A differentiation-based phylogeny of cancer subtypes.
Histopathological classification of human tumors relies in part on the degree of differentiation of the tumor sample. To date, there is no objective systematic method to categorize tumor subtypes by maturation. In this paper, we introduce a novel computational algorithm to rank tumor subtypes according to the dissimilarity of their gene expression from that of stem cells and fully differentiated tissue, and thereby construct a phylogenetic tree of cancer. We validate our methodology with expression data of leukemia, breast cancer and liposarcoma subtypes and then apply it to a broader group of sarcomas. This ranking of tumor subtypes resulting from the application of our methodology allows the identification of genes correlated with differentiation and may help to identify novel therapeutic targets. Our algorithm represents the first phylogeny-based tool to analyze the differentiation status of human tumors.
Riester
Markus
M
Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
Stephan-Otto Attolini
Camille
C
Downey
Robert J
RJ
Singer
Samuel
S
Michor
Franziska
F
D050156:Adipogenesis / Q000235:genetics; D000465:Algorithms; D000704:Analysis of Variance; D002454:Cell Differentiation / Q000502:physiology; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D009369:Neoplasms / Q000145:classification / Q000235:genetics* / Q000473:pathology; D010802:Phylogeny
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