ECEESPE2025 Oral Communications Oral Communications 1: Adrenal and Cardiovascular Endocrinology (6 abstracts)
Quantitative proteomics of pediatric adrenocortical tumors reveals a continuum of molecular alterations and identifies prognostically relevant subgroups
Andreas Metousis 1 , Victoria Fincke 2 , Stefan Wudy 3 , Joern Pons-Kuehnemann 3 , Marina Kunstreich 2 , Eva Jüttner 4 , Pascal Johann 2 , Antje Redlich 5 , Lisa Schweizer 1 , Matthias Mann 1 , Rainer Claus 2 & Michaela Kuhlen 2
1Max Planck Institute of Biochemistry, Planegg, Germany; 2University of Augsburg, Pediatrics and Adolescent Medicine, Augsburg, Germany; 3Justus Liebig University Giessen, Giessen, Germany; 4University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany; 5Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
JOINT1209
Introduction: Pediatric adrenocortical tumors (pACTs), comprising highly malignant carcinomas (pACCs) and less aggressive adenomas (pACAs), pose significant diagnostic and therapeutic challenges due to their molecular heterogeneity and variable clinical outcomes. In this study, we performed an extensive quantitative proteomic analysis of pACTs and matched normal adrenal tissue to delineate molecular alterations, identify deregulated proteins and pathways, and define novel prognostically relevant subgroups.
Methods: Bulk proteomes were extracted from 85 pACTs and 43 matched normal adrenal samples, macrodissected from H&E-stained sections. Following protein extraction, lysis, and enzymatic digestion, the samples were analyzed on a Thermo Orbitrap Astral mass spectrometer coupled to an Evosep One LC system operating at 60 samples per day. The resulting data were log2 transformed and Z-score normalized prior to further analysis.
Results: A total of 10,714 proteins were quantitatively identified. Protein counts were robust, with tumor samples yielding a median of 8,246 proteins (range: 7,312–8,806) and normal samples a median of 7,497 proteins (range: 4,128–8,578). Unsupervised hierarchical clustering and principal component analysis (PCA) effectively separated normal from tumor samples, yet revealed a proteomic continuum between these states. Notably, traditional histological subtypes (ACA, ACC, and ACX) did not segregate into distinct clusters in PCA or clustering analyses. Differential expression analysis identified approximately 3,400 significantly regulated proteins, with roughly four times more downregulated (2,766) than upregulated (628) in pACTs. Key steroidogenic enzymes such as 3β-hydroxysteroid dehydrogenase were consistently downregulated, supporting a common origin in the adrenal cortex’s zona reticularis. Among the top hits were IGF2, CCNE, and SGCG, with significant enrichment of proteins involved in the IGFR signaling and β-catenin pathways. Further dimensionality reduction using PCA and UMAP followed by k-means clustering delineated four distinct tumor clusters (comprising 17, 25, 13, and 30 samples, respectively) that differed in protein signature enrichment, gene ontology profiles, and prognostic outcomes. Moreover, samples of these clusters grouped together in a pseudotime analysis, suggesting a cancer development–associated transition between the clusters.
Conclusions: Our high-sensitivity mass spectrometry approach enables an in-depth proteomic characterization of pACTs, uncovering a continuum of molecular alterations from normal to tumor tissue and identifying novel molecular subgroups with distinct prognostic implications. These findings advance our understanding of pACT pathophysiology and pave the way for refined diagnostic stratification and targeted therapeutic interventions.
Volume 110
Article tools
My recent searches
My recently viewed abstracts
Authors
Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
© Bioscientifica 2025 |
Privacy policy |
Cookie settings
BiosciAbstracts
Bioscientifica Abstracts is the gateway to a series of products that provide a permanent, citable record of abstracts for biomedical and life science conferences.
Find out more