Principal component analysis of personalized biomolecular corona data for early disease detection

• Published in: Nano today Vol. 21; pp. 14 - 17
• Main Authors: Papi, Massimiliano, Caracciolo, Giulio
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2018
• Subjects: Biomolecular corona; Early disease detection; Nanomedicine; Personalized medicine; Principal component analysis; Biomolecular corona; Early disease detection; Personalized medicine; Nanomedicine; Principal component analysis
• ISSN: 1748-0132; 1878-044X
• DOI: 10.1016/j.nantod.2018.03.001

[Display omitted] •New therapies are improving care, but early diagnosis remains critical in the effective treatment of most diseases.•Identity of nanoparticles in biological milieu is derived from the biomolecular corona adsorbed on their surface.•Biomolecular corona is affected by individual changes in concentration and structure of plasma proteins as those produced by clinical manifestations.•Principal component analysis of biomolecular corona datasets will be a turning point in early detection of diseases. Today, early disease detection (EDD) is a matter of more importance than ever in medicine. Upon interaction with human plasma, nanoparticles are covered by proteins leading to formation of a biomolecular corona (BC). As the protein patterns of patients with conditions differ from those of healthy subjects, current research into technologies based on the exploitation of personalized BC patterns could be a turning point for early disease detection. Here, we present a framework based on principal component analysis of large personalized BC datasets. We comment on how principal component analysis of personalized BC data is a fundamental step towards turning the output of basic research into fast, safe and inexpensive technologies with superior prediction ability than current methods.