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Dong Y, Xiao Y, Shi Q, Jiang C. Dysregulated lncRNA-miRNA-mRNA Network Reveals Patient Survival-Associated Modules and RNA Binding Proteins in Invasive Breast Carcinoma. Front Genet 2020; 10:1284. [PMID: 32010179 PMCID: PMC6975227 DOI: 10.3389/fgene.2019.01284] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 11/21/2019] [Indexed: 12/16/2022] Open
Abstract
Breast cancer is the most common cancer in women, but few biomarkers are effective in clinic. Previous studies have shown the important roles of non-coding RNAs in diagnosis, prognosis, and therapy selection for breast cancer and have suggested the significance of integrating molecules at different levels to interpret the mechanism of breast cancer. Here, we collected transcriptome data including long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA for ~1,200 samples, including 1079 invasive breast carcinoma samples and 104 normal samples, from The Cancer Genome Atlas (TCGA) project. We identified differentially expressed lncRNAs, miRNAs, and mRNAs that distinguished invasive carcinoma samples from normal samples. We further constructed an integrated dysregulated network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs and found housekeeping and cancer-related functions. Moreover, 58 RNA binding proteins (RBPs) involved in biological processes that are essential to maintain cell survival were found in the dysregulated network, and 10 were correlated with overall survival. In addition, we identified two modules that stratify patients into high- and low-risk subgroups. The expression patterns of these two modules were significantly different in invasive carcinoma versus normal samples, and some molecules were high-confidence biomarkers of breast cancer. Together, these data demonstrated an important clinical application for improving outcome prediction for invasive breast cancers.
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Affiliation(s)
- Yu Dong
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yang Xiao
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Qihui Shi
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunjie Jiang
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
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Dai W, He J, Zheng L, Bi M, Hu F, Chen M, Niu H, Yang J, Luo Y, Tang W, Sheng M. miR-148b-3p, miR-190b, and miR-429 Regulate Cell Progression and Act as Potential Biomarkers for Breast Cancer. J Breast Cancer 2019; 22:219-236. [PMID: 31281725 PMCID: PMC6597412 DOI: 10.4048/jbc.2019.22.e19] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 02/20/2019] [Indexed: 01/24/2023] Open
Abstract
Purpose Breast cancer is the most frequently diagnosed malignancy in women worldwide. MicroRNAs (miRNAs) are thought to serve as potential biomarkers in various cancers, including breast cancer. Methods We evaluated the miRNA expression profiles in 1,083 breast cancer samples and 104 normal breast tissues from The Cancer Genome Atlas database. We used the edgeR package of R software to analyze the differentially expressed miRNAs in normal and cancer tissues, and screened survival-related miRNAs by Kaplan-Meier analysis. A receiver operating characteristic curve was generated to evaluate the accuracy of these miRNAs as molecular markers for breast cancer diagnosis. Furthermore, the functional role of these miRNAs was verified using cell experiments. Targets of candidate miRNAs were predicted using 9 online databases, and Gene Ontology (GO) functional annotation and pathway analyses were conducted using Database for Annotation, Visualization and Integrated Discovery online tool. Results A total of 68 miRNAs showed significantly different expression patterns between the groups (p < 0.001), and 13 of these miRNAs were significantly associated with poor survival (p < 0.05). Three miRNAs with high specificity and sensitivity, namely, miR-148b-3p, miR-190b, and miR-429, were selected. In vitro experiments showed that the overexpression of these 3 miRNAs significantly promoted the proliferation and migration of MDA-MB-468 and T47D cells and reduced the apoptosis of T47D cells. GO and pathway enrichment analyses revealed that the targets of these dysregulated miRNAs were involved in many critical cancer-related biological processes and pathways. Conclusion The miR-148b-3p, miR-190b, and miR-429 may serve as potential diagnostic and prognostic markers for breast cancer. This study demonstrated the roles of these 3 miRNAs in the initiation and progression of breast cancer.
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Affiliation(s)
- Wenzhu Dai
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
| | - Jixiang He
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
| | - Ling Zheng
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
| | - Mingyu Bi
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
| | - Fei Hu
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
| | - Minju Chen
- Department of Mammary Gland and Thyroid Disease, First People's Hospital of Yunnan Province, Yunnan, China
| | - Heng Niu
- Department of Mammary Gland and Thyroid Disease, First People's Hospital of Yunnan Province, Yunnan, China
| | - Jingyu Yang
- Department of Mammary Gland and Thyroid Disease, First People's Hospital of Yunnan Province, Yunnan, China
| | - Ying Luo
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
| | - Wenru Tang
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
| | - Miaomiao Sheng
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Yunnan, China
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