When most cancers cells cannot make their very own fats, they eat what’s round them

According to researchers, switching the cancer fat metabolism from production to import could be used for therapy. Credit: National Institutes for Healthy Public Library

Cancer cells rewire their metabolism to make up for a halt in fat production by importing more fat molecules from their environment.

Knowing what will do next for cancer can reduce the chance it will become resistant to treatment. A new U of T study examines how cancer adjusts its metabolism to overcome therapies that may be under development.

“Several clinical trials have failed because metabolism is such an adaptive process that cancer cells gain drug resistance,” said Michael Aregger, co-lead author and research fellow with Jason Moffat, professor of molecular genetics at the Donnelly Center for Cellular and Biomolecular Research who guided the work. “If you know how cells can adapt to disruptions, we may be able to use them in a more targeted manner to avoid the development of resistance.”

“If you know how cells can adapt to disturbances, we can possibly use them in a more targeted manner in order to avoid the development of resistance” – Michael Aregger, research associate

The research was also led by Brenda Andrews and Charles Boone, professor and professor of molecular genetics at the Donnelly Center, and Chad Myers, professor of computer science at the University of Minnesota-Twin Cities.

The study, published this week in the journal Nature Metabolism, is the first to look at global changes in cancer cells as they adapt to a lack of critical nutrients such as fat molecules or lipids that make up the cell’s outer shell.

When cancer cells are unable to make their own lipids, they gobble them up from their surroundings to ensure a steady supply of these essential building blocks, the study said. Lipids also serve as fuel and chemical signals for communication between cells.

The change in metabolism could be bad news for drug manufacturers trying to fight cancer by reducing their lipid reserves. In particular, patients who inhibit an enzyme called FASN for fatty acid synthase, which is involved in an early step in lipid synthesis, are being studied in patient studies. Fatty acids are precursors to larger lipid molecules and their production is increased in many types of cancer thanks to elevated FASN levels, which are also linked to a poor prognosis for the patient.

The U of T study suggests that the effectiveness of FASN inhibitors may be short-lived due to cancer’s ability to find another way to source lipids.

“Because FASN is upregulated in many types of cancer, bold acid Synthesis is one of the most promising pathways of metabolism, ”said Keith Lawson, co-lead author and PhD student in Moffat’s laboratory, a member of the medical school’s surgeon scientist program. “Knowing that metabolic processes are very plastic, we wanted to identify and predict ways in which cancer cells could possibly overcome the inhibition of lipid synthesis.”

To block fatty acid synthesis, the researchers used a human cell line from which the FASN-coding gene had been removed. Using the CRISPR genome editing tool, they successively deleted all around 18,000 human genes from these cells in order to find those that could compensate for the stagnation in lipid production. Such functional relationships are also referred to as “genetic interactions”.

The data analysis, conducted by Maximilian Billmann, co-lead author and postdoctoral fellow at Myers’ laboratory in Minnesota-Twin Cities, revealed hundreds of genes that become important when cells are fat starved. Their protein products are grouped into known metabolic pathways through which cells take up cholesterol and other lipids from their environment.

The uptake of cholesterol by cells has become a textbook that won a Nobel Prize and inspired the blockbuster drug statin and many others since its discovery half a century ago. However, the new study found that one component of this process had been overlooked all along.

The gene coding for it was known only as C12orf49, named for its location on chromosome 12. The researchers renamed the LUR1 gene for lipid uptake regulator 1 and showed that it helps turn on a number of genes that are directly involved in lipid import.

“It was a big surprise to us that we could identify a new component of the process that we thought we knew everything about,” says Aregger. “It really highlights the power of our global approach to genetic interaction which has allowed us to identify a new player in lipid uptake in a completely unbiased manner.”

By a remarkable coincidence, two independently working groups in New York and Amsterdam have also linked C12orf49 to lipid metabolism, which further supports the role of the gene in this process. The New York team published their findings in the same journal as Moffat and colleagues.

Inhibiting LUR1 or other components of lipidimport along with FASN could lead to more effective cancer treatments. Such combination therapies are believed to be less prone to emerging drug resistance because cells would have to overcome two obstacles at the same time – blocked lipid production and import – that are less likely to occur.

“The therapeutic context that emerges from our work is that in addition to lipid synthesis, you should target lipid uptake as well. Our work highlights some specific genes that may be candidates,” says Lawson.

Reference: “The systematic mapping of genetic interactions for de novo fatty acid synthesis identifies C12orf49 as a regulator of lipid metabolism” by Michael Aregger, Keith A. Lawson, Maximillian Billmann, Michael Costanzo, Amy HY Tong, Katherine Chan, Mahfuzur Rahman and Kevin R. Brown, Catherine Ross, Matej Usaj, Lucy Nedyalkova, Olga Sizova, Andrea Habsid, Judy Pawling, Zhen-Yuan Lin, Hala Abdouni, Cassandra J. Wong, Alexander Weiß, Patricia Mero, James W. Dennis, Anne-Claude Gingras, Chad L. Myers, Brenda J. Andrews, Charles Boone, and Jason Moffat, June 1, 2020, Nature Metabolism.
DOI: 10.1038 / s42255-020-0211-z

The research was supported by the Canadian Institutes for Health Research, the Ontario Research Fund, the Canada Research Chairs Program, and the US National Institutes of Health.

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