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3D shape of genome could diagnose leukaemia type

By examining the shape of the DNA bundled up inside cancerous cells, researchers may have hit upon a new way to diagnose leukaemia
Telling shapes: a transmission electron micrograph showing an isolated chromatin
Telling shapes: a transmission electron micrograph showing an isolated chromatin
(Image: Biology Pics/SPL)

When someone has leukaemia, differences in how their genome is folded up into the nucleus of their cells can reveal what form of the cancer they have. The finding 鈥 the first time that the 3D structure of a cell鈥檚 genome has accurately identified human disease 鈥 could lead to a better way to predict the course of the disease.

A human genome, with its DNA stretched out, is over a metre long. To fit into the nucleus of a cell, it is crumpled into a little ball held together by proteins. That complex is called chromatin.

The 3D structure of the DNA in each cell affects which genes it uses, or expresses. In some cases, the precise shape of the DNA can have specific effects. For example, if a bit of DNA code that normally controls how strongly nearby genes are expressed is folded over and touches another gene, it can switch that gene on or off even if it鈥檚 on a completely different chromosome.

Since one of the hallmarks of leukaemia is gene over-expression, at McGill University in Montr茅al, Canada, and her colleagues wondered whether that was associated with changes in the chromatin shape.

Secrets of shape

To investigate, the team examined data from 30 DNA samples of cells grown in a lab. These cells originally came from people with three different subtypes of the cancer 鈥 acute myeloid leukaemia, acute lymphoblastic leukaemia and embryonic carcinoma.

They focused on a particular region of the genome where a set of genes called HOXA are found. These are associated with many cancers, including leukaemia. The team identified the points of contact between the parts of the genome in this region of the chromatin complex and fed these data into a computer model. The model then predicted the chromatin shapes that the three different types of leukaemia would form.

With their model duly trained using known leukaemia samples, the team then tested their system鈥檚 predictive power. They did this by providing it with data on an unknown set of leukaemia cells, all of which had one of the three leukaemia subtypes. They found that the model could identify the subtype with 93 per cent accuracy.

Finding the leukaemia subtype is the most important factor in defining treatment course, says Dostie. The standard way of diagnosing subtype involves several different clinical and histological tests. The overall level of accuracy is on a par with Dostie鈥檚 results, but it requires the expertise of several different laboratories, which is not always available.

from the University of Sydney in Australia says the method is a long way from being something that could be used to treat patients, but he says it鈥檚 an exciting research tool. 鈥淚t has the possibility of shedding light on mechanisms that cause or sustain cancer, and therefore may provide us with new opportunities to develop therapeutics aimed at the 3D structure of DNA,鈥 he says.

Practical challenge

from the Council for Scientific and Industrial Research in Pretoria, South Africa, says that if the method is verified, the practical challenge to using the technique to help patients will be doing the analysis with small samples. 鈥淭he big caveat here is that to do these chromatin-confirmation studies at high resolution you need millions of cells. You can鈥檛 get this from a tumour biopsy.鈥

In addition, from the University of Melbourne, Australia, warns that there鈥檚 no guarantee the results will hold up when tested on samples from people because culturing the cells in the lab could have altered their chromatin shape.

Dostie says her team is looking forward to testing the results in larger samples taken directly from people with leukaemia. 鈥淲e are currently collaborating with oncologists to that end,鈥 she says.

Journal reference: Genome Biology, DOI:

Topics: DNA / Genetics