Powerful Algorithm Could Help Cancer Researchers Understand The Disease

Doctors Meet AI! Researchers may be able to better understand cancer with the help of a powerful algorithm

Researchers at the University of Miami Miller School of Medicine’s Sylvester Comprehensive Cancer Centre have made an innovative discovery in the treatment of cancer. In collaboration with international researchers, an expert team has developed a cutting-edge artificial intelligence algorithm called Substrate Phosphosite-based Inference for the Network of Kinases (SPINKS). Using the algorithm, it is possible to perform complex computational analysis in order to determine potential treatments for patients suffering from Glioblastoma multiforme (GBM) and other types of cancer.

The National Health Institute describes glioblastoma multiforme as a fast-growing brain tumor that affects the central nervous system. GBM is the most common type of primary malignant brain tumor, and almost 90% of patients who are diagnosed with it will die within 24 months of diagnosis.

However, the recent study published in the journal Nature Cancer offers hope to patients suffering from GBM and other types of cancer. SPINKS AI has identified two protein kinases, which are vital targets in precision cancer treatment, which are connected to tumour progression in two subtypes of GBM and other cancers.

According to research author Antonio Iavarone, MD, and deputy director of Sylvester Comprehensive Cancer Centre, SPINKS will likely play a critical role in the development of new cancer therapies. The study, which used a variety of omics platforms, including genes, proteins, fat molecules, epigenetics, and metabolites, confirms the categorization of a previous study and allows SPINKS to create an interactome, a collection of biological interactions that identifies the kinases driving treatment resistance in each subtype of GBM.

SPINKS researchers are confident that the algorithm can be easily incorporated into molecular pathology laboratories. According to the study, a clinical classifier can identify the appropriate subtype of GBM for each patient, which may benefit approximately three-fourths of patients with GBM. Anna Lasorella, MD, co-senior author of the study and professor of biochemistry and molecular biology at Sylvester Comprehensive Cancer Centre, emphasized the immediate applications of the classifier in patient care.

SPINKS research could lead to a new clinical trial and have implications for other cancers, such as breast, lung, and child brain tumors. The same kinases that cause cancer were discovered in these tumors, making SPINKS a valuable tool in the fight against cancer.

As a result of the development of the SPINKS AI algorithm, the Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine has made an impressive discovery. The algorithm has the potential to change the way glioblastoma patients are routinely managed and offer new opportunities for precision cancer medicine.

Written by Aly Bukshi

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