Anne Jouinot1,2, Guillaume Assie1,3, Rossella Libe1,3, Martin Fassnacht4,5, Thomas Papathomas6, Olivia Barreau1,3, Bruno de la Villeon1, Simon Faillot1, Nadim Hamzaoui7, Mario Neou1, Karine Perlemoine1, Fernande Rene-Corail1, Stéphanie Rodriguez1, Mathilde Sibony1,8, Frédérique Tissier1,8, Bertrand Dousset9, Silviu Sbiera4, Cristina Ronchi4, Matthias Kroiss5, Esther Korpershoek6, Ronald de Krijger6,10, Jens Waldmann11, Detlef K, Marcus Quinkler12, Magalie Haissaguerre13, Antoine Tabarin13, Olivier Chabre14, Nathalie Sturm15, Michaela Luconi16, Franco Mantero17, Massimo Mannelli16, Regis Cohen18, Véronique Kerlan19, Philippe Touraine20, Gaelle Barrande21, Lionel Groussin1,3, Xavier Bertagna1,3, Eric Baudin22, Laurence Amar23, Felix Beuschlein24, Eric Clauser7, Joel Coste25, Jérôme Bertherat1,3. 1. Institut Cochin, INSERM U1016, CNRS UMR8104, Paris Descartes University, 75014 Paris, France. 2. Medical Oncology. 3. Department of Endocrinology. 4. Endocrinology and Diabetes Unit, University Hospital, and. 5. Comprehensive Cancer Center Mainfranken, University of Würzburg, 97070 Würzburg, Germany. 6. Department of Pathology, Erasmus MC University Medical Center, 3062 PA Rotterdam, The Netherlands. 7. Department of Oncogenetics. 8. Department of Pathology, and. 9. Department of Digestive and Endocrine Surgery, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, 75014 Paris, France. 10. Department of Pathology, Reinier de Graaf Hospital, 2625 AD Delft, The Netherlands. 11. Department of Surgery, University Hospital Giessen and Marburg, 35043 Marburg, Germany. 12. Department of Medicine, Charite University, 10117 Berlin, Germany. 13. Department of Endocrinology, Diabetes and Metabolic Diseases, University Hospital of Bordeaux, 33000 Bordeaux, France. 14. Department of Endocrinology and. 15. Department of Biology and Pathology, University Hospital of Grenoble, 38700 La Tronche, France. 16. Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50121 Florence, Italy. 17. Department of Medicine, Endocrinology Unit, University of Padova, 35122 Padova, Italy. 18. Department of Endocrinology, Saint Denis Hospital, 93200 Saint Denis, France. 19. Department of Endocrinology, Brest University Hospital, 29200 Brest, France. 20. Department of Endocrinology, Groupe Hospitalier Pitié-Salpêtrière. 21. Department of Endocrinology, Regional Hospital of Orléans, 45770 Saran, France. 22. Department of Nuclear Medicine and Endocrine Oncology, Institut Gustave Roussy, 94800 Villejuif, France; and. 23. Hypertension Unit, Hôpital Européen Georges Pompidou and. 24. Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-Universität München, 80539 München, Germany. 25. Biostatistics and Epidemiology Unit, Hôtel Dieu, Assistance Publique-Hôpitaux de Paris, 75000 Paris, France.
Abstract
CONTEXT: Adrenocortical cancer (ACC) is an aggressive tumor with a heterogeneous outcome. Prognostic stratification is difficult even based on tumor stage and Ki67. Recently integrated genomics studies have demonstrated that CpG islands hypermethylation is correlated with poor survival. OBJECTIVE: The goal of this study was to confirm the prognostic value of CpG islands methylation on an independent cohort. DESIGN: Methylation was measured by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). SETTING: MS-MLPA was performed in a training cohort of 50 patients with ACC to identify the best set of probes correlating with disease-free survival (DFS) and overall survival (OS). These outcomes were validated in an independent cohort from 21 ENSAT centers. PATIENTS: The validation cohort included 203 patients (64% women, median age 50 years, 80% localized tumors). MAIN OUTCOME MEASURES: DFS and OS. RESULTS: In the training cohort, mean methylation of 4 genes (PAX5, GSTP1, PYCARD, PAX6) was the strongest methylation marker. In the validation cohort, methylation was a significant prognostic factor of DFS (P < 0.0001) and OS (P < 0.0001). Methylation, Ki67, and ENSAT stage were combined in multivariate models. For DFS, methylation (P = 0.0005) and stage (P < 0.0001) but not Ki67 (P = 0.19) remained highly significant. For OS, methylation (P = 0.0006), stage (P < 0.0001), and Ki67 (P = 0.024) were independent prognostic factors. CONCLUSIONS: Tumor DNA methylation emerges as an independent prognostic factor in ACC. MS-MLPA is readily compatible with clinical routine and should enhance our ability for prognostication and precision medicine.
CONTEXT: Adrenocortical cancer (ACC) is an aggressive tumor with a heterogeneous outcome. Prognostic stratification is difficult even based on tumor stage and Ki67. Recently integrated genomics studies have demonstrated that CpG islands hypermethylation is correlated with poor survival. OBJECTIVE: The goal of this study was to confirm the prognostic value of CpG islands methylation on an independent cohort. DESIGN: Methylation was measured by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). SETTING: MS-MLPA was performed in a training cohort of 50 patients with ACC to identify the best set of probes correlating with disease-free survival (DFS) and overall survival (OS). These outcomes were validated in an independent cohort from 21 ENSAT centers. PATIENTS: The validation cohort included 203 patients (64% women, median age 50 years, 80% localized tumors). MAIN OUTCOME MEASURES: DFS and OS. RESULTS: In the training cohort, mean methylation of 4 genes (PAX5, GSTP1, PYCARD, PAX6) was the strongest methylation marker. In the validation cohort, methylation was a significant prognostic factor of DFS (P < 0.0001) and OS (P < 0.0001). Methylation, Ki67, and ENSAT stage were combined in multivariate models. For DFS, methylation (P = 0.0005) and stage (P < 0.0001) but not Ki67 (P = 0.19) remained highly significant. For OS, methylation (P = 0.0006), stage (P < 0.0001), and Ki67 (P = 0.024) were independent prognostic factors. CONCLUSIONS: Tumor DNA methylation emerges as an independent prognostic factor in ACC. MS-MLPA is readily compatible with clinical routine and should enhance our ability for prognostication and precision medicine.
Authors: Dipika R Mohan; Antonio Marcondes Lerario; Tobias Else; Bhramar Mukherjee; Madson Q Almeida; Michelle Vinco; Juilee Rege; Beatriz M P Mariani; Maria Claudia N Zerbini; Berenice B Mendonca; Ana Claudia Latronico; Suely K N Marie; William E Rainey; Thomas J Giordano; Maria Candida B V Fragoso; Gary D Hammer Journal: Clin Cancer Res Date: 2019-02-15 Impact factor: 12.531
Authors: Mark Sherlock; Andrew Scarsbrook; Afroze Abbas; Sheila Fraser; Padiporn Limumpornpetch; Rosemary Dineen; Paul M Stewart Journal: Endocr Rev Date: 2020-12-01 Impact factor: 19.871