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Using 3D-genomics to classify leukaemia

Using 3D-genomics to classify leukaemia
30 Apr 2014

The 3D shape of a leukemia cell's genome differs depending on the subtype of the disease it comes from, and this shape is as good or better at indicating leukemia type than gene expression, according to research published in the open access journal Genome Biology.

The proof of principle study focused on the shape made by the HOXA genes in human cells. Researchers found that the shape of a tumor cell's genome is excellent at indicating the subtype of leukemia tumor it comes from. These initial results suggest that '3D genomics' might be a way of improving personalized treatment, though application in the clinic is a long way off.

Previous studies have shown that looking at gene expression - the specific proteins produced by the genes, is a good predictor of whether patients have leukemia. This study however, found that different types of leukemia cells also have a distinctive chromatin interaction - how the chromatin that makes up the genome is folded.

The HOXA genes are involved in embryo development and are found in many human cancers, including leukemia. The scientists from McGill University took data about the HOXA genes in human leukemia cells generated by the 5C technique. This showed the chromatin interaction and they used computational techniques to work out which shape was linked with each leukemia type. Taking a representative sample of cells, they found that the 3D shape of HOXA genes could predict the type of leukemia with 93% accuracy, while gene expression only had a 62% accuracy.

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 will also be needed to see whether genome shape is as good at indicating other types of cancer.

Lead author Josee Dostie from McGill University said: "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.

"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, our study demonstrates a novel approach for classifying human disease that must be explored further, if only for what it can reveal about how the human genome works."


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Notes to Editor

Classifying leukemia types with chromatin conformation data
Mathieu Rousseau, Maria A Ferraiuolo, Jennifer L Crutchley, Xue Qing David Wang, Hisashi Miura, Mathieu Blanchette and Josee Dostie
Genome Biology 2014, 15:R60
Article available at journal website

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