Cancer Detection Method Overcomes Problem of Samples with Few Cells

Finding cancer in a tiny drop of body fluid containing relatively few cells now may be possible with a new method of analyzing multiple genes in small samples of DNA, the cellular building blocks of our genetic code. The molecular test may be especially helpful in detecting cancer cells in breast fluid.

Preliminary tests of the new method, which can detect cancer in a sample with as few as 50 cells, were conducted on a small number of breast tissue samples and are reported in the July 1 issue of Cancer Research. “Our goal is to add a molecular solution to problems in cancer diagnosis where the sample is not adequate or microscopic evaluation of cells is unclear,” says Sara Sukumar, Ph.D., the Barbara B. Rubenstein Professor of Oncology at the Johns Hopkins Kimmel Cancer Center. “If additional studies prove the feasibility of this test, it will provide molecular clues to cellular pathology and mammography findings that may help to decide whether cancer is present.”

The test, called quantitative multiplex methylation-specific PCR or QM-MSP, works by looking for unusually high levels of molecules embedded by a process called methylation within critical regions of DNA. In this process, small methyl groups regulate DNA’s message-manufacturing process by attaching to the “on” switch of genes. Abnormal levels of methylation improperly turn the gene switch off, which ultimately leads to the loss of critical proteins found in normal cells. This adds to the cascade of genetic events leading to cancer.

“Until now, accurate levels of methylation in many genes at the same time was impossible without repeated tests, and with a small sample, we didn’t have enough DNA to perform all those tests,” says Mary Jo Fackler, Ph.D., research associate at the Kimmel Cancer Center and first author of the study. “Now, we’ve taken two existing types of MSP tests and put them together, which minimizes the amount of sample needed.”

QM-MSP determines the percentage of methylation present in each of four to five breast cancer genes. The percentages are added together for a cumulative score, which is compared to a threshold value. Levels above the threshold indicate the potential presence of cancer cells and below threshold suggests that the samples are normal.

In the first set of experiments, the Hopkins scientists tested QM-MSP on tissue samples using a panel of genes whose abnormal methylation patterns are known to be associated with breast cancer. The test detected cancer in 84 percent (16 of 19) of breast tumor samples, and found no cancer in 89 percent (eight of nine) normal tissues.

Next, the team tested QM-MSP on breast duct fluid samples obtained through a process called ductal lavage, a saline wash via a catheter threaded through the nipple. Of seven patients at high-risk for breast cancer and no known cancer present, six had no detectable levels of abnormal methylation in their breast cells, and one woman had low levels of abnormal methylation in one gene. QM-MSP detected cancer in two out of four breast cancer patients, which, the investigators say, indicates that this assessment tool holds some promise and is being evaluated in larger studies at Johns Hopkins.

According to the Hopkins team, the QM-MSP technique could be applied to the analysis of methylation in other cancers, such as oral lavage in head and neck, or sputum for lung cancer in which tissue samples are typically small.

This research was funded by the National Cancer Institute, Avon Foundation, Susan G. Komen Foundation, and the Department of Defense.

Other scientists participating in this research are Pedram Argani, M.D., Julie Lange, M.D., Elizabeth Garrett, Ph.D., Megan McVeigh, Jyoti Mehrotra, Ph.D., Marissa A. Blum, and Amanda Lapides from Johns Hopkins University School of Medicine.

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