Biomarkers: current perspectives and future prospects

Editorial

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Biomarkers: current perspectives and future prospects

Stephen Naylor Department of Genetics and Genomics, Boston University School of Medicine, Boston, MA 02118, USA Tel.: +1 781 389 4206 [email protected]

‘...a biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention.’ Expert Rev. Mol. Diagn. 3(5), 525–529 (2003)

Biomarkers appear to be entities that are every- associated with their discovery, validation and thing to everyone. They appear to be amor- use. Finally, a consideration of the future of phous in shape, size and impact. Enormous biomarkers and the necessary tools and techinterest has been generated in this fledgling nologies needed for the field to grow into a arena and in August 2003 alone, two major mature and productive arena should provide a events in this field, namely the IBC Biomark- unifying backdrop for ongoing and additional ers in Drug Discovery (August 12–13, 2003, discussion about the continued development MA, USA) and the CHI Protein Biomarkers: of this exciting new scientific discipline. Applications in Diagnostics, Drug Development and Toxicoproteomics (August 25–26, Current status of biomarkers 2003, PA, USA) were held. The conferences The broad array of scientists participating in were extremely well attended and two signifi- the development of this arena can be excused cant observations emerged. Firstly, that the use for sometimes feeling a sense of confusion and of the word biomarker lack of definition ‘...biomarker is an umbrella is, in reality, an about the subject umbrella coalescence coalescence term which covers area. However, in an term that covers a the use and development of tools attempt to bring vast number of disci- and technologies, monitoring of some order to this plines, including the diverse field, the drug discovery and development Biomarkers and Suruse and development of -omic tools and and understanding of prediction, rogate Endpoint technologies, moni- causes, progression, regression, Working Group toring drug discovery (under the direction outcome, diagnosis and and development of the Office of the treatment of disease.’ processes and more Director, National fully understanding the prediction, causal Institutes of Health), have agreed on both a onset, progression, regression, outcome, diag- definition as well as a classification system for nosis and treatment of disease. The second was biomarkers [1]. The definition of a biomarker is a cacophony of comments best summarized by as follows: a characteristic that is objectively ‘biomarkers, biomarkers everywhere but not a measured and evaluated as an indicator of drop to use!’ Hence, one may characterize this normal biological processes, pathogenic procemerging field of endeavor as being filled with esses or pharmacological responses to a theraexcitement, expectation, uncertainty, chaos peutic intervention. As this definition encomand enormous potential. In this commentary, passes many elements of the pharmaceutical it is worthwhile to consider the current status and biotechnology industries, as well as much of biomarkers, as well as the perceived problems of the biomedical and conventional biological

