Mathematical tree models for cytogenetic development in solid tumors.
We present a new approach for modeling the occurrence of genetic changes in human tumors over time. In solid tumors, data on genetic alterations are usually only available at a single point in time, allowing no direct insight into the sequential order of genetic events. In our approach, genetic tumor development and progression is assumed to follow a probabilistic tree model. We use maximum likelihood estimation to reconstruct a tree model for the genetic evolution of a given tumor type. The use of the proposed method is illustrated by an application to cytogenetic data from 173 cases of clear cell renal cell carcinoma, which results in a model for the karyotypic evolution of this tumor.
von Heydebreck
A
A
Max-Planck-Institut für Molekulare Genetik, Abt Computational Molecular Biology, Berlin.
Gunawan
B
B
Huber
W
W
Vingron
M
M
Füzesi
L
L
D002292:Carcinoma, Renal Cell / Q000235:genetics / Q000473:pathology; D002869:Chromosome Aberrations; D020732:Cytogenetic Analysis; D003663:Decision Trees; D006801:Humans; D007680:Kidney Neoplasms / Q000235:genetics / Q000473:pathology; D016013:Likelihood Functions; D008957:Models, Genetic; D009369:Neoplasms / Q000235:genetics* / Q000473:pathology*