wasting pathologists’ time, only the best candidates are given to them for assessment. Once a pathologist is interested in some promising candidates, he or she will likely bring more clinical colleagues to the study. Many clinicians who conduct research were formally trained in medicine and basic science, so they are interested in developing research collaborations. Dennis Sgroi, who is at Massachusetts General Hospital, earned M.D. and Ph.D. degrees and performed postdoctoral research in a
genomics laboratory. As a translational scientist who works with patients, he says that he can identify clinical problems that could be solved with basic-science techniques. Translational science is a growing area, he adds. According to Omenn, NIH is revamping the clinical research training scheme for the U.S. “It’s a time of high expectations and what NIH Director [Elias] Zerhouni calls ‘transformation’ for clinical translational research,” he says. “NIH has invested billions and billions in basic science for medicine, and people
want to see results.” Omenn predicts that in the future, even more collaborations between clinicians and basic researchers will develop. “The emergence of validated biomarkers will probably be what will bring clinicians, basic scientists, and informaticians closer together,” he says. “Talking about things in the abstract is much less capable of attracting people’s detailed attention than having a useful application that can actually make a difference.” —Katie Cottingham
Proteomic profiling method not suitable for detecting prostate cancer
cohort. However, this new algorithm could not distinguish healthy from cancerous samples nor could it discriminate between samples from more aggressive versus less aggressive cancers. Semmes and colleagues note that a major challenge for biomarker research is minimizing the incidence of false discovery from biased samples. For that, researchers must spend the time and effort to put together enough ideal specimens. The authors say that their results do not indicate whether a particular method works and do not imply that previous studies were wrong. However, they do conclude that the particular SELDI TOFMS method used in their study has no diagnostic value for prostate cancer detection. Finally, they recommend that all other biomarker assays be rigorously validated.
to PubMed Central when they are accepted for publication. These articles will be made public no later than 12 months after the official publication date. In addition, as of May 25, authors must include the PubMed Central reference number when citing their NIHfunded articles in NIH applications, proposals, or progress reports. NIH joins public funding agencies in Belgium, Canada, France, Switzerland, and the U.K. that already have mandated open-access archiving. In addition, policies that strongly encourage open-access archiving have been implemented in Australia, Austria, and Germany. Most recently, the European Research Council mandated open-access archiving of publications and data from projects it has funded.
New law mandates open access for NIHfunded research The National Institutes of Health (NIH) has become the first public funding agency in the U.S. to mandate that publications resulting from its research grants be deposited in an open-access archive. The provision was included in the Consolidated Appropriations Act of 2008, which was signed into law on December 26, 2007. One requirement of the new policy (see http://public access.nih.gov) is that, starting April 7, electronic versions of final, peer-reviewed manu scripts that originated from NIH funds must be submitted
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The use of SELDI TOFMS for the early identification of cancers has been controversial. As a result of this and other questions about diagnostic approaches, the National Cancer Institute’s Early Detection Research Network organized a validation study of serum proteomic profiling to diagnose prostate cancer. Two recent papers published by a collaboration involving 29 researchers at 10 institutions present the results from the second stage of the validation study. (Clin. Chem. 2008, 54, 44–52; 53–60) In a previous publication, O. John Semmes from Eastern Virginia Medical School and colleagues determined in the first stage of the validation study that with frequent instrument calibration and automated sample preparation, the SELDI TOFMS method was sufficiently reproducible across laboratories. In addition, the decision algorithm could identify samples from cancer patients correctly when the samples originated from the patient cohort that was used to derive the algorithm. In the first of two new papers published by Semmes and co-workers, the decision algorithm could not distinguish between healthy and cancer patients correctly when applied to geographically diverse samples that were not from the cohort used to derive the algorithm. This result prompted the group to look for evidence of sample bias, which they found. In the companion paper, the authors compiled a new cohort of specimens that eliminated the sample bias, and they derived another decision algorithm from the new sample
For the public. Publications resulting from NIHfunded projects must be placed into an open-access repository starting April 7.
Journal of Proteome Research • Vol. 7, No. 3, 2008 843
