Performance of DNA-based biomarkers for classification of adrenocortical carcinoma: a prognostic study

Abstract

Objective: Adrenocortical carcinoma (ACC) is a rare aggressive malignancy with heterogeneous clinical outcomes. Recent studies proposed a combination of clinical/histopathological parameters (S-GRAS score) or molecular biomarkers (BMs) to improve prognostication. We performed a comparative analysis of DNA-based BMs by evaluating their added prognostic value to the S-GRAS score.

Design and methods: A total of 194 formalin-fixed, paraffin-embedded (FFPE) ACC samples were analysed, including a retrospective training cohort (n = 107) and a prospective validation cohort (n = 87). Targeted DNA sequencing and pyrosequencing were used to detect somatic single-nucleotide variations in ACC-specific genes and methylation in the promoter region of paired box 5 (PAX5). The European Network for the Study of Adrenocortical Tumors (ENSAT) tumour stage, age, symptoms at presentation, resection status, and Ki-67 were combined to calculate S-GRAS. Endpoints were overall (OS), progression-free (PFS), and disease-free survival (DFS). Prognostic role was evaluated by multivariable survival analysis and their performance compared by Harrell's concordance index (C index).

Results: In training cohort, an independent prognostic role was confirmed at multivariate analysis for two DNA-based BMs: alterations in Wnt/β-catenin and Rb/p53 pathways and hypermethylated PAX5 (both P< .05 for PFS and DFS, hazard ratio [HR] 1.47-2.33). These were combined to S-GRAS to obtain a combined (COMBI) score. At comparative analysis, the best discriminative prognostic model was COMBI score in both cohorts for all endpoints, followed by S-GRAS score (C index for OS 0.724 and 0.765, PFS 0.717 and 0.670, and DFS 0.699 and 0.644, respectively).

Conclusions: Targeted DNA-based BM evaluated on routinely available FFPE samples improves prognostication of ACC beyond routinely available clinical and histopathological parameters. This approach may help to better individualise patient's management.