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sciences, practitioners may still be excused from being lost in structurally identified and validated. However, a number of the morass and size of the biomarker space. However, in a fur- companies, including Caprion (Montreal, Canada), Ciphergen ther attempt to bring clarity to the subject matter, a classifica- (CA, USA), Beyond Genomics (MA, USA), Metabometrix tion system has been devised. Type 0 biomarkers purportedly (London, UK) and Surromed (CA, USA), all have discovery measure the natural history of a disease and should correlate programs to find biomarkers in specific disease states for preover time with known clinical indicators. Type I biomarkers dictive, early onset, progression, regression, treatment efficacy indicate the intervention effect of, for example, a therapeutic and diagnosis of disease (Type 0-like biomarkers). It is interestdrug, whereas Type II biomarkers are considered surrogate end ing to note that in this particular situation, the expectation of a point markers. This Working Group has also given much good biomarker can range from a molecular signature of thought to defining surrogate end point as well as clinical end structurally unidentified markers (similar in perspective to the point and the reader, if interested, should peruse the original pattern recognition mindset of the pharmaceutical industry), to discussion [1], as well as the excellent review by Frank and Har- a panel of identified biomarkers specific for the disease process greaves [2]. From a much more practical and focused perspective, being evaluated. As noted above, opinion on what constitutes the optimal the US Food and Drug Administration (FDA) have proposed that a surrogate end point or marker is a laboratory measurement biomarker is diverse. However, this pales into insignificance or physical sign that is used in therapeutic trials as a substitute when considering the tools and technologies utilized to discover for a clinically meaningful end point that is a direct measure of and validate biomarkers. The platforms (hardware and software) available, as well as in develophow a patient feels, functions or ‘In the rapidly developing world of ment, for use in biomarker discovsurvives, and is expected to predict biomarker ranking/prioritization, an ery include the existing -omic the effect of the therapy [3]. These attempts to bring clarity to alphabet soup of different approaches technologies currently employed in this burgeoning field are most wel- exist, including signal-to-noise ratio, genome, transcriptome, proteome come. However, it is interesting to SVM, t-test, Ecombo and stepwise (differential and functional) and metabolome analyses, as well as the note that what constitutes a biomarlinear discriminant analysis.’ integrative analysis of systems ker and how best to use it depends upon the particular practitioner describing it. At present, the (commonly referred to as systems biology, pathway or network biomarker arena can be divided into two broad subsets. The biology or panomics). Such discovery platforms, which typically pharmaceutical industry has adopted them as a wide-ranging analyze molecular components, commonly utilize genetic linkage set of tools in monitoring and providing information feedback analysis, expression arrays, chromatography coupled with mass along the drug discovery and development process (Type I-like spectrometry, nuclear magnetic resonance (NMR) and other senbiomarkers). As Greg Preston (Senior Research Investigator, sitive detection devices, such as electrochemical and laserPfizer Global Research and Development, NJ, USA) noted in induced fluorescence detection. However, a wide variety of other his excellent overview perspective at the IBC Biomarkers in approaches are also used, including incorporation of convenDrug Discovery conference, they have an impact on the deter- tional clinical chemistry measurements, all forms of imaging mination of clinically relevant targets, through screening chem- from immunohistochemical staining to NMR imaging and istries and preclinical absorption, distribution, metabolism, whole cell analysis using flow cytometry approaches. In order to excretion and toxicology, to clinical decision making markers at mine and exploit the data acquired on such diverse platforms, a Phase I–IV. They are pervasively used throughout the entire panoply of data-handling tools are required. They include data drug discovery and development pipeline. However, in most preprocessing software to subtract out baseline deviations as well cases, the biomarkers of indication are used primarily in pattern as align individual data files. A broad array of biostatistical tools recognition mode. For example, a specific but unidentified set are in use to identify specific cohorts of individual samples from a of markers (genomic, proteomic, metabolomic or a combination set of analyses and include principal component analysis and thereof ) may signify a hepatotoxic response in rats to a new principal component discriminant analysis. Prioritizing individcompound being evaluated. It is not necessary a priori to deter- ual biomarkers into panels based on fold-change and significance mine biomarker constituent identities, since the pattern alone (Pearson coefficient) requires a suite of conventional statistical denotes toxicity. Hence, armed with such limited information, approaches including ANOVA, t-test and Kolmogorov–Smirnov, as well as more recent developments, such as support vector the decision can still be made to kill the compound. The second broad area where biomarkers are currently finding machine analysis (SVM). Data visualization, storage and retrieval use is in the disease mechanism, monitoring and prediction packages are also critical in order to carry out such analyses. arena. Numerous companies are interested in determining Finally, given the plethora of platforms used to acquire data, data specific biomarkers (gene, transcript, protein or metabolite) for integration and correlation (linear and non-linear) are also very either diagnosis of disease (e.g., diaDexus, CA, USA), or important features to have in the biomarker software toolbox. The development of the necessary tools and technologies, as screening for a disease (e.g., Pediatrix/NeoGen, PA, USA). These compounds can be considered as Type II-like biomarkers. well innovative new research in biomarker discovery, is In these cases, it is important that a single biomarker has been vibrant and active and has dominated the arena. This is in

