Parathyroid carcinoma (PCa) is a rare endocrine neoplasia that typically has unfavourable outcomes. The contribution of long non-coding RNAs (lncRNAs) to the development of malignant and benign parathyroid tumours remains largely unknown. In this study, we explored transcriptomic profiling of lncRNA and mRNA expression in 6 PCa, 6 parathyroid adenoma (PAd) and 4 normal parathyroid (PaN) tissues. In total, 2641 lncRNA transcripts and 2165 mRNA transcripts were differentially expressed between PCa and PAd. Enrichment analysis demonstrated that dysregulated transcripts were involved mainly in the extracellular matrix (ECM)–receptor interaction and energy metabolism pathways. Bioinformatics analysis suggested that ATF3, ID1, FOXM1, EZH2 and MITF may be crucial to parathyroid carcinogenesis. Series test of cluster analysis segregated differentially expressed lncRNAs and mRNAs into several expression profile models, among which the ‘plateau’ profile representing components specific to parathyroid carcinogenesis was selected to build a co-expression network. Seven lncRNAs and three mRNAs were selected for quantitative RT-PCR validation in 16 PCa, 41 PAd and 4 PaN samples. Receiver-operator characteristic curves analysis showed that lncRNA PVT1 and GLIS2-AS1 yielded the area under the curve values of 0.871 and 0.860, respectively. Higher hybridization signals were observed in PCa for PVT1 and PAd for GLIS2-AS1. In conclusion, the current evidence indicates that PAd and PCa partially share common signalling molecules and pathways, but have independent transcriptional events. Differentially expressed lncRNAs and mRNAs have intricate interactions and are involved in parathyroid tumourigenesis. The lncRNA PVT1 and GLIS2-AS1 may be new potential markers for the diagnosis of PCa.
Supplementary Table 1 Clinical and laboratory characteristics of parathyroid carcinoma cohort
Supplementary Table 2 Diagnostic efficacy of PVT1 and GLIS2-AS1 in differentiating CDC73-mutant PCa via ROC analysis
Supplementary Figure 1 IPA molecular network 1
Supplementary Figure 2 IPA molecular network 2
Supplementary Figure 3 IPA molecular network 3
Supplementary Figure 4 The predicted regulatory effects via IPA analysis. Integrated analysis of up-stream regulators, biological functions and gene interactions revealed the most focused gene crosstalk. Orange ellipses and lines represent predicted activation and leading to activation. Blue ellipses and lines represent predicted inhibition and leading to inhibition. Yellow lines represent findings that are inconsistent with state of down-stream molecules. Grey lines indicate unpredicted effects.
Supplementary Figure 5 The predicted core up-stream regulators (ATF3)
Supplementary Figure 6 The predicted core up-stream regulators (ID1)
Supplementary Figure 7 The predicted core up-stream regulators (FOXM1)
Supplementary Figure 8 The predicted core up-stream regulators (EZH2)
Supplementary Figure 9 The predicted core up-stream regulators (MITF)