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Promise and pitfalls of the cancer biomarker search
Author(s) -
Sarah A. Webb
Publication year - 2010
Publication title -
biotechniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/000113474
Subject(s) - biomarker , cancer , computational biology , biology , medicine , genetics
In the middle of the last decade, the search for cancer biomarkers shifted from a type of gold rush to an elusive quest. The potential payoff is substantial: if oncologists had molecules that could help them find and treat a cancer at an early stage, they expect that they could boost survival. In addition, biomarkers could profile tumors, helping doctors and patients make informed decisions about treatment strategies. Initially, as the human genome was published, analyzing samples using mass spectrometry looked like a potential gold mine for biomarker discovery. But even after the publication of a number of papers that described biomarker candidates, no new cancer biomarkers have entered the clinic. About five years ago, researchers realized that mining the proteome for cancer biomarkers was much more complicated than they'd anticipated. But improvements in methodology— along with increasing sensitivity in mass spectrometry—are renewing optimism that proteomics can still help uncover new cancer biomarkers. Cancer biomarker research is founded on the theory that as a solid tumor grows, it will shed unique proteins into surrounding tissues and into the bloodstream of a patient, says Michael Gillette, a research fellow at the Broad Institute in Cambridge, MA. A decade ago, researchers were optimistic that surface-enhanced laser desorption/ ionization (SELDI) and other mass spectrometry–based approaches could quickly distinguish between the serum protein profiles of healthy patients and those with cancer, and use the resulting patterns in diagnostics. " There turned out to be an enormous number of problems with doing this: everything from the technology to bad experimental design to bad biostatistics and informatics, " says Daniel Liebler, professor of biochemistry and director of proteomics at Vanderbilt University School of Medicine in Nashville, TN. But from those missteps also came an important lesson, he says: researchers needed to distinguish between the platforms that discover new biomarkers and the ones that do targeted analysis. " It was just a mismatch of the technology to the objective. " Tools to mine the proteome Even with the challenges of searching for biomarkers, researchers and funding agencies are still pursuing the promise of these techniques. The National Cancer Institute's Clinical Proteomic Technolog y Assessment for Cancer (CPTAC) network is one such multidisciplinary collaboration that is refining methods and looking for new cancer biomarkers. It turns out that proteins that are likely to be biomarkers are also likely to be present in low concentrations relative to the host …

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