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stark contrast to the validation and use of new molecular signa- least understood components of biomarker discovery. The tures, individual biomarkers or biomarker panels. In part, this is appropriate number of samples to be analyzed that will provide simply due to temporal events and participant foci. Many of the statistically significant data outcomes must be considered. Adenecessary tools and technologies for biomarker discovery have quate controls are a very necessary element in the design of only recently become available, at least when used in a concerted such studies. One also needs to consider whether a global or manner. However, this does not diminish the underlying com- targeted analysis is appropriate, as well as whether tissue and/or plexity and time-consuming nature of validating biomarkers for body fluid should be analyzed. routine use. This has been discussed in some depth by Frank and Hargreaves [2], as well as by De Meyer and Shapiro [4]. As noted Sample quality by the aforementioned authors, the standard concepts of test– The old adage of ‘garbage in, garbage out’ when applied to retest reliability and validity apply with equal force to clinical analysis of biological samples is particularly relevant in biomarkers as they do in any (classical, standard) assay system. biomarker discovery. The quality of samples analyzed will They also note that rigorous standards and protocols are already ultimately determine the quality of biomarkers produced. A in place for the latter and therefore provide a lattice framework number of factors must be taken into consideration. For for the former. Furthermore, they ruefully and correctly note that example, a clear lineage and adequate care for animals is necthe work required to establish the reliability and validity of a new essary, whereas in the case of human samples, history, outbiomarker should not be underestimated and needs planning for comes and storage conditions are all very important. In pareach combination of clinical indication and mechanism of ticular, one must also consider whether to pool samples or action. For example, Type 0 biomarkers can be validated longitud- analyze individual samples. Most practitioners today tend to inally, in a well-defined patient population against a gold standard agree that the intrinsic biological variability present in indiclinical assessor. Type I biomarkers should be validated in parallel vidual samples contains important information and provided with the drug candidate and Type II that you have the appropriate biomarkers must be relevant both to ‘The development of the necessary informatic and biostatistical tools and technologies, as well the mechanism of action of the drug tools, pooling is inappropriate. and to the pathophysiology of the innovative new research in biomarker In the case of heterogeneous tisdisease. The tools and technologies discovery, is vibrant and active and sue (e.g., brain) one must decide needed to undertake such tasks in the whether to analyze the mix of has dominated the arena.’ validation process are for the most cellular material or specific cell part already available. They include expression and protein populations, which can be acquired using laser capture microarrays, high-throughput immunoassays and conventional statisti- dissection. At a more refined level, should one analyze the cal and epidemiological analyses. Hence, it is rather paradoxical content of specific organelles by using biological sample prepto note that a reasonably well-defined paradigm is in place to val- aration techniques? All such questions are determined by the idate biomarkers once they exit the discovery phase. Whilst this is focus of the study and biological indication of the biomarkers time consuming and rigorous, it is in contrast to the biomarker being sought. discovery phase which still appears to be in its formative stages. Technology platforms Issues in biomarker discovery

As already noted, biomarker discovery is an active but emerging field of endeavor, where definitions and optimal outcomes are still being discussed and debated. There are, however, numerous practical issues and limitations that have to be considered. These include experimental design, biological sample quality and variability, technology platform capability, paucity of good ranking and predictive modeling algorithms, lack of context in disease and drug discovery and development process, limited use of knowledge assembly tools, lack of consideration of global initiatives in biomarkers of disease, company versus public databases, cost-benefit of technologies and ultimately a poor understanding of the potential for reimbursement and/or analysis of value of biomarkers. Experimental design

It is imperative that one considers what the intended outcome of the biomarker discovery experiment is designed to achieve. Experimental design is probably one of the most overlooked,

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There has been tremendous developments in -omic platform capability over the past decade. However, there still remains a number of concerns. Expression profiling has matured into a stable, commercially-available platform technology. However, questions continue to arise about the precision and reproducibility of this approach. In the differential proteomic and metabolomic analyses of complex mixtures, a number of issues still need to be addressed. One of the major limitations of current technologies (predicated on chromatography and mass spectrometry) is the limited measurable dynamic range (typically 104). Given that dynamic range can vary from 106 to 1010 in biological tissue and fluids, this creates significant problems in terms of breadth of coverage and limited sensitivity. Additional problems involve limited throughput capability and limited automation. Precision and reproducibility as well as accurate quantitation are also issues that are still being addressed. In the case of imaging, the problem of limited throughput is still an issue. Finally, in integrative biology approaches, developing integrated platforms to carry out such analyses is still in its infancy.

