Bioinformatics Tool to Identify Chromosomal Alterations in Tumor Cells Can Improve Cancer Diagnosis

Chromosomal instability is a common characteristic in solid tumors, playing a crucial role in the start, progression, and spread of cancer. This condition arises from alterations in the chromosome number and structure during cell division, leading to DNA changes and impacts on cellular functions. Furthermore, chromosomal instability contributes to tumor development and progression, increases tumor diversity, and fosters resistance to cancer treatments. Now, a new bioinformatics tool that can identify these chromosomal alterations characteristic of cancer cells could improve diagnosis and help design personalized treatment plans.

This new detection system, known as QATS (QuAntification of Toroidal nuclei in biological imageS), has been designed by a research team from the University of Barcelona (Barcelona, Spain) and IRB Barcelona (Barcelona, Spain). This computational biological imaging processing tool can improve tumor research and classification by automatically identifying and quantifying the phenotypes associated with chromosomal instability in the nuclei of cancer cells. QATS focuses on detecting and quantifying toroidal nuclei, which are new biomarkers of chromosomal instability, in biological images. Unlike normal nuclei, toroidal nuclei are phenotypically different as they have a ring-like shape with a void containing cytosolic material. Recognized recently as critical biomarkers for chromosomal instability, toroidal nuclei offer a new avenue for understanding and combating cancer.

Image: Toroidal nuclei marked in magenta and micronuclei in green (Photo courtesy of IRB Barcelona)

Until now, the assessment of chromosomal instability in cancer cells has been primarily based on quantifying micronuclei, which are irregular structures derived from the cell nucleus that may contain chromosomes or chromosomal fragments. By introducing the assessment of toroidal nuclei into both research and clinical settings, there is significant potential for improving tumor classification and developing treatments tailored to individual patients. The QATS system has already proven effective in preclinical studies involving cancer cell lines by demonstrating its capability to identify and quantify toroidal nuclei accurately.

“In the future, the application of QATS in more complex biological scenarios — human tissue samples from patient biopsies — will represent a breakthrough for the scientific and medical communities to improve cancer diagnosis and patient treatment”, concluded the researchers.

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University of Barcelona
IRB Barcelona