February 15, 2011 (Vol. 31, No. 4)

Personalized Tests and Treatments Are Heightened by Repertoire of Advances in DNA-Based Technologies

Few clinical niches are currently spared from the reach of novel genomic technologies. Molecular analysis technologies enable the parsing of biological pathways with previously unattainable granularity. Stratifying patient populations based on their genetic markers is becoming a clinical reality. In the near future, some of these markers may become targets for developing better treatment options.

Utilization of molecular diagnostics in specific clinical scenarios, however, still needs to be significantly optimized. In particular, results from these novel assays need to be interpreted in a context of traditional clinicopathologic criteria, particularly in situations where the novel and the traditional measurements produce conflicting results. But even with validation of novel technologies for molecular diagnostics still ongoing, clinicians are already able to apply the first insights to patient treatment.

CHI’s upcoming “Molecular Medicine” conference will explore new frontiers of DNA-based diagnostic technologies. Several cutting-edge technologies may be discussed that have a potential to make a profound difference in our way of diagnosing and treating disease.

The potential for prenatal diagnosis would explode if clinicians could avoid amniocentesis and easily access fetal DNA from maternal blood. Most current maternal screening tests are based on associations between various maternal blood levels and fetal outcomes and can only indirectly assign a risk of a particular fetal abnormality. By contrast, amniocentesis enables direct sampling of fetal DNA for diagnostic purposes.

A small amount of amniotic fluid, which contains fetal cells, is extracted from the amniotic sac surrounding a developing fetus, and the fetal DNA or chromosomes can then be evaluated for genetic abnormalities. But amniocentesis is expensive and can lead to complications including miscarriage. The work of Y. M. Dennis Lo, M.D., a professor at the Chinese University of Hong Kong, has resulted in the ability to detect cell-free fetal DNA in the maternal circulation (ccff DNA).

In the maternal circulation, about 3–5% of all circulating cell-free DNA comes from the fetus. Cell-free fetal DNA has led to the development of several noninvasive tests using maternal blood to directly determine the fetal status, Dr. Lo explains. He notes that this discovery has allowed amniocentesis to be deferred in some cases.

One such example is the test for rhesus factor, a problem in about 15% of pregnancies. “By testing the mother’s blood for the Rh antigen of the fetus, we could potentially avoid the unnecessary use of Rh immunoglobulin (a blood product) in nearly 200,000 women in the U.S. alone,” comments Roger Lenke, M.D., director of the Indiana Center for Prenatal Diagnosis.

“Another—potentially more dramatic—use of cell-free DNA would be in the detection of fetal chromosome abnormalities. Current maternal serum tests for Down syndrome are based on indirect associations and only give the mother a risk, not an answer. The current screening tests have both high false-positive and false-negative rates.”

Several companies are developing ccff-based tests for Down syndrome. Sequenom is proceeding with a DNA-based method for the detection of trisomy 21 using massively parallel shotgun sequencing.

The technology enables detection of the additional chromosome by quantitating the volume of short sequences corresponding to chromosome 21, according to the company. Last month, Sequenom initiated a pivotal clinical study in which samples from high-risk pregnancies will be analyzed. These blinded studies are designed to support launch of a noninvasive T21 laboratory-developed test.

Future applications of shotgun sequencing of ccff DNA include early identification of cystic fibrosis, beta thalassemia, or congenital adrenal hyperplasia, all of which could potentially be treated in utero. Detection of elevated levels of circulating fetal DNA may even enable the early diagnosis of pre-eclampsia. Similar molecular analysis principles could be applied to other types of foreign DNA, such as circulating tumor DNA or DNA from organ transplants.

The Sequenom® MassARRAY® 4 Analyzer is used in molecular diagnostic applications.

Lung Cancer

It is now widely accepted that classification of tumors based on their genetic markers is an important prerequisite for designing and choosing an appropriate disease-management strategy. Classification of lung cancer, however, still relies on the visual evaluation of the morphology of the tissue. What makes it even more difficult is that each of the major histological types of lung cancer is a heterogeneous collection of tumor subtypes.

The World Health Organization has attempted to describe these subtypes based on morphological appearance, but this classification is of limited usefulness in clinical practice due to high subjectivity of such characterization.

“Other cancers, such as breast cancer, have clearly identifiable genetic characteristics that profoundly influence the choice of therapies,” says D. Neil Hayes, M.D., Lineberger Comprehensive Cancer Center, University of North Carolina. “We were able to lay the background work for clear and reproducible identification of lung cancer subtypes based on DNA microarrays.”

Dr. Hayes’ group supplemented its own studies with the meta-analysis of previously published independent datasets, resulting in a sizable cohort of over 1,000 patients. “Historically, reconciliation of the results of individual gene-expression studies proved to be very difficult. Although tumor subtypes seemed to exist, there was no consensus of their number on nature.

“We realized that if we correct for technical imperfections, we should be able to uncover biological bases characteristic to each subtype.”

The researchers analyzed the studies generated on several different gene-expression platforms and utilized integration correlation statistics to select for the probes that measured the expression reproducibly across the chosen platforms. Out of 3,000–5,000 genes selected by this method, about one-third demonstrated reproducible differential expression of varying degrees.

The analysis placed all adenocarcinoma samples into three subtypes, and squamous cell carcinomas into four subtypes. The subtypes have statistically significant survival differences and patient demographics, independent of disease stage. They are comprised of tumors with differing underlying rates of mutations in key lung cancer genes, including KRAS and EGFR.

