Abstract
There is a plethora of published cancer biomarkers but the reality is that very few, if any, new circulating cancer biomarkers have entered the clinic in the last 30 years. I here try to explain this apparent oxymoron by classifying circulating cancer biomarkers into three categories: fraudulent reports (rare); true discoveries of biomarkers, that then fail to meet the demands of the clinic; and false discoveries, which represent artifactual biomarkers. I further provide examples of combinations of some known cancer biomarkers that can perform well in niche clinical applications, despite individually being not useful.
Highlights
There is wide debate recently as to why very few, if any, new circulating cancer biomarkers have entered the clinic in the last 30 years
The vast majority of clinically useful cancer biomarkers were discovered between the mid-1960s and the early 1980s (for example, prostate-specific antigen (PSA) and carbohydrate antigen 125 (CA125))
A search in PubMed for the term ‘p53 AND breast cancer prognosis’ identifies 1470 papers, with the vast majority confirming the prognostic value of p53, despite its sparse use at the clinic, if any, due to the reasons mentioned above
Summary
There is wide debate recently as to why very few, if any, new circulating cancer biomarkers have entered the clinic in the last 30 years. A search in PubMed for the term ‘p53 AND breast cancer prognosis’ identifies 1470 papers, with the vast majority confirming the prognostic value of p53, despite its sparse use at the clinic, if any, due to the reasons mentioned above (imperfect or weak prognostic value) Other examples in this category include those biomarkers that have been discovered and validated thoroughly by industry, and found to have some use in clinical prediction, the strength of their predictive ability is not enough to persuade clinicians to use them, or clinical practice guideline developers to recommend them. There are numerous examples of this sort in the literature, that is, of reasonable and working biomarkers that fall short of fulfilling a clear clinical need and unlikely to be profitable if marketed From this discussion, it can be concluded that a very large number of candidate biomarkers have been discovered, and have been confirmed by reliable methods to provide diagnostic, prognostic or predictive information in certain groups of patients. Recommendations for this problem have been proposed elsewhere [2,8] and include understanding and avoidance of pre-analytical shortcomings; careful study design to avoid bias [13,14]; use of analytical methodologies that are sensitive, specific and precise; selecting appropriate samples (in numbers and quality) and patient subgroups for validation; and application of robust and rigorous statistics to avoid data over-fitting
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