Uppsala University: Effective collaboration enables earlier detection of drug resistance

Patients with chronic myeloid leukemia (CML) are primarily treated with tyrosine kinase inhibitors, an effective therapy but to which some patients develop resistance over time. Historically, such resistance has been profiled using Sanger sequencing, but now the Uppsala University Hospital has switched to a new technology that can sequence considerably longer DNA sequences and whose higher sensitivity enables earlier detection of the acquired gene mutations that occur with resistance.

“In a validation study with long-read sequencing, we identified all 17 mutations that we could find with Sanger sequencing. Furthermore, we detected an additional 16 mutations whose frequencies are below the limit of detection for Sanger sequencing. In parallel with this study, we have built an infrastructure for efficient handling of samples and data at the clinic and laboratory, and today the method is implemented as routine protocol at the Uppsala University Hospital,” says Ola Spjuth, Professor of Pharmaceutical Bioinformatics.

For patients, the new method means that resistance mutations can be detected earlier than is possible with Sanger sequencing. For healthcare providers, the results of analysis performed with long-read sequencing offer am improved basis for decision making while treating CLM.


“This is a valuable progress made possible by the fruitful collaboration between our research group at Uppsala University, the Uppsala University Hospital and SciLifeLab’s Clinical Genomics platform. We are well aware of the challenges that can arise in constellations where not least time is a constant commodity, but throughout the project we have had the support of driving people and the fact that we have now reached our goal is a clear confirmation that it is entirely possible to weave together all the skills needed for success in precision medicine,” states Ola Spjuth.

The system is currently managed within the framework of the start-up company Pincer Bio which, in collaboration with SciLifeLab, offers integrated solutions from sample to data analysis and report. All developed software is available as open source. In the long term, the ambition is to develop the method for other clinical applications as well.