Pathway analysis methods are frequently applied to cancer gene expression data to
identify dysregulated pathways. These methods often infer pathway activity based on
the expression of genes belonging to a given pathway, even though the proteins ultimately
determine the activity of a given pathway. Furthermore, the association between gene
expression levels and protein activities is not well-characterized. Here, we posit
that pathway-based methods are effective not because of the correlation between expression
and activity of members of a given pathway, but because pathway gene sets overlap
with the genes regulated by transcription factors (TFs). Thus, pathway-based methods
do not inform about the activity of the pathway of interest but rather reflect changes
in TF activities.
