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Meding, S. ; Nitsche, U.* ; Balluff, B. ; Elsner, M. ; Rauser, S. ; Schöne, C. ; Nipp, M. ; Maak, M.* ; Feith, M.* ; Ebert, M.P.* ; Friess, H.* ; Langer, R.* ; Höfler, H. ; Zitzelsberger, H. ; Rosenberg, R.* ; Walch, A.K.

Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging.

J. Proteome Res. 11, 1996-2003 (2012)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter proteomic classifier; tumor classification; proteomic classification; CUP classification; tumor diagnosis; MALDI imaging; MALDI-IMS; MALDI-MSI; imaging MS; GENE-EXPRESSION SIGNATURES; CHAIN-REACTION ASSAY; UNKNOWN PRIMARY CUP; MASS-SPECTROMETRY; BREAST-CANCER; MOLECULAR CLASSIFICATION; HEPATOCELLULAR-CARCINOMA; TISSUE; ADENOCARCINOMA; PATTERNS
Sprache
Veröffentlichungsjahr 2012
HGF-Berichtsjahr 2012
ISSN (print) / ISBN 1535-3893
e-ISSN 1535-3907
Zeitschrift Journal of Proteome Research
Quellenangaben Band: 11, Heft: 3, Seiten: 1996-2003 Artikelnummer: , Supplement: ,
Verlag American Chemical Society (ACS)
Begutachtungsstatus Peer reviewed
Institut(e) Research Unit Analytical Pathology (AAP)
Institute of Pathology (PATH)
Translational Metabolic Oncology (IDC-TMO)
POF Topic(s) 30205 - Bioengineering and Digital Health
30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
30203 - Molecular Targets and Therapies
Forschungsfeld(er) Enabling and Novel Technologies
Radiation Sciences
PSP-Element(e) G-500390-001
G-500300-001
G-501000-001
PubMed ID 22224404
DOI 10.1021/pr200784p
WOS ID WOS:000300916200052
Scopus ID 84857824513
Erfassungsdatum 2012-04-20
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