Endocrine Abstracts

Background: Cushing’s syndrome (CS) is associated with high morbidity and presents high interindividual variability. Easily measurable biomarkers, in addition to the hormone assays currently used for diagnosis, could better quantify the individual biological impact of glucocorticoids. The aim of this study is to identify such biomarkers through the analysis of whole blood transcriptome.Methods: Whole blood transcriptome was evaluated in 57 samples (...

Background: Adrenocortical cancer (ACC) is an aggressive tumor with heterogeneous prognosis. Previous genomic studies have demonstrated the importance of molecular classification for the prognostic assessment. Among molecular markers, transcriptome profiles “C1A” (steroid and proliferative signature) and “C1B” (immune signature) show the strongest association with outcome. However these markers are determined so far only from frozen tissue samples, sinc...

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...

Background: Bulk genomic studies have identified distinct molecular classes of adrenocortical tumors (ACT). Transcriptome profiles separate benign ACT (“C2” cluster) from carcinomas (ACC) and identify two groups of ACC, “C1A” (“steroid” and “proliferation” signatures) and “C1B” (“immune” signature), of poor and better prognosis respectively. However, these signatures were characterized at the tissue level (“bulk&...