Sciclips's Blog

Is it too early to brand biomarker discovery as a“Hype”?

Posted on: August 1, 2011

It is very interesting to read some of the recent studies and discussions in various scientific publications which revealed the negative aspects of biomarkers. Question is whether these reports or views really conveying the true message or simply trying to create a “negative hype” that the biomarker discoveries are a failure: a conclusion based on discouraging results from a particular technology area? We would like address two different aspects in this blog, first “biomarker hype” and second the current limitations of proteomics technology that may have created this “biomarker hype”.

The diagnostic biomarkers can be used not only for the detection of diseases but also for monitoring the drug effect as well as for defining drug dosage. It is a well-established fact that the use of biomarkers in multiple clinical applications may have significant impact on early diagnosis, clinical monitoring, fine-tune the efficacy of the drug. If the definition of a biomarker is based on the concept of “one biomarker-one disease”, it will be hard to find biomarkers for complex diseases, such as cancer. Our current understanding of clinical diagnostics, infrastructure, and expertise may dictate that the single biomarker approach would be more practical, feasible and reliable. At the same time, we should also consider the fact that major breakthroughs in recent years on gene and protein expression analysis have not only resulted in generating significant scientific discoveries for clinical applications of multiple biomarkers but also the involvement of these biomarkers in disease pathogenesis and progression. On the contrary, we are still spending valuable scientific resources to find perfect single biomarkers for various diseases. A recent study from National Cancer Institute (Cancer Prev. Res. (2011) 4:365) has been cited as a classic example of biomarker hype or the failure of biomarker discovery. According to this report the researchers have tested more than 35 ovarian biomarkers that have been claimed in many scientific publications to be better than CA125, a well established ovarian cancer biomarker. After analyzing hundreds of tissue samples, the researchers found that none of the biomarkers were better than CA125. Now the question is, based on this experimental data, can we truly claim that those biomarkers which did not perform well in this particular experiment are not better than CA125 and hence, are not true biomarkers? Several questions still remains unanswered such as: do we know for sure how many patients who were diagnosed using CA125 biomarker were responded completely or partially or none to the chemo or radiation therapies? If we would have carefully analyzed the CA125 selected patients along with other biomarkers (in combination), wouldn’t it be possible to predict a specific biomarker combination pattern that would have helped us to understand: a) the disease variation among patients and b) the patient response to a given therapy, which will ultimately help us to develop better treatment methods. The biomarkers are not only for the detection of a disease but also to provide clues for the disease state and variation in a particular patient. Expression level of a particular biomarker or a panel of biomarkers can be used to select a specific drug dose or a treatment regimen. Wouldn’t it be reasonable to think that the presence of other biomarkers in addition to CA125 in ovarian cancer patients might have some biological and clinical significance? Otherwise, a test sample from an ovarian cancer patient should not have shown positive to a second biomarker that is not present in healthy controls.

Based on our analysis using data from various clinical trials, we found out that it is very difficult to find biomarkers that have high specificity, in terms of diagnosing a particular cancer in all the patients who were enrolled in a clinical trial. It was also true that in some studies a particular biomarker that was found in majority of cancer patients were absent or merely detected in few patients, though these patients were all diagnosed with the same cancer like the biomarker positive patients. The data from clinical studies needs to be evaluated critically for developing innovative strategies for biomarker discovery and clinical diagnostics assays. All the biomarkers that are experimentally validated need to be carefully evaluated and considered for developing most efficient and clinically useful diagnostic/prognostic assays. Biomarker or proteomics researchers need to develop creative thinking, planning and execution of ideas with a “birds view” not with a “microscopic view” that fails to interpret the long-term impact of research findings beyond the areas of expertise. In other words, for developing an intelligent and smart research plan for high value areas like biomarkers, researchers need to develop broader understanding and knowledge on current and future clinical applications of biomarkers. Constant interaction with clinical and diagnostic researchers in academic and industrial laboratories could be a first step towards achieving this goal. Collaboration with researchers from established pharmaceutical or biotechnology companies will be an advantage to academic researchers to design their strategies and experiments that may lead to the discovery and validation of clinically viable biomarkers.

The false hopes that are created by current proteomics approaches can be blamed for the “biomarker hype”. More often the term “biomarkers” are confined to or projected as proteomics based biomarkers; mainly by the proteomics researchers. We sometime knowingly or unknowingly tend to ignore the fact that biomarkers can be proteins, peptides, DNA, mRNA, SNP, miRNAs or metabolites. It would be tough to predict whether protein or molecular biomarkers will be more commercially viable and successful; not to forget the fact that molecular biomarkers are more robust and cost effective than protein biomarkers. Even if we consider proteomics is the way for biomarker discovery, current proteomic approaches would need a 360° make over, especially in sample preparation and analysis methods that are suitable for clinically relevant biomarker discovery platform. Starting from sample preparation to enzyme digestion followed by fractionation are the major limitations of mass spectrometry (MS) based proteomics approach in a clinical set up. The difficulty in sample analysis, sample loss, lack of reproducibility and the high cost in identifying a biomarker are additional limitations. It is even more confusing when proteomics approaches claim absolute quantitation of biomarkers based on the data that have been generated through complex sample preparation that lacks reproducibility. Moreover, the biological significance and relevance of absolute quantitation of biomarkers in diagnostics applications are debatable. Unless, we have a robust sample preparation and analysis technique, MS based proteomics approaches may continue to generate false positives/negatives. Unfortunately, optimization of sample preparation techniques also includes development of new LC and MS instrument platforms that can handle heterogeneous “dirty” samples without specialized sample cleaning steps.

The lack of true collaboration between mass spectrometry scientists, biological and clinical researchers is another limitation in MS based approach. The protein mass spectrometry field is generally dominated by analytical scientists and there is an urgent need for more productive collaborative research, not just a core facility confined consultation, to identify true biomarkers that are biologically and clinically relevant. Analyzing the peak shifts and peptides may not be the only major thrust area, rather, the identification of biological relevance and validation of biomarkers should also be the priorities of proteomics researchers. Proteomics laboratories need to develop strategies, skills and infrastructure for true biomarker discovery. Currently, mass spectrometry based proteomics skills or expertise is confined to very few laboratories or core facilities that have independent mass spectrometer capabilities. This severely cripples innovations in proteomics based biomarker discoveries. Breakthroughs in biomarker discoveries may happen once portable mass spectrometers are available to research laboratories, like PCR machines or ELISA readers. It is noteworthy to point out that emerging areas such as MALDI imaging using tissue arrays and whole protein mass spectrometry analysis look very promising and hopefully these technologies might address the current limitations in proteomics based biomarker discovery.

The current criticism over biomarkers can be purely based on the putative or false biomarkers that were identified and claimed using mass spectrometry based proteomics approaches. Nonetheless, the failure of proteomics technology should not invalidate the biomarkers (proteins, SNPs, miRNA etc) that were discovered and validated through other conventional and modern biological tools, such as tissue arrays and various antibody based technologies, in a pre-clinical or clinical set-up. These technologies will continue to discover new biomarkers that may have the potential for developing novel diagnostic tools.

Related blog

1. Strategies for Rational and Personalized Cancer Biomarker Discovery


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