A common denominator of inflammations and fatty liver

Stephan Herzig, head of the Emmy Noether and Marie Curie Junior Research Group “Molecular Metabolic Control” at DKFZ, and his co-workers have focused on the other end of the signaling chain: They studied liver cells of tumor-bearing mice showing signs of severe cancer cachexia. In particular, they searched for a molecule called RIP140, previously identified by Herzig as a regulator suppressing fat breakdown in the livers of healthy mice. Indeed, the investigators found a high activity of RIP140 in the cancerous mice and, accordingly, signs of fatty liver in these animals. When Herzig specifically switched off this molecule in the liver cells of tumor-bearing mice, the lipid balance of the liver normalized within a few days. The researchers have now published their results in Hepatology.

Apart from fatty liver, highly active immune cells are another characteristic of wasting in tumor patients: Increased levels of macrophages invade fatty or liver tissue and release messaging substances such as interleukin-6 and tumor necrosis factor-alpha. The result is an inflammatory response in these organs, which eventually contributes to a disruption of metabolism and loss of energy in affected patients. Collaboration partners of Stephan Herzig in London have bred mice that completely lack the RIP140 molecule. These animals are lean and stay lean, even on a rich diet. When the researchers in Herzig’s group compared these animals to normal mice, they also found that their macrophages release only small amounts of proinflammatory messaging substances. The RIP140 molecule in these inflammatory cells exercises its effect through another “master regulator”: the NFkB transcription factor. These results have just been published in Blood.

“Thus we have put another small link into the long unknown signaling chain from tumor to tumor cachexia,” says Stephan Herzig, characterizing the relevance of his two papers. “Now, of course, we will search for the activator of RIP140,” Herzig explains. “Thus, we will proceed from one link to the next until we arrive at the tumor.” And, hopefully, find the “hunger signal” of tumors one day.