Published: 07-12-2022 08:22 | Updated: 07-12-2022 08:25

New method for detecting multiple cancers early

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Researchers from Chalmers and KI, among others, have developed a new method that can identify several types of newly formed cancer through blood or urine samples. The method measures cancer-indicating changes in so-called glycosaminoglycans, sugars that are part of our metabolism. Photo: Elypta AB, Graphic illustration: Toby Logan.

When cancer is detected at an early stage, the rates of survival increase drastically, but today only a few cancer types are screened for. An international study led by researchers at Chalmers University of Technology and affiliated with Karolinska Institutet shows that a new, previously untested method can find multiple types of newly formed cancers at the same time – including cancer types that are difficult to detect with comparable methods. The results are published in the journal PNAS.

Cancer is one of the deadliest diseases in the world and is more difficult to cure when detected at a late stage.

Finding effective methods for early detection of several types of cancer at the same time, so-called Multi-Cancer Early Detection (MCED), is an emerging research area. Today's established screening tests are cancer type-specific, which means that patients need to be tested for each cancer type separately. Emerging MCED tests under development are usually based on genetics, for example measuring DNA fragments from tumours circulating in the blood. But DNA-based methods can only detect some types of cancer and have limited ability to find tumours at the earliest stage, so called stage I.

Method based on human metabolism

In the current study, the researchers describe a new method for multi-cancer early detection that is instead based on human metabolism. The results uncover new opportunities for cheaper and more effective cancer screening.

In the study with blood and urine samples from 1,260 participants, the researchers discovered that the new method could detect all 14 cancer types that were tested. Next, they demonstrated in a subset of participants that the method could detect 20 percent of stage I cancers in asymptomatic and otherwise healthy people, which is twice as many as the emerging DNA-based MCED tests.

Francesco Gatto
Francesco Gatto, researcher at Chalmers and Karolinska Institutet. Photo: Paul Wennerholm.

"This is a previously unexplored method, and thanks to the fact that we have been able to test it in a large population, we can show that it is effective in finding more stage I cancers and more cancer types. The method makes it possible to find cancer types that are not screened for today and cannot be found with DNA-based MCED tests, such as brain tumours and kidney cancer," says the study’s corresponding author Francesco Gatto, who is a visiting researcher at the Department of Biology and Biological Engineering at Chalmers and is affiliated with the Department of Oncology-Pathology at Karolinska Institutet.

The method is based on a discovery by Dr. Francesco Gatto and Prof. Jens Nielsen at Chalmers almost ten years ago: that so-called glycosaminoglycans – a type of sugar that is an important part of our metabolism – are excellent biomarkers to detect cancer noninvasively. The researchers developed a machine learning method in which algorithms are used to find cancer-indicating changes in the glycosaminoglycans. The method uses comparatively small volumes of blood or urine, which makes them more practical and cheaper to use.

Cheaper and more practical tests

"The fact that the method is comparatively simple means that the cost will be significantly lower, ultimately enabling more people to have access to and take the test," says Francesco Gatto.

In the next step, the researchers hope to be able to conduct a study with more participants to further develop and confirm the method’s potential for screening use. The hope is to one day be able to create screening programmes that can detect all cancer types early.

The study has been conducted in collaboration with over 30 partners at ten different universities and research institutes in Sweden and internationally.

Funding was provided by the Knut and Alice Wallenberg Foundation, the Swedish Cancer Society, the Ingabritt och Arne Lundbergs Forskningsstiftelse, the European Union’s Horizon 2020 research and innovation programme, the EIT Health 2019 Digital Sandbox, the Marta and Gustaf Agren Foundation and grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement.

Three of the study authors have declared potential conflicts of interests, including being shareholders and employees of the startup Elypta. Elypta develops and commercializes MCED tests for early cancer discovery and have developed the measurement methods used in the study.

This news article is based on a press release from Chalmers.


"Non-invasive multi-cancer early detection using glycosaminoglycans." Sinisa Bratulic, Angelo Limeta, Saeed Dabestani, Helgi Birgisson, Gunilla Enblad, Karin Stalberg, Goran Hesselager, Michael Haggman, Martin Hoglund, Oscar E Simonson, Peter Stalberg, Henrik Lindman, Anna Bang-Rudenstam, Matias Ekstrand, Gunjan Kumar, Ilaria Cavarretta, Massimo Alfano, Francesco Pellegrino, Thomas Mandel, Clausen, Ali Salanti, Francesca Maccari, Fabio Galeotti, Nicola Volpi, Mads Daugaard, Mattias Belting, Sven Lundstam, Ulrika Stierner, Jan Nyman, Bengt Bergman, Per-Henrik Edqvist, Max Levin, Andrea Salonia, Henrik Kjolhede, Eric Jonasch, Jens Nielsen, Francesco Gatto. Proceedings of the National Academy of Sciences (PNAS), online 5 December, 2022, doi: 10.1073/pnas.2115328119