Computational methods can help track the spread of cancer

The migration of cells from one part of the body to the other can lead to cancer and increase deaths from solid tumors.

Researchers at Princeton University have developed a new method of computation that increases the spread of cancer.

Understanding the drivers of metastasis can lead to new treatments aimed at blocking the process of cancer spreading through the body.

Metastasis is the spread of a pathogen from an initial or primary site to a different or secondary site in the body of the host as it is usually spread by a cancerous tumor.

This technique provided a clearer picture of cancer migration histories.

By simultaneously investigating mutations and cell motions, the disease in some patients may result from fewer cell migrations than previously thought.

Several additional features helped improve accuracy. The algorithm included a model for the co-migration of genetically different cells, based on experimental evidence that tumor cells can travel in clusters to new sites in the body. He also explained the uncertainty in the DNA data from sequencing mixtures of genetically distinct tumor cells and healthy cells.

This approach also overcame a number of challenges to draw meaningful conclusions from the "hard to badyze, noisy" data. "I predict that this new method will be widely used by the genomics community and shed new light on the most lethal phase of cancer evolution," said Andrea Sottoriva, researcher.

paved the way for a broader review of metastasis patterns in large cohorts of cancer patients, which may reveal key mutations that cause the spread of different types of cancer.

The results are published in the Journal of Nature Genetics. (ANI)

This is published unedited from the ANI feed.

Posted: 1 July 2018 5:49 pm