Two new prediction models help identify which patients suspected of having Lynch syndrome should undergo extensive genetic testing for the mutations associated with colorectal cancer.
Lynch syndrome, also known as hereditary nonpolyposis colorectal cancer, is characterized by the predisposition to develop early-onset colorectal cancer as well as cancers of the endometrium, gastrointestinal tract, ovary, hepatobiliary system, urinary tract, brain, and other sites. It is almost always associated with underlying mutations in the mismatch DNA repair system, most often in the MLH1 and MSH2 genes.
Currently, screening for Lynch syndrome is fraught with challenges. Clinical criteria for identifying which patients are likely to have the syndrome are restrictive and don't take into account several variants of the disease. They also rely on detailed family histories or on tumor samples, which often are not available. Further genetic testing is not very sensitive or specific and is expensive.
Two research groups have developed different models to predict the likelihood that patients have Lynch syndrome and should undergo genetic testing, much like the models that are widely used by health care professionals to predict mutations in the BRCA1 and BRCA2 genes in assessing patients' breast cancer risk.
The PREMM1,2 (Prediction of Mutations in MLH1 and MSH2) model was developed using a cohort of 898 probands and 1,618 first- or second-degree relatives who submitted blood samples for sequencing of the two genes, then validated in another cohort of 1,016 probands. This genetic testing had been ordered by the probands' health care providers—chiefly geneticists, oncologists, gastroenterologists, and gynecologists—who suspected Lynch syndrome because the patients' personal or family histories were suggestive, according to Dr. Judith Balmana of Dana-Farber Cancer Institute, Boston, and her associates.
These large, diverse, national cohorts allowed the investigators to incorporate great detail into their prediction model, including the age at diagnosis of probands and their relatives, the presence of colonic adenomas, and the different degrees of risk for different cancers.
The PREMM1,2 model thus is more sensitive and specific than clinical criteria in determining which patients should undergo extensive genetic testing. It also helps decide which approach to genetic testing will be most useful (JAMA 2006;296:1469–78). The PREMM1,2 model is available through the Dana-Farber Web site (www.dfci.org/premm
The MMRpro (Mutations of Mismatch Repair) model also is more sensitive and specific than existing clinical guidelines for identifying patients who may benefit from genetic testing, reported Sining Chen, Ph.D., of Johns Hopkins Bloomberg School of Public Health, Baltimore, and associates.
In particular, this statistical model estimates the likelihood that a patient carries deleterious mutations of the MLH1, MSH2, or MSH6 genes in cases in which tumor tissue is not available for analysis or commercial germline testing techniques have been insufficiently sensitive to detect a mutation.
The MMRpro model was developed using a meta-analysis of studies that provided risk estimates for colorectal and endometrial cancers. It was then validated in a cohort of 279 patients who had undergone germline testing and who were from 226 families believed to be affected by Lynch syndrome.
The MMRpro model incorporates both a mutation-prediction algorithm and a cancer-risk prediction algorithm. The latter allows clinicians to estimate the likelihood that cancer will develop in patients who have strong evidence of Lynch syndrome but in whom no mutation has been found. “This feature is also valuable for [patients] who do not wish to be genotyped but would still like to consider preventative measures,” Dr. Chen and associates said (JAMA 2006;296:1479–87).
“Software for performing MMRpro calculations is open source and available free of charge via either the mendelian risk prediction package Bayes Mendel at www.astor.som.jhmi.edu/BayesMendelwww.utsouthwestern.edu/breasthealth/cagene
In an editorial comment accompanying these reports, Dr. James M. Ford and Dr. Alice S. Whittemore of Stanford (Calif.) University's clinical cancer genetics program said that both prediction models should prove to be “very useful tools for clinicians and their patients, as well as for epidemiologists.”
These models should improve clinicians' ability to identify patients at risk for Lynch syndrome “and hopefully to prevent cancer from occurring using intensive surveillance techniques and prevention schemes,” Dr. Ford and Dr. Whittemore said (JAMA 2006;296:1521–3).