Researchers from the Department of Bioinformatics of the Cyprus Institute of Neurology and Genetics (CING) have published a new study in the journal Cancers, which opens new avenues for the accurate staging and early detection of Multiple Myeloma (MM), a complex and dangerous form of blood cancer
The research was carried out by Dr. Nestos Karathanasis, a postdoctoral researcher at the Department of Bioinformatics, in collaboration with Dr. George Spyrou, Director of the Department of Bioinformatics, with funding from the European ELMUMY project, which focuses on investigating risk factors for the progression of monoclonal gammopathies (MGUS) in multiple myeloma.
Study highlights:
- Developed machine learning models using gene expression data to accurately identify the stage of MM (MGUS or PM) and predict the progression of asymptomatic patients (MGUS) to symptomatic MM.
- The study used multiple gene expression data and multiple artificial intelligence algorithms achieving high accuracy in identifying the stage of MM as well as predicting the progression of asymptomatic patients.
- AI models identified molecular features associated with biological mechanisms (PI3K-Akt, MAPK, Wnt and mTOR pathways) that are important in the pathogenesis of MM.
This is, to our knowledge, one of the first studies to use gene expression data to classify patients at different stages of MM and to predict disease progression from asymptomatic cases. More information about the study can be found here: https://www.mdpi.com/2072-6694/17/2/332.
Source: The Cyprus Institute Of Neurology & Genetics | News & Events | Media (https://shorturl.at/g0eDH)