This heatmap depicts mRNA expression by shading from blue (low expression) to yellow (high expression). Genes are rows, and lung tumors are columns. The colored rectangles atop the heatmap indicate each sample subtype, in which samples of the same color are the same subtype (black, red, green).[University of North Carolina]

Predicting Radiation Resistance

Sixty percent of cancer patients undergo radiation therapy (RT). However, the majority of epithelial cancers is only marginally sensitive to RT, requiring very large doses to produce a measurable effect. Some types of cancer (such as renal cell and melanoma) are notoriously resistant to RT.

“We started with the idea that tumor regulatory pathways are organized in complex networks where a significant redundancy could be expected,” comments Javier F. Torres-Roca, M.D., division of experimental therapeutics, H. Lee Moffitt Cancer Center and Research Institute and CMO at Cvergenx. “Therefore, to understand tumor radiosensitivity, one needs to understand the structural molecular components of radiation sensitivity networks.”

The team began by analyzing individual gene expression in cancer cell lines and correlating it with cellular response to radiation. “However, just gene expression was not enough to develop the mathematical algorithm. The model had to include other biological data, such as mutation status of RAS and p53 genes. Once we added the biological data, we were able to use linear regression to fit a predictive model to an observed dataset.”

The studies supported linear regression analysis as a valid approach to correlate gene expression with intrinsic radiosensitivity of the cells lines. The resulting map of 500 interconnecting genes was further distilled to the network of 10 gene hubs. The predictive value of the model was validated using knockouts of hub genes, which increased tumor radiosensitivity.

“Not surprisingly, the analysis of known radiosensitizer drugs showed that they interfered with just a few of the hubs, suggesting that our clinical approach needs to include combination strategies, overcoming the redundancy of signals,” says Dr. Torres-Roca.

The current model predicts a radiosensitivity index (RSI) for tumors of epithelial origin. A positive predictive RSI value was 86% when correlated with the pathological response to RT in esophageal, rectal, and head-and-neck patients. And while the model is still being validated, it may be the first step to understanding how RT may be tailored for the maximum patient benefit.

Radiosensitivity network hubs: Ten hubs were identified from an original analysis that had identified a 500 gene network. Known biological interactions were used to interconnect the network and hubs were identified as those having more than five connections within the network. Hubs that are circled are currently therapeutically actionable with drugs available or in development to modify radiation response. A clinical assay to predict intrinsic radiosensitivity was developed based on gene expression of the ten hubs. This test has been validated in three independent datasets totaling 118 patients with rectal, esophageal, and head and neck cancer. Currently, an NCI-sponsored clinical trial is under way to prospectively validate the radiosensitivity test.


“Similarly to radiosensitivity, we are yet to stratify the patients based on the benefits that they may receive from chemotherapy,” adds Kenneth J. Bloom, CMO at Clarient, a GE Healthcare company.

“Traditionally, tumor recurrence was estimated by looking at tumor burden and proliferation status,” he explains. “Approximately 85% of lymph-node negative breast cancer patients who express hormone receptors could be cured by surgery alone, but since our current methods of evaluating tumor specimens cannot accurately predict who benefits from the addition of chemotherapy, thousands of women worldwide may be treated with chemotherapy unnecessarily.”

Clarient has developed a new tool for pathologists to aid them in assessing the biologic aggressiveness of a breast cancer specimen. Its InSight® Dx Mammostrat® assay assigns a patient’s tumor to one of three risk categories—low risk, intermediate risk, or high risk—indicating the relative risk of recurrence. The pathology sample is evaluated with a five-antibody reagent assay that corresponds to gene-expression clusters found to be predictive of recurrence.

“The Mammostrat test fits perfectly into the currently established prognostic workup of biopsy specimens. The pathologist, who already visually evaluates tumor size and grade, will now also have a chance to look at the staining localized to the specific cancer cells,” says Dr. Bloom. “Conversely, with genomic analysis, DNA or mRNA is extracted from tissue sections containing not only tumor but variable amounts of stroma cells, inflammatory cells, and other cell types that are all blended together, diluting the signal from actual cancer cells.”

The antibodies used in the Mammostrat assay were chosen after several rounds of validation. An initial set of 700 antibodies was evaluated, but most of these antibodies were eliminated from further exploration because of poor staining characteristics or limited discriminatory ability on a training set with known outcomes.

A final set of five antibodies was modeled into an algorithm that was tested on three independent cohorts and then on two national randomized sets of samples from patients receiving tamoxifen or placebo in one trial and tamoxifen or tamoxifen plus chemotherapy in the other trial. Based on the data from these trials, 58% of the patients were assigned to the low-risk category while 21% of patients were assigned to each of the moderate- and high-risk categories.

The ten-year recurrence rates for the three categories are 7.6%, 16.3%, and 20.9% based on a 1,500 patient cohort from Scotland. “Adding this independent data element to the typical pathology evaluation has the potential to decrease the number of women treated with chemotherapy by one-third,” remarks Dr. Bloom. “It is now possible to combine clinical assessment, tumor burden, tumor proliferation, and tumor biology to give women the best possible treatment recommendations.”

The Mammostrat test is available through Clarient’s CLIA-certified laboratory. Clarient plans to continue to improve the test and incorporate next-generation quantitative microscopy being developed at GE for readouts.

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