New tool can detect pancreatic cancer more effectively than current tests

August 4, 2009
By admin

cancer patientsVan Andel Research Institute (VARI) scientists have developed a new tool that can detect pancreatic cancer much more effectively than current tests.

Pancreatic cancer is one of the deadliest forms of cancer due to the difficulty of diagnosing it in its early stages.

The method, which studies carbohydrate structures in the bloodstream, could lead to the development of blood tests that can detect cancer more effectively.

“Tumour cells sometimes shed proteins into a patient’’s bloodstream. These proteins can have carbohydrate structures attached to them that might be able to tell us not only if a patient has cancer, but also more about the cancer and how to treat it,” said VARI Senior Scientific Investigator Dr. Brian Haab.

The current, most-commonly-used method of blood testing for many types of cancer is by associating specific carbohydrate alterations on proteins with cancer, which could provide better cancer detection than the measuring of protein levels alone.

Haab said that specific alterations also could be connected to specific cancer characteristics, such as the ability to spread or resistance to therapy.

Some carbohydrate alterations also could have distinct functions in cancer progression, which might have therapeutic value.

The researchers used the method to study blood samples from pancreatic cancer patients at Evanston Northwestern Healthcare in Illinois and they identified the prevalence of a variety of alterations on different proteins.

“Interestingly, the protein with the most alterations was not previously recognized as a marker for pancreatic cancer, perhaps because the protein level alone did not provide good cancer detection. This protein is found in pre-malignant lesions and could be valuable for early detection if we can find unique alterations associated with it,” said Tingting Yue, lead author of the study.

The study has been published in the journal Molecular & Cellular Proteomics.

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