Original Article
Identification and Survival of Carriers of Mutations in DNA Mismatch-Repair Genes in Colon Cancer
N Engl J Med 2006; 354:2751-2763June 29, 2006
- Abstract
Background
The identification of mutations in germ-line DNA mismatch-repair genes at the time of diagnosis of colorectal cancer is important in the management of the disease.
Methods
Without preselection and regardless of family history, we recruited 870 patients under the age of 55 years soon after they received a diagnosis of colorectal cancer. We studied these patients for germ-line mutations in the DNA mismatch-repair genes MLH1, MSH2, and MSH6 and developed a two-stage model by multivariate logistic regression for the prediction of the presence of mutations in these genes. Stage 1 of the model incorporated only clinical variables; stage 2 comprised analysis of the tumor by immunohistochemical staining and tests for microsatellite instability. The model was validated in an independent population of patients. We analyzed 2938 patient-years of follow-up to determine whether genotype influenced survival.
Results
There were 38 mutations among the 870 participants (4 percent): 15 mutations in MLH1, 16 in MSH2, and 7 in MSH6. Carrier frequencies in men (6 percent) and women (3 percent) differed significantly (P<0.04). The addition of immunohistochemical analysis in stage 2 of the model had a sensitivity of 62 percent and a positive predictive value of 80 percent. There were 35 mutations in the validation series of 155 patients (23 percent): 19 mutations in MLH1, 13 in MSH2, and 3 in MSH6. The performance of the model was robust among a wide range of cutoff probabilities and was superior to that of the Bethesda and Amsterdam criteria for hereditary nonpolyposis colorectal cancer. Survival among carriers was not significantly different from that among noncarriers.
Conclusions
We devised and validated a method of identifying patients with colorectal cancer who are carriers of mutations in DNA repair genes. Survival was similar among carriers and noncarriers.
Media in This Article
Figure 1
Survival Analysis of 870 Patients, According to Mutational Status and Tumor Staging.Table 1
Clinical and Molecular Data on Patients under the Age of 55 Years Who Had Colorectal Cancer with Pathogenic Mutations.Article Activity
- Article
Genes responsible for several autosomal dominant and recessive colorectal-cancer–susceptibility syndromes have been mapped and causative mutations characterized.1,2 Most autosomal dominant syndromes are defined empirically on the basis of family history and clinical and pathological criteria, such as the criteria for hereditary nonpolyposis colorectal cancer (also called the Lynch syndrome).3,4 In clinical practice, however, the use of these approaches creates a bias against low-penetrance alleles, small families, nonpaternity or adoption, and newly arisen mutations. The Lynch syndrome is caused by inactivating mutations of DNA mismatch-repair genes (mostly MSH2, MLH1, and MSH6),5 but many patients with colorectal cancer who have such mutations do not fulfill the empirical criteria for the Lynch syndrome.6-8 Moreover, about 1 in 3100 people between the ages of 15 and 74 years carries a defective DNA mismatch-repair gene.9 This finding implies that patients with incident colorectal cancer who fulfill the criteria for the Lynch syndrome do not account for all mutation carriers. The fact that asymptomatic carriers have a substantial risk of colorectal and other cancers10-12 underscores the importance of identifying these carriers early enough to allow for counseling and surveillance.
Practical and financial constraints often require initial testing (prescreening) of tumor DNA for microsatellite instability or immunohistochemical assessment of tumor sections for DNA mismatch-repair proteins, or both, before the genotyping of incident cases of cancer. Prescreening assumes that microsatellite instability is a consistent feature of tumors from carriers, but some tumors do not have microsatellite instability.8 Moreover, prescreening misses an appreciable number of mutations in DNA repair genes6,8 and has a relatively poor positive predictive value.6,8,13 In addition, analysis of patients with incident colorectal cancers for microsatellite instability and DNA mismatch-repair proteins14 without previous genetic counseling and explicit consent raises ethical concerns, because patients with tumors that do not have DNA mismatch-repair proteins and do have microsatellite instability are likely to carry heritable germ-line mutations.
There is inconclusive evidence that the prognosis of colorectal cancer among patients with the Lynch syndrome is better than that among patients with sporadic cases.15-17 Sporadic colorectal cancers with microsatellite instability have a better prognosis than do microsatellite-stable sporadic tumors,18-20 but this difference does not necessarily apply to tumors with germ-line defects in DNA mismatch-repair genes.
