Biomarkers Improving Genetic and Metastatic Disease Prediction in Paraganglioma: Insights From a Prospective Study.

CONTEXT AND

OBJECTIVE

Identifying the risk of malignancy and genetic status in primary paraganglioma or pheochromocytoma (PPGL) is a key challenge. The aim was to assess the diagnostic accuracy of genomic, metabolomic and histopathological biomarkers for predicting metastatic and genetic status.

DESIGN, SETTING, AND PATIENTS: COMETE-TACTIC is a prospective study (NCT02672020) conducted from November 2015 to March 2019 across 16 referral centers. Tumor samples and liquid biopsies from 231 consecutive patients with PPGL were collected.

MAIN OUTCOME MEASURES: Germline and somatic genetic status were determined by next-generation sequencing, SDHB, SDHA and CA9 immunohistochemistries were performed on tumor tissues. TERT promoter methylation was assessed by pyrosequencing. Metabolomic profile and circulating miRNAs were measured in liquid biopsies by gas chromatography MS/MS and TaqMan assay quantified by droplet digital PCR, respectively.

RESULTS

Tumor analysis outperformed germline analysis for determining genetic status. Positive SDHA and SDHB staining combined with negative CA9 labeling indicated the absence of SDHx and VHL variants. Plasma succinate levels above 4.94 µM identified SDHx mutation carriers with 65% sensitivity and 92% specificity [area under the receiver operating characteristic curve (AUC-ROC) 0.82, 95% confidence interval (CI) 0.70-0.93]. Among circulating miRNAs, miR-483-5p was the best classifier of metastatic status (AUC-ROC 0.64, 95%CI 0.52-0.77). A sum of dinucleotide methylation rate of TERT promoter CpGs above 42% predicted metastatic status (AUC-ROC 0.75, 95% CI 0.65-0.85). Multivariate analyses showed that biomarker combinations significantly predicted SDHx status (AUC-ROC 0.99, 95% CI 0.98-1.00) and metastatic potential (AUC-ROC 0.93, 95% CI 0.84-1).

CONCLUSION

Circulating miR-483-5p, plasma succinate, TERT promoter methylation, and SDHB immunostaining are valuable for PPGL risk stratification. Combining biomarkers with clinical data provides excellent diagnostic accuracy for metastatic patients (AUC-ROC 0.97, 95%CI 0.93-1).