AI Summary
The article discusses a new method using machine learning to identify repeat elements of DNA sequences, also known as 'junk DNA' or 'dark matter', in cancerous tissue and cell-free DNA (cfDNA). This approach could potentially offer a noninvasive way to detect cancers or track how well a patient is responding to therapy.
Repeats of DNA sequences, often referred to as ‘junk DNA’ or ‘dark matter,’ that are found in chromosomes and could contribute to cancer or other diseases have been challenging to identify and characterize. Now, researchers have developed a novel approach that uses machine learning to identify these elements in cancerous tissue, as well as in cell-free DNA (cfDNA) — fragments that are shed from tumors and float in the bloodstream. This new method could provide a noninvasive means of detecting cancers or monitoring response to therapy.