Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets

He, Kan; Li, Wen‐Xing; Guan, Daogang; Gong, Mengting; Ye, Shoudong; Fang, Zekun; Huang, Jing‐Fei; Lu, Aiping

doi:10.1007/s10142-019-00670-7

Cited by 29 publications

(19 citation statements)

References 42 publications

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“…The present study used TCGA data and three GEO datasets to identify common dysregulated miRNAs in GC. A similar analysis has also been reported by a number of other groups (16)(17)(18)(19).…”

Section: Methodssupporting

confidence: 86%

Integrated miRNA profiling and bioinformatics analyses reveal upregulated miRNAs in gastric cancer

Yuan

Zhang

et al. 2019

Oncol Lett

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Gastric cancer is one of the most common malignancies in China and exhibits a poor prognosis. The most significant challenge for gastric cancer treatment is the absence of early diagnostic biomarkers. MicroRNAs (miRNAs) are small non-coding RNAs, which possess clinical value in a number of different types of cancer. The current study identified 13 miRNAs (hsa-miR-22, hsa-miR-545, hsa-let-7i, hsa-miR-15b, hsa-miR-221, hsa-miR-196a, hsa-miR-20a, hsa-miR-196b, hsa-miR-93, hsa-miR-19a, hsa-miR-503, hsa-miR-106b and hsa-miR-18a) that were significantly overexpressed in GC, by analyzing 1,000 GC samples included in four public datasets, including GSE23739, GSE78091, GSE30070 and The Cancer Genome Atlas. Furthermore, it was revealed that the expression levels of these 13 miRNAs were significantly higher in gastric cancer tissues of grades I, II and III compared with normal controls. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that the differentially expressed miRNAs were involved in regulating transcription, protein amino acid phosphorylation, signal transduction, protein binding, zinc ion binding, the mitogen-activated protein kinase signaling pathway and focal adhesion. In summary, the present study may provide potential new therapeutic and prognostic targets for gastric cancer.

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Section: Methodssupporting

confidence: 86%

Integrated miRNA profiling and bioinformatics analyses reveal upregulated miRNAs in gastric cancer

Yuan

Zhang

et al. 2019

Oncol Lett

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“…Lai et al [22] established a six-miRNA-based signature to predict the five-year OS in a small population of BC patients. In the study conducted by He et al [23], they selected five miRNA candidates to establish the prognosis predicting signature. Although the signature has some impacts on the prognosis prediction, initially, these candidates were not strongly associated with the prognosis of BC patients revealed by the univariate Cox regression test.…”

Section: Discussionmentioning

confidence: 99%

“…Li et al [27] evaluated the clinical value of miR-101-2 for the prognosis and diagnosis of BC and concluded that downexpression of miR-101-2 could be 13 Disease Markers utilized as a diagnostic marker, previously validated by a 1064-case-control study in 2014 [28]. miR-22 has been reported to play a dual role in the prognosis and recurrence of BC [23,29,30]. Damavandi et al [31] firstly demonstrated a significant upregulation of miR-22 in breast cancer tissues through RT-PCR, and then, both Zou et al and Liu et al's [32,33] studies showed that aberrant expression of miRNA decreased the MCF-7 BC cell's ability to proliferate, migrate, and invade, facilitating our understanding of the molecular mechanism underlying the malignant behaviors of breast cancer cells.…”

Section: Discussionmentioning

confidence: 99%

Identification of miRNA-Based Signature as a Novel Potential Prognostic Biomarker in Patients with Breast Cancer

Tang

Zeng³

et al. 2019

Disease Markers

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To identify the novel, noninvasive biomarkers to assess the outcome and prognosis of breast cancer (BC), patients with high sensitivity and specificity are greatly desired. Herein, the miRNA expression profile and matched clinical features of BC patients were extracted from The Cancer Genome Atlas (TCGA) database. The preliminary candidates were screened out by the univariate Cox regression test. Then, with the help of LASSO Cox regression analysis, the hsa-let-7b, hsa-mir-101-2, hsa-mir-135a-2, hsa-mir-22, hsa-mir-30a, hsa-mir-31, hsa-mir-3130-1, hsa-mir-320b-1, hsa-mir-3678, hsa-mir-4662a, hsa-mir-4772, hsa-mir-493, hsa-mir-556, hsa-mir-652, hsa-mir-6733, hsa-mir-874, and hsa-mir-9-3 were selected to construct the overall survival (OS) predicting signature, while the hsa-mir-130a, hsa-mir-204, hsa-mir-217, hsa-mir-223, hsa-mir-24-2, hsa-mir-29b-1, hsa-mir-363, hsa-mir-5001, hsa-mir-514a-1, hsa-mir-624, hsa-mir-639, hsa-mir-659, and hsa-mir-6892 were adopted to establish the recurrence-free survival (RFS) predicting signature. Referring to the median risk scores generated by the OS and RFS formulas, respectively, subgroup patients with high risk were strongly related to a poor OS and RFS revealed by Kaplan-Meier (K-M) plots. Meanwhile, receiver operating curve (ROC) analysis validated the accuracy and stability of these two signatures. When stratified by clinical features, such as tumor stage, age, and molecular subtypes, we found that the miRNA-based OS and RFS classifiers were still significant in predicting OS/RFS and showed the best predictive values than any other features. Besides, functional prediction analyses showed that these targeted genes of the enrolled miRNAs were enriched in cancer-associated pathways, such as MAPK/RTK, Ras, and PI3K-Akt signaling pathways. In summary, our observations demonstrate that the novel miRNA-based OS and RFS signatures are independent prognostic indicators for BC patients and worthy to be validated by further prospective studies.

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“…By informatics analysis using TCGA and GEO data, reciprocal regulatory networks among protein-coding genes, lncRNAs and microRNAs have been revealed to participate in cancer progression. 15,16 Lou et al described a miRNA-mRNA regulatory network by using DEPs between GBM samples and normal samples that was involved in tumorigenesis and the development of GBM. 17 Deng et al also revealed hub DEPs by constructing PPI networks of DEPs between primary and recurrent LGG tumor tissues in the TCGA database.…”

Section: Introductionmentioning

confidence: 99%

<p>Comprehensive Transcriptomic Analysis and Experimental Validation Identify lncRNA HOXA-AS2/miR-184/COL6A2 as the Critical ceRNA Regulation Involved in Low-Grade Glioma Recurrence</p>

Chen

et al. 2020

OTT

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Purpose: The recurrence and metastasis of glioma are closely related to complex regulatory networks among protein-coding genes, lncRNAs and microRNAs. The aim of this study was to investigate core genes, lncRNAs, miRNAs and critical ceRNA regulatory mechanisms, which are involved in lower-grade glioma (LGG) recurrence. Materials and Methods: We employed multiple datasets from Chinese Glioma Genome Atlas (CGGA) database and The Cancer Genome Atlas (TCGA) to perform comprehensive transcriptomic analysis. Further in vitro experiments including cell proliferation assay, luciferase reporter assay, and Western blot were performed to validate our results. Results: Recurrent LGG and glioblastoma (GBM) showed different transcriptome characteristics with less overlap of differentially expressed protein-coding genes (DEPs), lncRNAs (DELs) and miRNAs (DEMs) compared with primary samples. There were no overlapping gene in ontology (GO) terms related to GBM recurrence in the TCGA and CGGA databases, but there were overlaps associated with LGG recurrence. GO analysis and protein-protein interaction (PPI) network analysis identified three core genes: TIMP1, COL1A1 and COL6A2. By hierarchical cluster analysis of them, LGGs could be clustered as Low_risk and High_risk group. The High_risk group with high expression of TIMP1, COL1A1, and COL6A2 showed worse prognosis. By coexpression networks analysis, competing endogenous RNA (ceRNA) network analysis, cell proliferation assay and luciferase reporter assay, we confirmed that lncRNA HOXA-AS2 functioned as a ceRNA for miR-184 to regulate expression of COL6A2, which induced cell proliferation of low-grade glioma. Conclusion: In this study, we revealed a 3-hub protein-coding gene signature to improve prognostic prediction in LGG, and identified a critical ceRNA regulation involved in LGG recurrence.

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Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets

Cited by 29 publications

References 42 publications

Integrated miRNA profiling and bioinformatics analyses reveal upregulated miRNAs in gastric cancer

Integrated miRNA profiling and bioinformatics analyses reveal upregulated miRNAs in gastric cancer

Identification of miRNA-Based Signature as a Novel Potential Prognostic Biomarker in Patients with Breast Cancer

<p>Comprehensive Transcriptomic Analysis and Experimental Validation Identify lncRNA HOXA-AS2/miR-184/COL6A2 as the Critical ceRNA Regulation Involved in Low-Grade Glioma Recurrence</p>

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