A new computational method will help track the progression of colon cancer

A team of researchers has designed a computational method to determine the progression of colorectal cancer, a scientific breakthrough that may open new perspectives regarding the factors that enhance this pathology and the selection of effective therapies. Experts Victor Moreno, of the School of Medicine and Health Sciences of the UB, the Institute of Biomedical Research of Bellvitge (IDIBELL) and the Catalan Institute of Oncology (ICO) and Rebeca Sanz Pamplona (IDIBELL-ICO) are among the internationally renowned authors of this new study, published in the Proceedings of the National Academy of Sciences (PNAS) journal. What conditions make tumor growth easier?

While colon cancer has a similar frequency in men and women, rectal cancer is more common in men. Approximately 13,000 men and 14,000 women live with a diagnosis of colorectal cancer in Catalonia.

As explained by Professor Victor Moreno, from the Department of Clinical Sciences at UB, "as most tumors, colorectal ones are characterized by large chromosomal alterations (deletions, amplifications) and point mutations. These factors at DNA level end up generating significant alterations in the RNA and metabolism of tumor cells."

According to the first author, Professor Giulio Caravagna at the University of Edinburgh, "we propose a bioinformatics protocol to detect regularities that are common in the origin and development of the tumor. This protocol could be key to understand a disease that is characterized by a very low number of common genomic alterations in different patients”. According to expert Bud Mishra, University of New York, "the model helps predict how the tumor genome will change over time."

Traditionally, it was thought that cancer began with a rebel cell, that extended, in part, by a combination of autonomous genetic interactions: mutations in oncogenes, with the potential ability to cause cancer, and the failure of the tumor suppressor genes that control them. However, the availability of advanced sequencing techniques has outlined a more complex scenario on cancer progression. Specifically, it appears that the interaction between cells in a tumor population is more relevant than previously thought, since tumors are more heterogeneous at the cellular level.

PiCnIc: a new tool to understand cancer progression

The team has been able to observe these interactions using a model that aims to generate a cellular picture of the spread of colorectal cancer. In order to do this, they developed a modeling system (Pipeline for Cancer Inference, or PiCnIc) that uses genetic sequencing data to make predictions about causality.

PiCnIc, in particular, takes into account the function of the conductive (driver) mutations that stimulate cancer progression, in addition to other phenomena such as the influence of these mutations on other driving factors.

To verify the feasibility of the models, the research team compared the predictions with the available knowledge on the growth dynamics of colorectal cancer. According to the results, PiCnIc is effective as a disease progression tool.

"This methodology is completely new because it incorporates a probabilistic model that infers the order of events (mutations and alterations in the number of copies)", Professor Victor Moreno (UB-IDIBELL-ICO) explains.

This new research paper, published in the journal Proceedings of the National Academy of Sciences (PNAS), is supported by the National Science Foundation, the Carlos III Institute of Health, the European Development Fund, the Spanish Association Against Cancer (AECC) and the Generalitat of Catalonia.