Transcriptome in paraffin samples for the diagnosis and prognosis of adrenocortical carcinoma.

f Endocrinology A Jouinot and others FFPE transcriptome for the 186:6 607–617 diagnosis and prognosis of ACC Transcriptome in paraffin samples for the diagnosis and prognosis of adrenocortical carcinoma Anne Jouinot 1,2,3, Juliane Lippert4, Mathilde Sibony1,5, Florian Violon1,5, Lindsay Jeanpierre1,5, Daniel De Murat1, Roberta Armignacco1, Amandine Septier1, Karine Perlemoine1, Franck Letourneur1, Brigitte Izac1, Bruno Ragazzon1, Karen Leroy6, Eric Pasmant 6, Marie-Odile North6, Sébastien Gaujoux1,7, Bertrand Dousset1,7, Lionel Groussin1,2, Rossella Libe1,2, Benoit Terris5, Martin Fassnacht 4, Cristina L Ronchi 4,8,9, Jérôme Bertherat1,2 and Guillaume Assie1,2 1Université de Paris, Institut Cochin, INSERM U-1016, CNRS UMR-8104, Paris, France, 2Endocrinology, AP-HP Hôpital Cochin, Paris, France, 3Institut Curie, INSERM U900, MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Paris, France, 4Division of Endocrinology and Diabetes, Department of Internal Medicine I, University Hospital, University of Wuerzburg, Wuerzburg, Germany, 5Pathology, 6Genetics and Molecular Biology, 7Digestive and Endocrine Surgery, AP-HP Hôpital Cochin, Paris, France, 8Institute of Metabolism and System Research, University of Birmingham, Birmingham, UK, and 9Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK Abstract Design: Molecular classification is important for the diagnosis and prognosis of adrenocortical tumors (ACT). Transcriptome profiles separate adrenocortical adenomas ‘C2’ from carcinomas, and identify two groups of carcinomas ‘C1A’ and ‘C1B’, of poor and better prognosis respectively. However, many ACT cannot be profiled because of improper or absent freezing procedures, a mandatory requirement so far. The main aim was to determine transcriptome profiles on formalin-fixed paraffin-embedded (FFPE) samples, using the new 3’-end RNA-sequencing technology. A secondary aim was to demonstrate the ability of this technique to explore large FFPE archives, by focusing on the rare oncocytic ACT variants. Methods: We included 131 ACT: a training cohort from Cochin hospital and an independent validation cohort from Wuerzburg hospital. The 3’ transcriptome was generated from FFPE samples using QuantSeq (Lexogen, Vienna, Austria) and NextSeq500 (Illumina, San Diego, CA, USA). Results: In the training cohort, unsupervised clustering identified three groups: ‘C1A’ aggressive carcinomas (n = 28, 29%), ‘C1B’ more indolent carcinomas (n = 28, 29%), and ‘C2’ adenomas (n = 39, 41%). The prognostic value of FFPE transcriptome was confirmed in the validation cohort (5-year OS: 26% in ‘C1A’ (n = 26) and 100% in ‘C1B’ (n = 10), P  = 0.003). FFPE transcriptome was an independent prognostic factor in a multivariable model including tumor stage and Ki-67 (OS HR: 7.5, P  = 0.01). Oncocytic ACT (n = 19) did not form any specific cluster. Oncocytic carcinomas (n = 6) and oncocytic ACT of uncertain malignant potential (n = 4) were all in ‘C1B’. Conclusions: The 3’ RNA-sequencing represents a convenient solution for determining ACT molecular class from FFPE samples. This technique should facilitate routine use and large retrospective studies. [ABSTRACT FROM AUTHOR]