Papadaki Chara, Thomopoulou Konstantina, Monastirioti Alexia, Koronakis George, Papadaki Maria A, Rounis Konstantinos, Vamvakas Lambros, Nikolaou Christoforos, Mavroudis Dimitrios, Agelaki Sofia
Laboratory of Translational Oncology, School of Medicine, University of Crete, Heraklion, Vassilika Vouton, 71003 Crete, Greece.
Department of Medical Oncology, University General Hospital of Heraklion, Vassilika Vouton, 71110 Crete, Greece.
Biomedicines. 2021 Apr 13;9(4):421. doi: 10.3390/biomedicines9040421.
MicroRNAs (miRNAs) are involved in the regulation of immune response and hold an important role in tumor immune escape. We investigated the differential expression of the immunomodulatory miR-10b, miR-19a, miR-20a, miR-126, and miR-155 in the plasma of healthy women and patients with early stage breast cancer and interrogated their role in the prediction of patients' relapse. Blood samples were obtained from healthy women ( = 20) and patients with early stage breast cancer ( = 140) before adjuvant chemotherapy. Plasma miRNA expression levels were assessed by RT-qPCR. Relapse predicting models were developed using binary logistic regression and receiver operating curves (ROC) were constructed to determine miRNA sensitivity and specificity. Only miR-155 expression was lower in patients compared with healthy women ( = 0.023), whereas miR-155 and miR-10b were lower in patients who relapsed compared with healthy women ( = 0.039 and = 0.002, respectively). MiR-155 expression combined with axillary lymph node infiltration and tumor grade demonstrated increased capability in distinguishing relapsed from non-relapsed patients [(area under the curve, (AUC = 0.861; < 0.001)]. Combined miR-19a and miR-20a expression had the highest performance in discriminating patients with early relapse (AUC = 0.816; < 0.001). Finally, miR-10b in combination with lymph node status and grade had the highest accuracy to discriminate patients with late relapse (AUC = 0.971; < 0.001). The robustness of the relapse predicting models was further confirmed in a 10-fold cross validation. Deregulation of circulating miRNAs involved in tumor-immune interactions may predict relapse in early stage breast cancer. Their successful clinical integration could potentially address the significance challenge of treatment escalation or de-escalation according to the risk of recurrence.
微小RNA(miRNA)参与免疫反应的调节,在肿瘤免疫逃逸中起重要作用。我们研究了免疫调节性miR-10b、miR-19a、miR-20a、miR-126和miR-155在健康女性和早期乳腺癌患者血浆中的差异表达,并探讨了它们在预测患者复发中的作用。在辅助化疗前,从健康女性(n = 20)和早期乳腺癌患者(n = 140)采集血样。通过RT-qPCR评估血浆miRNA表达水平。使用二元逻辑回归建立复发预测模型,并构建受试者工作曲线(ROC)以确定miRNA的敏感性和特异性。与健康女性相比,仅患者的miR-155表达较低(P = 0.023),而与健康女性相比,复发患者的miR-155和miR-10b较低(分别为P = 0.039和P = 0.002)。miR-155表达与腋窝淋巴结浸润和肿瘤分级相结合,在区分复发患者和未复发患者方面显示出更强的能力[曲线下面积(AUC)= 0.861;P < 0.001]。联合miR-19a和miR-20a表达在鉴别早期复发患者方面表现最佳(AUC = 0.816;P < 0.001)。最后,miR-10b与淋巴结状态和分级相结合,在鉴别晚期复发患者方面具有最高的准确性(AUC = 0.971;P < 0.001)。在10倍交叉验证中进一步证实了复发预测模型具有稳健性。参与肿瘤免疫相互作用的循环miRNA失调可能预测早期乳腺癌的复发。它们在临床上的成功整合可能潜在地解决根据复发风险进行治疗强化或降级的重大挑战。