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

被引:1
作者
Fan, Jingjing [1 ]
Tang, Yunjian [1 ]
Wang, Kunming [1 ]
Yang, Shu [1 ]
Ma, Binlin [1 ,2 ]
机构
[1] Xinjiang Med Univ, Dept Breast & Thyroid Surg, Canc Hosp, Urumqi 830011, Xinjiang, Peoples R China
[2] Xinjiang Med Univ, Canc Hosp, 789 Suzhou East St, Urumqi, Xinjiang, Peoples R China
关键词
breast cancer; neoadjuvant chemotherapy; drug resistance; serum microRNAs; nomogram model; 5-miRNAs; GO and KEGG enrichment analyses; CHEMORESISTANCE; DIAGNOSIS; MICRORNAS;
D O I
10.2147/BCTT.S415080
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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.
引用
收藏
页码:591 / 604
页数:14
相关论文
共 40 条
[1]   Conversion of Stem Cells to Cancer Stem Cells: Undercurrent of Cancer Initiation [J].
Afify, Said M. ;
Seno, Masaharu .
CANCERS, 2019, 11 (03)
[2]   Breast cancer in young women: an overview [J].
Anastasiadi, Zoi ;
Lianos, Georgios D. ;
Ignatiadou, Eleftheria ;
Harissis, Haralampos V. ;
Mitsis, Michail .
UPDATES IN SURGERY, 2017, 69 (03) :313-317
[3]   Screen for MicroRNA and Drug Interactions in Breast Cancer Cell Lines Points to miR-126 as a Modulator of CDK4/6 and PIK3CA Inhibitors [J].
Baldassari, Federica ;
Zerbinati, Carlotta ;
Galasso, Marco ;
Corra, Fabio ;
Minotti, Linda ;
Agnoletto, Chiara ;
Previati, Maurizio ;
Croce, Carlo M. ;
Volinia, Stefano .
FRONTIERS IN GENETICS, 2018, 9
[4]   MicroRNAs miR-142-5p, miR-150-5p, miR-320a-3p, and miR-4433b-5p in Serum and Tissue: Potential Biomarkers in Sporadic Breast Cancer [J].
Carvalho, Tamyres Mingorance ;
Brasil, Guillermo Ortiz ;
Jucoski, Tayana Schultz ;
Adamoski, Douglas ;
de Lima, Rubens Silveira ;
Spautz, Cleverton C. ;
Anselmi, Karina Furlan ;
Ozawa, Patricia Midori Murobushi ;
Cavalli, Iglenir Joao ;
de Oliveira, Jaqueline Carvalho ;
Gradia, Daniela Fiori ;
Ribeiro, Enilze Maria de Souza Fonseca .
FRONTIERS IN GENETICS, 2022, 13
[5]   RAS signalling through PI3-Kinase controls cell migration via modulation of Reelin expression [J].
Castellano, Esther ;
Molina-Arcas, Miriam ;
Krygowska, Agata Adelajda ;
East, Philip ;
Warne, Patricia ;
Nicol, Alastair ;
Downward, Julian .
NATURE COMMUNICATIONS, 2016, 7
[6]   Identification of lncRNA/circRNA-miRNA-mRNA ceRNA Network as Biomarkers for Hepatocellular Carcinoma [J].
Chen, Shanshan ;
Zhang, Yongchao ;
Ding, Xiaoyan ;
Li, Wei .
FRONTIERS IN GENETICS, 2022, 13
[7]   Plasma and Tissue Specific miRNA Expression Pattern and Functional Analysis Associated to Colorectal Cancer Patients [J].
Cojocneanu, Roxana ;
Braicu, Cornelia ;
Raduly, Lajos ;
Jurj, Ancuta ;
Zanoaga, Oana ;
Magdo, Lorand ;
Irimie, Alexandru ;
Muresan, Mihai-Stefan ;
Ionescu, Calin ;
Grigorescu, Mircea ;
Berindan-Neagoe, Ioana .
CANCERS, 2020, 12 (04)
[8]   Bioinformatics-based interaction analysis of miR-92a-3p and key genes in tamoxifen-resistant breast cancer cells [J].
Cun, Jinjing ;
Yang, Qifeng .
BIOMEDICINE & PHARMACOTHERAPY, 2018, 107 :117-128
[9]   MicroRNA Expression Profiles and Breast Cancer Chemotherapy [J].
Davey, Matthew G. ;
Lowery, Aoife J. ;
Miller, Nicola ;
Kerin, Michael J. .
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2021, 22 (19)
[10]   Immune-Related Genes to Construct a Novel Prognostic Model of Breast Cancer: A Chemosensitivity-Based Study [J].
Deng, Zhi-Min ;
Hu, Wei ;
Dai, Fang-Fang ;
Yuan, Meng-Qin ;
Hu, Min ;
Cheng, Yan-Xiang .
FRONTIERS IN IMMUNOLOGY, 2021, 12