Science: Using CRISPR to build a melanoma model from scratch

Scientists have created models of skin cancer by gradually introducing cancer-causing mutations into healthy skin cells, revealing the effects of mutations.

Histological image of melanoma model


Over the past 20 years, researchers have discovered genetic mutations in thousands of cancers, but understanding how they affect tumor growth and spread in the body remains is a challenge because each patient’s tumor may have many different mutations.

Now, scientists at the Broad Institute of MIT and Harvard use the The CRISPR-Cas9 gene editing system creates a cellular model of the deadliest skin cancer, melanoma. In the journal Science, the team describes how they individually implanted five melanoma mutations in different combinations into the genome of healthy human skin cells. The edited cells grow and multiply into tumors with melanoma characteristics, including rapid growth, increased ability to invade other tissues, activation of certain genetic programs, and specific pigmentation patterns.

Because researchers introduce mutations one at a time in a controlled manner, they are able to precisely determine the impact of individual and specific combinations of mutations. They even found a causal link between the mutation and tumor metastasis, the spread of a tumor in the body. The results not only reveal key mutations in melanoma, but also provide a new way to study the role of specific genes in other cancers.

The work is the first time scientists have used precisely controlled genetic engineering, said Eran Hodis, first author and one of the corresponding authors of the study. Create human cancer models from fully differentiated or specialized cells, rather than stem cells. Stem cells are not associated with every cancer type. He began the research while earning his Ph.D. at Dana-Farber Cancer Institute and Harvard University, and is now an internal medicine resident at Brigham and Women’s Hospital. “We hope that this approach will provide an opportunity to build similar models in many other cancer types, accelerating the link between cancer genetics and specific disease characteristics,” he said.

“With this toolbox, we can ask what effect the mutation has on the cell,” said Elena Torlai Triglia, a postdoctoral scholar at Broad University and one of the first authors. “These questions help us understand how the disease develops and how to target it.

” In order to design these models, we must put cutting-edge , precise gene editing technology combined with high-resolution, massively parallel single-cell genomics analysis to generate and characterize cells and tumors, combined with machine learning algorithms to analyze the data. ”

Making Melanoma Models

When studying melanoma, it is especially difficult to correlate a tumor’s genetic makeup or genotype with a specific trait or phenotype. “The skin is exposed to many external factors, such as UV light, so melanoma tumors,” Torlai Triglia said. Patients have many mutations that may not be the real cause of the disease. “By introducing the mutation into healthy human melanocytes — the skin cells that produce melanin and become melanoma cancer cells — the team could see the effects of the mutation on a blank sheet of paper.

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To create their melanoma model, the team used CRISPR-Cas9 to install mutations in the CDKN2A, BRAF and TERT genes commonly found in melanoma. These three mutations add to Together, it causes the cells to behave like cancer, dividing indefinitely.

Next, the researchers identified the known melanoma genes PTEN, TP53 and APC with different combinations of additional mutations added to create nine different cell models, which were then implanted in mice. These animals grew tumors that showed similar pigmentation and cellularity to human tumors. Single-celled RNA-sequencing revealed that as more mutations were added, cells gradually changed their gene expression programs, with animal tumor models having similar gene expression patterns to patient tumors with the same genotype—something the researchers were surprised to observe. “If we were going to do simulations in the lab, that would be impossible,” Hodis said. We’re talking about the coordinated expression of thousands of genes. This is one of the best evidence we have that the melanomas we build ‘from scratch’ faithfully mirror the melanomas that develop in our patients. “

Melanoma is notorious for early metastases—a often fatal process whose genetic basis is unknown. Hodis, Torlai Triglia and their collaborators found that metastasis often occurs in APC-mutated tumors, suggesting that inactivation of this gene may contribute to the tumor’s ability to spread.

Hodis, Torlai Triglia and Regev plan to use their method to build more cancer models and study mutations that are not yet understood. Their findings, they say, underscore the importance of studying gene interactions in disease models important, their method may help scientists study how tumors develop resistance to targeted therapies that cannot always be explained by a single mutation.

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Stepwise-edited, human melanoma models reveal mutations’ effect on tumor and microenvironment