Adipose tissue pathways involved in weight loss of cancer cachexia

Abstract

Background: The regulatory gene pathways that accompany loss of adipose tissue in cancer cachexia are unknown and were explored using pangenomic transcriptome profiling.

Methods: Global gene expression profiles of abdominal subcutaneous adipose tissue were studied in gastrointestinal cancer patients with (n=13) or without (n=14) cachexia.

Results: Cachexia was accompanied by preferential loss of adipose tissue and decreased fat cell volume, but not number. Adipose tissue pathways regulating energy turnover were upregulated, whereas genes in pathways related to cell and tissue structure (cellular adhesion, extracellular matrix and actin cytoskeleton) were downregulated in cachectic patients. Transcriptional response elements for hepatic nuclear factor-4 (HNF4) were overrepresented in the promoters of extracellular matrix and adhesion molecule genes, and adipose HNF4 mRNA was downregulated in cachexia.

Conclusions: Cancer cachexia is characterised by preferential loss of adipose tissue; muscle mass is less affected. Loss of adipose tissue is secondary to a decrease in adipocyte lipid content and associates with changes in the expression of genes that regulate energy turnover, cytoskeleton and extracellular matrix, which suggest high tissue remodelling. Changes in gene expression in cachexia are reciprocal to those observed in obesity, suggesting that regulation of fat mass at least partly corresponds to two sides of the same coin.

Figure 1

Functional profiling depicts significantly overrepresented KEGG pathways on the basis of differentially expressed genes in cachexia vs weight-stable patients. Using the FunNet tool, functional profiling was performed using an FDR of 5%. Only genes that have at least one annotation in KEGG were analysed. Of the 61 upregulated genes, 35 were annotated. Of the 364 downregulated genes, 92 were annotated. The number of genes associated with each significant pathway is indicated in relation to the total number of annotated genes in our lists of differentially expressed genes. Transcriptional domain coverage indicates the most significant biological functions that are represented among annotated genes, ranked by percentage.