Cheating death: How cancer cells escape

While studies of other forms of cell death such as apoptosis focus largely on the roles of proteins, a hallmark of ferroptosis is lipid oxidation and, hence, metabolomics -- the study of all small molecules in cells -- and lipidomics -- the study of lipid metabolites and the proteins that create, modify and break them.

In a groundbreaking study, researchers have identified a dual role in the intricate dance of cell survival and death. The enzyme 7-dehydrocholesterol reductase (DHCR7) is unveiled as a pro-ferroptotic player, while its substrate, 7-dehydrocholesterol (7-DHC), surprisingly demonstrates a pro-survival function in cancer cells. This knowledge provides key information for future cancer-fighting studies.

The study is an international collaboration between five countries. The senior author is Jose Pedro Friedmann Angeli of the Rudolf Virchow Center for Integrative and Translational Bioimaging at the University of Wurzburg in Germany. ASU's contribution comes from Professor Judith Klein-Seetharaman, who has a dual appointment in ASU's School of Molecular Sciences and the College of Health Solutions. Klein-Seetharaman is also a faculty member of the Biodesign Institute's Center for Applied Structural Discovery.

Klein-Seetharaman's research uniquely combines protein structural biology with metabolomics. Her expertise in biology and chemistry serves her interdisciplinary research in machine learning-driven multi-omics and the integration of computational and experimental approaches in systems and structural biology of proteins. Klein-Seetharaman's former postdoc Lokender Kumar, currently a professor at Shoolini University in Solan Himachal Pradesh, India, also contributed to the research.

Klein-Seetharaman became involved in this international collaboration through the Human Frontier Science Program (HFSP), which promotes international collaboration in basic research through their grant entitled "Oxidized lipidome: the unspoken language of non-apoptotic cell death." Klein-Seetharaman, together with Raj Reddy at Carnegie Mellon University, had pioneered more than 20 years ago an analogy between biology and language that focused on the study of proteins in an NSF-funded large-scale center on biological language modeling (NSF awards 0225656 and 0225636). Today, large language models (LLMs) have become a mainstay of prediction of protein structure, interactions and functions trained on large protein sequence datasets.

The work on DHCR7's role in the lipidome language and ferroptosis in cancer has just been published today in the journal Nature.

The research

7-DHC is the precursor to the production of cholesterol in our bodies. The production of low-density lipoproteins, or LDLs (so-called bad cholesterol), versus high-density lipoproteins, or HDLs (good cholesterol), is totally dependent on which protein attaches to the cholesterol in our blood.

Klein-Seetharaman's principal contribution involves prediction of the functional consequences of mutations in DHCR7 that are associated with a very rare type of cancer. Klein-Seetharaman needed to structurally model the DHCR7 protein because there was no known crystal structure available.

"We used computational tools to predict DHCR7's structure and orientation in the membrane," explained Klein-Seetharaman. "It was very obvious from a membrane protein perspective which mutations would likely cause misfolding of the protein and which ones wouldn't. We made the prediction that two out of four known amino acids would cause misfolding." The paper shows successful experimental validation of Klein-Seetharaman's predictions -- which is a modeler's dream come true.

Klein-Seetharaman has worked a lot with membrane proteins since her doctoral work with the late Nobel laureate H. Gobind Khorana on the G protein-coupled receptor, rhodopsin. Mutations in rhodopsin associated with Retinitis pigmentosa cause misfolding. Klein-Seetharaman has since developed a conceptual model for folding of membrane proteins that has been able to anticipate disease-causing mutations, even before they have been found in Retinitis pigmentosa patients. This strongly supports the utility of computational structural biology in understanding disease mechanisms.

Klein-Seetharaman began using computational language techniques in 2000, when the human genome was published and hailed as "the book of life." She explains the approach by giving the example of "New York." In human language technologies, the co-occurrence of words is exploited in so-called n-gram models. For example, in "New York," there is a higher chance of finding the word "York" after "New." "New York" is an n-gram with n=2, because you have two words and you can predict the second word after seeing the first.

In studies of lipid oxidation in ferroptosis, Klein-Seetharaman and her team created N-Gram models for cardiolipin, which has three fatty acid tails. So, for every cardiolipin, you can have a combination of three tails -- a n-gram with n=3. The team created N-gram models for the lipid species to see what kind of combinations of oxidized lipids are observed, and then they found those associated with cancer development. Furthermore, they have created the first in silico model of a lipid droplet and were able to observe the effects of lipid peroxidation and subsequent fragmentation on lipid droplet structure and dynamics through molecular dynamics simulations.

These are the kinds of cellular effects that are prevented when DHCR7 is inhibited; its substrate 7-DHC accumulates and shields lipids from oxidation and fragmentation. The point mutations in DHCR7 that cause misfolding of the enzyme would lead to accumulation of 7-DHC, preventing lipid peroxidation and thus suppressing ferroptosis. That's why the mutations are associated with cancer because the loss of this enzyme gives cancer cells the ability to escape programmed cell death. Klein was the only computational biologist on the team. Her expertise was important in the study of DHCR7 structure and its folding, as well as lipid metabolite binding to this protein.

Klein-Seetharaman has devoted much of her career to the mapping of protein sequence to structure space. With the incredible amount of genome sequence data out there, as well as efforts made with structural proteomics accumulating experimental protein structures, she believes that the next frontier is to use the experimental and predicted structures to map the structure space of all proteins in an organism, like the 20,000 genes encoding proteins in a human, as well as interactions with other biomolecules, which is at the heart of biological function.

"What's interesting are the metabolites like the lipids that we are talking about in this study. We want to know what these metabolites do, which targets and where on their structures they bind, and how they manipulate the cell," explained Klein-Seetharaman. "The metabolite identities and concentrations are what makes organisms most resilient to environmental change, because ligand binding and enzymatic reactions are the fastest way an organism can respond to its environment."

Contrary to earlier notions associating elevated 7-DHC levels with cytotoxicity in developing neurons, this research establishes 7-DHC accumulation as a robust pro-survival mechanism in cancer cells, making cancer cells resilient to death by ferroptosis. The key lies in 7-DHC's remarkable reactivity against peroxyl radicals, effectively shielding phospholipids from autoxidation and fragmentation. Understanding this process altering metabolite concentrations will allow us to address it and make patients resilient to cancer.

The study further validates these findings in neuroblastoma and Burkitt lymphoma, shedding light on 7-DHC's potential to induce a death-resistant state in tumors, ultimately contributing to a more aggressive cancer phenotype. This discovery unveils a previously unrecognized anti-ferroptotic activity of 7-DHC, presenting a cell-intrinsic mechanism that cancer cells might exploit to evade death.