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Wang, Q. ; Sun, N. ; Meixner, R. ; Le Gleut, R. ; Kunzke, T. ; Feuchtinger, A. ; Wang, J. ; Shen, J. ; Kircher, S.* ; Dischinger, U.* ; Weigand, I.* ; Beuschlein, F.* ; Fassnacht, M.* ; Kroiss, M.* ; Walch, A.K.

Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes.

JCI insight 8:18 (2023)
DOI PMC
Creative Commons Lizenzvertrag
Open Access Gold möglich sobald Verlagsversion bei der ZB eingereicht worden ist.
Spatially resolved metabolomics enables the investigation of tumoral metabolites in situ. Inter- and intratumor heterogeneity are key factors associated with patient outcomes. Adrenocortical carcinoma (ACC) is an exceedingly rare tumor associated with poor survival. Its clinical prognosis is highly variable, but the contributions of tumor metabolic heterogeneity have not been investigated thus far to our knowledge. An in-depth understanding of tumor heterogeneity requires molecular feature-based identification of tumor subpopulations associated with tumor aggressiveness. Here, using spatial metabolomics by high-mass resolution MALDI Fourier transform ion cyclotron resonance mass spectrometry imaging, we assessed metabolic heterogeneity by de novo discovery of metabolic subpopulations and Simpson's diversity index. After identification of tumor subpopulations in 72 patients with ACC, we additionally performed a comparison with 25 tissue sections of normal adrenal cortex to identify their common and unique metabolic subpopulations. We observed variability of ACC tumor heterogeneity and correlation of high metabolic heterogeneity with worse clinical outcome. Moreover, we identified tumor subpopulations that served as independent prognostic factors and, furthermore, discovered 4 associated anticancer drug action pathways. Our research may facilitate comprehensive understanding of the biological implications of tumor subpopulations in ACC and showed that metabolic heterogeneity might impact chemotherapy.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Bioinformatics ; Cancer ; Metabolism ; Oncology; Imaging Mass-spectrometry; Intratumor Heterogeneity; Genomic Characterization; Cancer; Management; Chemotherapy; Multicenter; Mechanisms; Algorithm; Proposal
ISSN (print) / ISBN 2379-3708
e-ISSN 2379-3708
Zeitschrift JCI insight
Quellenangaben Band: 8, Heft: 16, Seiten: , Artikelnummer: 18 Supplement: ,
Verlag Clarivate
Verlagsort Ann Arbor, Michigan
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Research Unit Analytical Pathology (AAP)
CF Statistical Consulting (CF-STATCON)
Förderungen
University Hospital of Wuerzburg
Deutsche Krebshilfe
Deutsche Forschungsgemeinschaft
China Scholarship Council