OC02 - Using genomics to characterize features of aggressiveness in PitNETs

Background/Introduction 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. Purpose Identify genomic features associated with PitNET aggressiveness. Methods Nine features of aggressiveness were explored: tumor maximal diameter ≥ 40 mm, cavernous invasion, sphenoid invasion, Ki67 ≥ 10%, post-radiotherapy progression, rapid tumor progression speed, temozolomide resistance, metastasis, and disease- specific death. A cohort of 210 tumors, with or without these features, was analyzed by transcriptome, methylome, SNP array, and NGS sequencing. Transcriptome and methylome signatures of aggressiveness were established by linear regression stratified by lineage. Results In corticotroph tumors, Ki67 ≥ 10%, post-radiotherapy progression, rapid tumor progression speed, metastasis, and disease-specific death were associated with a transcriptome signature linked to proliferation. In mammo-thyro-somatotroph tumors, post-radiotherapy progression, rapid tumor progression speed, and disease-specific death were associated with a transcriptome signature linked to proliferation. These two transcriptome signatures were nevertheless different and specific to distinct phases of mitosis. Corticotroph and mammo-thyro-somatotroph tumors displayed a common methylome signature of aggressiveness linked to hypermethylation. Tumors accumulating features of aggressiveness were associated with pathogenic somatic variants, including TP53, DAXX, CDKN2A/B, MEN1 and PTEN. Conversely, tumors with USP8 and GNAS mutations were associated with less aggressive behavior, in the corticotroph and mammo-thyro-somatotroph lineages, respectively. Longitudinal omics samples highlighted genomic alterations already present in the earliest stages of tumor progression. The evolution of these alterations also revealed chromosomal rearrangements generating new aggressive clones. Consequently, the aggressiveness status of tumors can shift throughout the course of the disease. 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.