SurgicAl Metabolic Phenotyping Longitudinal Evaluation Study

This work will use a new approach to measure how surgery effects human biochemistry and metabolism. It will create a metabolic signature or 'phenotype' for surgical injury that will help clinicians choose the right surgical treatments for an individual. This is because metabolism is based on an individual's genes, disease burden and environmental influences such as gut microbiota. This study will use a scientific method based on computational analysis of spectra taken from techniques known as Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) spectroscopy. This science is called 'metabonomics' and it has many advantages. Firstly, it provides a measure of thousands of metabolites at a single moment in time that are unique to the individual and it therefore gives a 'systems' overview of a persons metabolism. Secondly it is able to process many hundreds of samples quickly. The investigators are aiming to integrate the investigators metabolic data with genetic information about patients or bacteria wherever possible. This will be the first time that a 'systems biology' approach has been used in surgery, with potentially significant gains to me made in pre operative risk stratification and optimisation. By performing this analysis at all stages of the surgical journey (preoperatively, during the operation and after the surgery) it will ensure the right treatments are given to the right patient at the right time. By creating longitudinal models of the biochemical responses to surgery, predict at a much earlier stage those patients at risk of developing complications. This will improve outcome after surgery. This work will use a metabonomic approach to create new tools for surgeons to use during operations based on tissue biology. For example the investigators will be able to measure the metabolic content of tumours in real time by measuring the biological content of diathermy smoke. This has the potential to change intra-operative decision making and further improve outcome.

Sex

All

Minimum age

18 Years

Inclusion Criteria:

1. Elective surgery (n=200)

   * Patients with cancer. This will include patients with malignancy of the gastrointestinal and colorectal tract (including those excised by microsurgery)cancer of the breast or solid tumours of the kidney.
   * Patients with benign disease of the bowel requiring surgery e.g. inflammatory bowel disease
   * Benign surgical conditions, usually operated on in a day surgery setting. These will specifically be of the biliary tree (gall stones) and the anterior abdominal wall (e.g. Hernia surgery)
   * Patients will be recruited if seen under the 'two week' wait rule with suspected cancer for the general surgery, upper GI surgery, Breast and Urology surgery teams at St. Mary's hospital in the outpatient setting will be recruited
   * Patients attending for elective inpatient surgery under the general, upper GI or breast surgery teams at St. Mary's hospital, London will be recruited at the pre admission clinic.
2. Acute surgery (n=200) Patients presenting to Accident and emergency under the care of the general surgery on call team will be recruited into this study group. This study group will have the following subgroups:

   * Acute abdominal pain
   * Patients with acute sepsis thought to be of surgical origin as diagnosed by their history, clinical examination and routine investigations.
   * Patients suffering major trauma with an Injury severity score (ISS) of \>15, multiple injuries, who require surgery or who have \>1 organ system that is failed or who are admitted to the intensive care department.

Exclusion Criteria:

* All patients under the age of 18 years
* All patients who are pregnant
* Patients receiving Advanced Life Support by cardiopulmonary resuscitation on their arrival in hospital.
* Patients with advanced cancer only suitable for palliative care at presentation to the clinical team.
* Patients presenting for the first time with other known malignancies for which they are receiving treatment e.g. Prostate cancer
* Patients already recruited into other clinical studies.

• BACKGROUNDKinross JM, Holmes E, Darzi AW, Nicholson JK. Metabolic phenotyping for monitoring surgical patients. Lancet. 2011 May 28;377(9780):1817-9. doi: 10.1016/S0140-6736(11)60171-2. Epub 2011 May 17. No abstract available. PMID 21596428
• BACKGROUNDLi JV, Ashrafian H, Bueter M, Kinross J, Sands C, le Roux CW, Bloom SR, Darzi A, Athanasiou T, Marchesi JR, Nicholson JK, Holmes E. Metabolic surgery profoundly influences gut microbial-host metabolic cross-talk. Gut. 2011 Sep;60(9):1214-23. doi: 10.1136/gut.2010.234708. Epub 2011 May 14. PMID 21572120
• BACKGROUNDKinross JM, Darzi AW, Nicholson JK. Gut microbiome-host interactions in health and disease. Genome Med. 2011 Mar 4;3(3):14. doi: 10.1186/gm228. PMID 21392406
• BACKGROUNDKinross JM, Alkhamesi N, Barton RH, Silk DB, Yap IK, Darzi AW, Holmes E, Nicholson JK. Global metabolic phenotyping in an experimental laparotomy model of surgical trauma. J Proteome Res. 2011 Jan 7;10(1):277-87. doi: 10.1021/pr1003278. Epub 2010 Nov 24. PMID 21105667
• BACKGROUNDKinross J, von Roon AC, Penney N, Holmes E, Silk D, Nicholson JK, Darzi A. The gut microbiota as a target for improved surgical outcome and improved patient care. Curr Pharm Des. 2009;15(13):1537-45. doi: 10.2174/138161209788168119. PMID 19442171
• BACKGROUNDNicholson JK, Wilson ID, Lindon JC. Pharmacometabonomics as an effector for personalized medicine. Pharmacogenomics. 2011 Jan;12(1):103-11. doi: 10.2217/pgs.10.157. PMID 21174625
• BACKGROUNDBeckonert O, Coen M, Keun HC, Wang Y, Ebbels TM, Holmes E, Lindon JC, Nicholson JK. High-resolution magic-angle-spinning NMR spectroscopy for metabolic profiling of intact tissues. Nat Protoc. 2010 Jun;5(6):1019-32. doi: 10.1038/nprot.2010.45. Epub 2010 May 13. PMID 20539278