ECE2023 Rapid Communications Rapid Communications 5: Adrenal and Cardiovascular Endocrinology 1 (6 abstracts)
1University Hospital of Wuerzburg, Division of Endocrinology and Diabetes, Wuerzburg, Germany; 2University of Wuerzburg, Core Unit Bioinformatics, Wuerzburg, Germany; 3University of Birmingham, Institute of Metabolism and System Research, Birmingham, United Kingdom; 4University of Wuerzburg, Institute of Pathology, Wuerzburg, Germany; 5University Hospitals Birmingham NHS Foundation Trust, Department of Histopathology, Birmingham, United Kingdom
Adrenocortical carcinoma (ACC) is a rare malignant tumour with heterogeneous outcome. Prognostic classification relies on individual clinical/histopathological parameters that have limited performance. Recent studies proposed the use of selected DNA-based biomarkers to improve prognostication of ACC. Aim of the study was to perform a comparative analysis of DNA-based biomarkers (BM) for prognostic assessment of ACC by evaluating their added value to the established prognostic S-GRAS score, a combination of five clinical/histopathological parameters. A total of 194 formalin-fixed, paraffin-embedded (FFPE) samples from patients with histologically confirmed ACC were analysed. Targeted DNA sequencing and pyrosequencing were used to detect single nucleotide variations (SNV) in ACC-specific genes (two different panels with 100 and 33 genes, respectively) and methylation in the promoter region of PAX5. ENSAT tumour stage, age, symptoms, resection status, and Ki-67 index were collected for calculation of the S-GRAS score. Endpoints were overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Prognostic role of each parameter was evaluated by uni- and multivariable Cox regression analysis and compared by Harrells C-index. The prognostic role of following DNA-based BMs was confirmed at univariable analysis: more than one SNV-affected gene (BM1), alterations in Wnt/β-catenin and Rb/p53 pathways (BM2) and hypermethylated PAX5 (BM3) (P<0.01 for both OS and PFS). However, only BM2 and BM3 showed an independent prognostic impact at multivariable analysis including S-GRAS score (P<0.05 for all three endpoints, HR between 1.4 and 1.9). Importantly, looking at the C-index, the best discriminant prognostic model was represented by the combination of DNA-based BM2 and BM3 with S-GRAS (combined score) as compared to S-GRAS alone, which was the second best prognostic factor (C-index for OS 0.734 vs 0.704, for PFS 0.697 vs 0.676, for DFS 0.674 vs 0.633, respectively). In conclusion, targeted DNA-based biomarkers evaluated on routinely available FFPE samples improve prognostication of ACC beyond combined clinical/histopathological parameters. This approach is easily applicable in clinical practice and may help to optimise patients management.