Scientists at McGill University say they have discovered that the 3D shape of a leukemia cell's genome holds a key to solving the puzzle of human diseases. The researchers report their findings (“Classifying leukemia types with chromatin conformation data”) in Genome Biology.
Josée Dostie, Ph.D., a researcher in the faculty of medicine in the department of biochemistry, focused on the shape made by the region spanning the Homeobox A (HOXA) genes in human cells, a set of 11 genes encoding proteins that are highly relevant to numerous types of cancers. Dr. Dostie and colleagues discovered that the shape of this region of the genome provided an excellent indicator for determining the subtype of leukemia it comes from.
“We explore whether chromatin conformation can be used to classify human leukemia. We map the conformation of the HOXA gene cluster in a panel of cell lines with 5C chromosome conformation capture technology, and use the data to train and test a support vector machine classifier named 3D-SP,” wrote the investigators. “We show that 3D-SP is able to accurately distinguish leukemias expressing MLL-fusion proteins from those expressing only wild-type MLL, and that it can also classify leukemia subtypes according to MLL fusion partner, based solely on 5C data. Our study provides the first proof-of-principle demonstration that chromatin conformation contains the information value necessary for classification of leukemia subtypes.”
It is not clear at the moment whether the genome shape plays a role in causing the cancer, or whether the cancer causes the genome to change shape. Further studies are needed to determine whether genome shape is as good at indicating other types of cancer.
“Our study validates a new research avenue: the application of 3D genomics for developing medical diagnostics or treatments that could be explored for diseases where current technologies, including gene expression data, have failed to improve patient care,” says Dr. Dostie, “While the use of 3D genomics in the clinic is still remote when considering the technical challenges required for translating the information to the bedside, we discovered a new approach for classifying human disease that must be explored further, if only for what it can reveal about how the human genome works.”