ECE2018 Oral Communications Clinical practice in endocrine tumours: combining conventional and molecular features (5 abstracts)
Targeted molecular analysis in adrenocortical carcinomas: a way towards improved personalized prognostication
Juliane Lippert 1 , Silke Appenzeller 2 , Raimunde Liang 3 , Silviu Sbiera 3 , Stefan Kircher 4 , Barbara Altieri 3, , Indrajit Nanda 1 , Isabel Weigand 3 , Andrea Gehrig 1 , Sonja Steinhauer 3 , Clemens Mueller 1 , Matthias Kroiss 3 , Simone Rost 1 , Andreas Rosenwald 4 , 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, University Hospital of Wuerzburg, Wuerzburg, Germany; 4Department of Pathology, University of Wuerzburg, Wuerzburg, Germany; 5Division of Endocrinology, Catholic University of the Sacred Heart, Rome, Italy; 6Institute of Metabolism and System Research, University of Birmingham, Birmingham, UK.
Adrenocortical carcinoma (ACC) has heterogeneous prognosis and no effective targeted therapies. Pan-genomic studies identified complex molecular patterns related to outcome. Our study aimed at identification of an ‘easy-to-apply’ molecular signature for better personalized prognostic stratification. A total of 107 ACC patients were enrolled. Clinical/histopathological parameters of prognostic relevance were evaluated. Targeted molecular analysis was performed on DNA isolated from FFPE tumor samples, including mutations and copy number alterations, methylation of promoter regions. Primary endpoint was progression-free survival (PFS). 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 in the present series (P<0.0001; chi-square=49.0) and in an independent cohort of 368 ACC patients (P<0.0001; chi-square=202.5). The most frequent genetic alterations were mutations at TP53 (22%), CTNNB1 (17%), NF1 (11%), ZNRF3 (9.3%), APC (8.4%), MEN1 (7.4%), and CN gains of CDK4 (43%) and TERT (12%). Some recurrent mutations were also observed in genes previously not associated with ACC (e.g. NOTCH1, CIC, KDM6A, BRCA1 and BRCA2). Interestingly, the combination between clinical/histopathological data and specific molecular alterations (>1 somatic mutation, alterations in Wnt/β-catenin and/or p53 pathways and high methylation pattern) showed the best prediction of PFS (P<0.0001; chi-square=68.6). Searching for potentially druggable targets, CN gains at CDK4 locus and mutations affecting NF1 or members of the DNA repair system or mismatch repair were the most frequent. This study shows the feasibility of DNA analysis on FFPE tumor tissues in the clinical practice. We demonstrate that selected 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 56
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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