Cancer Research Center, Sheba Medical Center, Tel-Hashomer, Israel.
Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel.
Clin Cancer Res. 2016 Jul 15;22(14):3651-62. doi: 10.1158/1078-0432.CCR-15-2313. Epub 2016 Mar 8.
Molecular evolution of tumors during progression, therapy, and metastasis is a major clinical challenge and the main reason for resistance to therapy. We hypothesized that microRNAs (miRNAs) that exhibit similar variation of expression through the course of disease in several patients have a significant function in the tumorigenic process.
Exploration of evolving disease by profiling 800 miRNA expression from serial samples of individual breast cancer patients at several time points: pretreatment, posttreatment, lymph nodes, and recurrence sites when available (58 unique samples from 19 patients). Using a dynamic approach for analysis, we identified expression modulation patterns and classified varying miRNAs into one of the eight possible temporal expression patterns.
The various patterns were found to be associated with different tumorigenic pathways. The dominant pattern identified an miRNA set that significantly differentiated between disease stages, and its pattern in each patient was also associated with response to therapy. These miRNAs were related to tumor proliferation and to the cell-cycle pathway, and their mRNA targets showed anticorrelated expression. Interestingly, the level of these miRNAs was lowest in matched recurrent samples from distant metastasis, indicating a gradual increase in proliferative potential through the course of disease. Finally, the average expression level of these miRNAs in the pretreatment biopsy was significantly different comparing patients experiencing recurrence to recurrence-free patients.
Serial tumor sampling combined with analysis of temporal expression patterns enabled to pinpoint significant signatures characterizing breast cancer progression, associated with response to therapy and with risk of recurrence. Clin Cancer Res; 22(14); 3651-62. ©2016 AACR.
肿瘤在进展、治疗和转移过程中的分子进化是一个主要的临床挑战,也是治疗耐药的主要原因。我们假设,在多个患者的疾病过程中表现出相似表达变化的 microRNAs(miRNAs)在肿瘤发生过程中具有重要功能。
通过对 19 名患者的 58 个独特样本中的 800 个 miRNA 表达进行分析,从个体乳腺癌患者的多个时间点的系列样本中(治疗前、治疗后、淋巴结和复发部位)探索不断变化的疾病。使用动态分析方法,我们确定了表达调节模式,并将不同的 miRNA 分为八种可能的时间表达模式之一。
发现各种模式与不同的肿瘤发生途径有关。确定的主要模式是 miRNA 集,它可以显著区分疾病阶段,并且每个患者的模式也与治疗反应相关。这些 miRNA 与肿瘤增殖和细胞周期途径有关,其 mRNA 靶标显示出反相关表达。有趣的是,这些 miRNA 在匹配的远处转移复发样本中的水平最低,表明在疾病过程中增殖潜力逐渐增加。最后,在比较复发患者和无复发患者的预处理活检中,这些 miRNA 的平均表达水平存在显著差异。
连续肿瘤采样结合时间表达模式分析,可准确确定乳腺癌进展、与治疗反应和复发风险相关的特征性显著特征。临床癌症研究;22(14);3651-62. 2016 年 AACR。