The objective of this project, which has obtained €1.85 million of European funds through the State Research Agency, is to design digital models that will integrate the information of the patient (what was the diagnosis, how was the response to treatment or what is their genetic background) and that of their malignant cells (mutations genetics, gene expression subprograms, genome architecture, and biomechanical features).
It is a personalized model for predicting the evolution of the disease in different simulated scenarios, without the need for direct patient intervention, minimizing the level of therapeutic risk, explained the oncologist. Manuel Ramirez Orellana, Project coordinator. Thus, for the first time, computational models of the disease and computing resources from data science are incorporated into childhood leukemia research.
The major problem in the treatment and clinical management of childhood leukemia, pointed out Francisco Monroy, leader of the project, “is the determination of the phenotypic characteristics that make the leukemia cells particularly susceptible to a relapse or an infiltration problem in the patient.” in the central nervous system. These phenotypic characteristics, he added, “can be determined with the mechanical methodologies available at the Transnational Biophysics Unit of the 12 de Octubre Hospital associated with the Complutense University.
The project will sequence and store the genetic, biochemical and biophysical data of cancer cells from 100 cancer patientss from the Niño Jesús hospital.
The project will sequence and store the genetic, biochemical and biophysical data of cancer cells from 100 cancer patients
“Our goal is to create a new resource consisting of a virtual twin of each acute leukemia patient. The basic idea is to develop a tool that helps the oncologist to make decisions in the consultation in a few minutes”, affirmed Ramírez.
The CNIC bioinformatics unit has more than 10 years of experience working with biomedical big data. Specifically, Fátima Sánchez-Cabo points out, within the project, “we are going to work with genetic data at the single cell level with the purpose of improving both the diagnosis and treatment of children with leukemia.”