A morning gargle could someday be more than a breath
freshener — it could spot head and neck
cancer, say scientists at Johns Hopkins. Their new study of
a mouth rinse that captures genetic
signatures common to the disease holds promise for
screening those at high risk, including heavy
smokers and alcohol drinkers.
Lead investigator Joseph Califano says that his group
at both Johns Hopkins'
Department of
Otolaryngology-Head and Neck Surgery and
Kimmel Cancer Center asked 211 head and neck cancer
patients and 527 individuals without cancers of the mouth,
larynx or pharynx to brush the inside of
their mouths, then rinse and gargle with a salt solution.
The researchers collected the rinsed saliva
and filtered out cells thought to contain one or more of 21
bits of chemically altered genes common
only to head and neck cancers. Tumor and blood samples also
were collected.
The cellular mishaps occur when small molecules called
methyl groups clamp onto the DNA
ladder structure of a gene. In the grip of too many methyl
groups, these genes can incorrectly switch
on or off in a process called hypermethylation.
"Mass-methylation" of particular genes can lead to
cancer, the researchers say; methylation mistakes in other
genes could be triggered simply by aging
and amount to no more than fine lines and wrinkles.
"The challenge is to predict which hypermethylated
genes are most specific to cancer," Califano
said. And because every cancer process involves a unique
genetic fingerprint, combining several gene
signatures for the disease rather than using single ones
may identify a larger percentage of cancer
patients.
A report by Califano and his colleagues in the Jan. 1
issue of Clinical Cancer Research noted that
of 21 hypermethylated genes, seven were the best predictors
of cancer within cell-laden saliva. Of
the seven best, he tested panels of three to five genes on
saliva rinses.
One panel correctly identified 66 out of 154 patients
with the disease (42.9 percent) and
accurately ruled out the disease in 203 of 248 healthy
subjects (81.9 percent).
Califano's team used a different set of seven
hypermethylated genes among blood samples.
Although the blood test was more accurate than the saliva
test at detecting cancer in patients with
the disease (34 out of 37), there was a trade-off in the
number of healthy individuals it spotted (53
of 173).
"Few tests can be perfect 100 percent of the time in
identifying both normal and cancerous
cells," Califano said. "Because head and neck cancers are
not widespread, it makes more sense to
screen those [people] at high risk and to focus on a test's
ability to accurately rule out healthy
people."
Califano notes that tests designed for broader
populations, such as PSA, focus on identifying a
widespread disease in large numbers of people.
A saliva test, Califano says, is easy to do, painless
and cheap, capturing cells from a wide area of
the mouth. Some head and neck tumors do not shed genetic
material into the blood, making the saliva
test a better bet.
The Johns Hopkins investigators say that more studies
are needed to refine the test by
uncovering additional hypermethylated genes that play a
role, and to automate the test before multi-
institutional clinical trials can begin. One of the first
clinical uses for such a test could be to detect
recurrence in current head and neck cancer patients.
There are nearly 50,000 cases of head and neck cancer
diagnosed in the United States annually.
Most are found when the disease has spread, and less than a
year after diagnosis, many recur. Causes
include heavy tobacco and alcohol use. Other head and neck
cancers are caused by the sexually
transmitted human papillomavirus.
The study was funded by the Damon Runyon Cancer
Research Foundation, Flight Attendant
Medical Research Institute, National Institute of Dental
and Craniofacial Research and National
Cancer Institute.
Additional participants in the research, all of Johns
Hopkins, are Andre Lopes Carvalho, Carmen
Jeronimo, Michael M. Kim, Rui Henrique, Zhe Zhang, Mohammad
O. Hoque, Steve Chang, Mariana Brait,
Chetan S. Nayak, Wei-Wen Jiang, Quia Claybourne, Yutaka
Tokumaru, Juna Lee, David Goldenberg,
Elizabeth Garrett-Mayer, Steven Goodman, Chul-so Moon,
Wayne Koch, William H. Westra and David
Sidransky.