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乳腺癌患者血液中显示对新辅助化疗耐药的预测性miRNA模式

Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy.

作者信息

Fan Jingjing, Tang Yunjian, Wang Kunming, Yang Shu, Ma Binlin

机构信息

Department of Breast and Thyroid Surgery, Cancer Hospital Affiliated to Xinjiang Medical University, Urumqi, Xinjiang, 830011, People's Republic of China.

出版信息

Breast Cancer (Dove Med Press). 2023 Aug 11;15:591-604. doi: 10.2147/BCTT.S415080. eCollection 2023.

Abstract

OBJECTIVE

The effect of chemotherapy in patients with breast cancer (BC) is uncertain. This study attempted to analyze serum microRNAs (miRNAs) in NAC resistant and sensitive BC patients and develop a miRNA-based nomogram model. To further help clinicians make treatment decisions for hormone receptor-positive patients.

METHODS

A total of 110 BC patients with NAC were recruited and assigned in sensitive and resistant group, and 4 sensitive patients and 3 resistant patients were subjected to high-throughput sequencing. The functions of their target genes were analyzed by GO and KEGG. Five BC-related reported miRNAs were selected for expression pattern measurement by RT-qPCR and multivariate logistic analysis. The nomogram model was developed using R 4.0.1, and its predictive efficacy, consistency and clinical application value in development and validation groups were evaluated using ROC, calibration and decision curves.

RESULTS

There were 44 differentially-expressed miRNAs in resistant BC patients. miR-3646, miR-4741, miR-6730-3p, miR-6831-5p and miR-8485 were candidate for resistance diagnosis in BC. Logistic multiple regression analysis showed that miR-4741 (or = 0.30, 95% CI = 0.08-0.63, P = 0.02) and miR-6831-5p (or = 0.48, 95% CI = 0.24-0.78, P = 0.01) were protective factors of BC resistance. The ROC curves showed a sensitivity of 0.884 and 0.750 for miR-4741 and miR-6831-5P as markers of resistance, suggesting that they can be used as independent risk factors for BC resistance. The other 3 miRNAs can be used as calibration factors to establish the risk prediction model of resistance in BC. In risk model, the prediction accuracy of resistance of BC is about 78%. 5-miRNA signature diagnostic models can help clinicians provide personalized treatment for NAC resistance BC patients to improve patient survival.

CONCLUSION

MiR-4741 and miR-6831-5p are independent risk factors for breast cancer resistance. This study constructed a nomogram model of NAC resistance in BC based on 5 differentially-expressed serum miRNAs.

摘要

目的

化疗对乳腺癌(BC)患者的疗效尚不确定。本研究试图分析新辅助化疗(NAC)耐药和敏感的BC患者血清中的微小RNA(miRNA),并建立基于miRNA的列线图模型。以进一步帮助临床医生为激素受体阳性患者做出治疗决策。

方法

共招募110例接受NAC治疗的BC患者,分为敏感组和耐药组,对4例敏感患者和3例耐药患者进行高通量测序。通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析其靶基因的功能。选择5个已报道的与BC相关的miRNA,采用逆转录定量聚合酶链反应(RT-qPCR)和多因素逻辑分析检测其表达模式。使用R 4.0.1软件建立列线图模型,并采用受试者工作特征曲线(ROC)、校准曲线和决策曲线评估其在开发组和验证组中的预测效能、一致性和临床应用价值。

结果

耐药BC患者中有44个差异表达的miRNA。miR-3646、miR-4741、miR-6730-3p、miR-6831-5p和miR-8485是BC耐药诊断的候选指标。多因素逻辑回归分析显示,miR-4741(比值比[OR]=0.30,95%可信区间[CI]=0.08-0.63,P=0.02)和miR-6831-5p(OR=0.48,95%CI=0.24-0.78,P=0.01)是BC耐药的保护因素。ROC曲线显示,以miR-4741和miR-6831-5P作为耐药标志物时,敏感度分别为0.884和0.750,提示它们可作为BC耐药的独立危险因素。其他3个miRNA可作为校准因素,建立BC耐药的风险预测模型。在风险模型中,BC耐药的预测准确率约为78%。5-miRNA特征诊断模型可帮助临床医生为NAC耐药的BC患者提供个性化治疗,以提高患者生存率。

结论

MiR-4741和miR-6831-5p是乳腺癌耐药的独立危险因素。本研究基于5个差异表达的血清miRNA构建了BC中NAC耐药的列线图模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792f/10427486/b5052125e7a7/BCTT-15-591-g0001.jpg

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