The research is conducted in collaboration between ICAR-CNR (L. Maddalena, I. Granata, I. Manipur, M.R. Guarracino) and the University of Naples “L’Orientale” (M. Manzo).

In this work, an omics imaging approach to the classification of different grades of gliomas is proposed, which are primary brain tumors arising from glial cells. Omics imaging is an emerging interdisciplinary field concerned with the integration of data collected from biomedical images and omics experiments. Bringing together information coming from different sources, it permits to reveal hidden genotype-phenotype relationships, with the aim of better understanding the onset and progression of many diseases, and identifying new diagnostic and prognostic biomarkers. Imaging data considered in this research come from analyses available in The Cancer Imaging Archive, while omics attributes are extracted by integrating metabolic models with transcriptomic data available from the Genomic Data Commons portal. The results of feature selection are investigated for the two types of data separately, as well as for the integrated data, providing hints on the most distinctive ones that can be exploited as biomarkers for glioma grading. Moreover, it is shown how the integrated data can provide additional clinical information as compared to the two types of data separately, leading to higher performance.