09/H0504/6

Southampton and South West Hampshire LREC (B)

Nottingham City Hospital

Cancer biomarker, molecular and immunological characterisation

Cancer biomarker, molecular and immunological characterisation

Permission to publish contact details not yet received

Permission to publish contact details not yet received

We will collect blood samples from which we will harvest the DNA/RNA and the remaining will be sample serum/plasma all of which will be stored for research purposes. If possible urine will also be collected and stored for research analyses. For the purpose of this proposal "tissue bank" refers to collected serum/plasma, DNA/RNA and urine.

N/A

The existence of the bank will be advertised via Nottingham University Hospitals Trust and Nottingham Trent university. The samples stored in the tissue bank will be made available to other researchers providing their research is scientifically sound. Research proposals will all be subject to an internal review with structured applications being made to the research coordinator, Mr Owen Cole. Each proposal will then be considered taking into account the quality of the proposed research, the available expertise of the researchers and available research facilities and funding. Samples will be supplied for free except for the transport costs.
The results of the research and data gained from the samples will be made available to the public through peer reviewed publications. All patients will be covered under the NHS indemnity scheme as well Nottingham Trent university's indemnity scheme.

The research on samples stored in the tissue bank will relate to cancer, and under the umbrella of the John Van Geest Cancer Research Centre (JVG CRC) headed by Prof. Robert Rees at Nottingham Trent University. Research will be carried out by a team of scientists in the fields of biomarker and antigen discovery and molecular and immunological characterisation and overall analysis will entail sophisticated computer alogrithms by a team of bioinformaticians. The serum/plasma and urine samples will be analysed with various scientific methods including proteomics, which relies on testing minute amounts of sample for proteins and peptides, "screening", present in the samples. This method allows us to identify new markers of cancer. The analysis of identified markers is usually very complex and requires specialised computer programs to identify the markers that occur most frequently and have prognostic value. Additionallty, antigen discovery will be also carried out using patient sera which targets a patients antibody reportoire toward an anitgen library. The reactive "spots" are then identified using sequence analysis by PCR based techniques. In this way we can identify new tumour markers which may have the potential as future diagnostic markers or therapeutic targets. Serum/plasma will be used to characterise immunological responses against cancer associated antigens using techniques such as ELISA and western blotting. The results from this study will allow us to develop better and more effective cancer vaccines . The full results from all studies will then be analysed in conjunction with clinical data, the disease stage, response to treatment, rate of progression and clinical outcome using bioinformatics. We would collect the data and patients would receive information with regards to data collection. No data or samples would be collected without informed consent.
Patients who are diagnosed with prostate cancer will then be followed up every six months. We would ensure that any repeat sample collection (blood and urine only)coincides with the routine follow up appointment and we would collect a minimum set of clinical data at the same time again with patient consent. The data would include the current status of the disease i.e. confined within the prostate or metastatic, current treatment, response to current treatment, PSA level and general performance status. After 12 to 18 months of sample and data collection we would analyse the serum/plasma, DNA/RNA and urine using immunological and molecular biological technique and proteomics. This analysis will be undertaken in collaboration with The JvGCRC at Nottingham Trent University as outlined above. Also data analysis would be carried by our collaborators as they have expertise in proteomic and bioinformatic analysis using artificial neural network, a form of machine learning capable of accurately modelling biological systems and identifying biomarkers.
We would aim to identify changes in biomarker profile, antigen expression, molecular and immunological characterisation relating to cancer stage and cancer grade in newly diagnosed cancer, following radical treatment, in patients on hormonal treatment, in patients with hormone–resistant disease and in patients with metastatic disease at a hormone-sensitive and hormone-resistant stage.

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