SFEBES2018 Oral Communications Clinical highlights (6 abstracts)
Targeted molecular analysis in adrenocortical carcinomas: a strategy towards improved personalized prognostication
Juliane Lippert 1 , Silke Appenzeller 2 , Raimunde Liang 3 , Silviu Sbiera 3 , Stefan Kircher 4 , Barbara Altieri 3, , Isabel Weigand 3 , Renzo Riemens 1, , Andreas Rosenwald 4 , Matthias Kroiss 3, , Simone Rost 1 , Martin Fassnacht 3, & Cristina Ronchi 3,
1Institute of Human Genetics, University of Wuerzburg, Wuerzburg, Germany; 2Core Unit Bioinformatics University of Wuerzburg, Wuerzburg, Germany; 3Division of Endocrinology and Diabetes, University Hospital of Wuerzburg, Wuerzburg, Germany; 4Institute for Pathology, University of Wuerzburg, Wuerzburg, Germany; 5Division of Endocrinology and Metabolic Diseases, Catholic University of the Sacred Heart, Rome, Italy; 6Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands; 7Comprehensive Cancer Center Mainfranken, University of Wuerzburg, Wuerzburg, Germany; 8Central Labor, University Hospital of Wuerzburg, Wuerzburg, Germany; 9Institute of Metabolism and System Research, University of Birmingham, Birmingham, UK.
Background: Adrenocortical carcinoma (ACC) has a heterogeneous prognosis and current medical therapies have limited efficacy in its advanced stages. Genome-wide multi-omics-studies identified molecular patterns associated with clinical outcome. Here, we aimed at identifying a molecular signature useful for both personalized prognostic stratification and druggable targets, using methods applicable in clinical routine.
Methods: 117 tumor samples from 107 ACC patients 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 Ki67) 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). The association of age ≥50 years, tumor- or hormone-related symptoms, ENSAT tumor stage, resection status and ki67 proliferation index (modified GRAS classification) could prognosticate recurrence risk (P<0.0001; χ2=49.0). However, best prediction of PFS was obtained integrating molecular results (>1 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 ROC curve: 0.872, 0.80–0.94). Furthermore, 17 potentially targetable alterations were found in 64 patients (e.g. in CDK4, NOTCH1, NF1, MDM2, EGFR and in DNA repair system).
Conclusions: This study shows the feasibility of DNA analysis on FFPE tumor tissues in the clinical practice. We demonstrate that clinical/histopathological parameters might predict the clinical outcome of ACC patients. However, the combination with specific molecular alterations increases the power of the prognostic stratification and may identify new potential drug targets. Our findings might pave the way to a precision medicine approach in ACC.
Volume 59
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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