Simple Model Proposed to Predict Breast Cancer Risk in Postmenopausal Women
A new, simpler model for predicting estrogen receptor-positive breast cancer risk in postmenopausal women appears to perform almost as well as the standard model. This new model could be used to identify postmenopausal women at high risk of estrogen receptor-positive breast cancer who may benefit from risk reduction strategies.
Many women must be screened to identify the minority who would benefit from taking a chemoprevention drug to reduce their breast cancer risk. A faster method of identifying these women is needed.
Rowan Chlebowski, M.D., Ph.D., of Harbor-UCLA Medical Center in Torrance, Calif., and colleagues used data from the Women’s Health Initiative to compare estimates of breast cancer risk using several different risk prediction models, including the widely used Gail model.
The Gail model underestimated 5-year breast cancer incidence by almost 20 percent, but it performed better when predicting estrogen receptor-positive breast cancer than estrogen receptor-negative breast cancer. The simpler model that used only three factors for calculating risk—age, family history of breast cancer, and previous breast biopsy—was almost as accurate as the Gail model for predicting estrogen receptor-positive breast cancer.
The simpler model “would be more accessible for routine and rapid prescreening in the prevention or routine care setting,” the authors write.
In an accompanying editorial, Mitchell Gail, M.D., Ph.D., of the National Cancer Institute in Bethesda, Md., after whom the Gail model is named, and colleagues write that many of Chlebowski’s results were consistent with epidemiologic literature. But they also note that breast cancer incidence in this study was higher than in the general U.S. population and that the risk from family history for estrogen receptor-negative breast cancer was much smaller than in many other studies.
“Chlebowski [and colleagues] have presented useful and important results that illustrate the promise and difficulty of estimating absolute risk in subtypes of breast cancer,” the editorialists write.
Contact:
- Article: Rowan Chlebowski, (310)222-2217, rchlebowski@gmail.com
- Editorial: National Cancer Institute press office, (301) 496-6641, ncipressofficers@mail.nih.gov
Smoking is Associated with Rectal Cancer
Cigarette smoking may be a risk factor for rectal— but not colon—cancer.
The evidence linking cigarette smoking and colorectal cancer risk has been inconsistent. Electra Paskett, Ph.D., of Ohio State University in Columbus and colleagues investigated the association between smoking history and colorectal cancer among nearly 147,000 participants in the Women’s Health Initiative.
After an average follow-up of about 8 years, 1,242 women were diagnosed with colorectal cancer. Increased colorectal cancer incidence was associated with more cigarettes smoked per day, more years as a smoker, and older age when the women quit smoking. Current smokers were at an increased risk for rectal cancer, but not colon cancer, compared with never smokers. Secondhand exposure to cigarette smoke was not associated with either cancer.
“Our data add to the extensive evidence indicating that preventing smoking initiation and decreasing the duration of smoking might reduce colorectal cancer risk,” the authors write.
Contact: Eileen Scahill, Ohio State University medical center communications, 614-293-3737, Eileen.scahill@osumc.edu
Researchers Discover How Cancer Drug Causes Heart Damage
Changes in the cardiovascular system caused by the anticancer drug ZD6126 may lead to heart damage in rats.
Drugs targeted at the blood vessels that feed a tumor, particularly drugs like ZD6126 that work by destabilizing microtubules, are associated with cardiovascular problems including high blood pressure or heart attack.
Anderson Ryan, Ph.D., of AstraZeneca in Cheshire, U.K., and colleagues investigated the mechanisms behind these adverse effects in rats. They monitored the rats’ heart rates and blood pressure and measured levels of a biomarker that indicates damage to the heart.
The researchers found that ZD6126 increases blood pressure and heart rate, which was associated with higher levels of the biomarker and increased death of heart muscle tissue.
“This conclusion has potential therapeutic implications because our studies also suggest that these [blood circulation] changes, and the subsequent cardiac side effects, may be ameliorated by [blood pressure medications] without overtly affecting the antitumor efficacy of ZD6126,” the authors write.
Contact: Anderson Ryan, 011-44-1625-512927, anderson.ryan@astrazeneca.com
Gene May Inhibit Lung Cancer in Mice and Humans
The GPRC5A gene acts as a lung tumor suppressor in mice and may work the same way in humans.
