May 15, 2008 (Vol. 28, No. 10)

Emerging Technology Has Promise for Analyzing Copy Number Variation

Genetic aberrations that cause a gain or loss of chromosomal material are associated with mental retardation and congenital malformations and linked to development of cancer. Comparative genomic hybridization (CGH) is making strides as a powerful tool for analyzing such DNA copy-number alterations. This emerging technology is poised to reap big rewards in the burgeoning molecular diagnostics market. Further, as CGH’s precision and reliability continue to grow, important uses in the clinic and for personalized medicine will advance.

How does it work? Typically, genomic DNA from test and reference are isolated, differentially labeled, and then hybridized with DNA microarrays. The relative amount of hybridization signal is proportional to the copy number of the sequences tested. So-called CNPs (copy-number polymorphisms) are areas in the genome with altered DNA copy numbers. Identifying regions of genomic gains or losses can reveal chromosomal aberrations and define relative phenotypes within the population. Detecting and interpreting such aberrations can identify genes and pathways involved in pathological states.

Although microarrays for gene expression have been available for several years, arrays for CGH are fairly new, with usage growing at a tremendous pace, according to Condie E. Carmack, Ph.D., program manager, microarrays, diagnostics, Agilent Technologies (

“Array CGH (aCGH) provides an efficient means to determine changes in genomic copy number as well as transition points,” notes Dr. Carmack. “In a recent study, we applied high-resolution microarray-based aCGH analysis to FFPE breast cancer samples.” Dr. Carmack’s team used the company’s 244K CGH array, which consists of 244,000 in situ synthesized 60-mer oligonucleotide probes on a single 1×3 inch slide. The long probes are designed to offer high sensitivity and selectivity to improve the results of aCGH experiments, explains Dr. Carmack.

“It’s important to accurately determine copy number transitions and boundaries to define the genes that lie within aberrations. CGH provides this information, but working with FFPE samples can be challenging. This type of sample is often difficult to work with, because the fixatives interfere with the enzymes used to label DNA. But, we do not use enzymes, we use a universal labeling system from Kreatech (”

There are an estimated 400 million FFPE-preserved samples in tissue banks worldwide, underscoring the value of their use for analyzing DNA and genetic associations related to diseases such as cancer and autism.

Dr. Carmack’s studies identified three different classes of samples based on their CGH profile, two of which indicated a poor prognosis/survival outcome class and one that correlated with a good prognosis/survival outcome class.

“Overall, our studies help identify hot spots in the genome. In fact, we are seeing that the genome is much more dynamic than previously realized. Genes frequently amplify, replicate, and delete. Cancers can use these hot spots to gain growth advantages over normal cells. Identifying these areas associated with abnormal growth can lead to a targeted therapy, like in the case of Herceptin.”

Dr. Carmack expects that Agilent’s array will increase to a million features within a few months, offering even more information with no decrease in signal quality. The greater density is designed to drive resolution up while driving costs down, according to Dr. Carmack. “It is similar to increasing the pixel resolution on your digital camera.”

Some of the applications for aCGH technology are genotyping and medicinal genetics, reports Dr. Carmack. “All individuals have their own unique profile that shows familial, racial, and idiotypic differences, and these can be identified by genotyping. Secondly, we expect to see CGH used increasingly for personalized medicine.

For example, a drug might be dosed depending on how many copies a patient has of a particular gene impacted by the drug. If the gene is deleted, the patient might be too sensitive, while if they have 10 copies, they may need 10 times the dose. We know that people react differently to different drugs, and CGH will help the medical community get a much better handle on dosing.”

Making Sense of Massive Data Sets

Array CGH is an efficient approach for scanning entire genomes to seek variations in DNA copy number. “The technique of array CGH is changing from being only a research tool to being a tool for clinical diagnostics,” explains Anton Petrov, Ph.D., scientific director at infoQuant ( “But this requires a new generation of analytical solutions that can reliably and automatically report copy-number changes.”

InfoQuant offers two software products to assist with this analysis. “Our CGH Fusion™ analyzes CGH data across multiple samples,” says Dr. Petrov. “Ultimately, researchers want to be able to access information about the comparative frequency of appearance of each region of chromosomal aberration in patients with similar disorders and then compare that to healthy patients. CGH Fusion can find areas of common copy-number changes within the same biological condition. It is also scalable and user-friendly.”

