American researchers have developed an algorithm to trace the migration of cancer cells in the body and thus better understand the origin of metastases.
Researchers at Princeton University (United States) have developed a new calculation method to track the spread of cancer cells in the body. This migration of cells can lead to metastatic disease, which causes about 90% of cancer deaths. “So are there specific changes, or mutations, in these cells that allow them to migrate?” Asked Ben Raphael, professor of computer science at Princeton and lead author of the study.
Cellular movement traceability
To find out, the researchers developed an algorithm to track metastases by integrating DNA sequence data where cells are located in the body. Their study was published in Nature Genetics. Called “MACHINA”, this new calculation system helps to understand cancer migration. More simply, it amounts to marking the cells with what could be an electronic chip to follow their movement.
By simultaneously tracing cell mutations and movements, MACHINA shows that metastatic disease in some patients results from less cell migration than previously thought. For example, a recent analysis suggested that the metastatic disease of a breast cancer patient resulted from 14 migrations, while MACHINA indicates that a single secondary tumor in the lung caused five cell migrations. The researchers tested their invention on patients with breast cancer, melanoma, ovarian cancer and prostate cancer.
Better understand the “killing phase” of cancer
According to Andrea Sottoriva of the Institute of Cancer Research in London, this approach is a small revolution. “I predict that this new method will be widely used by the genomic community and will shed new light on the deadliest phase in the evolution of cancer.”
The development of MACHINA paves the way for larger tests carried out on large cohorts. Understanding the “birth” of metastases could lead to new treatments aimed at blocking the process of cancer spreading through the body. The researchers plan to make the method more powerful by incorporating data from the DNA of tumor cells that travel through the bloodstream, as well as epigenetic changes (chemical changes in DNA). “A better algorithm is like a better microscope,” says Ben Raphael. “When you look at nature with a magnifying glass you can miss important details, if you look with a microscope you see a lot more.”
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