By using a unique combination of database information, intelligent computer algorithms and experimental measurements, an ideal focal point for cancer diagnostics and therapy was established. The hope is that the research could lead to an effective system for diagnosing and treating cancer based on immune reactions.
The team, based at The Medical University of Vienna, (MUW), concentrated on ovarian cancer - the fifth leading cause of cancer deaths in women in the US and the leading cause of death from gynaecological malignancy.
Cancer cells can provoke an immune response in the body. These responses are caused by proteins that are unique to cancer cells or adopt a different form to that found in healthy cells.
Numerous surface structures of these proteins - or antigens - offer points of attack for the immune system, even if they only rarely enable the tumour to be eliminated.
The team identified a total of 86 proteins that occurred most prominently in cancer cells, narrowing this group down to 31 proteins. This was achieved using a strategy that combined systems biology with clinical findings.
A programme, developed in-house, was used to compare and analyse publicly available data on important ovarian cancer proteins. As a result, it was possible to review the group of altered proteins that appear in cancer cells much faster than normal.
These proteins were then tested for immune reactivity using the blood serum from ovarian cancer patients. Test results revealed that an immune response was initiated between the proteins and the blood serum.
The next step was to identify exactly which proteins were causing an immune response in the patients. Exact protein identification was necessary to ensure an ELISA Assay could be performed accurately.
"The use of intelligent computer algorithms is essential when seeking to identify clinically relevant epitopes (three-dimensional surface feature of an antigen molecule that is recognised by an antibody)," said Professor Michael Krainer, an oncologist at the Department of Internal Medicine at MUW.
"Each protein has several surface structures, but only a small number are relevant. If the wrong epitopes are tested it will not be possible to identify the immunogenicity of the protein in question, even though it does exist due to other epitopes. We used a programme that draws on an analysis of large volumes of data from experimentally verified B-cell epitopes. Their structures are known and have already been analysed," he added.
Krainer's team were able to identify 18 epitopes from 12 proteins that reacted to serum from the patients including an epitope known as TP53, already recognised as a cancer antigen. The recognition of TP53 was, according to Krainer, clear evidence of the accuracy of the algorithms used.
In addition, an epitope of a protein that has not previously been considered an antigen, or even linked to cancer, RNA helicase DDX21 was also recognised.
The publication, 'Linking the ovarian cancer transcriptome and immunome,' is published in the BMC Syst Biol. 2008 Jan 3;2(1):2 PMID: 18173842