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Breast Cancer News

Molecular Networks Predict Breast Cancer Survival With 80 Per Cent Accuracy

Main Category: Breast Cancer
Also Included In: Medical Devices / Diagnostics
Article Date: 04 Feb 2009 - 6:00 PDT

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A woman's chance of recovering from breast cancer can be predicted with more than 80 per cent accuracy, following the development of a new computer software called 'DyNeMo' that analyses changing patterns of protein activity within the body. These findings are reported in today's Nature Biotechnology journal.

The study found that women who survive breast cancer have subtle differences in how proteins behave within a network, compared with patients who eventually succumb to the illness.

These differences in protein activity can be then used to predict a newly diagnosed breast cancer patient and to direct clinicians and patients towards more appropriate treatments. In the future, this prognostic tool may also identify multiple targets for drugs and might be a useful technology for predicting an individual's response to particular drugs.

The collaboration was led by Canadian PhD candidate Ian Taylor and performed by scientists at The Institute of Cancer Research (ICR) and the Samuel Lunenfeld Research Institute (Mount Sinai Hospital, Toronto, Canada). Data for more than 350 women with non-familial breast cancer were involved in this major study of network medicine.

Dr Rune Linding of The Institute of Cancer Research, co-researcher on the project, says:

"Our work is another significant step in the direction of network medicine, which aims to maximise knowledge of proteins to better direct drug development and cancer treatments. Solutions like this in the fight against cancer are becoming increasingly possible as we use computers to tackle the complexity of human biology.

"The identification of distinct network processes within our body that help predict cancer is a real step forward and we hope that it can help new therapies or screening techniques. The next step is to see if more networks can be identified and what other cancers we might be able to apply this to."

"Our hope with this technology is to eventually provide individualised analysis and prognosis to breast cancer patients so that they are better informed and empowered to select a treatment best suited to them." said Dr. Jeff Wrana, Senior Investigator and the Mary Janigan Research Chair in Molecular Cancer Therapeutics at the Samuel Lunenfeld Research Institute of Mount Sinai Hospital.

The research was funded by The Institute of Cancer Research, Genome Canada with funds from Ontario Genomics Institute, and the Canadian Breast Cancer Foundation.

Notes

1. The article is available from the Nature Biotechnology journal website (http://nature.com/nbt).
2. Breast cancer is now the most common cancer in the UK. Each year more than 44,000 women are diagnosed with breast cancer.

The Institute of Cancer Research

The Institute of Cancer Research is Europe's leading cancer research centre with expert scientists working on cutting edge research.

In 2009, the ICR marks its 100 years of groundbreaking research into cancer prevention, diagnosis and treatment. The ICR is home to the world's leading academic drug development team which has developed many drugs now used as standard cancer treatments. It continues to be at the forefront of drug development, taking 10 cancer drugs to clinical trial in the past 10 years. The Institute is a charity that relies on voluntary income. It is one of the world's most cost-effective major cancer research organisations with more than 95p in every £ directly supporting research. For more information visit http://www.icr.ac.uk.

About the Samuel Lunenfeld Research Institute of Mount Sinai Hospital

The Samuel Lunenfeld Research Institute of Mount Sinai Hospital, a University of Toronto affiliated research centre established in 1985, is one of the world's premier centres in biomedical research. Thirty-four principal investigators lead research in diabetes, cancer biology, epidemiology, stem cell research, women's and infants' health, neurobiology and systems biology. For more information on the Samuel Lunenfeld Research Institute, please visit http://www.lunenfeld.ca

Samuel Lunenfeld Research Institute of Mount Sinai Hospital


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