What about cancer biomarkers? A handful of cancer biomarkers are currently recommended for clinical use but mainly for monitoring response to treatment among patients with advanced disease. With some notable exceptions (eg, the biomarkers, human choriogonadotropin for germ cell tumors and gestational trophoblastic disease and α-fetoprotein for hepatocellular and testicular carcinoma), most cancer biomarkers in clinical use are not suitable for population screening or for early diagnosis, and the use of prostate-specific antigen for prostate cancer screening is still controversial (2
). But why are so few new and effective cancer biomarkers that are suitable for screening and early diagnosis being discovered and validated? The answer cannot be attributed to the lack of pathophysiological knowledge, powerful techniques, or investment of funds and so may reside in difficulties that are associated with biomarker discovery, which have apparently been underestimated.
Many requirements must be fulfilled before a cancer biomarker can be approved for clinical use. If a molecule is to be effective in early diagnosis, it must be released into circulation in appreciable (and easily detectable) amounts by a small asymptomatic tumor (or its microenvironment), a requirement that could be considered an oxymoron. This requirement may explain why many cancer biomarkers detect disease relatively well among patients with late-stage disease but detect disease poorly among patients with early-stage disease or not at all among patients with asymptomatic disease. Another requirement is that the biomarker should be highly specific for the tissue of origin because if other tissues also produce this biomarker, then its background level in normal healthy individuals will likely be high. Thus, the tumor must produce levels of the marker that are substantially higher than background, a requirement that will probably require larger tumors. Another caveat for non–tissue specific biomarkers is that, if the level of a biomarker is affected by a noncancer disease, then its utility for cancer detection may also be compromised. Prostate-specific antigen is an example of such a biomarker; it is well established that prostate-specific antigen is elevated in benign prostatic hyperplasia (resulting from an enlarged prostate) and prostatitis (resulting from inflammation). To date, with the possible exception of posttranslational modifications (eg, pancreatic ribonuclease in pancreatic adenocarcinoma and kallikrein 6 in ovarian cancer), very few, if any, molecules have been identified that are expressed only by a cancer tissue but not by the corresponding normal tissue.
Problems can develop at many stages of biomarker discovery and validation that contribute to the short life span of many “newly discovered” biomarkers. These problems can occur during preanalytical, analytical, and postanalytical phases of cancer biomarker discovery and validation. The preanalytical phase includes aspects that may play a role before sample analysis (such as sample collection). The analytical phase includes aspects of the assay (such as its specificity and sensitivity). The postanalytical phase includes aspects that may play a role after sample analysis (such as data interpretation). In the preanalytical phase, it is important to examine whether various individual characteristics (eg, patient age, diet, sex, ethnicity, lifestyle, drugs, or exercise) and/or storage of tissue samples could independently affect biomarker levels. In addition, a molecule in circulation may be quickly cleared by the kidneys or the liver, captured by other serum molecules, or degraded by serum proteases. After sample collection, the marker could be released by blood cells (eg, red cells or eosinophils) during clotting or centrifugation, altering the originally present concentration. In the analytical phase, a quantitative and validated analytical method must be available that is highly specific, sensitive, and precise to avoid introducing measurement biases (ie, that over- or underestimation of the true concentration) or artifacts. A sufficiently large number of high-quality tissue samples should be available for validation so that any statistically significant results can be unambiguously identified. Finally, in the postanalytical phase, sound data interpretation is essential so that the findings can be generalized to other series of specimens or the general population.
Press releases and news conferences that immediately accompany publication of a high-profile biomarker generate high expectations about the new biomarker. However, media ignores reports that the biomarker failed to be validated for clinical use. Consequently, the general public receives skewed information about the biomarker.
Careful validation in independent datasets by independent investigators and publication of the findings are probably the best way to identify a good biomarker. In 2001, Pepe et al. (3
) described five phases of biomarker development that were based on published evidence. My group has used these five phases to classify cancer biomarkers as we prepare clinical guidelines for use of tumor markers (4
), under the sponsorship of The National Academy of Clinical Biochemistry of USA. Guidelines for the clinical use of tumor markers have also been issued by other organizations, including the American Society for Clinical Oncology. Such guidelines are very useful because they use published evidence or expert opinion to specify the clinical utility of a biomarker. Biomarkers that have recently been discovered (and for which much published evidence does not exist) can be most effectively assessed in several blinded and independent validation studies. The Early Detection Research Network of the National Cancer Institute (http://edrn.nci.nih/gov/
) is an organization that supports collaborative efforts for the discovery and validation of cancer biomarkers that are primarily suited for early detection but may also be useful in diagnostic, prognostic, predictive, and monitoring applications. An indication of difficulty in the discovery and validation of clinically useful cancer biomarkers is the fact that Early Detection Research Network has invested hundreds of millions of dollars since its inception approximately 10 years ago searching for new biomarkers, but to my knowledge, none of the new biomarkers discovered by investigators in the Early Detection Research Network has been approved for clinical use. This observation underlines the facts that adequate funding is available for the discovery and validation of biomarkers and that a highly competent group of international investigators participate in the Early Detection Research Network. Many other organizations heavily fund cancer biomarker and translational cancer research investigations, so the cause of recent failures in cancer biomarker discovery and validation is not either shortage of funds or lack of effort.
In 2009, the Early Detection Research Network began a hallmark study to validate a large number of candidate ovarian cancer biomarkers, individually and in panels, by using a phase III blinded design and high-quality clinical samples from the Prostate, Lung, Colorectal, and Ovarian Cancer study (8
). Below, I have used publicly released results from this study (8
) and from a few high-profile articles on cancer biomarkers that subsequently failed validation to illustrate why I believe that these “successes” soon became “failures.”
In addition to independent validation, promotion of scientific discussions and debates on newly discovered cancer biomarkers at conferences and in journals may accelerate the determination of whether a new biomarker has the potential for clinical utility. This procedure could ensure that valuable resources (time and money) are invested appropriately and promptly or directed instead to other projects. A highly useful online forum, BioMed Critical Commentary (www.bm-cc.org
), posts opinions on published papers in biomedical sciences, including cancer biomarkers. This process may assist researchers to quickly identify opposing opinions on published biomarkers. As Ransohoff (9
) has pointed out, deficiencies in study design are a major reason for the biomarkers to encounter difficulties during their discovery and validation.