April 15, 2005 (Vol. 25, No. 8)
Interpretation of Data and Information Is Currently One of the Biggest Challenges
Microarrays allow researchers to better understand the relationship between gene expression and physiological function. Thanks to many recent technology and bioinformatics advances, clinicians are starting to apply this information. Experts in this field will gather at the CHI “Microarrays in Medicine” conference in May to present their latest products and data.
Targeted Arrays In-House
Signature Genomic Laboratories (www.signaturegenomics. com) constructs its SignatureChip microarrays in house, selects all the loci, and confirms all the inclusive DNA pieces.
“We spent a considerable amount of time identifying the clones of human DNA we wanted. This validation step is extremely important because you don’t want to put something on your microarray that isn’t representing the correct location in the genome,” says Lisa Shaffer, Ph.D., technical director and company co-founder.
This “targeted” microarray includes 126 clinical loci, with three to six overlapping clones for each locus, plus 104 control loci (to help determine the size of abnormality).
“Our interest was to cover all known microdeletion syndromes, all subtelomere regions, and all pericentromeric regions,” Dr. Shaffer explains.
Most cases analyzed are newborns with mental retardation or birth defects, who had a prior standard karyotype or routine chromosomal analysis that was normal, yet the physician knows the child has a chromosomal abnormality. Since the company can use DNA from any cells (e.g., placenta), its analysis takes about four days; faster than routine cytogenetics, which requires three days just to culture cells.
In order to compare a patient’s genome to a control genome, comparative genomic hybridization is used. Each genome is labeled with its own color, and hybridized in equal quantities together on the zxmicroarray. If the patient’s genome is missing a piece of DNA, it changes the dye ratio for a particular spot.
The company recently examined data from 700 of its processed cases and found 5.1% (36 cases) had a clinically relevant DNA alteration. “This is important data because it shows that routine chromosome analysis is missing abnormalities because the resolution is so pooryou just can’t see things as small as what we can see with the microarray,” Dr. Shaffer explains.
Monitoring Alternative Splicing
Although alternative splicing was discovered in the late 1970s, it has only recently been appreciated that almost 60% of all genes undergo some form of mRNA splicing, which is a potential source of diversity for protein expression.
Characterization of splice-specific alterations can provide potential new therapeutic targets and diagnostics. Exonhit Therapeutics (www.exonhit.com) recently launched its SpliceArray Service to detect and quantify these alternative-splicing events. This is now available using G-protein coupled receptor and ion-channel microarrays; future microarrays will include nuclear receptors and co-regulators, as well as the apoptosis-signaling pathway.
“We’ve developed a bioinformatic platform and database that utilizes the mRNA and EST (expressed sequence tag) public collection and aligned all those sequences back to the human genome. This is the database for all the source information for SpliceHit, our program that identifies the events,” says Richard Einstein, Ph.D., vp, research, USA.
A set of six proprietary oligonucleotides is used to surround and monitor each event that has been identified. “We then take the probes we’ve designed against this event and submit them to Agilent Technologies (www.agilent.com), which builds an array for us,” Dr. Einstein adds.
The service, launched in February 2005, is currently being used mostly for diagnostics and drug discovery, but can also be used for biomarker discovery, drug profiling, quality control, and pharmacogenomics.
“Alternative splicing is a sensitive and dynamic process that can be influenced by drug treatment and disease, and it is a strong mechanism for gene expression, signaling, and protein function. Our splice arrays give researchers the first real opportunity to use a tool that’s been designed to identify all these different transcripts and events that are occurring,” summarizes Dr. Einstein.
Eugene Brown, Ph.D., senior director, molecular profiling and biomarker discovery, biological technologies department, Wyeth Research (www.wyeth.com), will present how to combine tissue microarray analysis with transcriptional profiling for target identification. The researchers were able to identify a number of candidate targets suitable for the treatment of prostate cancer.
Combining Technologies
“The tissue arrays we used consisted of about 100 human specimenshalf were prostate cancer and half were benign prostatic hyperplasia (BPH). One of the targets was identified via RNA analysis, as well as being shown to be up-regulated in human prostate cancer samples.
“We were able to show on the tissue array that there was a significant difference in the protein expression of this particular gene (FKBP51) in the prostate cancer versus the BPH,” says Dr. Brown.
The target identification process used is a three-step approach. First, RNA analysis is done with the company’s cell lines. Then, the RNA data from the cell lines is compared to RNA data from the prostate samples. Finally, using the Gene Logic (www.genelogic.com) Bioexpress RNA data, Dr. Brown’s group compared that data to the data they started withthe prostate cancer cell lines treated with an androgen, dihydrotesterone.
“The whole thrust of this work is to understand the role of testosterone in the progression of prostate cancer. The genes we found that we were most interested in were based on statistical analysis and through data from BioExpress, we were able to further identify these targets as likely to be expressed in prostate cancer.”
The company has also used this approach to identify targets for inflammatory and cardiovascular diseases and other types of cancer. “This method has really helped Wyeth have a full early-stage pipeline because of the use of our own technology and outside information, along with our data-management efforts and bioinformatics.”
Chrosome Microdeletions
When a clinician examines a child who doesn’t fit one of the classic microdeletion syndromes, but has mild-to-severe mental retardation, and a standard chromosome analysis doesn’t reveal that, a subtelomere FISH analysis is conducted. Allen Lamb, Ph.D., laboratory director, Genzyme Genetics (www. genzymegenetics.com), will report on results from this assay, as well as potential ways to enhance it.
