Attributing Meaning to Molecular Interaction Networks by Leveraging Clinical and Omic Data: The Missing Link between Tumor Biology and Treatment Strategies in Glioma

Abstract

The pace of data growth in the molecular space has led to the evolution of sophisticated approaches to data aggregation and linkages, such as IPA, STRING, KEGG, and others. These tools aim to generate molecular interaction networks harnessing growing molecular data at all levels to link tumor biology knowledge to signaling pathways and matched analyses. Potentially actionable biomarkers, however, are evaluated based on clinically associated prognosis, and necessary computational approaches should be vetted for interpretability through a clinical lens. Intersectional clinical and computational expertise is needed to link omics, molecular interactions, and clinical data to address the missing link between tumor biology and treatment strategies.