SAB NewsClinical Proteomics Research Aids Cancer Diagnosis and TreatmentPosted 7/28/2003 The body's 25,000 or so genes carry the blueprint for making proteins, of which all living matter is made. Each protein has a particular shape and function that determine its role in the body. Cancer researchers are turning to "proteomics" - the study of protein shape, function, and patterns of expression - in hopes of developing better prevention, screening, and treatment options. Below is a summary of three recent advances in the field of clinical proteomics that have exciting implications for human health. Monitoring Cancer Treatment According to researchers from the National Cancer Institute (NCI) and the Food and Drug Administration (FDA), a new technique may allow physicians to monitor patients' responses to molecularly targeted drugs. Scientists have successfully identified specific proteins that may be useful in monitoring patients treated for breast or ovarian cancer. Their approach, based on changing levels of active proteins inside tumor cells, could help physicians determine early during treatment whether a particular drug is working effectively for an individual cancer patient. "The results of our study suggest this approach may help us tailor treatment to individual patients," noted Virginia Espina, M.S., M.T. (ASCP), NCI, the lead investigator on the study. Because molecularly targeted drugs are designed to target specific molecules that have gone awry in cancer cells, researchers can predict which of the cell's many complex signaling pathways these drugs are likely to affect. In ongoing studies at NCI, researchers are using proteomic technology to monitor the key pathways likely to be influenced by the molecularly targeted drugs Gleevec®, Herceptin®, and Iressa®. To monitor changes in tumor cell proteins, the researchers isolated cancer cells from tumor biopsies and measured the level of various proteins involved in the signaling pathways targeted by the drugs. The scientists measured not only the total amount of each protein, but also how much of the protein was in its active form. These proteins were measured prior to treatment and at selected times after treatment. The researchers found that prior to treatment, patients with breast cancer who had a poor clinical outcome tended to have more of the active form of a protein known as AKT, which promotes cell survival. Treatment with Herceptin®, however, resulted in a change in the relative amount of the active form of AKT, enabling tumor cell death. "Treatment with Herceptin® appears to alter the level of active AKT in tumors. We may be able to measure the degree of this change in patients who are receiving treatment to determine whether a drug that inhibits this signaling pathway is best for their individual cancer," said Lance Liotta, M.D., Ph.D., co-director of the Clinical Proteomics Program and the senior NCI investigator on the study. The researchers expect to be able to apply the proteomic approach to monitor the treatment of other cancers with molecularly targeted drugs, but further research is required to identify the best proteins to measure in those tumors. Diagnosing Ovarian Cancer Recently a study on computer-assisted detection of proteomic patterns in ovarian cancer was completed marking the first application of proteomic technology to patient diagnosis. NCI and FDA scientists in collaboration with Correlogic Systems Inc did this study. Mass spectroscopy was first utilized to analyze blood proteins to provide a snapshot of thousands of proteins. A new computer-based artificial intelligence algorithm, designed by Correlogic, identified diagnostic patterns of proteins in the blood and detected the presence of disease even at early stages. The initial assessment included 50 women with known ovarian cancer and 50 women without disease and enabled the creation of distinct proteomic patterns that distinguished cancer from non-cancer. These patterns were then used to analyze an independent set of blinded samples, 50 from women with ovarian cancer and 66 from unaffected women or those with non-malignant disorders. The discriminatory pattern correctly identified all 50 ovarian cancer cases, including all 18 stage I cases. Of the 66 non-malignant cases, 63 were identified as not being cancer. This result yielded a sensitivity of 100% and a specificity of 95%. A truly important finding was the ability to correctly identify all stage I ovarian cancer cases. Currently, more than 80% of ovarian cancer patients are diagnosed at a late stage and have a 20% or less chance of survival at five years. In contrast, the 20% of women diagnosed with early stage disease have a 95% survival rate at five years. This early detection method has the potential to make a substantial difference in the mortality rate of ovarian cancer with additional larger scale testing. There is also the exciting potential of using this technique to diagnose additional types of diseases. Visualizing Protein Patterns The NCI-FDA team has also developed new tools for visualizing and analyzing protein patterns. Beyond identifying the presence of ovarian cancer and other diseases, these tools may allow researchers to determine how far the disease has progressed by matching specific proteomic patterns to a particular stage. "The new tools improve upon previous methods of identifying discriminatory protein patterns by allowing researchers to visualize the entire set of proteins in a single view, as well as zoom in and out to focus on regions of interest within the data," said Emanuel Petricoin III, Ph.D., co-director of the Clinical Proteomics Program and the senior FDA researcher on the project. "Using these visualization tools, the identification of proteomic patterns that aid in disease diagnosis can be done with greater sensitivity and accuracy," said Donald Johann Jr., M.D., of the NCI-FDA Clinical Proteomics Program, lead investigator of the study. "This new method reduces the risk of error, increases our productivity, and provides an efficient method to analyze large sets of protein data. # # # Produced by the National Cancer Institute’s Information Office For more information on proteomics, visit NCI's Proteomics Digest Page |
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