“One of the things we wanted was a way to look at the ends of chromosomes to see what was going on there. It was a more difficult problem to solve in terms of getting probesyou want to get as close to the end of the chromosome as possible, but to have it meaningful so that when a locus is missing, it is associated with an abnormal phenotype.
“It took a while to get a set of working probes because of the difficulty of the repeated sequences in that region,” explains Dr. Lamb.
His research group combined data from 10,000 case results of subtelomere FISH analysis with researchers from Emory University and LabCore (www.lab-core.com). There were 355 cases (3%) with abnormal chromosome ends; 2.6% of these were clinically significant.
“The subtelomere FISH extends our resolution or banding in specific regions that have been identified as having potential losses at a more frequent rate than other areas of the genome,” he adds.
Currently, some of the difficulties with this assay are that it is labor-intensive and cannot easily detect duplicated regions at the ends of chromosomes. In addition, in order to interpret results, the patient’s parents must also be karyotyped.
However, Dr. Lamb says his group is trying to develop this assay as a microarray. “We would like to initially have all the subtelomeres and a large number of the microdeletion syndromes available to do in one test.
“The goal is to be able to replace G-banding and have something consistent and reliable. We feel this is going to be a way to assess a large part of the genome in one experiment.”
VigeneTech (www.vigenetech. com) has adapted its original microarray image analysis software to support Reserve Phase Protein microarray analysis through a collaboration with researchers at NIH/NCI.
Software Enhances Image Analysis of Tissue Microarrays
“Our original software was for DNA and protein marker arrays, and we were approached by researchers who wanted to adapt our software to tissue microarrays,” explains Minzi Raun, Ph.D., CEO.
“Tissue arrays have a lot of biological informationeach array can have four to five screens, so you really can’t see what happens on each spot, unlike DNA arrays where you just measure each spot. It is challenging because the tissue arrays are difficult to automate.”
The MicroVigene 2.0 provides an automated solution for reverse-phase protein microarray image analysis. It supports various image layouts and dilution curve designs. Data analysis allows data comparison among different studies and clinical trials. It also provides a way to extract cell feature information for multiple channels and levels (i.e., cell membrane, plasma, nucleus).
Antibodies can be added to show cell changes for biomarker discovery and full spectral color options can be used to quantify immunohistochemistry for pathway analysis. “If you provide full spectrum you can see multiple protein staining on the spots and can see what contributes to changes within cells,” says Dr. Raun.
The research team at NIH/NCI is using the software to search for proteins that can be used for early biomarkers of disease, predict patient response to therapy, and for potential new therapeutics.
Currently, the software includes algorithms for breast, ovarian, prostate, lung, and colon cancers. The company will be presenting at the conference data in these disease areas, showing how the software is able to support the automated analysis.
Microarray System
Applied Biosystems’ (www. appliedbiosystems.com) Expression Array System offers several key features for gene expression profiling.
The company will present how the system is designed and how it performs, emphasizing two main pointsthe annotated gene content on the microarray and the fact that the system is a complete product.
“We think of gene expression as a whole application space where the microarray is at the top in terms of the highly parallel discovery tool where you can look at all the genes at once.
“Most researchers want to move quickly down to smaller sets of genes and that’s where we provide all the tools in terms of bioinformatics, to interpret results, and other tools like TaqMan to validate microarray results,” Gary Schroth, Ph.D., group leader, arrays, explains.
Since the company has a good handle on where genes are located, he notes, this enables it to design arrays with only one spot and one probe for each gene. Other approaches use ESTs to design microarrays, leading to five to six probe sets per gene, which don’t always give the same results.
There are currently three genome arrays available: full human, mouse, and rat. The human array contains 29,098 genesapproximately 6,000 of these are not present on any other commercially available array, according to the company.
The rat array is currently being used in a toxicology study with the National Center of Toxicology Research (division of the FDA) and was able to distinguish “good” compounds from “bad” compounds by providing distinct gene expression profiles for each group.
Overall, Dr. Schroth says their microarray system provides information, annotation, the ability to link results to pathways, and allows user to design their experiments logically. “We’ve found that these data-interpretation tools help people recognize the biological significance of their results and help them make the next step or decision to follow-up on that.”
Improving Medicine Through Genomics
How will genomic technologies help improve diagnosis, identify people at risk of disease, or better predict disease progression and treatment response?
Ellen Feigel, Ph.D., vp of clinical sciences and deputy scientific director, Translational Genomics Research Institute (www.tgen. org), will discuss how these technologies will advance into the clinic and, ultimately, create the foundation of personalized medicine.
Gene expression, molecular profiling, and RNA interference are integrated, says Dr. Feigel, because “on one end you want to identify the appropriate patient population who will benefit from a certain intervention, and then use RNAi to develop new therapies.”
She will provide some examples of applications of these technologies: gene profiling to predict prognosis for patients with early-stage breast cancer to help identify patients most likely to benefit from adjuvant treatment, RNAi research to study drug resistance, and combining the technologies to extend the use of currently available agents to tumors that were previously resistant to them or perhaps to new tumors.
“Using these technologies,” says Dr. Feigel, “will actually guide what therapies we put together for a patient. The point is to try and use information-based medicine to guide treatment.”
One of the biggest challenges in medicine now, adds Dr. Feigel, is interpreting all the data and information. “I think we’re going to see a lot of changes in medicine within the next decade. I hope we can do more pro-active risk mitigation, and that the new technology will tailor the type of interventions we provide to patients.
“But, it is going to require integrating our information databases, educating people about what’s going on in science and technology, and providing data in a user-friendly way so people have access to it.”
