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Diagnostic Peptide pattern for early stage disease detection


Cancer is one of the most common diseases. Because it is only diagnosed after serious patient symptoms, earlier detection of cancer and earlier treatment can result in patient benefits and reduction of healthcare costs. The approach to go for an earlier treatment requires diagnosis with more sensitive equipment and new ways of diagnosis. For this the use of proteomics to identify prognostic markers for cancer diagnosis is relevant. This multi-analyte technique offers the potential to utilize not only single markers, but also to base a diagnosis on marker combinations. These act as a statistically "fingerprint" to discriminate between patient groups.

Profiling peptides of bodily fluids by mass spectrometry (MS), followed by data mining for MS patterns indicative of diseases in an early stage is seen as a very promising, cost effective approach with diagnostic potential. Also, the combination of this with diagnostic imaging (DI) is even more interesting; this combination to screen and pre-select patients before using imaging optimises the related costs. This ToK proposal is part of the development and clinical acceptance of mass spectrometric peptide patterns (MSPPs) for diagnostic use. This tool is presently still in a research phase in laboratories. Philips considers this project part of a larger scheme to evaluate, improve, and commercialise MSPP as a tool linked to its imaging technologies (both diagnostic and animal imaging).

The areas of proteomics, biomedical and clinical chemical knowledge as well as the dev. of a molecular diagnostic platform require researchers with different background and practical medical experience. Currently, Philips has no access to such background or the experience for medical trials. This proposal aims at getting access to this knowledge by hosting two researchers. We plan to combine MSPP-related know-how then available within the MC project with materials, technologies, and procedures available at Philips Research Aachen.

Field of science

  • /natural sciences/biological sciences/biochemistry/biomolecules/proteins/proteomics
  • /natural sciences/chemical sciences/analytical chemistry/mass spectrometry
  • /medical and health sciences/clinical medicine/cancer/prostate cancer
  • /engineering and technology/medical engineering/diagnostic imaging
  • /natural sciences/computer and information sciences/data science/data mining

Call for proposal

See other projects for this call

Funding Scheme

TOK - Marie Curie actions-Transfer of Knowledge


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