深入了解原发性中枢神经系统淋巴瘤(PCNSL)的基础生物学对于开发早期检测策略、分子标志物和新疗法至关重要。本研究旨在确定与 PCNSL 患者生存相关的基因。

实验设计

对 32 例 PCNSL 进行了表达谱分析。使用随机生存森林模型开发了基因分类器。在此基础上,还使用另一个包含 43 例 PCNSL 的数据集进行了基于免疫组织化学分析的预后预测评分(PPS)的开发和验证。

结果

我们确定了 23 个表达与患者生存强烈且一致相关的基因。使用单变量 Cox 模型开发了总生存期(OS)的 PPS。使用选定的 23 基因分类器进行的生存分析显示,高剂量甲氨蝶呤(HD-MTX)和包含 HD-MTX 的多化疗方案治疗的患者具有预后价值。通过 PPS 预测为预后良好的患者的生存时间明显长于预测预后不良的患者(P < 0.0001)。免疫组织化学分析的 PPS 在测试数据集中也具有显著意义(P = 0.0004)和验证数据集(P = 0.0281)。基因预测器是包括临床风险分层在内的多变量模型中的独立预后因素(P < 0.0001)。在这些基因中,BRCA1 蛋白表达与患者生存最密切相关。

结论

我们已经确定了可以准确预测 PCNSL 患者生存的基因表达特征。这些预测基因可用作分子生物标志物,并为治疗干预提供新的靶点。

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