Tumorigenesis requires the re-organization of metabolism to support malignant proliferation. We examine how the altered metabolism of cancer cells is reflected in the rewiring of co-expression patterns among metabolic genes. Focusing on breast and clear-cell kidney tumors, we report the existence of key metabolic genes which act as hubs of differential coexpression, showing significantly different co-regulation patterns between normal and tumor states. We compare our findings to those from classical differential expression analysis, and counterintuitively observe that the extent of a gene's differential co-expression only weakly correlates with its differential expression, suggesting that the two measures probe different features of metabolism. Focusing on this discrepancy, we use changes in co-expression patterns to highlight the apparent loss of regulation by the transcription factor HNF4A in clear cell renal cell carcinoma, despite no differential expression of HNF4A. Finally, we aggregate the results of differential co-expression analysis into a Pan-Cancer analysis across seven distinct cancer types to identify pairs of metabolic genes which may be recurrently dysregulated. Among our results is a cluster of four genes, all components of the mitochondrial electron transport chain, which show significant loss of co-expression in tumor tissue, pointing to potential mitochondrial dysfunction in these tumor types.
Author SummaryThe metabolism of malignant tumors is deranged. The transition from healthy to cancerous state involves, among other factors, the transcriptional coordination of genes spread throughout the cell's metabolic pathways. An examination of this multivariate regulatory effort can offer insights which may remain hidden from analyses focusing on a single gene in isolation. Such an analysis is particularly relevant for metabolic networks, whose constituent enzymes are fundamentally linked through their common utilization of a limited pool of substrates. Here, we examine the extent to which altered metabolism is reflected in the co-expression patterns of genes, shedding light on the differential regulation of metabolic genes within tumors. We study patterns of differential co-expression across metabolic pathways in both breast and kidney tumors, and integrate regulatory information to study the drivers of these changes. Among the results of our analysis is the apparent PLOS Computational Biology |