Department of Breast Surgery, National Cancer Center Hospital, Tokyo, Japan.
Keio University School of Medicine, Tokyo, Japan.
Clin Cancer Res. 2019 Mar 15;25(6):1817-1827. doi: 10.1158/1078-0432.CCR-18-1414. Epub 2018 Nov 27.
Sentinel lymph node biopsy (SLNB) is the gold-standard procedure for evaluating axillary lymph node (ALN) status in patients with breast cancer. However, the morbidity of SLNB is not negligible, and the procedure is invasive for patients without ALN metastasis. Here, we developed a diagnostic model for evaluating ALN status using a combination of serum miRNAs and clinicopathologic factors as a novel less-invasive biomarker. Preoperative serum samples were collected from patients who underwent surgery for primary breast cancer or breast benign diseases between 2008 and 2014. A total of 958 serum samples (921 cases of primary breast cancer, including 630 cases in the no ALN metastasis group and 291 cases in the ALN metastasis group, and 37 patients with benign breast diseases) were analyzed by miRNA microarray. Samples were randomly divided into training and test sets. Logistic LASSO regression analysis was used to construct diagnostic models in the training set, which were validated in the test set.
An optimal diagnostic model was identified using a combination of two miRNAs (miR-629-3p and miR-4710) and three clinicopathologic factors (T stage, lymphovascular invasion, and ultrasound findings), which showed a sensitivity of 0.88 (0.84-0.92), a specificity of 0.69 (0.61-0.76), an accuracy of 0.818, and an area under the receiver operating characteristic curve of 0.86 in the test set.
Serum miRNA profiles may be useful for the diagnosis of ALN metastasis before surgery in a less-invasive manner than SLNB.
前哨淋巴结活检(SLNB)是评估乳腺癌患者腋窝淋巴结(ALN)状态的金标准。然而,SLNB 的发病率不容忽视,对于没有 ALN 转移的患者,该操作具有侵袭性。在此,我们开发了一种使用血清 miRNA 联合临床病理因素的诊断模型,作为一种新的微创生物标志物来评估 ALN 状态。收集了 2008 年至 2014 年间接受原发性乳腺癌或乳腺良性疾病手术的患者的术前血清样本。通过 miRNA 微阵列分析了 958 份血清样本(921 例原发性乳腺癌,包括 630 例无 ALN 转移组和 291 例 ALN 转移组,37 例乳腺良性疾病)。样本随机分为训练集和测试集。在训练集中使用逻辑 LASSO 回归分析构建诊断模型,并在测试集中进行验证。
使用两种 miRNA(miR-629-3p 和 miR-4710)和三种临床病理因素(T 分期、脉管侵犯和超声表现)的组合确定了最佳诊断模型,在测试集中的灵敏度为 0.88(0.84-0.92),特异性为 0.69(0.61-0.76),准确性为 0.818,ROC 曲线下面积为 0.86。
血清 miRNA 谱可能有助于在手术前以比 SLNB 更微创的方式诊断 ALN 转移。