The possibility of patients with pancreatic cancer being able to have their cancer tissue 'profiled' to understand how they will react to different treatments before they are given to them has moved a lot closer, a new research paper shows, published in the peer reviewed journal PLOS ONE. This will enable more accurate profiling and the best drug selection for each individual. Trials are being planned to undertake the final stage of the process.
A recent study by UK Biosciences company, Proteome Sciences plc, in collaboration with leading academic partners King's College Hospital, Imperial College London and the University of Cardiff, has shown this new method of analysis, using a system known as 'SysQuant' developed by Proteome Sciences, can unravel the chain of complex molecular activity that leads to and propagates cancer and be used to accurately predict how specific drug treatments will affect different patients with pancreatic cancer.
This new technique, which does not increase the overall cost of treatment, will provide doctors with information that will allow them to select which therapy will best work on an individual patient using existing medicines, something which to date has not been possible to achieve in most types of cancer. The researchers hope this will soon be applied across all cancers.
In the study, tumour, or cancerous tissue from 12 pancreatic cancer patients was analysed involving over 2,100 proteins and 6,284 unique phosphorylation sites (which are common in modulating the activity of cancer suppressing proteins) being surveyed in each sample.
Commenting on this study, Professor Nigel Heaton, Professor of Professor of Liver Transplant, Hepatobiliary and Pancreatic Surgery at King's College Hospital said: "Cancer is caused by a chain reaction of many different chemicals in the body. Treatment looks to disrupt that chain reaction but how we do this can vary hugely from one person to the next. "Understanding the chemical make-up of an individual patient will help us understand which patients will respond to treatment. At the moment, only 20% of patients will respond to standard treatment for pancreatic cancer so this new technology will help us predict beforehand which patients are most likely to respond and which will not.
"If we know what treatments will be the most effective before we administer them this gives us a huge advantage to help patients as well as save the NHS money by eliminating spending on treatments that won't work.
"It is a hugely promising step forward, not just for patients with pancreatic cancer, but for all people with cancer."
Dr. Debashis Sarker, Senior Lecturer and Consultant in Medical Oncology at Kings College Hospital, London added: "The PLOS ONE paper shows the critical cancer proteins and pathways that are deregulated for each patient in pancreatic cancer using SysQuant. These differ from patient to patient indicating the need for a personalised approach to each patient's treatments. Clinical trials should now be designed to compare standard therapy approaches compared to matching aberrant protein pathways with specific targeted therapies."
Professor Justin Stebbing, Professor of Cancer Medicine and Medical Oncology, Consultant Oncologist, Imperial College London and Imperial College Healthcare NHS Trust said: "This work demonstrates the network of interactions, the fingerprint and signature of phosphorylation events in cancer. It provides an opportunity to study some of the major tumorigenic events in a test tube using the very latest in mass spectrometry-based technologies. This is the way forwards in cell signalling".
Referring to the study, Dr. Ian Pike, Chief Operating Officer at Proteome Sciences, commented: "This study is the first peer-reviewed article using the SysQuant® technology, which in this case identified the common and unique molecular events involved in pancreatic cancer. The results clearly demonstrate the potential to significantly improve the way bespoke treatments can be matched to each individual patient, prior to the administration of any drugs, using already approved medicines.
"This technology can also be used for the analysis of tissues across a range of different diseases including all other cancers. Furthermore it can be utilised to assess drugs which are in pre-clinical development much more efficiently and cost effectively than is currently possible."