Monday 18 August 2008

Prototype Test For Predicting Clinical Outcome For Melanoma Patients - Gene Signature Prognostication Of Rapid Progression From Stage III To Stage IV

�Investigators from the Melbourne Center of the external Ludwig Institute for Cancer Research (LICR) and Pacific Edge Biotchnology Ltd today reported that they get developed a test to predict whether a patient will advance rapidly from Stage III melanoma to metastatic Stage IV crab and last.


More than 70% of patients with Stage III melanoma - melanoma that has bedcover to the lymph nodes - testament typically possess a rapid time to progression (TTP) to Stage IV malignant melanoma, and pass by away inside five years of their diagnosis. However, the unexpended

The LICR Melbourne team, together with collaborators from Pacific Edge Biotechnology Limited in New Zealand, has developed a prototype test that throne distinguish between these deuce patient subtypes with 85-90% accuracy. However, the team cautions that these findings must be validated in a larger number of patients ahead the test can be applied routinely as a prognostic instrument.


According to the senior author of the study, LICR's Professor Jonathan Cebon, M.D., the predictive test could assist patients and their wellness care teams in making treatment decisions. Perhaps near importantly, organism able to distinguish 'tween the subtypes could have a enormous impact on the development of new melanoma therapies. "One of the major problems we have in clinical trials for new melanoma therapies is that we can't identify the people wHO are departure to have a slower disease progression no matter what they receive in a clinical trial," says Professor Cebon. "When newfangled treatments ar tested it is necessary to evidence clinical benefit by comparison patients world Health Organization receive the new therapy with those who do not. Although patients power all make the same type of cancers, there can be big differences in their survival simply because their cancers bear differently - and this may take in nothing to do with the treatment. If we are able to identify the salutary players and the bad players upfront, it becomes a whole lot easier figuring out whether ripe results ar due to the new treatment or not. Most importantly far fewer patients would be needed for the clinical trials. It's partly because we can't clinically identify subtypes of patients that we consume to do very gravid and identical expensive trials. And, of course, this increases the time it takes to test the clinical welfare of voltage new therapies."


The joint Australian/New Zealand team used microarrays to measure the expression of more than 30,000 genes in lymph lymph node sections taken from 29 patients with Stage III melanoma. There were 2,140 genes differentially expressed in the sections from people wHO had already had a "poor" termination (average TTP of simply four months) and patients that had had a "good" final result (average TTP of 40+ months). Using statistical analyses, the squad identified 21 genes that could be used to differentiate betwixt the deuce subtypes of patients in the retrospective analysis. This gene signature was then used to prospectively psychoanalyse another 10 patients, with the clinical outcome for nine of the 10 (90%) patients proving to be predicted accurately. The one affected role who was incorrectly predicted to stimulate a "upright" prognosis did have a rapid TTP to Stage IV. However, this patient went on to have a extended survival of six years. The team also applied the examine to published data sets and showed they could get a prediction accuracy of 85%, event though data was not available for all 21 genes in the published literature.


This study was conducted under the auspices of the Hilton - Ludwig Cancer Metastasis Initiative. It was lED by investigators from: LICR Melbourne Center Austin Health, Melbourne, Australia; Department of Biochemistry, University of Otago, Otago, New Zealand; Pacific Edge Biotechnology Limited, Dunedin, New Zealand, and; Department of Statistics, University of Auckland, Auckland, New Zealand.


Source - Sarah L. White
Ludwig Institute for Cancer Research


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