Min Liu1, Siying Zhou2, Jinyan Wang3, Qian Zhang3, Sujin Yang3, Jifeng Feng4, Bin Xu5, Shanliang Zhong6. 1. Department of Clinical Laboratory, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China. 2. The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, China. 3. Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China. 4. Department of Medical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China. 5. Center of Clinical Laboratory Science, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, 210009, China. 6. Center of Clinical Laboratory Science, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, 210009, China. slzhong@foxmail.com.
Abstract
BACKGROUND: We aimed to investigate the potential of microRNA expression profiles to predict survival in breast cancer. METHODS: MicroRNA and mRNA expression data of breast cancer were downloaded from The Cancer Genome Atlas. LASSO regression was used to identify microRNAs signature predicting survival of breast cancer patients. Transfection experiment was conducted to explore the influence of microRNAs on their potential targets. RESULTS: We identified 56 differentially expressed microRNAs in breast cancer tissues compared to adjacent normal tissues. 10 microRNAs with non-zero coefficient were selected from the 56 microRNAs using LASSO Cox regression. After predicting the targets for the 10 microRNAs, we further obtained 155 targets that were associated with overall survival of breast cancer patients. Spearman's correlation analysis found that the expression of SCUBE2, SCRN3, YTHDF3, ITFG1, ITPRIPL2, and JAK1 was an inversely correlated with their microRNAs. Transfection experiment showed that YTHDF3 was down-regulated in cells transfected with miR-106b-5p mimics compared with those transfected with negative control of mimics (fold change 4.21; P < 0.01). CONCLUSIONS: In conclusion, we identified a 10-miRNA signature associated with prognosis of breast cancer patients. The expression of YTHDF3 was down-regulated by miR-106b-5p.
BACKGROUND: We aimed to investigate the potential of microRNA expression profiles to predict survival in breast cancer. METHODS: MicroRNA and mRNA expression data of breast cancer were downloaded from The Cancer Genome Atlas. LASSO regression was used to identify microRNAs signature predicting survival of breast cancerpatients. Transfection experiment was conducted to explore the influence of microRNAs on their potential targets. RESULTS: We identified 56 differentially expressed microRNAs in breast cancer tissues compared to adjacent normal tissues. 10 microRNAs with non-zero coefficient were selected from the 56 microRNAs using LASSO Cox regression. After predicting the targets for the 10 microRNAs, we further obtained 155 targets that were associated with overall survival of breast cancerpatients. Spearman's correlation analysis found that the expression of SCUBE2, SCRN3, YTHDF3, ITFG1, ITPRIPL2, and JAK1 was an inversely correlated with their microRNAs. Transfection experiment showed that YTHDF3 was down-regulated in cells transfected with miR-106b-5p mimics compared with those transfected with negative control of mimics (fold change 4.21; P < 0.01). CONCLUSIONS: In conclusion, we identified a 10-miRNA signature associated with prognosis of breast cancerpatients. The expression of YTHDF3 was down-regulated by miR-106b-5p.
Entities:
Keywords:
Breast cancer; MicroRNA; Prognosis; Survival
Authors: Daniela Tejada-Martinez; Roberto A Avelar; Inês Lopes; Bruce Zhang; Guy Novoa; João Pedro de Magalhães; Marco Trizzino Journal: Mol Biol Evol Date: 2022-02-03 Impact factor: 16.240