Transcriptome Analysis of lncRNAs in Pheochromocytomas and Paragangliomas.

Abstract

Pheochromocytomas and paragangliomas (PPGLs) are neuroendocrine tumors explained by germline or somatic mutations in about 70% of cases. Patients with SDHB mutations are at high risk of developing metastatic disease, yet no reliable tumor biomarkers are available to predict tumor aggressiveness. We aimed at identifying long noncoding RNAs (lncRNAs) specific for PPGL molecular groups and metastatic progression. To analyze the expression of lncRNAs, we used a mining approach of transcriptome data from a well-characterized series of 187 tumor tissues. Clustering consensus analysis was performed to determine a lncRNA-based classification, and informative transcripts were validated in an independent series of 51 PPGLs. The expression of metastasis-related lncRNAs was confirmed by RT-qPCR. Receiver operating characteristic (ROC) curve analysis was used to estimate the predictive accuracy of potential markers. Univariate/multivariate and metastasis-free survival (MFS) analyses were carried out for the assessment of risk factors and clinical outcomes. Four lncRNA-based subtypes strongly correlated with mRNA expression clusters (chi-square P-values from 1.38 × 10-32 to 1.07 × 10-67). We identified one putative lncRNA (GenBank: BC063866) that accurately discriminates metastatic from benign tumors in patients with SDHx mutations (area under the curve 0.95; P = 4.59 × 10-05). Moreover, this transcript appeared as an independent risk factor associated with poor clinical outcome of SDHx carriers (log-rank test P = 2.29 × 10-05). Our findings extend the spectrum of transcriptional dysregulations in PPGL to lncRNAs and provide a novel biomarker that could be useful to identify potentially metastatic tumors in patients carrying SDHx mutations.