EYES2023 ESE Young Endocrinologists and Scientists (EYES) 2023 Oral communication 4: Pituitary and Neuroendocrinology (8 abstracts)
Transcriptome in paraffin samples for the diagnosis and prognosis of pituitary neuroendocrine tumors (PITNETS)
Nesrine Benanteur 1 , Chiara Villa 2 , Maria Francesca Birtolo 1 , Anne Jouinot 1 , Daniel De Murat 1 , Franck Letourneur 3 , Stephan Gaillard 4 , Marie-Laure Raffin-Sanson 5 , Jean-François Emile 6 , Jérôme Bertherat 3 , Bertrand Baussard 7 & Guillaume Assié 3
1Institut Cochin U1016 Inserm/Cnrs/Umr-S8104 – Université de Paris, Team ‘Genomics and Signaling of Endocrine Tumors’, Paris, France; 2Département de Neuropathologie de la Pitié Salpêtrière Hôpital de la Pitié-Salpêtrière (Assistance Publique des Hopitaux de Paris), Institut Cochin U1016 Inserm/Cnrs/Umr-S8104 – Université de Paris, Paris, France; 3Institut Cochin U1016 Inserm/Cnrs/Umr-S8104 – Université de Paris, Paris, France; 4Département de Neurochirurgie – Hôpital de la Pitié-Salpêtrière (Assitance Publique des Hopitaux de Paris), Paris, France; 5Département D’endocrinologie, Hôpital Ambroise Paré (Assistance Publique des Hopitaux de Paris), Paris, France; 6Anatomie Pathologie, Hôpital Ambroise Paré (Assistance Publique des Hôpitaux de Paris), Boulogne Billancourt, France; 7Département de Neurochirurgie – Hôpital de la Pitié-Salpêtrière (Assitance Publique des Hopitaux de Paris), Institut Cochin U1016 Inserm/Cnrs/Umr-S8104 – Université de Paris, Paris, France.
An initial multi-omics analysis of PitNETs has refined histological classifications, and could improve diagnostic and prognostic assessment (Neou, Cancer Cell 2020). Of all omics, transcriptome best discriminates between these different classes. This molecular classification has been built upon frozen samples, which are difficult to use in routine clinical practice.
Aim: Demonstrate the feasibility of measuring the transcriptome in Formalin-Fixed Paraffin-Embedded (FFPE) samples using 3’ end RNA sequencing.
Methods: RNA extraction was performed on 198 PitNETs FFPE samples (RNEasy DSP FFPE kits, Qiagen) operated between 2005 and 2022. 3′ transcriptome was sequenced using the 3′RNASeq technique (Lexogen, Illumina). After alignment, counting (STAR), normalization (DESeq2) and dimension reduction (NMF), unsupervised clustering was performed.
Results: The proportion of informative samples reached 98%. The average sequencing depth was 11 million transcripts. With these FFPE samples, we find the clustering established on frozen samples and reflecting lineage, with the different subgroups of corticotroph tumors, prolactinomas, somatotroph tumors mixed with ‘Mixed GH-PRL’ tumors, gonadotroph tumors mixed with ‘null-cell’ and thyrotroph tumors. The molecular group can be predicted individually from this transcriptome.
Conclusion: The molecular classification of PitNETs can be predicted from FFPE samples. This opens up the prospect of larger cohorts, enabling prognostic assessment of the transcriptome, stratifying by subtype.
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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