Catching cancer in act

When cancer is confined to one area of ​​the body, doctors can often treat it with surgery or other treatments. Much of the mortality associated with cancer, however, is due to a tendency to metastasize, producing seeds of its own that can take root throughout the body. . The very moment of metastasis is imminent, lost in the millions of tumors that occur in tumors. “It is usually impossible to track these events in real time,” Whitehead Institute Member Jonathan Weissman said.

Now, researchers led by Weissman, who is also a professor of biology at the Massachusetts Institute of Technology and a researcher with the Howard Hughes Medical Institute, have turned the CRISPR machine into a method to do that. In a paper published 21 January in Science, The Weissman Laboratory, in collaboration with Nir Yosef, a computer scientist at the University of California, Berkeley, and Trever Bivona, a cancer biologist at the University of California, San Francisco (UCSF), treats cancer cells as which evolutionary biologists might look at. species, mapping a family tree in great detail. By examining the branches, they can monitor the cell line to find out when one tumor cell went wrong, spreading its generation to the rest of the body.

“With this approach, you can ask questions like, ‘How often does this tumor metastasize? Where did the metastases come from? Where do they go from?'” Weissman said. “By being able to follow the history of the tumor in vivo, you will reveal differences in the biology of the tumor that were otherwise invisible.”

Scratch paper cells

Scientists have tracked sequences of cancer cells in the past by comparing shared mutations and other changes in their DNA blueprints. These methods, however, are partly dependent on the fact that there are enough naturally occurring mutations or other signals to correctly express cellular relationships.

That’s where Weissman and co-author Jeffrey Quinn, then a postgraduate researcher in the Weissman lab, and Matthew Jones, a graduate student in the Weissman lab, saw an opportunity to use CRISPR technology – in particular, a way that developed by Weissman Lab member Michelle Chan to track embryo development – to make tracking easier.

Instead of just hoping that a cancer line was producing enough signals with respect to a particular line, the researchers decided to use the No method to insert signals themselves. “Basically, the idea is to invent a cell that has a genomic scan of DNA, which can be‘ written ’about using CRISPR,” Weissman said. This ‘writing’ in the genome is done in such a way that it is hereditary, meaning that a ‘parent’ cell would have offspring and progenitor cells recorded in its genome.

To create these unique “scratchpad” cells, Weissman invented human cancer cells with additional genes: one for the bacterial protein Cas9 – the famous “molecular scissors” used in CRISPR genome editing – others for glorious proteins for microscope, and a few. series that would be targets for CRISPR technology.

They then translocated thousands of modified human cancer cells into mice, mimicking lung tumors (a model developed by the Bivona collaborator). Mice with human lung tumors often show aggressive metastasis, so the researchers reasoned that they would provide a good model for monitoring cancer progression in real time.

As the cells began to divide, Cas9 made small incisions at these target sites. When the cell repaired the incisions, it randomly absorbed or eliminated several nucleotides, resulting in a special repair sequence called indel. This cutting and repair occurred randomly in almost every generation, creating a map of cell divisions that Weissman and the team could follow using specific computer models they created by working. by Yosef, a computer scientist.

Appears the invisible

An interesting result was the monitoring of cells in this way. For one thing, individual tumor cells were very different from each other than the researchers expected. The cells the researchers used were from a human lung cancer cell line called A549. “You’d think they’d be pretty homogeneous,” Weissman said. “But of course, we saw striking differences in the propensity of different tumors to metastasize – even in the same mouse. Some had a very small number of metastatic events, while others quickly jumped around.”

To determine where this heterogeneity came from, the team placed two clones of the same cell in different mice. As the cells grew, the researchers found that their offspring metastasized at a very similar rate. This was not the case with children from different cells from the same cell line – the original cells appeared to have developed different metastatic abilities as the cell line was maintained over many generations.

The scientists then figured out which genes were responsible for this difference between cancer cells from the same cell line. So they started looking for genes that were differentially expressed between nonmetastatic, metastatic weakened and highly metastatic tumors.

Many genes stood out, some of which were previously known to be associated with metastasis – although it was not clear whether they drove the metastasis or just a side effect of it. One of them, the gene encoding for the Keratin 17 protein, is more strongly expressed in lower metastatic tumors than in highly metastatic tumors. “When we dropped Keratin 17 or put too much pressure on it, we showed that this gene actually controlled tumor aggression,” Weissman said.

By being able to identify genes associated with metastasis in this way researchers could answer questions about how tumors grow and adapt. “It’s a whole new way to look at tumor behavior and evolution,” Weissman said. “We think it can be applied to many different problems in cancer biology. “

Where did you come from, where did you go?

Weissman ‘s CRISPR method also allowed the researchers to find out in more detail where and when metastasizing cells in the body took place. For example, a single cancer cell-induced metastasis underwent metastasis five times, spreading each time from the left lung to other tumors such as the right lung and liver. Other cells jump to a different area, and then metastasize again from there.

These movements can be neatly mapped in phylogenetic trees (see photo), where each color represents a different place in the body. A very colorful tree exhibits a highly metastatic phenotype, in which cell progeny jumped several times between different figs. A tree that is mostly one color represents a less metastatic cell.

By mapping tumor progression in this way allowed Weissman and his team to make some interesting observations about the mechanics of metastasis. For example, some clones seeded in a textbook manner, traveling from the left lung, where they started, to specific areas of the body. Others would spawn worse, first moving to other cigarettes before metastasizing again from there.

One such substance, the mediastinal lymph material that sits between the lungs, appears to be a medium of sorts, said co-author Jeffrey Quinn. “It’s a pathway that connects the cancer cells to all this fertile ground that they can go and settle,” he said.

Therapeutically, detecting such ‘hub’ metastasis can be extremely helpful. “If you focus cancer treatments on those areas, you could then slow down metastasis or prevent it in the first place,” Weissman said.

In the future, Weissman hopes to move beyond just observing the cells and start predicting their behavior. “It’s like Newtonian mechanics – if you know the speed and position and all the forces working on a ball, you can find out where the ball is going at any point in time. future, “Weissman said. “We hope to do the same with cells. We want to build a fundamental function of what drives tumor differentiation, and then be able to measure where they are at any given time,” and predict where they’re going. to be in the future. “

The researchers hope that it will be useful to monitor individual cell family trees in real time in other situations as well. “I think it’s going to unlock a whole new aspect of what we think of as measurable quantity in biology,” said co-author Matthew Jones. What is so appealing about this area in general is that we are redefining what is invisible and what is visible. ”

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