Computer Science Department
School of Computer Science, Carnegie Mellon University
Cancer Phylogenetics from Single-Cell Assays
Gregory Pennington, Stanley Shackney*, Russell Schwartz**
Keywords: Computational biology, cancer, FISH, phylogeny
In the field of cancer biology, there is currently great interest in
the development of "targeted therapeutics" that attack specific
molecular abnormalities characterizing subsets of cancers.
Computational methods have been essential in identifying subsets
of tumors sharing a common molecular mechanism, making it possible
to identify meaningful groupings for targeted therapy. To date,
such approaches have been limited in their ability to infer the
specific sequences of molecular changes, or progression pathways,
by which a tumor forms and increases in aggressiveness. In the
present work, we develop computational methods for inferring
progression pathways from cell-bycell assays. Our methods bypass
important limitations of the current approaches by recognizing and
taking advantage of tumor heterogeneity. We define a model for tumor
progression and introduce a procedure for cancer phylogenetics based
on the inference of likely progression pathways in individual patients.
This procedure is formulated as a set of easily tractable graph problems.
We demonstrate the methods on a set of fluorescence in situ hybridization
(FISH) assays, which measure gene and chromosome gain and loss from
a collection of fifty tumor samples. The results are consistent with
prior knowledge about the role of the genes examined in cancer
progression, and they suggest additional features of progression
pathways involving the genes studied.
*Allegheny Singer Research Institute, Allegheny General Hospital, Pittsburgh,
**Department of Biological Sciences, Carnegie Mellon University, Pittsburgh