cfSort Uses Methylation Patterns to Identify Tissue Origin in Cell-Free DNA Testing

UCLA researchers have made a significant breakthrough in addressing a key challenge in cell-free DNA (cfDNA) testing, also known as liquid biopsy. They have discovered specific methylation patterns that are unique to each tissue, potentially revolutionizing the identification of the tissue or organ associated with cfDNA alterations detected through testing. This advancement is crucial for accurate disease diagnosis and monitoring.

Cell-free DNA has shown great potential in disease detection and monitoring. However, accurately determining the tissue origin of cfDNA fragments has proven difficult using current methods. In their study published in the Proceedings of the National Academy of Sciences (PNAS), the research team developed a comprehensive and high-resolution methylation atlas using a vast dataset of 521 noncancerous tissue samples, representing 29 major types of human tissues. Their approach, called cfSort, successfully identified tissue-specific methylation patterns at the fragment level. These findings were further validated using additional datasets.

Moreover, the researchers demonstrated the clinical applications of cfSort by utilizing it for disease diagnosis and monitoring treatment side effects. By estimating the tissue-derived cfDNA fraction using cfSort, they were able to assess and predict clinical outcomes in patients.

First author Shuo Li stated, "We have shown that cfSort outperformed existing methods in terms of accuracy and detection limit, providing more precise tissue fraction estimation and distinguishing lower levels of tissue-derived cfDNA. Furthermore, cfSort demonstrated remarkable robustness towards variations in tissue compositions, making it widely applicable to diverse individuals."

This method holds promise for enhancing the accuracy and reliability of cfDNA testing, enabling more accurate identification of the tissue or organ associated with cfDNA alterations.