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Informatics & databases

clarity of goals and continued fortification of the biomarker foundation, more organization needs to be brought to bear. Such a diverse group of people and skill sets needs a variety of tools to hone and fashion this industry. Several initiatives need to be considered. For example, in order to build on the excellent progress of the Biomarkers and Surrogate End point Working Group, a grass roots type organization needs to be formed. This could take the form of a formal professional society, or a more loose-knit structure (e.g., the HUPO organization focused on proteomics). This structure can provide a forum for broad-based discussions on definitions, as well as defining key elements of new tools and technologies required to advance in the field. An annual meeting or meetings need to be scheduled that augment the current gatherings organized by professional conference companies, such as CHI or IBC. Consideration of consortia formation is also something that needs to be discussed, particularly in regard to biomarker databases, nomenclature and data visualization. Economics The development of new tools and technologies that impact Gordon Ringhold (CEO, Surromed), at the recent IBC confer- on the biomarker space will for the most part be developed in ence in Boston, talked about the fact that while there is genomics, the respective -omic arenas. For example, the issue of reproducibility, quantitation, sensitivity transcriptomics, pharmacogenomics, ‘In order to provide direction, enhancement and high-throughput proteomics and metabolomics, the clarity of goals and continued capability in both proteomic and only really important -omics is metabolomic analyses will be economics. His comment from a fortification of the biomarker addressed by those respective scienbusiness perspective was most foundation, more organization tific communities. However, a key appropriate and timely. The issue of needs to be brought to bear.’ area that does need to be addressed reimbursement for biomarkers is a quagmire, mired in the political debate of escalating healthcare by the biomarker practitioners is how to rapidly and reliably costs in both North America and Europe. The conventional integrate data from different platforms. The value of a biomarker diagnostics marketplace provides some background for consid- panel containing genes/transcripts, proteins and metabolites is eration of the monetary value of biomarkers. However, who at present unknown. We need to address and understand if and will actually bear the cost of discovery and how that might be why a composite panel is more valuable (scientifically and ecoreimbursed is not so clear. In part it will be determined by the nomically) than individual panels of genes or proteins or role of the biomarker and its use. For example, the use of metabolites alone. Furthermore, there will be significant debate biomarkers in the pharmaceutical industry is somewhat more in the future as to the advantages of genes versus proteins versus straightforward, since the intrinsic value of biomarkers is to metabolite panels. Which type of constituent component will reduce the approximately US$800 million needed to bring a provide the most information about the process being investidrug to market. Unfortunately, it is not so clear-cut as to the gated? Finally and more near term, the issue of whether a value of biomarkers in monitoring disease processes. How one molecular signature, an individual biomarker (diagnostic) or may go about actually valuing biomarkers has been elegantly panel of identified biomarkers is the best approach as a final discussed by Ferber in a recent paper [5]. He considers the use product clearly needs to be debated. The answer to this conunof the Pearson index (a normalized measure of the financial drum is at present not clear, since who you ask dictates the expevalue of a drug development project) in the context of using diency of the response, and the regulatory agencies, such as the biomarkers as tools in acquiring additional information about FDA, will certainly (and correctly) weigh in on this discussion. As the field continues to develop, one will see continued conthe process. He concludes that economy makes us try to obtain the most valuable, albeit still incomplete information certed efforts from individuals from very different disciplines. with a limited investment. It is in this context that biomarkers For example, as the biomarker discovery engine becomes more refined and capable, integration with the knowledge assembly play their role. team to put the biomarkers into biological context will be Future & conclusions essential. This latter event is, in effect, a prevalidation step, The future of biomarkers appears to be tinged with a mixture of since it places the biomarker components in the biology of the excitement and uncertainty. In part, this uncertainty is predi- system under study. This prevalidation step should therefore cated upon the fact that numerous disciplines and practitioners provide a qualifier prior to sending on the biomarkers for the contribute to the biomarker effort. In order to provide direction, time-consuming, though well-defined validation steps. The ability to integrate data from different platforms is not a straightforward procedure. To date, only a limited number of companies, such as Beyond Genomics, Paradigm Genetics (NC, USA), as well as academic institutions, such as Institute for Systems Biology (WA, USA) and Max Planck Institute, have such capability. The algorithms are proprietary and to date there is nothing that is commercially available. In the rapidly developing world of biomarker ranking/prioritization, an alphabet soup of different approaches exist, including signal-tonoise ratio, SVM, t-test, Ecombo and stepwise linear discriminant analysis. Unfortunately, many of these are customized approaches and hence there are no unifying standards in the biomarker field. Furthermore, global databases are still only being considered but most remain proprietary. Finally, the data visualization tools available today continue to develop at a good pace but are still in their infancy.

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Finally, the regulatory bodies in North America, Europe and Japan/South East Asia will play a significant role in how the biomarker space continues to develop. At present, the value of biomarkers in the drug discovery and development pipeline, as well as indicators of disease, is the subject of debate and scrutiny References 1

2

Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69(3), 89–95 (2001). Frank R, Hargreaves R. Clinical biomarkers in drug discovery and development. Nature Rev. Drug Discov. 2(7), 566–580 (2003).

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by such regulatory authorities. It is important for the biomarker community to continue to debate and educate the authorities, since the decisions will impact significantly on the economic value of biomarkers in the future. It is an exciting future, one that needs help in defining the importance and direction of biomarkers.

3

Temple R. Are surrogate markers adequate to address cardiovascular disease drugs? JAMA 282, 790–795 (1998).

4

De Meyer G, Shapiro F. Biomarker development: the road to clinical utility. Current Drug Discovery 23–27 (2003) (available at www.inpharm.com/static/ intelligence/pdf/MAG_47535.pdf)

5

Ferber G. Biomarkers and proof of concept. Methods Find. Exp. Clin. Pharmacol. 24(Suppl. C), 35–40 (2002).

Affiliation •

Stephen Naylor, PhD Department of Genetics and Genomics, Boston University School of Medicine, Boston, MA 02118, USA Tel.: +1 781 389 4206 [email protected]

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