Phylogenetic modeling of heterogeneous gene-expression microarray data from cancerous specimens

Abstract

The qualitative dimension of gene expression data and its heterogeneous nature in cancerous specimens can be accounted for by phylogenetic modeling that incorporates the directionality of altered gene expressions, complex patterns of expressions among a group of specimens, and data-based rather than specimen-based gene linkage. Our phylogenetic modeling approach is a double algorithmic technique that includes polarity assessment that brings out the qualitative value of the data, followed by maximum parsimony analysis that is most suitable for the data heterogeneity of cancer gene expression. We demonstrate that polarity assessment of expression values into derived and ancestral states, via outgroup comparison, reduces experimental noise; reveals dichotomously expressed asynchronous genes; and allows data pooling as well as comparability of intra- and interplatforms. Parsimony phylogenetic analysis of the polarized values produces a multidimensional classification of specimens into clades that reveal shared derived gene expressions (the synapomorphies); provides better assessment of ontogenic pathways and phyletic relatedness of specimens; efficiently utilizes dichotomously expressed genes; produces highly predictive class recognition; illustrates gene linkage and multiple developmental pathways; provides higher concordance between gene lists; and projects the direction of change among specimens. Further implication of this phylogenetic approach is that it may transform microarray into diagnostic, prognostic, and predictive tool.

FIG. 1.

A cladogram of a parsimony phylogenetic analysis of microarray gene-expression data representing normal myometrium (n = 4), leiomyoma (n = 7), leiomyosarcoma (n = 9), and extrauterine leiomyosarcoma (n = 4) specimens. The leiomyomas and leiomyosarcomas form a clade defined by 32 synapomorphies (Table 1). The leiomyosarcoma specimens form a terminal clade that is circumscribed by 20 synapomorphies (Table 3). Asterisk (*) denotes extrauterine leiomyosarcomas.

FIG. 2.

A cladogram of a parsimony phylogenetic analysis of gastric cancer and noncancerous specimens. It shows a clade delineated by 34 synapomorphies (Table 6)encompassing all cancer specimens.

FIG. 3.

A cladogram representing a comparability analysis of the gastric (GDS1210) and uterine (GDS533) datasets. The polarized matrices of the two datasets were pooled together and processed by the parsimony phylogenetic algorithm, MIX. Each of the cancers (gastric and leiomyosarcoma) forms its own clade, and the inclusive clade encompassing the two cancers and leiomyomas is delimited by a set of synapomorphies (Table 9).