ECE2018 Oral Communications Clinical practice in endocrine tumours: combining conventional and molecular features (5 abstracts)
Molecular classifiers refine the prognostic stratification of adrenocortical carcinoma
Anne Jouinot 1, , Guillaume Assié 1, , Martin Fassnacht 3, , Rossella Libe 1, , Simon Garinet 1 , Louis Jacob 1 , Simon Faillot 1 , Nadim Hamzaoui 5 , Mario Neou 1 , Julien Sakat 1 , Karine Perlemoine 1 , Mathilde Sibony 1, , Frederique Tissier 7 , Bertrand Dousset 8 , Silviu Sbiera 3 , Cristina Ronchi 3 , Matthias Kroiss 4 , Esther Korpershoek 9 , Ronald De Krijger 9, , Jens Waldmann 11 , Marcus Quinkler 12 , Antoine Tabarin 13 , Olivier Chabre 14 , Joel Coste 15 , Michaela Luconi 16 , Massimo Mannelli 16 , Lionel Groussin 1, , Xavier Bertagna 1, , Eric Baudin 17 , Laurence Amar 18 , Felix Beuschlein 19 & Jérôme Bertherat 1,
1Institut Cochin, INSERM U1016, CNRS UMR8104, Paris Descartes University, Paris, France; 2Department of Endocrinology, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France; 3Endocrinology and Diabetes Unit, University Hospital, University of Würzburg, Wurzburg, Germany; 4Comprehensive Cancer Center Mainfranken, University of Würzburg, Wurzburg, Germany; 5Department of Oncogenetics, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France; 6Department of Pathology, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France; 7Department of Pathology, Assistance Publique Hôpitaux de Paris, Hôpital Pitié Salpétrière, Paris, France; 8Department of Digestive and Endocrine Surgery, Assistance Publique Hôpitaux de Paris, Paris, France; 9Department of Pathology, Erasmus MC University Medical Center, Rotterdam, Netherlands; 10Department of Pathology, Reinier de Graaf Hospital, Delft, Netherlands; 11Department of Surgery, University Hospital Giessen and Marburg, Marburg, Germany; 12Department of Medicine, Charite University, Berlin, Germany; 13Department of Endocrinology, Diabetes and Metabolic Diseases, University Hospital of Bordeaux, Bordeaux, France; 14Department of Endocrinology, University Hospital of Grenoble, Grenoble, France; 15Biostatistics and Epidemiology Unit, Hôtel Dieu, Assistance Publique-Hôpitaux de Paris, Paris, France; 16Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy; 17Department of Nuclear Medicine and Endocrine Oncology, Institut Gustave Roussy, Villejuif, France; 18Hypertension Unit, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France; 19Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-Universität München, Munchen, Germany.
Background: Adrenocortical cancer (ACC) is an aggressive tumour with heterogeneous prognosis. Pan-genomic studies identified molecular subgroups of ACC, remarkably associated with outcome. For routine prospective use, targeted molecular measures are needed, combined into reasonably easy and cheap techniques. The aim was to develop and validate different combinations of targeted molecular markers reflecting the molecular subgroup, and compare their prognostic value to standard prognostic factors of ACC.
Patients and methods: We performed a meta-analysis of pan-genomic studies in a training cohort of 144 ACC, determining their transcriptome (C1A or C1B), methylome (CIMP or nonCIMP), chromosomal alterations (Noisy or Chromosomal/Quiet) and mutational (Cell-cycle and Wnt-betacatenin pathways) profiles. A subset of 72 ACC was studied by targeted measures, including BUB1B-PINK1 differential expression by RT-qPCR and CpG islands methylation of 4 genes (PAX5-GSTP1-PYCARD-PAX6) by MS-MLPA. An independent cohort of 224 ACC from 21 ENSAT centers was used for prognostic validation with RT-qPCR, MS-MLPA, SNP array and targeted NGS. Analyses of disease-free survival (DFS) –for stage I-III ACC- and overall survival (OS) –for stage IV ACC- were performed using Cox models.
Results: Pan-genomic studies identified 4 molecular groups: I) C1A, CIMP and Noisy, II) C1A, (CIMP OR Noisy), III) C1A, nonCIMP and Chromosomal/Quiet and IV) C1B, showing major survival differences (logrank P<10−11). In the training cohort, targeted measures were combined into three distinct targeted classifiers: i) a 3D-targeted classifier, recapitulating most comprehensively the pan-genomic classification, combining gene expression, chromosome alterations and methylation profiles; ii) a PCR-based classifier, measurable by PCR-based techniques, combining gene expression and methylation profiles; iii) a DNA-based classifier, using tumor DNA only and so forth combining methylation, chromosome alteration and mutational statuses. All these targeted classifiers presented a strong association with the pan-genomic molecular classification (Fisher P<10−9). The prognostic value of targeted molecular classifiers was confirmed in the validation cohort. In localized ACC, all three molecular classifiers were identified as independent prognostic factors of recurrence (DFS HR: 5.96, 5.24 and 2.61, P=0.003, 0.002 and 0.006 for the 3D-, PCR-based and DNA-baseed markers respectively) in multivariable models including ENSAT stage and tumor grade. In metastatic ACC, molecular classifiers were associated with overall survival (OS HR=3.16, 4.53 and 3.02, P=0.18, 0.08 and 0.006 for the 3D-, PCR-based and DNA-based markers respectively in univariate analysis).
Conclusion: Molecular classification can be recapitulated with targeted molecular measures. In localized ACC, molecular classifiers are strong prognostic independent markers of recurrence, usable in clinical routine.
Article tools
My recent searches
My recently viewed abstracts
Authors
Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
© Bioscientifica 2024 |
Privacy policy |
Cookie settings
BiosciAbstracts
Bioscientifica Abstracts is the gateway to a series of products that provide a permanent, citable record of abstracts for biomedical and life science conferences.
Find out more