The second product, oneClickCGH™, facilitates automated analysis of array CGH data on a per-patient basis. “This package allows a diagnostician to analyze low- and high-resolution data from various array CGH platforms. Discovered chromosomal regions are compared to various publicly available databases such as Entrez, Database of Genomic Variants (DVV), or the UCSC Genome Browser. This type of application is helpful for diagnosticians since they can use it to discover regions of a chromosome where if the copy number is changed, there is an increased risk of a disorder.”

More than 178,000 U.S. women are diagnosed with invasive breast cancer each year, with approximately 41,000 fatalities. CGH is being utilized along with other technologies to identify ethnic-specific differences. “These differences are increasingly evident in both stage at presentation as well as survival rates,” according to Lisa Baumbach-Reardon, Ph.D., associate research professor and director of molecular genetics for the Miami GeneCure Diagnostic Laboratory at the Dr. John T. MacDonald Foundation Center for Medical Genetics, University of Miami.

“We are investigating the genetic basis for these differences,” reports Dr. Baumbach-Reardon. “We initially studied African-American women and now are pursuing a multiethnic cohort consisting of 20 patients who are matched for age of diagnosis, cancer stage, and hormone-receptor status.”

To perform these studies, Dr. Baumbach-Reardon’s team characterizes DNA copy number and chromosome alterations by CGH arrays and also examines RNA expression differences in microarrays. “These technologies when applied together are even more powerful than if done alone because they help identify the multiple mechanisms involved. We are asking questions at the whole-genome level and are finding some interesting data. There are inherent variations in ethnicity and sorting out normal variations from pathological ones is the challenge.”

Use with Gene-Expression Arrays

The complementary technologies of CGH and gene-expression arrays are already revealing unexpected connections in a subset of breast cancer patients, so-called triple negatives (not associated with estrogen receptors, progesterone receptors, and HER2), according to Dr. Baumbach-Reardon.

“There are no helpful therapies for these women. We are already seeing significant differences across ethnicities. Our goal is to develop a signature profile that would be predictive of breast cancer for this subset of women. By assessing variations in copy number with CGH arrays, we hope to better understand the biological basis of ethnic-specific breast cancer disparities and to develop improved individualized diagnostic and therapeutic approaches.”

Initially aCGH was used to analyze copy-number changes in tumors in order to identify the genes involved. An emerging application of this technology is to detect so-called “unbalanced constitutional rearrangements” in nontumorous tissue.

“Several recent studies have mapped normal genomic variations, so called hot spots, using different high-resolution whole-genome screening platforms,” reports Karoly Szuhai, M.D., Ph.D., group leader, department of molecular cell biology, Leiden University Medical Center. “As a result, a collective database of genomic variants (DVV) was assembled that contained several normal variation loci. One problem is that this database is often consulted in screening for pathogenic alterations in order to exclude these normal variants. We showed that this could lead to false negative reporting.”

Dr. Szuhai describes a patient with mild hearing loss and mental retardation who inherited a homozygous deletion from nonrelated heterozygous carrier parents. “Interestingly, other families have been identified with a comparable syndrome of hearing impairment that point to an involved gene at this locus. The frequency of a hemizygous deletion is about 1.4%.

“The relatively high incidence of genomic variation of this region that is involved in both a syndrome and nonsyndromic hearing impairment points to it being an important locus for hearing loss. Furthermore, these studies point out the critical importance of a careful interpretation of results especially for cases involving normal variations at specific loci. This patient would have been shown to be negative by comparison to the DVV, whereas he actually does have a genetic aberration at this locus.”

Despite these concerns, Dr. Szuhai says that aCGH will likely be the first choice for clinical diagnostics in the near future. “Array CGH is rapidly evolving. New and increasingly higher-resolution technologies for genome-wide screening are currently being developed. In addition, there is also a significant cost-and-benefit relationship in being able to use such an automated and quantitative measure of chromosomal aberrations.”

Although many in the field feel that our understanding of benign and pathogenic genome variation is in its infancy, most expect rapid progress and even dramatic results will likely be realized in the years to come.

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