The algorithm, developed by researchers at the University of Trieste in collaboration with Genomics England, allows the level of tumor contamination to be measured, improving diagnosis and treatment.
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In the fight against cancer, the use of innovative analysis tools is emerging as a precious weapon capable of improving diagnosis and treatment of many types of cancer. A new confirmation arrives from the TINC algorithmEnglish acronym for Tumour In Normal Contamination assessment (Tumor evaluation in normal contamination), an IT tool developed by researchers at the University of Trieste in collaboration with Genomics England and implemented in a clinical context throughout England. The application, detailed in a study just published on Nature Communicationsallows you to measure the level of tumor contaminationimproving diagnosis and treatment of various blood cancers.
What is TINC, the algorithm that helps fight blood cancers
The TINC algorithm (Tumour In Normal Contamination assessment) is a new IT tool that allows you to estimate the level of tumor contamination in the so-called normal samples, i.e. those which, in principle, they should contain only healthy cells. In cancer patients, these samples (generally obtained from a blood sample) are compared with those taken directly from tumor tissues, in order to identify mutations present in the diseased cells, which can influence the subsequent development of the tumor and therefore the prognosis of the disease. illness.
The recognition of these mutations occurs through the DNA sequencing contained in the two samples, which is compared using automated procedures. If, however, the sample of healthy cells is contaminated with tumor cells, the accuracy of the results obtained with this procedure may be negatively affected, leading to a reduction in sensitivity in mutation detection. In the patients with blood cancersthis risk is particularly relevant, as the tumor cells are found right in the bloodstream and it is therefore almost impossible to separate them from healthy ones during a blood sample.
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To solve this problem, researchers have come up with the TINC algorithm That “helps to establish the percentage of tumor cells present in the normal sample, so that, in the presence of a high level of contamination, an alternative analysis flow to the standard one can be activated, capable of providing scientists and doctors with more precise data on the tumor genome” they explain the developers of TINC – . The goal is to arrive to a more accurate diagnosis that allows you to choose the most suitable therapies to be administered to each patient”.
TINC was tested using whole genome sequencing data from 771 people involved in the project 100.000 Genome of Genomics England, including 617 from patients with blood cancers.
The scholars then compared the data processed by the algorithm with those obtained through standard technologies used for the residual disease test (in which the number of tumor cells remaining in a patient’s blood after treatment is verified), detecting levels of tumor contamination in normal samples. “Our work highlights the importance of contamination assessment for accurate detection of somatic variants in clinical and research settings, particularly with large-scale sequencing projects used to provide accurate data from which to make clinical decisions for patient care” the researchers point out.
In light of the result, the new algorithm has become part of the work tools with which Genomics England provides genome sequencing analyzes to hospitals and clinical centers of the National Health Service in the United Kingdom on a daily basis. “The implementation of TINC in a clinical context across England represents an exceptional achievementwhich confirms the value of our university’s data science research” says Giulio Caravagna, co-corresponding author of the study and professor of Computer Science at the University of Trieste, head of the Cancer Data Science Laboratory, supported by the AIRC Foundation for cancer research.
“Projects that use sequencing technologies on a large scale to study oncological diseases they have revolutionary potential, but the use of these innovative technologies requires equally innovative analysis tools. And our laboratory – conclude Caravagna – is highly specialized in the construction of such instruments”.