文章：

一种基因表达炎症特征可特异性预测多发性骨髓瘤的进展及患者生存

A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival

原文发布日期：2016-12-16

DOI: 10.1038/bcj.2016.118

类型: Original Article

开放获取: 是

英文摘要：

Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients’ survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment.

摘要翻译： 

多发性骨髓瘤（MM）的进展与恶性浆细胞及炎症/免疫抑制性骨髓微环境中的细胞组分之间的相互作用密切相关，这种相互作用促进疾病进展、耐药、新生血管生成、骨质破坏和免疫损伤。我们研究了炎症基因在预测疾病演变和患者生存方面的意义。通过Ingenuity Pathway Analysis生物信息学工具对意义未明单克隆丙种球蛋白病、冒烟型及症状性MM的基因表达谱数据集进行分析，发现炎症和细胞因子/趋化因子通路在疾病演变过程中受影响最为显著。随后我们筛选出20个参与B细胞炎症的候选基因，并通过单变量与多变量分析（对数秩检验、逻辑回归和Cox回归模型）探讨其在预测临床结局中的作用。我们确定了一个8基因特征（IL8、IL10、IL17A、CCL3、CCL5、VEGFA、EBI3和NOS2），能以84%的准确率区分不同疾病状态（意义未明单克隆丙种球蛋白病/冒烟型/症状性MM）。此外，发现六个基因（IFNG、IL2、LTA、CCL2、VEGFA、CCL3）与患者生存期独立相关。若骨髓瘤细胞高表达Th1细胞因子（IFNG/LTA/IL2/CCL2）且低表达CCL3和VEGFA，患者生存期最长。基于这六个基因，我们构建了一个预后风险评分，并在三个独立数据集中得到验证。本研究为“炎症在MM患者疾病进展和生存中起关键作用”这一概念提供了证据。在不同数据集中验证的炎症基因预后特征明确指出了个性化抗MM治疗的新机遇。

原文链接：

A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival