Dataset Information

Identification of MicroRNAs as Diagnostic Biomarkers for Breast Cancer Based on the Cancer Genome Atlas.

ABSTRACT: Breast cancer is the most common cancer among women worldwide. MicroRNAs (miRNAs or miRs) play an important role in tumorigenesis, and thus, they have been identified as potential targets for translational research with diagnostic, prognostic, and therapeutic markers. This study aimed to identify differentially expressed (DE) miRNAs in breast cancer using the Cancer Genome Atlas. The miRNA profiles of 755 breast cancer tissues and 86 adjacent non-cancerous breast tissues were analyzed using Multi Experiment Viewer; miRNA-mRNA network analyses and constructed KEGG pathways with the predicted target genes were performed. The clinical relevance of miRNAs was investigated using area under the receiver operating characteristic curve (AUC) analysis, sensitivity, and specificity. The analysis identified 28 DE miRNAs in breast cancer tissues, including nine upregulated and 19 downregulated miRNAs, compared to non-cancerous breast tissues (p < 0.001). The AUC for each DE miRNA, miR-10b, miR-21, miR-96, miR-99a, miR-100, miR-125b-1, miR-125b-2, miR-139, miR-141, miR-145, miR-182, miR-183, miR-195, miR-200a, miR-337, miR-429, and let-7c, exceeded 0.9, indicating excellent diagnostic performance in breast cancer. Moreover, 1381 potential target genes were predicted using the prediction database tool, miRNet. These genes are related to PD-L1 expression and PD-1 checkpoint in cancer, MAPK signaling, apoptosis, and TNF pathways; hence, they regulate the development, progression, and immune escape of cancer. Thus, these 28 miRNAs can serve as prospective biomarkers for the diagnosis of breast cancer. Taken together, these results provide insight into the pathogenic mechanisms and potential therapies for breast cancer.

SUBMITTER: Kim J

PROVIDER: S-EPMC7827427 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Identification of MicroRNAs as Diagnostic Biomarkers for Breast Cancer Based on the Cancer Genome Atlas.

Kim Jungho J

Diagnostics (Basel, Switzerland) 20210111 1

Breast cancer is the most common cancer among women worldwide. MicroRNAs (miRNAs or miRs) play an important role in tumorigenesis, and thus, they have been identified as potential targets for translational research with diagnostic, prognostic, and therapeutic markers. This study aimed to identify differentially expressed (DE) miRNAs in breast cancer using the Cancer Genome Atlas. The miRNA profiles of 755 breast cancer tissues and 86 adjacent non-cancerous breast tissues were analyzed using Mult ...[more]

PMID: 33440868

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Project description:BackgroundMicroRNAs (miRNAs) have played important roles in the regulation of gene expression in many cancers, but their roles in esophageal squamous cell carcinoma (ESCC) are still unclear. The aim of this study was to determine the potential ESCC-specific key miRNAs from a large sample dataset in The Cancer Genome Atlas (TCGA).MethodsIntegrative bioinformatics analysis was used to identify key ESCC-specific miRNAs related to the ESCC patients' tumor histological grade and lymphatic metastasis from TCGA. Next, these key miRNA potential gene regulatory functions and relationships with ESCC patients' clinical characteristics and overall survival were analyzed. Finally, three key miRNAs were selected randomly and quantificational real-time polymerase chain reaction (qRT-PCR) was used to validate in 51 newly diagnosed ESCC patients' tissues samples (collected from Nov. 2017 to Feb. 2019, in Wuwei, China) whether the bioinformatics analyses results were reliable and valid. Two-tailed Student's t test, Pearson Chi-squared test and Kaplan-Meier survival analysis were used in this study.ResultsThirty-five ESCC-specific miRNAs from TCGA database were investigated (fold-change > 2.0, P < 0.05), and 28 participated in the miRNAs-mRNAs co-expression network construction, while 17 were related with ESCC patients' tumor histological grade, TNM stage, and lymphatic metastasis (P < 0.05). Meanwhile, six miRNAs (including miR-200b-3p, miR-31-5p, miR-15b-5p, miR-141-3p, miR-135b-5p, and miR-195-5p) were correlated with overall survival of ESCC patients (log-rank, P < 0.05). MiR-135b-5p, miR-15b-5p, and miR-195-5p were selected for verification of the expression levels in 51 ESCC patients' tissue samples by using qRT-PCR. We found that the fold-changes between qRT-PCR and TCGA were completely consistent. The results also suggested that miR-135b-5p, miR-15b-5p, and miR-195-5p were significantly correlated with tumor differentiation degrees (P < 0.05), miR-195-5p was significantly correlated with tumor TNM stage (P < 0.05), and miR-135b-5p was significantly correlated with lymph-node metastasis (P < 0.05). MiR-135b-5p, miR-15b-5p, and miR-195-5p expression levels, ESCC patient clinical features association analysis results and the aforementioned TCGA bioinformatics analyses were similar.ConclusionThis study identified key ESCC-related miRNAs. The key miRNAs are worthy of further investigation as potential novel biomarkers for diagnosis, classification, and prognosis of ESCC.

Project description:AbstractMicroRNAs (miRNAs) in tumor and tumor-adjacent tissues can be effective diagnostic and prognostic markers to monitor tumor occurrence and progression. Despite improvements in the diagnosis and treatment of esophageal cancer (EC), the survival rate is <25%; consequently, more effective EC-specific prognostic biomarkers are urgently needed to design effective treatment regimens. In this study, we focused on identifying independent prognostic miRNA signatures in tumor and tumor-adjacent tissues in EC.We screened candidate miRNAs using a genome-wide miRNA transcriptome dataset from The Cancer Genome Atlas (TCGA) database that included 82 patients with esophageal adenocarcinoma (EADC) and 83 patients with esophageal squamous cell carcinoma (ESCC). We validated potential prognostic miRNA markers using a microarray profiling dataset that included information of 32 patients with EADC and 44 patients with ESCC from the Gene Expression Omnibus database. TCGA dataset was additionally used to identify differentially expressed mRNAs (DEMs) between the tumor and tumor-adjacent tissues. Univariate and multivariate Cox analyses were performed to detect the relationship between miRNAs and the overall survival of patients with EC. Kaplan-Meier method was applied to assess the survival differences between groups with differential miRNA expression. Lastly, functional enrichment analysis was conducted using miRWalk 2.0 online database for annotation.Although there was a considerable difference between the DEMs of EADC and ESCC, 73 DEMs were differentially expressed in both EADC and ESCC samples in TCGA dataset. Cox regression and Kaplan-Meier survival analyses showed that a higher expression of hsa-miR-186-5p and hsa-let-7d-5p was independently associated with a poor prognosis of EADC and ESCC, respectively. Furthermore, gene functional enrichment analysis revealed that the target genes of hsa-miR-186-5p and hsa-let-7d-5p participated in various cancer-related pathways, including the MAPK signaling pathway, proteoglycans in cancer, and AGE-RAGE signaling pathway.Our results revealed that hsa-miR-186-5p and hsa-let-7d-5p could be used as independent prognostic biomarkers for EADC and ESCC, respectively.

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Dataset Information

Identification of MicroRNAs as Diagnostic Biomarkers for Breast Cancer Based on the Cancer Genome Atlas.

Publications

Identification of MicroRNAs as Diagnostic Biomarkers for Breast Cancer Based on the Cancer Genome Atlas.

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