Study to develop lab-on-a-chip for cancer diagnosis
Imec and European partners join MIRACLE project
Belgian nanoelectronics researcher Imec and its European study partners have launched the MIRACLE project, which aims to develop a lab-on-a-chip for the isolation and detection of tumour cells in blood. The company says this lab-on-a-chip is an essential step towards faster and cost-efficient diagnosis of cancer.
The detection of circulating and disseminated tumour cells in blood is normally performed in medical laboratories and requires labour intensive, expensive and time-consuming sample processing and cell isolation steps. A full tumour cell detection analysis can take more than a day.
Imec says a lab-on-a-chip, integrating the processing steps, would enable a faster, easy-to-use, cost-effective detection of tumour cells in blood.
In an earlier joint project by some of the partners (MASCOT FP6-027652), individual microfluidic modules for cell isolation, cell counting, DNA amplification and detection have been developed.
Based on this expertise and strengthened by additional partners, the development of a fully automated, lab-on-chip platform to isolate, count and genotype CTCs is envisaged within the framework of the MIRACLE project.
For genotyping, genetic material (i.e. the mRNA) will be extracted from the cells and multiple cancer-related markers will be amplified based on multiplex ligation dependent probe amplification (MLPA) followed by their detection using an array of electrochemical sensors.
Imec is coordinator for the MIRACLE project and is collaborating with the Universitat Rovira I Virgili (Spain), the Institut für Mikrotechnik Mainz, AdnaGen, ThinXXs and Consultech (Germany), MRC Holland (The Netherlands), the Oslo University Hospital (Norway), the KTH Royal Institute of Technology, Multi-D and Fujirebio Diagnostics (Sweden), ECCO (the European CanCer Organisation) and ICsense (Belgium) and Labman (UK).
The project aims to develop an automated and integrated microsystem providing the genotype (gene expression profile) of CTCs and DTCs starting from clinical samples.
