Statistical analysis of the cancer cell's molecular entropy using high-throughput data.

Abstract

As cancer progresses, DNA copy number aberrations accumulate and the genomic entropy (chromosomal disorganization) increases. For this surge to have any oncogenetic effect, it should (to some extent) be reflected at other molecular levels of the cancer cell, in particular that of the transcriptome. Such a coincidence of cancer progression and the propagation of an entropy increase through the molecular levels of the cancer cell would enhance the understanding of cancer evolution. A statistical argument reveals that (under some assumptions) an entropy increase in one random variable (DNA copy number) leads to an entropy increase in another (gene expression). Statistical methodology is provided to investigate the relation between the genomic and transcriptomic entropy using high-throughput data. Analyses of multiple high-throughput datasets using this methodology show a close, concordant relation among the genomic and transcriptomic entropy. Hence, as cancer evolves, and the genomic entropy increases, the transcriptomic entropy is also expected to surge.