Multi-omics biomarker in adrenocortical carcinoma: a clinical-chemistry perspective.

Adrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor (incidence 0.7-2.0 per million per year) with a 5-year survival rate of less than 15% at the European Network for the Study of Adrenal Tumors stage IV. The standard diagnostic workup in clinical chemistry laboratories for the detection of functional tumors (serum cortisol, DHEAS, and 24 h urinary free cortisol) and the Weiss/Helsinki histological scoring system cannot detect non-functioning tumors, lacks a standardized approach for predicting prognosis, and does not have a validated minimal-residual-disease marker for postoperative monitoring. This narrative review evaluated 246 original research publications on four multi-omic layers in relation to clinical laboratories. Genomic and transcriptomic analyses, including TCGA-ACC pan-genomic profiling, revealed recurrent driver mutations and prognostic molecular subtypes that outperform the ENSAT staging. Tissue and circulating proteomic analyses identified HNRNPA1, KPNA2, SOAT1, and plasma AgRP as diagnostic and pharmacoproteomic targets. Urinary and serum steroid metabolomics (GC-MS and liquid chromatography-tandem mass spectrometry) validated in a 2017-patient prospective EURINE-ACT cohort provided clinically actionable diagnostic accuracy of over 85% and proved informative for post-surgical recurrence monitoring. Multi-omics classification consistently identifies two distinct biologically based subtypes with therapeutic implications. We also discuss the pre-analytical, analytical, and inter-laboratory standardization requirements that must be met before each biomarker layer can be translated to the clinical chemistry laboratory and advocate a multi-omic implementation strategy for ACC diagnosis, prognosis, and recurrence detection.