Mutational analysis of germ-line DNA mismatch-repair genes without previous testing of the tumor has not been undertaken in a prospective, population-based series.21 In this study, we looked for such mutations without considering the family history or the results of tumor testing in a prospective, population-based series of 870 cases of early-onset colorectal cancer, a group enriched for genetically determined disease.6-8,13,22,23 This approach allowed us to construct a clinically driven predictive model that aids in the prediction of carriers of germ-line mutations of DNA mismatch-repair genes.
Methods
Beginning January 2, 1999, we identified all patients in Scotland (population, 5.06 million) who had received a diagnosis of colorectal cancer before the age of 55 years. All such patients were identified soon after the diagnosis and regardless of family history. After the exclusion of 15 patients with dominant polyposis syndromes, 1259 patients agreed to undergo genetic counseling and gave informed written consent for germ-line and tumor analysis before the end of 2005. The study population comprised 870 consecutive patients who received a diagnosis of colorectal cancer between February 1999 and July 2003 and in whom mutational analysis and follow-up were complete. The study population also included 72 percent of 1206 patients with incident cases identified independently by the Scottish Cancer Registry. Of these patients, 80 did not respond to our request, 156 had psychiatric or physical illnesses that precluded their enrollment in the study, and only 100 patients declined to participate, which left us with 90 percent compliance overall. The study was approved by the research ethics committees and National Health Service (NHS) management of every participating hospital.
An invitation to participate in the study was extended to patients within a few weeks after diagnosis to minimize survival bias. Family history was obtained at the time of the interview, a blood sample was taken for DNA analysis, and tumor samples were acquired from NHS pathology departments. The date of disease onset was defined as the date of the first histologic diagnosis of colorectal adenocarcinoma. The cancer history of patients was obtained by personal interview and cross-reference of personal identifiers with the Scottish Cancer Registry. Tumors were staged according to Dukes' classification and tumor–node–metastasis (TNM) criteria in accordance with recommendations of the American Joint Committee on Cancer.
Mutational Analysis
Germ-line DNA obtained from blood leukocytes was analyzed for MLH1, MSH2, and MSH6 mutations. Denaturing high-performance liquid chromatography analysis (Transgenomic) was used for 11 exons of MSH2 and 16 exons of MLH1. Variants noted on chromatography were sequenced, as were MSH2 exons 1, 4, 5, 10, and 13 and MLH1 exons 8, 12, and 15 in every sample (ABI 3730 DNA Analyzer, Applied Biosystems). All 10 MSH6 exons were sequenced. Sequencing chromatographs were assessed visually and with the use of Sequencher software. Mutations were confirmed by reamplification of an independent sample of DNA and resequencing in both directions. MLH1 and MSH2 were assessed for deletions by multiplex ligation-dependent probe amplification (MLPA, MRC-Holland), with products separated on an ABI 3100 xl Genetic Analyzer (Applied Biosystems) and analyzed with the use of custom software (available on the Web site of the United Kingdom National Genetics Reference Laboratory at www.ngrl.org.uk/Manchester/Publications.htm#MLPA).
Analysis of Microsatellite Instability
Tumor DNA that had been purified from microdissected 10-μm tumor sections (QIAamp DNA minikit, Qiagen) was subjected to multiplex polymerase-chain-reaction assay with the use of BAT25, BAT26, D2S123, D5S346, and D17S250 markers24 and compared with control DNA from blood or normal tissue in the section. Products were analyzed with the use of ABI PRISM 3100 and Genescan software (Applied Biosystems). Tumors with more than one shifted marker were categorized as having a high degree of microsatellite instability, those with one unstable marker were categorized as having a low degree of microsatellite instability, and those with no instability were categorized as being microsatellite stable.
Immunohistochemical Analysis
Paraffin-embedded sections that had been stained with antibodies against MLH1, MSH2, and MSH6 were assessed independently by two microscopists. If discrepancies could not be resolved, a third pathologist reviewed all slides.
Statistical Analysis
Two-Stage Predictive Model
Univariate analysis of clinical variables by logistic regression identified independently significant predictors of mutational status. These predictors were included in multivariate logistic regression to construct a two-stage model for the prediction of whether patients carry germ-line mutations of DNA repair genes on the basis of clinical variables (see the Supplementary Appendix, available with the full text of this article at www.nejm.org). The least significant variables were removed one by one until all variables remained significant. All variables (except the age at onset) were included as categorical variables. The use of automatic stepwise backward and forward selection criteria, on the basis of the likelihood ratio and the Wald statistic, yielded similar results on logistic regression with SPSS software, so we selected the simplest model. The final multivariable analysis that estimates carrier probabilities for stage 1 of the model can be described by the following equation, which can be solved electronically at http://www1.hgu.mrc.ac.uk/Softdata/MMRpredict.php 25: Pr/(1−Pr) = 1.39 × 0.89AGE × 2.57SEX × 4.45LOCATION × 9.53SYN/MET × 46.26CRCFH<50 × 7.04CRCFH≥50 × 59.36ECFH.
