John van Geest Cancer Research Centre

Clinical Proteomics

A key objective in the application of translational proteomic technologies towards the clinical management of patients is the development of diagnostic and predictive assays capable of aiding clinical decision making in a patient specific manner i.e., "personalised medicine".

The rapid and continued development of mass spectrometry instrumentation for evaluating proteins, combined with the availability of the human genome sequence and the other genomic databases has allowed unprecedented possibilities for characterising the proteomes of humans in the post-genomic era.

The Clinical Proteomics group is using a variety of proteomic mass spectrometry methods for early cancer diagnosis and prognosis research and characterisation of emerging vaccine research.

The primary cancers being targeted are prostate and breast cancer and a bio-repository has been established in conjunction with our clinical collaborators at The Urology Centre, Nottingham City Hospital. This tissue bank includes a range of patient samples which provides us with the bulk of our prostate cancer resource. This bank contributes material to the Clinical Proteomics Group as well as the Tumour Immunology and Molecular Genetics group.

Our current and on-going clinical proteomic research has stemmed from our previous FP6 EU-funded project (ENACT) which was co-ordinated by Professor Rees here at Nottingham Trent University.

Discovery of Biomarkers of Cancer Progression
Blood constitutes a potentially rich source of biomarkers that may reflect the state of the individual organism. The principle approach employed for our studies is "bottom up" proteomics where samples are fractionated and identified using MALDI-TOF-TOF hence enabling peptide sequencing and identification of the parent protein from which they are derived to be elucidated using MASCOT database to interogate protein sequence databases.

Tissue Imaging with MALDI mass spectrometry
Imaging is a valuable technique for the identification of changes in tissues related to diseases. Traditionally this has been performed using immunohistochemistry, for single markers.

Mass spectrometric imaging (MSI) of tissue is achieved by collecting a mass spectrum at every point on the tissue and then plotting intensities for individual masses across the whole tissue.

We are developing methods in MSI to image both benign and malignant prostate tissue to identify markers and underlying biochemistries. Using statistical methods we hope to be able to discriminate disease regions and markers for disease with a high confidence and reliability and use these predicatively in the future as clinical biomarkers.

We are also developing methods to identify markers directly from the tissue using MS and LCM techniques.

Investigating Biomarkers of Therapy Response
Clinical proteomics has the capability to define disease prognoses that may aid in determining the need for more or less aggressive therapies. In addition, clinicians may soon be able to use a patient’s specific proteomic profile to rationally select molecular therapy and then use proteomic analysis to monitor the disease response.

Proteomic characterisation of Immune and prostate cancer stem cells
A number of multi-disciplinary studies integrating clinical proteomic characterisation of the immune cells in prostate cancer patients have recently been initiated. It is anticipated that these studies will provide new biomarkers that may be used as a potential therapeutic targets and help further our understanding of tumour escape mechanisms. Other translational efforts will also focus on proteomic pathway characterisation of prostate cancer stem cells in collaboration with colleagues at University of York.

Validation / QC
We believe in order to have confidence in proteomic results we have to adopt rigorous QA and QC procedures. We have acquired over 12 months of data from our Bruker Ultraflex III instrument and we aim to create a statistical model that can be used rapidly to accept or reject a sample set based on the quality of the QC’s within each experiment. We have a number of collaborations formed for this part of our research.