Computational methods may help to track spread of cancer

Washington: Migration of cells from one part of the body to another can lead to cancer and can increase deaths from the solid tumor.

Researchers at Princeton University have developed a new computational method that increases the ability to track the spread of cancer cells from one part of the body to another.

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

Metastasis is a pathogenic agent’s spread from an initial or primary site to a different or secondary site within the host’s body as it is typically spread by a cancerous tumor.

This technique yielded a clearer picture of cancer migration histories.

By simultaneously tracing cells’ mutations and movements, researchers found that metastatic disease in some patients could result from fewer cellular migrations than previously thought.

Several additional features helped improve the research’s accuracy. The algorithm included a model for the comigration of genetically different cells, based on experimental evidence that tumor cells can travel in clusters to new sites in the body. It also accounted for the uncertainty in DNA data that came 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 ‘difficult to analyze, noisy’ data that result from tumor DNA sequencing.

“I predict this new method will be of widespread use to the genomics community and will shed new light on the most deadly phase of cancer evolution,” said Andrea Sottoriva, a researcher.

This development paved the way for a broader examination of metastasis patterns in large cohorts of cancer patients, which could reveal key mutations that cause different types of cancer to spread.

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