In this equation, Pr is the carrier probability, and age refers to the age at diagnosis. Male sex is assigned a value of 1, and female sex a value of 0. A proximal tumor location is assigned a value of 1, and a distal location a value of 0. The presence of a synchronous (SYN) metachronous (MET) tumor is assigned a value of 1, and the absence of a SYN/MET tumor is assigned a value of 0. Colorectal-cancer family history (CRCFH) is assigned a value according to the age of the youngest relative with the disease, so CRCFH<50 and CRCFH≥50 are 1 and 0, respectively, if the youngest relative is less than 50 years of age and 0 and 1, respectively, if the youngest relative is 50 years of age or older; the assigned values are 0 and 0 if there are no affected relatives. The endometrial cancer family history (ECFH) is assigned a value of 1 if any first-degree relative has endometrial cancer.
Stage 1 of the model used exclusively clinical variables to represent the situation at diagnosis and identify subgroups enriched for carriers. These groups then proceeded to stage 2 (analysis of the tumor for microsatellite instability and immunohistochemical analysis). Combining stage 1 with stage 2 allowed for the assessment of the model's performance and usefulness in predicting the carrier state at various cutoff probabilities, as compared with the use of modified Amsterdam and Bethesda criteria, which were similarly combined with data on microsatellite instability and immunohistochemical analysis.
Replication Set
We assessed the validity of the model in an independent retrospective series of 155 Scottish patients under the age of 45 years (mean age, 34 years) who had received a diagnosis of colorectal cancer between February 1973 and June 1998. The mutational analysis was undertaken without consideration of the family history, the microsatellite instability of tumors, or immunohistochemical analysis.
Survival Analysis
Patients were followed by contacts with hospital teams, general practitioners, and systematic flagging with the Registrar General for Scotland. We also cross-referenced our data with records from the Scottish Health Service Information and Statistics Division. Data were censored on April 30, 2005, and no patients were lost to follow-up. Patients were followed until they died or the study ended. Kaplan–Meier analysis was used to compare survival according to genotype, first for all patients and then in an analysis that excluded patients who had undergone surveillance screening or had had previous cancers. Data were excluded for patients who had undergone previous surveillance (4 carriers) or had a previous potentially lethal cancer (26 noncarriers and 1 carrier); 1 carrier fulfilled both criteria.
Results
Pathogenic mutations were identified in 38 of 870 patients (4 percent) (Table 1Table 1
Clinical and Molecular Data on Patients under the Age of 55 Years Who Had Colorectal Cancer with Pathogenic Mutations.). Carriers were younger than noncarriers (mean age, 42.7 and 48.2 years, respectively; P<0.001) (Table 2Table 2
Clinical Features and DNA Mismatch-Repair Genotype.), although 37 percent of all carriers were between the ages of 45 and 54 years. The mean age was 38.5 years for carriers of MLH1 mutations, 43.8 years for those with MSH2 mutations, and 49.0 years for those with MSH6 mutations (P=0.005), suggesting gene-specific penetrance effects. Carrier frequencies in men (6 percent) and women (3 percent) were significantly different (P<0.04). Most carriers fulfilled Bethesda criteria (95 percent), but only 42 percent fulfilled Amsterdam criteria.Sites of tumors in carriers were approximately evenly distributed (Table 2 of the Supplementary Appendix), but most sites were distal in noncarriers (P<0.001); 87 percent of carriers of MLH1 mutations had proximal tumors, similar to the percentage of patients with tumors bearing somatic MLH1 hypermethylation.26 Seven of 38 carriers (18 percent) and 14 of 832 noncarriers (2 percent) had synchronous or previous colorectal cancers. Three of 38 carriers (8 percent) and 37 of 832 noncarriers (4 percent) had synchronous or previous extracolonic tumors. A greater proportion of carriers (13 of 37 patients, or 35 percent) had mucinous tumors than did noncarriers (121 of 798, or 15 percent) (P<0.003). Genotype did not influence the tumor stage or differentiation; 12 of 38 carriers presented with metastases (32 percent).
