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

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. Mueller, Matthias Kroiss, Simone Rost, Martin Fassnacht, Cristina L. Ronchi*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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/beta-catenin and p53 pathways, high methylation pattern) and clinical/histopathological parameters into a combined score (P <0.0001, chi(2) = 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., inCDK4, 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.

Original languageEnglish
Pages (from-to)4511-4523
Number of pages13
JournalJournal of Clinical Endocrinology & Metabolism
Issue number12
Publication statusPublished - Dec 2018



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