GPRC5A is expressed at higher levels in normal human lung cells than in lung tumor cells, which led to the hypothesis that GPRC5A is a tumor suppressor gene.
To test this hypothesis, Reuben Lotan, Ph.D., of the University of Texas M. D. Anderson Cancer Center in Houston and colleagues developed a mouse model in which GPRC5A is inactivated. They also compared GPRC5A expression in normal and cancerous human lung tissues.
Among the mice without the gene, 93 percent developed benign and malignant lung tumors, compared with just 10 percent of the normal mice. In the human tissues, GPRC5A expression was lower in most of the lung cancers examined than in the normal lung tissues.
“We found that GPRC5A functions as a tumor suppressor in the mouse lung and obtained data that support the conclusion that the human GPRC5A may act as a tumor suppressor in human lung carcinogenesis as well,” the authors write.
In an accompanying editorial, Michael Sporn, M.D., of Dartmouth Medical School in Hanover, N.H., discusses this new mouse model in the context of previous studies on GPRC5A expression in the lung and how it will be useful for examining the multistep process of lung cancer development.
“Given the importance of Gprc5a in both the human and mouse lung, one can expect that new advances will be forthcoming.,” Sporn writes.
Contact:
- Article: Scott Merville, M.D. Anderson press office, 713-792-0661, sdmervil@mdanderson.org
- Editorial: Michael Sporn, 603-650-6557, michael.sporn@dartmouth.edu
BRCA Mutations Influence Cancer Cells’ Response to Drugs
Breast cancer cells’ response to antiestrogen drugs may depend on the BRCA1 protein.
Most breast tumors with BRCA1 mutations do not express estrogen receptor alpha (ERá), while sporadic tumors with a normal version of BRCA1 express ERá. Alison Hosey, Ph.D., of Queen’s University in Belfast and colleagues examined breast cancer cells to try to explain this difference in ERá expression. They found that the BRCA1 protein is involved in activating the gene that makes ERá. Expression of the ERá gene was 5.4-fold lower in tumors with BRCA1 mutations than in sporadic tumors, and expression of ERá in BRCA1-depleted breast cancer cells made the cells more sensitive to an antiestrogen drug. They conclude that BRCA1 alters the response of breast cancer cells to antiestrogen therapy by directly influencing ERá expression. “This study adds further insight into the complex interaction between BRCA1 and ERá and provides a simple mechanism to explain the high frequency of ERá negativity observed in BRCA1-deficient tumors,” the authors write. In an accompanying editorial, V. Craig Jordan, Ph.D., D.Sc., of Fox Chase Cancer Center in Philadelphia discusses the mysteries that surround estrogen receptor regulation in breast cancer and how this study offers a good model that can be further investigated. “Hosey [and colleagues] provide a fascinating insight into these issues by presenting a unifying hypothesis for the regulation of [estrogen receptor] synthesis in breast cancer,” Jordan writes. Contact:
- Article: D. Paul Harkin, 011-28-90263911, d.harkin@qub.ac.uk
- Editorial: Diana Quattrone, Fox Chase Cancer Center press office, 215-728-7784, diana.quattrone@fccc.edu
Study Points Out Difficulties in Assigning Patients to Cancer Subtypes
Assigning new patients to previously identified cancer subtypes using microarray data poses problems that are highlighted in a new study.
Using microarray technology to study gene expression in tumor samples, researchers have claimed that they can identify different subtypes of cancers and that these subtypes have different prognoses. Lara Lusa, Ph.D., of Istituto Nazionale dei Tumori in Milan and colleagues used a common method to assign new breast cancer samples with known characteristics to previously identified cancer subtypes. But the researchers found that several factors influence how accurately different tumors samples are classified into subtypes.
“We showed that many difficulties remain in validating and extending…results to new samples and that projections…from one dataset to another must be done with care,” the authors write.
Contact: Lara Lusa, 011-39-2-574303209, lara.lusa@ifom-ieo-campus.it
Also in the November 13 JNCI:
Contact: Liz Savage
jncimedia@oxfordjournals.org
301-841-1287
Journal of the National Cancer Institute
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JNCI Journal of the National Cancer Institute