Microsatellite Instability and Immunohistochemical Analysis
The presence of a high degree of microsatellite instability had a sensitivity of 67 percent for germ-line mutations, as compared with a sensitivity of 27 percent for the presence of a low degree of microsatellite instability and a sensitivity of 93 percent for the presence of any degree of microsatellite instability. The positive predictive values were 45 percent, 24 percent, and 36 percent, respectively (Table 3Table 3
Microsatellite Instability of Tumor and Immunohistochemical Analysis.). The presence of a high degree of microsatellite instability had a sensitivity of 83 percent for the detection of MLH1 mutations, of 75 percent for the detection of MSH2 mutations, and of 17 percent for the detection of MSH6 mutations. The presence of a low degree of microsatellite instability had sensitivities of 17 percent, 25 percent, and 50 percent, respectively, and the presence of any degree of microsatellite instability had sensitivities of 100 percent, 100 percent, and 67 percent, respectively. Table 3 lists the results of immunostaining for mismatch-repair proteins MSH2, MHL1, and MSH6, along with sensitivities, positive predictive values, and 95 percent confidence intervals. The absence of MSH6 protein predicted mutations in MSH2 or MSH6 (positive predictive value, 56 percent), as did the absence of MSH2 for mutations in MSH2 or MSH6 (positive predictive value, 52 percent), reflecting the biologic interaction between these proteins.Two-Stage Predictive Model
Tumor microsatellite instability and immunohistochemical data were assessed in stage 2 to refine the carrier prediction derived from stage 1. Clinical variables that were significant on univariate analysis (Table 4Table 4
Comparison of the Effectiveness of a Two-Stage Predictive Model at Various Cutoff Values with Bethesda and Amsterdam Criteria., and Table 3 of the Supplementary Appendix) were used to construct stage 1 of the model. The factors and P values in univariate analysis were age (P<0.001), sex (P=0.03), the location of the tumor (P<0.001), the presence of synchronous or metachronous tumors (P=0.001), having a first-degree relative with colorectal cancer (P<0.001), and having a first-degree relative with endometrial cancer (P=0.006). (The equation for the calculation of carrier probability is listed and described in the Methods section.25)The number of affected relatives was not a significant predictor of mutational status. Instead, the model gave priority to the youngest affected first-degree relative, resulting in three possible categories of family history (as described in the Methods section). Performance of the model can be assessed at various cutoffs, allowing tailoring of the proportion of patients proceeding to stage 2.26 The results can be compared with Amsterdam or Bethesda criteria combined with microsatellite instability and immunohistochemical data (Table 4, and Table 3 of the Supplementary Appendix). The use of Amsterdam criteria yielded a sensitivity and specificity similar to those obtained with the use of stage 1 of the model at the 0.45 probability cutoff, whereas Bethesda criteria perform similarly to a model cutoff approaching 0.005. In stage 2, immunostaining identified two thirds of all carriers (95 percent confidence interval, 0.46 to 0.77) and had a positive predictive value of 80 percent (95 percent confidence interval, 0.66 to 0.95; probability cutoff, 0.05) (Table 3 of the Supplementary Appendix). The addition of immunostaining can refine carrier prediction because stage 1 of the model (at a cutoff of 0.05) identified the 17 percent of the population of patients who are enriched for mutation carriers. Immunostaining of biopsy specimens from these patients provides good overall sensitivity and positive predictive values but indicates a requirement for mutational analysis in only 1 in 29 (3 percent) of all cases (Table 3 of the Supplementary Appendix).
As compared with stage 1 of the model combined with microsatellite-instability analysis at stage 2 (at the optimal 0.05 probability cutoff), the Amsterdam criteria combined with microsatellite instability had a low sensitivity (39 percent, as compared with 65 percent in our model) but a positive predictive value of 100 percent. A combination of the Bethesda criteria and microsatellite instability was sensitive (88 percent) but had a positive predictive value of only 32 percent, as compared with 80 percent in our model. Although the inclusion of microsatellite-instability analysis enhanced the ability to predict the carrier state for all cutoff points in stage 1 of our model and for the Amsterdam and Bethesda criteria, to be clinically useful it would necessitate the genotyping of DNA from biopsy specimens within a very short time after diagnostic biopsy.
Replication Set
Mutation analysis of germ-line DNA from the replication series identified mutations in 35 of 155 samples (23 percent): 19 mutations in MLH1, 13 in MSH2, and 3 in MSH6. Clinical variables for all 155 patients were entered into the prediction algorithm,25 and carrier probabilities were generated for each subject. The discriminatory power of the model across cutoff values was similar in both the prospective and retrospective series (receiver-operating-characteristic [ROC] curves are shown in Figure 1 of the Supplementary Appendix). Furthermore, there was no significant difference (P=0.3) between the area under the ROC curve for these independent series (0.85 for the prospective series; 95 percent confidence interval, 0.77 to 0.93; and 0.82 for the replication series; 95 percent confidence interval, 0.72 to 0.91).
