Recently, the healthcare industry has seen many cases of computer algorithm use. They have used neural network systems and machine learning models to detect brain haemorrhage and breast cancer. Now, scientists at Uppsala University, in collaboration with researchers at Lund University, the Karolinska Institute and Chalmers University of Technology, have used computer algorithms to design a new treatment for neuroblastoma.
Neuroblastoma is a potentially life-threatening cancer that occurs in special nerve cells of the sympathetic nervous system. The paper, published in Nature Communications, entitled “Comprehensive Treatment Findings for High-Risk Neuroblastoma,” notes that “about 50 percent of high-risk neuroblastoma patients lack effective treatment.” “
The team used intelligent algorithms to analyze genetic and pharmacological data from hospitals and universities in Europe and the United States. The algorithm then proposed new therapies that might affect the basic mechanisms of neuroblastoma. Subsequently, the researchers established CNR2 and MAPK8 as promising drug candidates for the treatment of high-risk neuroblastoma. One of the proposed treatments inhibits tumor growth by activating the receptor protein CNR2 (cannabinoid receptor 2) in the nervous system. Similarly, the protein kinase 8 (MAPK8), which promotes the activation of the proto-split progenitor, plays the same role.
The team then characterized selected targets in more than 700 RNA mapping experiments in drug-treated neuroblastoma cells and showed that interfering with two drug targets, fissure-acting protein kinase 8 (MAPK8) and cannabinoid receptor 2 (CNR2), inhibited tumor growth in zebrafish and mouse xenotransplant models. All in all, these results deepen researchers’ understanding of neuroblastoma vulnerability and provide tools for data-driven cancer target discovery.
Smart algorithms are becoming increasingly important in cancer research because they can help scientists find unexpected angles, researchers say.