Home
Deutsch
Advanced Search
Browse by ...
Publication overview
Contact persons
Help
Publ. Version/Full Text
DOI
PMC
 |
Open Access Gold |
|
as soon as is submitted to ZB.
Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes.
JCI insight 8:18 (2023)
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.
Altmetric
Additional Metrics?
Edit extra informations
Login
Publication type
Article: Journal article
Document type
Scientific Article
Keywords
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
Journal
JCI insight
Quellenangaben
Volume: 8,
Issue: 16,
Article Number: 18
Publisher
Clarivate
Publishing Place
Ann Arbor, Michigan
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Research Unit Analytical Pathology (AAP)
CF Statistical Consulting (CF-STATCON)
CF Statistical Consulting (CF-STATCON)
Grants
University Hospital of Wuerzburg
Deutsche Krebshilfe
Deutsche Forschungsgemeinschaft
China Scholarship Council
University Hospital of Wuerzburg
Deutsche Krebshilfe
Deutsche Forschungsgemeinschaft
China Scholarship Council