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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Article info
Publication history
Published online: May 18, 2021
Accepted:
May 8,
2021
Received in revised form:
April 26,
2021
Received:
February 2,
2021
Identification
Copyright
© 2021 Elsevier Inc. All rights reserved.
