Hot PTATO: A New Tool For Tracking Cancer Mutations


The Context: Our DNA is our blueprint, but it is prone to mutate when our cells make copies of themselves. Normally our cells have quality control systems that repair these mutations, but in diseases like cancer, the mutations accumulate with devastating consequences to health. New tools for sequencing our genomes (such as primary template-directed amplification, for you scientists!) are making it possible to pinpoint these mutations, but these genetic mixtures are difficult to parse out and can sometimes contain errors.

The Study: A new artificial intelligence-powered tool called PTATO developed by NYSCF – Robertson Stem Cell Investigator Ruben Van Boxtel, PhD, of the Princess Máxima Center for Pediatric Oncology in Utrecht, The Netherlands can identify mutations that occur in single cells during our lifetimes as part of diseases like cancer, providing insights into how DNA is impacted in disease. The study appears in Cell Genomics.

The Importance: PTATO allows for a better understanding of the progression of diseases like cancer, opening the door for better treatment options.

Cancer is a disease of the genome, with accumulation of mutations in cells causing tumors to grow out of control and evade therapies. Tracking the mutations that drive cancer is thus a critical task for scientists, but the data generated to do this can present as a massive puzzle. 

“Previously, the results obtained were not very accurate and there was no appropriate technology to improve this,” noted Sjors Middelkamp, PhD, the study’s first author, in an article from the Princess Máxima Center for Pediatric Oncology. “We used machine learning to train the PTATO program to automatically recognize and filter reading errors in DNA codes. Thanks to this form of artificial intelligence, we get a much more accurate picture of the DNA code in a cell. We also gain new insights faster because the program easily compares the results of different cells.”

PTATO in Patients

The team then tested their new tool in blood stem cells derived from patients with Fanconi anemia – a blood disorder known to increase one’s risk for developing cancers like leukemia. The results pointed to a higher level of DNA deletions in these patients that could be driving their disease.

‘With traditional techniques, we could only study the DNA of healthy stem cells. With PTATO we can now also properly map the DNA of individual stem cells from children with hereditary disorders, such as Fanconi anemia,” said Dr. Middelkamp. “Thanks to PTATO, we saw that these blood stem cells are missing pieces of the DNA code. This gives us insights into the biological processes that go wrong and possibly lead to cancer. Hopefully, in the future we will be able to closely monitor these processes in every child and even target treatments to them.’

The team has made PTATO an open source tool for the wider research community to inform progress toward better therapies.

“Because the results of DNA analysis of an individual cell are now much more accurate, I expect that we will learn a lot about the different types of cancer cells in a tumor and the evolution of cancer,” added Dr. van Boxtel. “This knowledge can then be turned into new and better treatments. This will enable us to achieve our mission to cure every child with cancer, with optimal quality of life.”

Journal Article:

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox
Sjors Middelkamp, Freek Manders, Flavia Peci, Markus J. van Roosmalen, Diego Montiel González, Eline J.M. Bertrums, Inge van der Werf, Lucca L.M. Derks, Niels M. Groenen, Mark Verheul, Laurianne Trabut, Arianne M. Brandsma, Evangelia Antoniou, Dirk Reinhardt, Marc Bierings, Mirjam E. Belderbos, Ruben van Boxtel. 2023. Cell Genomics. DOI:

Image credit: Marloes Verweij – Laloes Fotografie

Diseases & Conditions:

Cancer and Blood, Genomics & Gene Editing

People mentioned: