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  Spatial characterization and stratification of colorectal adenomas by deep visual proteomics

Kabatnik, S., Post, F., Drici, L., Bartels, A. S., Strauss, M. T., Zheng, X., et al. (2024). Spatial characterization and stratification of colorectal adenomas by deep visual proteomics. iScience, 27(9): 110620. doi:10.1016/j.isci.2024.110620.

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Genre: Zeitschriftenartikel

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 Urheber:
Kabatnik, Sonja, Autor
Post, Frederik, Autor
Drici, Lylia, Autor
Bartels, Annette Snejbjerg, Autor
Strauss, M. T., Autor
Zheng, Xiang, Autor
Madsen, Gunvor I., Autor
Mund, Andreas, Autor
Rosenberger, Florian A.1, Autor           
Moreira, Jose, Autor
Mann, Matthias1, Autor           
Affiliations:
1Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              

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Schlagwörter: CDX2 HOMEOBOX GENE; SUBSTRATE MARCKS; STEM-CELLS; IN-VITRO; EXPRESSION; CANCER; COLON; DIFFERENTIATION; PROTEIN; HETEROGENEITYScience & Technology - Other Topics;
 Zusammenfassung: Colorectal adenomas (CRAs) are potential precursor lesions to adenocarcinomas, currently classified by morphological features. We aimed to establish a molecular feature-based risk allocation framework toward improved patient stratification. Deep visual proteomics (DVP) is an approach that combines image-based artificial intelligence with automated microdissection and ultra-high sensitive mass spectrometry. Here, we used DVP on formalin-fixed, paraffin-embedded (FFPE) CRA tissues from nine male patients, immunohistologically stained for caudal-type homeobox 2 (CDX2), a protein implicated in colorectal cancer, enabling the characterization of cellular heterogeneity within distinct tissue regions and across patients. DVP identified DMBT1, MARCKS, and CD99 as protein markers linked to recurrence, suggesting their potential for risk assessment. It also detected a metabolic shift to anaerobic glycolysis in cells with high CDX2 expression. Our findings underscore the potential of spatial proteomics to refine early stage detection and contribute to personalized patient management strategies and provided novel insights into metabolic reprogramming.

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Sprache(n): eng - English
 Datum: 2024-09-20
 Publikationsstatus: Erschienen
 Seiten: 19
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISI: 001298341400001
DOI: 10.1016/j.isci.2024.110620
 Art des Abschluß: -

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Titel: iScience
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Amsterdam ; Bosten ; London ; New York ; Oxford ; Paris ; Philadelphia ; San Diego ; St. Louis : Elsevier
Seiten: - Band / Heft: 27 (9) Artikelnummer: 110620 Start- / Endseite: - Identifikator: ISSN: 2589-0042
CoNE: https://pure.mpg.de/cone/journals/resource/2589-0042