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Identification of circulating biomarkers for differentiating patients with papillary thyroid cancers from benign
1Department of Anesthesiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung City, Taiwan.
Background:
This study aimed to identify the potential circulating biomarkers of protein, mRNAs, and long non-coding RNAs (lncRNAs) to differentiate the papillary thyroid cancers from benign thyroid tumors.
Methods:
The study population of 100 patients was classified into identification (10 patients with papillary thyroid cancers and 10 patients with benign thyroid tumors) and validation groups (45 patients with papillary thyroid cancers and 35 patients with benign thyroid tumors). The Sengenics Immunome Protein Array-combined data mining approach using the Open Targets Platform was used to identify the putative protein biomarkers, and their expression validated using the enzyme-linked immunosorbent assay. Next-generation sequencing by Illumina HiSeq was used for the detection of dysregulated mRNAs and lncRNAs. The website Timer v2.0 helped identify the putative mRNA biomarkers, which were significantly over-expressed in papillary thyroid cancers than in adjacent normal thyroid tissue. The mRNA and lncRNA biomarker expression was validated by a real-time polymerase chain reaction.
Results:
Although putative protein and mRNA biomarkers have been identified, their serum expression could not be confirmed in the validation cohorts. In addition, seven lncRNAs (TCONS_00516490, TCONS_00336559, TCONS_00311568, TCONS_00321917, TCONS_00336522, TCONS_00282483, and TCONS_00494326) were identified and validated as significantly downregulated in patients with papillary thyroid cancers compared to those with benign thyroid tumors. These seven lncRNAs showed moderate accuracy based on the area under the curve (AUC = 0.736) of receiver operating characteristic in predicting the occurrence of papillary thyroid cancers.
Conclusions:
We identified seven downregulated circulating lncRNAs with the potential for predicting the occurrence of papillary thyroid cancers.
