Using genomics to characterize features of aggressiveness in PitNETs

Nesrine Benanteur; Chiara Villa; Murat Daniel De; Birtolo Maria Francesca; Fabio Bioletto; Victor Gravrand; Anne Jouinot; Franck Letourneur; Planchon Julien Masliah; Hage Mirella; Jean-Francois Emile; Jerome Bertherat; Bertrand Baussart; Guillaume Assie

doi:10.1530/endoabs.110.P825

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Endocrine Abstracts (2025) 110 P825 | DOI: 10.1530/endoabs.110.P825

ECEESPE2025 Poster Presentations Pituitary, Neuroendocrinology and Puberty (162 abstracts)

Using genomics to characterize features of aggressiveness in PitNETs

Nesrine Benanteur ¹ , Chiara Villa ^1,2 , Daniel De Murat ¹ , Maria Francesca Birtolo ^1,3 , Fabio Bioletto ^1,4 , Victor Gravrand ¹ , Anne Jouinot ¹ , Franck Letourneur ⁵ , Julien Masliah Planchon ⁶ , Hage Mirella ⁷ , Jean-François Emile ⁸ , Jérôme Bertherat ^1,9 , Bertrand Baussart ^1,10 & Guillaume Assié ^1,9

Author affiliations

¹Genomics and signaling of endocrine tumors, Institut Cochin (INSERM U1016 - CNRS UMR 8104), Université Paris Cité, Paris, France; ²Department of Pathology, Hôpital Lariboisière, APHP, Paris, France; ³Department of endocrinology and diabetology, Humanitas Research Hospital, Milan, Italy; ⁴Department of medical sciences, University of Turin, Turin, Italy; ⁵GENOM’IC, Institut Cochin, INSERM U1016, CNRS UMR 8104, Université Paris Cité, Paris, France; ⁶Genetics department, Institut Curie, Paris, France; ⁷Department of Endocrinology, Hôpital Ambroise Paré, APHP, Boulogne Billancourt, France; ⁸Department of Pathology, Hôpital Ambroise Paré, APHP, Boulogne Billancourt, France; ⁹Department of Endocrinology, Hôpital Cochin, APHP, Paris, France; ¹⁰Department of Neurosurgery, Hôpital Lariboisière, APHP, Paris, France

JOINT1671

PitNETs aggressiveness is currently assessed based on clinical and histological criteria, leading to regularly updated classifications. The role of molecular criteria has yet to be defined. Multi-omics analyses show the importance of lineage as the main driver of unsupervised classifications. Aggressive PitNETs appear to be scattered according to their lineage without forming a distinct molecular group.

Aim: Identify genomic features associated with PitNETs aggressiveness.

Methods: • Five features of aggressiveness were explored: post radiotherapy progression, rapid tumor progression speed, Ki67≽10%, cavernous invasion and sphenoid invasion. A cohort of 155 tumors with or without these features were analysed by transcriptome, methylome, SNP array and NGS sequencing.

• Transcriptome and methylome signatures associated with features of aggressiveness were established by logistic regression stratified by lineage.

• Response to temozolomide was evaluated on 17 samples collected before temozolomide treatment, following RECIST criteria. Transcriptome signatures of temozolomide response were assessed with a differential gene expression analysis.

Results: Post radiotherapy progression, rapid tumor progression speed, and Ki67≽10% were associated with distinct transcriptome signatures linked to RNA metabolism in TPIT lineage, and to proliferation and cell motility in PIT-1 lineage. Post radiotherapy progression and rapid progression speed were associated with tumor hypermethylation. The latter was not associated with any specific location related to gene structures. Post radiotherapy progression, rapid tumor progression speed, and Ki67≽10% were associated with a group of tumors cumulating pathogenic somatic variants, including TP53, CDKN2A/B, DAXX, MEN1, and PTEN. Reversely, USP8 and GNAS mutations weren’t associated with any feature of aggressiveness, in TPIT and in PIT1 lineages, respectively. Cavernous and sphenoid invasion were not associated with any molecular signature. Response to temozolomide was associated with a leukocyte migration and differentiation transcriptome signature. O-6-methylguanine-DNA methyltransferase gene (MGMT), which promoter methylation and expression was proved to be predictive of temozolomide response in gliomas, was found underexpressed in responders compared to non-responders through transcriptome analysis. Longitudinal samples omics highlight genomic alterations already present in the earliest samples of tumor progressions. Alteration evolution also shows chromosomal rearrangements generating new aggressive clones.

Conclusion: PitNETs accumulating features of aggressiveness are associated with specific genomic markers. The prognostic value of these potential markers remains to be confirmed in an independent cohort.