PuSH - Publication Server of Helmholtz Zentrum München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Abdelmoula, W.M.* ; Balluff, B.* ; Englert, S. ; Dijkstra, J.* ; Reinders, M.J.T.* ; Walch, A.K. ; McDonnell, L.A.* ; Lelieveldt, B.P.F.*

Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data.

Proc. Natl. Acad. Sci. U.S.A. 113, 12244-12249 (2016)
Publ. Version/Full Text Research data DOI PMC
Open Access Gold
The identification of tumor subpopulations that adversely affect patient outcomes is essential for a more targeted investigation into how tumors develop detrimental phenotypes, as well as for personalized therapy. Mass spectrometry imaging has demonstrated the ability to uncover molecular intratumor heterogeneity. The challenge has been to conduct an objective analysis of the resulting data to identify those tumor subpopulations that affect patient outcome. Here we introduce spatially mapped t-distributed stochastic neighbor embedding (t-SNE), a nonlinear visualization of the data that is able to better resolve the biomolecular intratumor heterogeneity. In an unbiased manner, t-SNE can uncover tumor subpopulations that are statistically linked to patient survival in gastric cancer and metastasis status in primary tumors of breast cancer.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
9.423
2.565
63
100
Tags
Annotations
Special Publikation
Hide on homepage

Edit extra information
Edit own tags
Private
Edit own annotation
Private
Hide on publication lists
on hompage
Mark as special
publikation
Publication type Article: Journal article
Document type Scientific Article
Keywords intratumor heterogeneity; mass spectrometry imaging; t-SNE; biomarker; cancer; Intratumor Heterogeneity; Clonal Evolution; Cancer; Visualization; Challenges; Expression; Brain
Language
Publication Year 2016
HGF-reported in Year 2016
ISSN (print) / ISBN 0027-8424
e-ISSN 1091-6490
Journal Proceedings of the National Academy of Sciences of the United States of America
Quellenangaben Volume: 113, Issue: 43, Pages: 12244-12249 Article Number: , Supplement: ,
Publisher National Academy of Sciences
Publishing Place Washington
Reviewing status Peer reviewed
Institute(s) Research Unit Analytical Pathology (AAP)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-500390-001
DOI 10.1073/pnas.1510227113
WOS ID WOS:000386087100073
PubMed ID 27791011
Erfassungsdatum 2016-11-04
[➜Report correction]