Targeted Molecular Analysis in Adrenocortical Carcinomas: A Strategy Toward Improved Personalized Prognostication

• DOI: 10.1210/jc.2018-01348
• Publication Date: 2018-08-02T18:36:25Z
• Authors: Juliane Lippert; Silke Appenzeller; Raimunde Liang; Silviu Sbiera; Stefan Kircher; Barbara Altieri; Indrajit Nanda; Isabel Weigand; Andrea Gehrig; Sonja Steinhauer; Renzo J M Riemens; Andreas Rosenwald; Clemens R Müller; Matthias Kroiss; Simone Rost; Martin Fassnacht; Cristina L Ronchi
• Keywords: Adult; Male; DNA Copy Number Variations; DNA Mutational Analysis; MULTICENTER; 610; Antineoplastic Agents; CLASSIFICATION; PATHWAY; 03 medical and health sciences; 0302 clinical medicine; MISMATCH-REPAIR; REVEALS; Adrenocortical Carcinoma; Biomarkers, Tumor; Humans; Point Mutation; Molecular Targeted Therapy; Precision Medicine; DNA METHYLATION; Aged; Aged, 80 and over; High-Throughput Nucleotide Sequencing; CHEMOTHERAPY; DNA Methylation; Middle Aged; TUMORS; CANCER; Adrenal Cortex Neoplasms; GENOMIC CHARACTERIZATION; 3. Good health; Adrenal Cortex; Female; Follow-Up Studies

Abstract

Context Adrenocortical carcinoma (ACC) has a heterogeneous prognosis, and current medical therapies have limited efficacy in its advanced stages. Genome-wide multiomics studies identified molecular patterns associated with clinical outcome.

Objective Here, we aimed at identifying a molecular signature useful for both personalized prognostic stratification and druggable targets, using methods applicable in clinical routine.

Design In total, 117 tumor samples from 107 patients with ACC were analyzed. Targeted next-generation sequencing of 160 genes and pyrosequencing of 4 genes were applied to formalin-fixed, paraffin-embedded (FFPE) specimens to detect point mutations, copy number alterations, and promoter region methylation. Molecular results were combined with clinical/histopathological parameters (tumor stage, age, symptoms, resection status, and Ki-67) to predict progression-free survival (PFS).

Results In addition to known driver mutations, we detected recurrent alterations in genes not previously associated with ACC (e.g., NOTCH1, CIC, KDM6A, BRCA1, BRCA2). Best prediction of PFS was obtained integrating molecular results (more than one somatic mutation, alterations in Wnt/β-catenin and p53 pathways, high methylation pattern) and clinical/histopathological parameters into a combined score (P < 0.0001, χ2 = 68.6). Accuracy of prediction for early disease progress was 83.3% (area under the receiver operating characteristic curve: 0.872, 95% confidence interval 0.80 to 0.94). Furthermore, 17 potentially targetable alterations were found in 64 patients (e.g., in CDK4, NOTCH1, NF1, MDM2, and EGFR and in DNA repair system).

Conclusions This study demonstrates that molecular profiling of FFPE tumor samples improves prognostication of ACC beyond clinical/histopathological parameters and identifies new potential drug targets. These findings pave the way to precision medicine in this rare disease.