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Identification of Differentially Expressed Plasma lncRNAs As Potential Biomarkers for Breast Cancer

      Abstract

      Background

      Breast cancer is the most common malignant tumor in women and is not easy to diagnose. Increasing evidence has underscored that long non-coding RNAs (lncRNAs) play important regulatory roles in the occurrence and progression of many cancers, including breast cancer. We aimed to identify lncRNAs in plasma as potential biomarkers for breast cancer.

      Patients and Methods

      We analyzed the Gene Expression Omnibus (GEO) datasets GSE22820, GSE42568, and GSE65194 to identify the common differential genes between cancer tissues and adjacent tissues. Then 14 lncRNAs were identified among the common differential genes and validated by using real-time quantitative polymerase chain reaction in 92 patients with breast cancer and 100 healthy controls. Receiver operating characteristic (ROC) curves were constructed to evaluate their diagnostic value for breast cancer.

      Results

      Integrated analysis of the GEO datasets identified three significantly upregulated and 11 downregulated lncRNAs in breast cancer tissues. Compared with healthy controls, MIAT was significantly upregulated in breast cancer patient plasma, and LINC00968 and LINC01140 were significantly downregulated. ROC curve analysis suggested that these three lncRNAs can discriminate breast cancer from healthy individual with high specificity and sensitivity.

      Conclusion

      This research identified three differentially expressed lncRNAs in breast cancer patient plasma. Our data suggest that these three lncRNAs can be used as potential diagnostic biomarkers of breast cancer.

      Keywords

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