Bioinformatics software detects cancer-related changes in single-cell studies

In recent years, the analysis of single-cell and spatial data has revolutionized biomedical research, making it possible to observe what happens in biological samples with an unprecedented level of detail. Interpreting this data, however, is not easy because different software offers different results which are hard to compare.

Taking this issue as the starting point, a research group from the University of Trento has developed the “Cell Marker Accordion,” a bioinformatics tool that makes the identification of cell types in the new generation data clearer and more robust. The results of the research, conducted in collaboration with Yale University (United States), the University of Trondheim (Norway), Policlinico di Milano and the Institute of Biophysics of the National Research Council—CNR, are published in Nature Communications.

“With Cell Marker Accordion we wanted to build a tool that helps researchers not only to classify cells, but also to understand why they have been classified in a certain way,” explains Emma Busarello, a Ph.D. candidate in biomolecular sciences at the University of Trento and first author of the work.

“Often software give a result, but do not say how they got there. We wanted to do something more transparent and useful for people working in clinical settings.”

The name of the instrument—”Accordion”—recalls the idea of harmonizing different data to provide a more robust result.

The software has been designed to help identify cell types in biological samples both under normal conditions and in the presence of disease. It can, for example, indicate the presence of leukemic stem cells or tumor plasma cells, also suggesting which genes could be involved in the alterations.

“Our tool does not limit itself to indicating what type of cell is present, but also helps to find out which genes make that cell unique and different from the others,” adds Toma Tebaldi, professor at the Department of Cellular, Computational and Integrative Biology—Cibio of the University of Trento and corresponding author of the research. “This can help identify new biomarkers or therapeutic targets.”

One of its strengths is accessibility. In addition to the software package for those with bioinformatics skills, the Accordion has a web version with an intuitive interface that can easily be used even by non-programmers.

The project was developed at the Cibio Department and involved research groups with specific expertise, from brain tumors to blood tumors. Among the partners are the teams coordinated by Paolo Macchi, Maria Caterina Mione, Luca Tiberi of the University of Trento and Gabriella Viero of CNR. They worked with Giulia Biancon (Policlinico di Milano), the University of Trondheim and Stephanie Halene of the Yale School of Medicine.

One of the future goals of the project is to adapt the instrument to new types of data and keep it updated over time, to make sure that the scientific community can always count on a reliable tool.

“A scientific software does not end with a publication,” concludes Tebaldi. “Quite the contrary: it must be maintained, constantly improved, made more and more useful in line with new discoveries. This too is a service to research.”