Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York.
Carcinogenesis Institute of N.N. Blokhin Russian Cancer Research Center, Moscow, Russia.
Clin Cancer Res. 2018 Feb 1;24(3):581-591. doi: 10.1158/1078-0432.CCR-17-0996. Epub 2017 Nov 14.
Breast cancer is among the leading causes of cancer-related death; discovery of novel prognostic markers is needed to improve outcomes. Combining systems biology and epidemiology, we investigated miRNA-associated genes and breast cancer survival in a well-characterized population-based study. A recently developed algorithm, , was used to identify key miRNA "activities" corresponding to target gene degradation, which were predictive of breast cancer mortality in published databases. We profiled miRNA-associated genes in tumors from our well-characterized population-based cohort of 606 women with first primary breast cancer. Cox proportional hazards models were used to estimate HRs and 95% confidence intervals (CI), after 15+ years of follow-up with 119 breast cancer-specific deaths. miR-500a activity was identified as a key miRNA for estrogen receptor-positive breast cancer mortality using public databases. From a panel of 161 miR-500a-associated genes profiled, 73 were significantly associated with breast cancer-specific mortality (FDR < 0.05) in our population, among which two clusters were observed to have opposing directions of association. For example, high level of was associated with reduced breast cancer-specific mortality (HR = 0.3; 95% CI, 0.2-0.4), whereas the opposite was observed for (HR = 2.7; 95% CI, 1.8-3.9). Most importantly, we identified set of genes for which associations with breast cancer-specific mortality were independent of known prognostic factors, including hormone receptor status and PAM50-derived risk-of-recurrence scores. These results are validated in independent datasets. We identified novel markers that may improve prognostic efficiency while shedding light on molecular mechanisms of breast cancer progression. .
乳腺癌是癌症相关死亡的主要原因之一;需要发现新的预后标志物以改善预后。我们结合系统生物学和流行病学,在一个特征明确的基于人群的研究中研究了 miRNA 相关基因与乳腺癌生存的关系。最近开发的算法 用于识别对应于靶基因降解的关键 miRNA“活性”,这些活性可预测已发表数据库中乳腺癌死亡率。我们对我们特征明确的基于人群的 606 名患有原发性乳腺癌的女性队列中的肿瘤进行了 miRNA 相关基因的分析。在经过 15 年以上的随访后,有 119 例乳腺癌特异性死亡,使用 Cox 比例风险模型估计了 HR 和 95%置信区间(CI)。使用公共数据库,确定 miR-500a 活性是雌激素受体阳性乳腺癌死亡率的关键 miRNA。在我们人群中,从 161 个 miR-500a 相关基因中鉴定出 73 个与乳腺癌特异性死亡率显著相关(FDR < 0.05),其中观察到两个簇具有相反的关联方向。例如,高水平的 与降低的乳腺癌特异性死亡率相关(HR = 0.3;95%CI,0.2-0.4),而 则相反(HR = 2.7;95%CI,1.8-3.9)。最重要的是,我们确定了一组基因,它们与乳腺癌特异性死亡率的关联独立于已知的预后因素,包括激素受体状态和 PAM50 衍生的复发风险评分。这些结果在独立数据集得到验证。我们发现了一些新的标志物,这些标志物可能会提高预后效率,同时揭示乳腺癌进展的分子机制。