Novel Tissue Types for the Development of Genomic Biomarkers

Novel Tissue Types for the Development of Genomic BiomarkersImagine a simple clinical test that can not only diagnose a disease, but that can also identify the exact, personal therapeutic regime to cure it. Not only that, imagine tests that can accurately predict the potential of developing a disease and provide an individualized roadmap on how it will progress. Now imagine that all you had to do was spit in a vial, or have a few hairs plucked for the analysis. While the promise of “personalized medicine” is technologically a reality, it relies on the development of disease and progression biomarkers.

Technology has finally caught up with science fiction. The idea of a pin prick to divine ones’ future is fast becoming a reality. Science is moving medicine in a direction where patient care will be predicted and prevented, and not watched from afar. Data-rich and highly sensitive techniques like microarray profiling, quantitative PCR, and Next Generation Sequencing are the genomics tools that are helping to drive these changes. However, to extract the greatest utility, tests need to be simple to complete, cost effective, and as noninvasive as possible. Clinical impact is directly related to the availability and cost of a test.

Ideally, the most clinically powerful information would come directly from the tissue of interest. To understand cancer, one must look at malignant cells, much as one must analyze brain tissue to understand complexities of neuroscience. However, many of these tissues are difficult to access or impossible to reach without potential injury to the patient. Alternative, or “surrogate” tissues can provide a means of assessing the genomic changes in the tissue of interest, without fear of harming the donor.

For example, surrogate tissues may contact the tissue of interest and retain sloughed cells, secreted molecules, or the contents of dying cells. While these molecular signals may not exactly mirror the tissue of origin, in many cases they are reproducible and can clearly point to underlying biology.

Clinical material suitable for biomarker testing can be divided into two different types. The first are those that require minimally invasive procedures to obtain. This type includes blood, cerebrospinal fluid, tissue biopsies, and so on. Type 2 tissues are those that can be obtained without any invasive means: hair, saliva, tears, epidermal cells, urine, etc. Below are two examples – hair and saliva – of clinical material suitable for biomarker testing that can be obtained without any invasive means.

Using Saliva for Disease Diagnostics

Saliva is an easily obtainable tissue that has been used in forensics for decades. However, new molecular profiling kits for voluntary saliva collection have made saliva an increasingly useful clinical biomarker tissue. The collection process in noninvasive, and can even be collected at home or in isolated locations using some of the newer collection kits (Oragene or Noragen products). This ease of collection results in higher compliance by patients.

It is possible that one day saliva samples could replace blood samples for many DNA studies. A study in Australia and New Zealand compared 10 matched pairs of blood and saliva, as well as nearly 2000 samples of either blood (Australia) or saliva (New Zealand) for use in genotyping. This study corroborated previous data that there is a donor dependency to DNA yield. Because of the large sample number, the authors were able to detect more sample variance. However, they also concluded that variance had more to do with collection, processing, and donor variability than variance due to tissue type. In most cases, there was enough mass from 1 ml of saliva sample to yield at least 4ug of DNA, which is enough DNA for most molecular biology assays (Bahlo, 2010).

Hair Follicles

Hair follicles are different from skin and blood in that they are made up of stem cells, which control the growth and cycling of hair. Stem cells are contained within the follicle, which makes hair follicle gene expression particularly intriguing. Hair follicle collection is being increasingly examined as a good investigatory and clinical biomarker tissue. This is due to advances in hair follicle extraction, isolation, amplification techniques, along with the relative ease of collection of the tissue.

To date, most research has been in diseases involving skin conditions; however, hair follicles are also being examined for markers to quantify exposures to pharmaceuticals or toxicology to certain drug targets. Hair follicles are obtained using tweezers, grasping at the hair as near to the scalp as possible, and quickly yanking upwards. The follicle should be clearly present and immediately preserved in the appropriate preservation solution. For those with longer hair, it is helpful to cut the hair close to the follicle before preservation.

While it’s possible to achieve results with a single, or up to three follicles, it’s better to acquire a larger set (up to 15 follicles), to ensure the needed mass for evaluation will be met. The follicles for the experiment should be taken from a similar location for each extraction, as there might be slight gene expression changes with different hair locations (head, arm, and eyebrow). Behind the ear for collection of the desired hairs for most applications is recommended. Following preservation, follow the manufacturer guidelines on storage and extraction/isolation of the RNA.

Sample Collection

The utility of a given sample to yield a clinically meaningful result is dependent on many factors. These include when and how samples were collected, the preservation method used to stabilize the analytes, shipping and storage effects, and the correct association of patient data with the sample. Variation in any of these areas can have a substantial impact on the usefulness of a sample.

There is conflicting data as far as the effect of time delay between sample collection and the time of extraction of RNA. Some studies report that any delay in getting the sample from the living state to a preserved state (frozen, in formalin (FFPE), or RNAlater) will decrease the quality of the sample. There are other studies that indicate that there is at least a 16 hour window in which the sample collection and the QC metrics of BioAnalyzer assessment do not show any degradation. In our experience, we have found that any interruption of sample collections state en route to preservation could lead to degradation of the RNA (unpublished observation). In order to leverage the value of biomarker samples, it is critical that the influence of these factors be minimized.

Treasure Trove of Clinically Useful Biomarkers

By studying overlooked sample types, we may identify a treasure trove of clinically useful biomarkers. While not every surrogate tissue will yield a disease or response-specific biomarker, there is substantial data to justify the investigation. There is undeniable value in the use of biomarkers in drug development and patient care, but this value is tempered with the cost of sample acquisition. Developing methods for the acquisition of clinically useful and easily obtainable samples is important as we move from a drug discovery process that is focused on finding the right drugs to one that focuses on finding the right patients.

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References
Bahlo, M., Stankovich, J., Danoy, P., Hickey, P. F., Taylor, B. V., Browning, S. R., The Australian and New Zealand Multiple Sclerosis Genetics Consortium, Brown, M. A., & Rubio, J. P. (2010). Saliva-derived DNA performs well in large-scale, highdensity single-nucleotide polymorphism microarray studies. Cancer Epidemiology, Biomarkers & Prevention, 19(3), 794-8

Sergueeva, Z., Collins, H., Dow, S., McWhorter, M., Parrish, M.L. Novel Tissue Types for the Development of Genomic Biomarkers. Biomarker edited by Kahn-T.K. ISBN: 978-953-51-0577-0 (April 2012)

Mark Parrish is the Associate Scientific Director of Biomarker Translation and Assay Development at the Covance Genomics Laboratory in Seattle, Washington. Parrish has over 12 years experience in the development and validation of genomics applications, including gene expression, genotyping and microRNA profiling. Prior to Covance, Parrish was a founding scientist at Rosetta Inpharmatics’ Gene Expression Lab, which was later acquired by Merck & Co. He received his Bachelor of Science degree from Indiana University-Purdue University at Indianapolis.