Lab-On-Chip based protein profiling for CANcer DIAgnosis (LOCCANDIA)

Grunddaten zu diesem Projekt

Beschreibung

The human plasma proteome holds the promise of a revolution in disease diagnosis and therapy. One major breakthrough should come from the detection of multiprotein disease markers including isoforms. We propose to integrate a full proteomics analysis chain, from blood sample to the diagnosis information, combining bio-, nano, and information-related technologies. It includes an innovative patented lab-on-chip developed at CEA. The clinical application is early pancreatic cancer diagnosis.The project is based on a panel of 3 identified proteins, a protein isolation protocol, an optimised chromatographic-electrospray lab-on-chip, an Integrated Clinico-Proteomics Environment including a Proteomic Information Management System, a Clinical Information System, and modules for pre-processing, reconstruction, visualisation, protein identification, data mining and knowledge discovery. The clinical validation is applied to a cohort of 92 patients. Our targeted performance is to get at least the sensitivity of an orthogonal ELISA approach, to operate the analysis chain in less than 12 hours, and to demonstrate the interest of multiprotein marker.The main research outcomes will be an optimised chromatographic-electrospray lab-on-chip, a software environment supporting the integrated device, a proof-of-concept of their application to protein profiling for cancer diagnosis and an exploitation plan.The roadmap of this 36 months project is defined according to three main milestones:1) at month 12, a first protein profile using a first version of the lab-on-chip on artificial samples is available,2) at month 24, all the final versions of the sub-systems are ready for integration and validation,3) at month 33, the validation on clinical samples is completed.The consortium partnership involves partners over 5 countries, combining basic and applied research (CEA, FORTH, SIB, WWU), 1 large company (ATOS) and 2 SMEs (BVN, GB), including clinicians and end-users (WWU, BVN).