Breast Cancer: Targets and Therapy (Aug 2023)

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

  • Fan J,
  • Tang Y,
  • Wang K,
  • Yang S,
  • Ma B

Journal volume & issue
Vol. Volume 15
pp. 591 – 604

Abstract

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Jingjing Fan, Yunjian Tang, Kunming Wang, Shu Yang, Binlin Ma Department of Breast and Thyroid Surgery, Cancer Hospital Affiliated to Xinjiang Medical University, Urumqi, Xinjiang, 830011, People’s Republic of ChinaCorrespondence: Binlin Ma, Cancer Hospital Affiliated to Xinjiang Medical University, 789 Suzhou East Street, Xincheng District, Urumqi, Xinjiang, People’s Republic of China, Tel +86-991-7819082, Email [email protected]: 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.Keywords: breast cancer, neoadjuvant chemotherapy, drug resistance, serum microRNAs, nomogram model, 5-miRNAs, GO and KEGG enrichment analyses

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