A molecular map of mesenchymal tumors.
BACKGROUND
Bone and soft tissue tumors represent a diverse group of neoplasms thought to derive from cells of the mesenchyme or neural crest. Histological diagnosis is challenging due to the poor or heterogenous differentiation of many tumors, resulting in uncertainty over prognosis and appropriate therapy.


RESULTS
We have undertaken a broad and comprehensive study of the gene expression profile of 96 tumors with representatives of all mesenchymal tissues, including several problem diagnostic groups. Using machine learning methods adapted to this problem we identify molecular fingerprints for most tumors, which are pathognomonic (decisive) and biologically revealing.


CONCLUSIONS
We demonstrate the utility of gene expression profiles and machine learning for a complex clinical problem, and identify putative origins for certain mesenchymal tumors.
Henderson
Stephen R
SR
Cancer Research UK, Viral Oncology Group, Wolfson Institute for Biomedical Research, Gower Street, University College London, London, WC1E 6BT, UK. s.henderson@ucl.ac.uk
Guiliano
David
D
Presneau
Nadege
N
McLean
Sean
S
Frow
Richard
R
Vujovic
Sonja
S
Anderson
John
J
Sebire
Neil
N
Whelan
Jeremy
J
Athanasou
Nick
N
Flanagan
Adrienne M
AM
Boshoff
Chris
C
D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D052138:Genes, Neoplasm / Q000235:genetics; D006801:Humans; D008648:Mesoderm / Q000378:metabolism*; D008954:Models, Biological; D018204:Neoplasms, Connective and Soft Tissue / Q000175:diagnosis / Q000235:genetics*