This article introduces MMRpro, a model for prediction of genetic susceptibility in the Lynch syndrome, which makes efficient use of family history and tumor information and provides individualized evaluations. Because model-based prediction algorithms are increasingly used in genetic counseling and prevention activities, MMRpro is a timely tool for identifying and counseling families at risk for the Lynch syndrome and can improve current genetic counseling and early detection practice. In an independent validation, MMRpro demonstrated a better ability to predict mutation carriers than both the Leiden model and Bethesda Guidelines–based screening.
Current Bethesda Guidelines–based screening practice aims at identifying individuals likely to harbor tumors with MSI. An important limitation is that these criteria are not applicable when a tumor block is unavailable or to unaffected individuals concerned by family history and considering genetic testing and secondary prevention. Among individuals with tumors, the Bethesda Guidelines are sensitive but not highly specific and rely on MSI testing to improve specificity. However, even when tumor samples are available, MSI testing may not be the optimal course of action for all families. The high-resolution quantitative assessment obtained by setting a high threshold on MMRpro offers the option of performing germline testing directly, without MSI testing, in selected families.46
This strategy can both increase specificity and decrease costs. In our validation sample, MMRpro provides equal or better sensitivity and specificity with less MSI testing. We also estimated that a large fraction of families in the validation sample can reach an informed decision on whether to undertake germline testing without testing for MSI. For others, such as small families, families with older ages at diagnosis, and some families not meeting the Bethesda Guidelines, MSI testing is highly informative.
Some clinics also use immunohistochemical staining, because the loss of a protein product is highly predictive of the presence of mutations.61
In our model we can account for either immunohistochemical or MSI results. Given the technical complexity of MSI analysis, which involves microdissection and DNA extraction, pathology departments may first perform immunohistochemical analysis and reserve MSI analysis for cases with a strong clinical suggestion. In that scenario, MMR-pro may also be useful, in that it would allow for setting a threshold for performing such additional analyses.
When germline mutation tests with relatively low sensitivity are used, MMRpro posttest probabilities are useful for individuals in whom, despite strong evidence of predisposition, no mutation is found. Before more sensitive techniques become available or new genetic factors are identified, the cancer risk predictions for such individuals provided by MMRpro help to guide subsequent clinical management. This feature is also valuable for counselees who do not wish to be genotyped but would still like to consider preventative measures.
Along with other screening approaches,62,63
risk prediction based on family history is routinely used to identify individuals for CRC screening. Due to the imperfect sensitivity of sequencing, it remains likely that high-risk in dividuals who are untested or who receive “no mutation found” results will undergo routine screening.When asymptomatic individuals and their family members age without developing CRC, their chance of carrying deleterious mutations decreases. MMRpro can be used to help adaptively update their screening choices.
While useful, our model has limitations, some of which will be addressed in future updates as new studies provide the necessary information. Currently, MMRpro considers only endometrial cancer, the most common type of extracolonic tumor associated with the Lynch syndrome. The spectrum is wider, but at present, data on penetrance for these cancers are insufficient for modeling purposes. Colorectal adenomas and polyps and their histological features may also be predictive of MMR mutations, but their predictive value is difficult to quantify. The predictive value of MSI may vary with age because of the age-related increase in hypermethylation of the MLH1
The MSI status of extracolonic cancers is likely to have different predictive abilities, depending on the site as well. Lifestyle risk factors also have yet to enter the model, as doprophylactic surgeries that reduce risks significantly.66
In model-based risk counseling, variability in the estimates should be recognized. Uncertainty remains on the risk conferred by MMR mutation (as illustrated by the supplementary figure
), calling attention to the importance of more extensive investigations of penetrance.
Finally, in decision making for germline testing, a mathematical model can be informative for the reasons we have described. However, decision making regarding germline testing should reflect a broader range of factors, including the effectiveness and cost of genotyping; the available means and efficacy of measures for early detection and risk reduction; and possible psychological, social, and ethical implications. This should be done in concert with a health care professional experienced in cancer genetics67–69
who can also advise on the choice of cutoffs appropriate for individual circumstances. The informed consent process will ensure that patients consider all of these issues prior to testing.70