Protein Patterns in Blood May Predict Prostate Cancer Diagnosis
Patterns of proteins found in patients' blood serum may help distinguish between
prostate cancer and benign conditions, scientists from the National Cancer
Institute (NCI) and the Food and Drug Administration (FDA) report today in the Journal
of the National Cancer Institute*. The technique, which relies on a
simple test using a drop of blood, may be useful in deciding whether to perform
a biopsy in men with elevated prostate specific antigen (PSA) levels.
Using a test that can analyze the patterns of small proteins in blood serum
samples in just 30 minutes, researchers were able to differentiate between
samples taken from patients diagnosed with cancer and those from patients
diagnosed with benign prostate disease. The technique proved effective not only
in men with normal and high PSA levels, but also in those whose PSA levels were
marginally elevated (4 to 10 nanograms of antigen per milliliter of fluid), in
whom it is difficult to rule out cancer without a biopsy.
Although the technique is still under evaluation, researchers believe the
analysis of protein patterns will be a useful tool in the future for deciding
whether men with marginally elevated PSA levels should undergo biopsy. PSA
levels are commonly used as a preliminary screen for prostate cancer, but 70
percent to 75 percent of men who undergo biopsy because of an abnormal PSA
level do not have cancer. The new proteomic approach has a higher specificity -
that is, of the samples the test identifies as cancer, a large percentage are
in fact cancer, rather than some other benign disease.
"For men with marginally elevated PSA levels, the specificity of the test is 71
percent, as opposed to a very low specificity for PSA in this range," said
Emanuel Petricoin III, Ph.D., of the FDA's Center for Biologics Evaluation and
Research, the first author of the study. "We hope that by using proteomic
pattern analysis screening in combination with other screening methods, we can
reduce the number of unnecessary biopsies for prostate cancer in the future."
The diagnostic test relied on computer software that detects key patterns of
small proteins in the blood. Researchers analyzed serum proteins with mass
spectroscopy, a technique used to sort proteins and other molecules based on
their weight and electrical charge. They then used an artificial intelligence
program developed by Correlogic Systems, Inc., in Bethesda, Md., to train a
computer to identify patterns of proteins that differed between patients with
prostate cancer and those in which a biopsy had found no evidence of disease.
These patterns were identified using serum samples from 56 patients who had
undergone a biopsy and whose disease status was known.
Once established, the protein patterns were then used to predict diagnosis in a
separate group of patients, whose biopsy results were not known by the
researchers. From this group, researchers were able to correctly identify 36 of
38 (95 percent) cases of prostate cancer and 177 of 228 (78 percent) cases of
benign disease.
The study follows up on the recent finding by the same research group that
protein patterns in serum can be used to detect ovarian cancer. "We have now
demonstrated that combining proteomic technology with artificial intelligence
based bioinformatics can be a powerful tool, and is a new paradigm in the
detection and diagnosis of both ovarian and prostate cancers," said Lance
Liotta, M.D., Ph.D., the senior investigator on the study from NCI's Center for
Cancer Research. "We are extremely optimistic that this new approach will prove
useful in detecting and diagnosing many other cancers and diseases in the
future."
* Petricoin EF, et al. Serum proteomic patterns for detection of prostate
cancer. Journal of the National Cancer Institute 2002;94:1576-1578.
For an interview, animation, and other supplemental materials on the science of
proteomics, please go to a February 2002 issue of NCI's "BenchMarks" at
http://www.cancer.gov/newscenter/BenchMarks-vol2-issue2.
Back to Top |