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Sequencing Strategy Detects Rearrangements, Could Find Use in Personalized Cancer Treatment


By Monica Heger

This story, originally published on February 18, 2010, has been updated to include additional comments from outside sources.

In a step towards personalized cancer treatment, researchers from Johns Hopkins University have devised a sequencing strategy specifically for identifying structural rearrangements, which they said could be used to develop patient-specific "personalized biomarkers" that could be used to monitor tumor response to specific therapies.

The researchers published a proof of principle of the work last week in Science Translational Medicine and are now testing it on more patients to determine its clinical usefulness.

"We know these structural alterations are a hallmark of solid tumors; therefore identification of any alteration can be used as a diagnostic marker," said Rebecca Leary, lead author of the study and graduate student at the Johns Hopkins Kimmel Cancer Center. "Next-gen sequencing technology allows us to rapidly identify these structural alterations, sequence the breakpoint, and then use that breakpoint for further monitoring of residual disease," she added.

Leary and her colleagues used a sequencing strategy they dubbed "personalized analysis of rearranged ends," or PARE, on Applied Biosystems' SOLiD to selectively identify structural rearrangements in breast and colon cancer tumors. They sequenced two cancer and normal samples of breast cancer and colon cancer, and an additional two colon cancer samples without a normal match.

Leary said that PARE is particularly well suited for the SOLiD platform because it provides lots of paired-end reads per run, which allows them to efficiently identify rearrangements.

Stan Nelson, professor of genetics at the University of California, Los Angeles, agreed that doing the method on SOLiD was especially efficient because of the number of paired-end reads generated from the SOLiD, and he estimated that doing the same approach would be about twice as expensive on Illumina, and ten times as expensive on 454.

Leary and colleagues generated libraries with mate-paired tags 1.4 kilobases apart and used a 25 base pair mate-paired end sequencing strategy. They obtained about 198 million 25 base pair reads and 40 million mate-paired reads per sample, where the reads mapped perfectly and uniquely to the reference human genome. They achieved about 18-fold coverage.

Leary said the PARE method was designed specifically for the detection of rearrangements. "It requires much less sequencing than is needed for a complete genome assembly," she said. "So we only sequenced enough for rearrangement detection."

The team then looked for rearrangements. "The mate-paired tags allowed us to detect rearrangements by looking for tag pairs that map to different chromosomes, with incorrect ordering, orientation, or spacing," said Leary. In the samples where they also sequenced the normal tissue, they compared the findings to the normal tissue to ensure that the mutations were somatically acquired.

While the team was also able to identify rearrangements in the tumor-only samples, they could not verify whether those were somatically acquired. As a result, when they tested the identified rearrangements, they were only able to confirm about 50 percent of the rearrangements in the tumor-only sample, and between 70 to 90 percent in the tumor-normal sample.

To determine whether the identified sequences would be useful biomarkers they attempted to detect them in a mixture of cancer and normal DNA. They were able to detect the biomarkers in DNA mixtures containing the equivalent of one cancer genome to 390,000 normal genomes.

They also tested the technique on an actual patient before and after surgery, and found the biomarker in the patient blood samples both before and after surgery, although in much lower concentration post surgery.

Specifically, they found that the level of mutant DNA in plasma samples was 37 percent prior to surgery but 14 percent one day after resection of the primary tumor. The amount of mutant DNA "decreased further after chemotherapy and subsequent removal of metastatic lesions from the right lobe of the liver," the authors added, but did not reach zero, which they said was "consistent with the fact that this patient had residual metastatic lesions in the remaining left lobe of the liver."

The study "demonstrates the possibilities of clonal markers for solid tumors, which have previously been unavailable," said Heidi Greulich, instructor of medicine at the Dana-Farber Cancer Institute. "I think there is potential there for being able to follow the status of a tumor to treatment."

However, she added that the approach doesn't allow researchers to detect the location of the tumor. "It can only give overall tumor status of the patient," she said. "It doesn't give you spatial information the way that imaging methods would." In the case of metastasis, knowing the location of the tumor would be particularly important.

Li Ding, research assistant professor of genetics at Washington University's sequencing center, said the study "demonstrates the power of next-gen sequencing at low coverage for identifying structural rearrangements," and using that method to "monitor tumor progression." She said that the Hopkins approach — using long insert sizes so that they didn't need as much depth of coverage — was a good way to efficiently look for rearrangements.

Ding's group has also developed a method for detecting rearrangements, an algorithm called BreakDancer, which they developed for the Illumina platform and have used to analyze rearrangements in acute myeloid leukemia samples. She said it would be interesting to compare the two methods on the same sample, or to use them together to improve specificity.

UCLA's Nelson added that the sequencing method itself wasn't particularly new, but said that the researchers were able to demonstrate that they could find rearrangements without having to generate lots of data, making the method more efficient and cost effective than previously demonstrated.

He also thought that it would be useful to monitor cancers that are often overtreated, like childhood cancers. In that case, he said the biomarkers could be used to monitor the cancer and determine when the cancer is cured. That would be useful for leukemia, because it is often unclear when treatment should be stopped. But, he added, in breast or colorectal cancer, it is rare that patients are overtreated.

The Johns Hopkins team is now testing the method on more patients and different cancer types, including 50 colorectal cancers and 50 pancreatic cancers, to see how it could be used in a clinical setting, and has filed patents on the technique. Before it could be clinically useful, though, the cost would need to come down to at least the level of conventional imaging methods, like CT scanning, which currently runs around $1,500 per scan.

The sequencing-based approach would likely be able to detect recurrent cancer before a CT scan would, but the authors noted that it currently costs around $5,000 per patient due to the level of sequencing required to identify patient-specific alterations.

"This cost is a consequence of the high physical coverage and the inefficiencies associated with stringent mapping of 25-bp sequence data to the human genome," they wrote. "As read quality and length continue to improve, less stringent mapping criteria and lower physical coverage will permit analyses similar to those in this study but with substantially less sequencing effort."

Leary noted that the method is "a really exciting test that could be used in a number of clinical settings."

For example, if a patient with early-stage cancer is treated surgically, "a clinician could use this to see if the surgery was curative. Alternatively, if a patient was in the late stages of the disease, a physician could use it to monitor throughout the course of treatment to see how well the treatment is working and to assess tumor burden," she said.

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