Matija Trickovic
© UNIGE/Ilija Trickovic
The first step was to analyse huge amounts of data. “As a bioinformatician, the challenge was to come up with an innovative approach for mass data analysis,” recalls Matija Trickovic, PhD student in the laboratory of Mirko Trajkovski and first author of this study. “We successfully developed the first comprehensive catalogue of human gut microbiota subspecies, together with a precise and efficient method to use it both for research and in the clinic.”
By combining this catalogue with existing clinical data, the scientists developed a model that can predict the presence of colorectal cancer solely based on the bacteria present in stool samples. “Although we were confident in our strategy, the results were striking,” enthuses Matija Trickovic. “Our method detected 90% of cancer cases, a result very close to the 94% detection rate achieved by colonoscopies and better than all current non-invasive detection methods.”
By integrating more clinical data, this model could become even more precise and match the accuracy of colonoscopy. It could become a routine screening tool and facilitate the early detection of colorectal cancer, which would then be confirmed by colonoscopy but only in a selected group of patients.
A first clinical trial is being set up in collaboration with the Geneva University Hospitals (HUG) to determine more precisely the cancer stages and the lesions that can be detected. However, the applications go beyond colorectal cancer. By studying the differences between subspecies from the same bacterial species, researchers can now identify the mechanisms of action by which the gut microbiota influences human health. “The same method could soon be used to develop non-invasive diagnostic tools for a wide range of diseases, all based on a single microbiota analysis,” concludes Mirko Trajkovski.
Source: University of Geneva