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DURHAM, N.C. – Researchers at Duke University Medical Center have developed a new technique that can rapidly determine differences between lung cancer tissue and normal lung tissue by measuring subtle variations in the proteins they produce.

The new technique identifies proteins that are produced in different amounts in diseased tissue compared with healthy tissue. Even small amounts of a protein can be important in cancer if is produced in the wrong tissue or in excessive amounts, said Edward Patz, Jr., M.D., professor of radiology and professor of pharmacology and cancer biology at Duke. Yet measuring low levels of proteins has proved extremely difficult using the traditional methods of protein detection, he said.

Patz said his new method, called ADEPPT -- accentuation of differentially expressed proteins using phage technology -- may ultimately enable researchers to detect proteins responsible for all types of cancer and potentially assist them in finding better drug targets to treat various diseases. Their study in lung cancer tissue provided "proof of principle" that ADEPPT can pick up proteins in lung cancer that are overlooked by more conventional methods of protein profiling.

"Increasingly, cancer diagnosis and treatment will become dependent upon isolating the proteins responsible for disease and using these proteins to develop targeted therapies aimed at blocking or enhancing them," said Patz. "But much of our time is spent on isolating which proteins are relevant to a particular cancer, and if we could speed that process, we may be able to develop new therapies."

Patz' team described their new technique in the Oct. 15, 2004, issue of the journal Analytical Biochemistry.

While every type of cancer produces its own unique concoction of proteins, detecting which proteins are relevant to the cancer has proved challenging, said Patz. ADEPPT was designed to boost or amplify levels of proteins that are produced in varying levels within both diseased and healthy tissues. ADEPPT allows even those proteins that are present at very low levels to be detected and identified – a step that is hard to achieve with conventional methods of profiling proteins such as 2-D gel electrophoresis and mass spectrometry, he said.

This information could also be used for early detection of cancers – for example by testing for elevated levels of proteins in the blood – which could potentially improve the chance of successful treatment. It could increase physicians' understanding of how diseases began and how they progress.

With lung cancer, the need for progress is particularly acute, the researchers said. It remains the most common cancer in the U.S., accounting for 32 percent of cancer deaths in men and 25 percent in women, according to the American Cancer Society. Despite extensive research efforts in genomics, drug discovery and screening, the overall five-year for lung cancer survival remains at around 14 percent. This has changed little over the last several decades. Alternative diagnostic and therapeutic strategies could clearly provide great benefits to patients, said Patz.

In a unique approach, ADEPPT uses bacteriophage - viruses that infects bacteria – to amplify proteins. This is the first time that bacteriophages have been used in this way, said Patz.

The study used a large "library" with thousands of strains of the bacteriophage known as M13. Each strain of M13 makes a different protein building block called a "peptide," and every peptide binds to a specific protein. By using a large bacteriophage library, the researchers had the best possible chance of detecting all the proteins that were produced at varying levels in different tissue samples.

The Duke study used the ADEPPT method to identify proteins that are produced in lung cancer tissue but not in normal cells. While lung cancer was used as the model, ADEPPT could be applied to any tissue or blood sample, said Patz.

"Further development of the ADEPPT method is needed, but initial indications are that it may complement existing methods – such as 2-D gel electrophoresis - by detecting less abundant proteins," said Patz. "This approach could be used in a wide range of disease types."

ADEPPT won't necessarily identify the full range of proteins that might be produced at different levels in different tissue samples, said Patz. But it has promise in recognizing proteins that might be missed by standard techniques and could provide an alternative strategy to understanding, detection and treatment of diseases.