Survival Analysis
Follow-up for a maximum of six years three months generated a total of 2938 patient-years for survival analysis (134 carriers and 2804 noncarriers). There was no significant difference in survival between carriers and noncarriers (five-year survival rate of 74 percent for carriers and 63 percent for noncarriers, P=0.18) (Figure 1AFigure 1
Survival Analysis of 870 Patients, According to Mutational Status and Tumor Staging.). The censoring of data from patients who had previous cancers or had undergone previous screening or surveillance did not change the result significantly (P=0.24) (Figure 1B). Figure 1C and 1D show survival according to tumor stage; carriers with stage II tumors survived longer (five-year survival rate of 100 percent) than those with stage I tumors (five-year survival rate of 75 percent). There was no significant difference in survival between carrier groups according to the extent of tumor spread at diagnosis: the five-year survival rate among patients with localized disease was 95 percent for carriers and 87 percent for noncarriers (Figure 1E); for those with metastatic disease, the five-year survival rate was 42 percent for both carriers and noncarriers (Figure 1F).Discussion
This large prospective, population-based study provides robust estimates of the prevalence of mutations in DNA mismatch-repair genes in incident cases of colorectal cancer. We did not prejudice the analysis by using the family history or by first testing the tumor for microsatellite instability or expression of DNA mismatch-repair proteins. This strategy allowed us to identify predictors of mutational status using univariate analysis and to develop a two-stage, clinically driven predictive model using a multivariate analysis that estimates carrier probabilities. As was previously stated, the factors involved in the model have been fitted into the equation that appears in the Methods section. A clinician-friendly electronic version to estimate the likelihood that a given patient with colon cancer has a mutation is available at www1.hgu.mrc.ac.uk/Softdata/MMRpredict.php.25
The model was replicated in an independent series, even though the replication set consisted of younger patients and recruitment was retrospective. Among the 870 patients with cancer, the prevalence of the mutation was 4 percent, which causes some imprecision in the values in Table 3. For instance, testing for microsatellite instability combined with the use of Bethesda or Amsterdam criteria or stage 1 of our model (probability cutoff set at 0.05) gave sensitivities of 88 percent (95 percent confidence interval, 77 to 98 percent), 39 percent (95 percent confidence interval, 24 to 55 percent), and 65 percent (95 percent confidence interval, 50 to 80 percent), respectively, whereas positive predictive values were 32 percent (95 percent confidence interval, 23 to 41 percent), 100 percent (95 percent confidence interval, 82 to 100 percent), and 53 percent (95 percent confidence interval, 39 to 68 percent), respectively. All the confidence intervals are shown in Table 3 of the Supplementary Appendix.
Immunostaining of biopsy specimens obtained during colonoscopy (stage 2 of the model) is a feasible means of preoperative prediction of the carrier state. Of patients who underwent surgical resection, 80 percent underwent a preoperative endoscopic diagnostic biopsy. At the 0.05 cutoff, the model identifies a subgroup of 17 percent of patients for whom tumor immunostaining could inform a decision concerning the surgical procedure. The use of a combination of clinical measures and immunohistochemical staining of the tumor gives a positive predictive value of 80 percent and a sensitivity of 62 percent for mutation carriers. This information could be used in preoperative counseling about options for surgical prophylaxis, including total colectomy, rather than segmental resection, or combining colectomy with hysterectomy for postmenopausal women or those who do not want more children. Carrier identification could also be used to inform decisions about adjuvant therapy, since there may be differences between carriers and noncarriers in their responsiveness to chemotherapy.27,28 In all, combining the model with immunohistochemical data identifies only 1 in 29 of all patients (3.4 percent) as being likely to carry a mutation (positive predictive value, 80 percent) and so represents a highly efficient means of identifying patients for mutation testing.
By varying the cutoff values, the model allows resource-constrained health systems to optimize the efficiency of carrier detection by matching available financial and sample resources with the capacity for immunohistochemical analysis, microsatellite-instability analysis, and an evaluation of mutational factors.
The model requires cautious application, because its performance has been assessed in only 73 patients with mutations in the primary set of 870 patients and the replication set of 155 subjects. The prevalence of mutations reported by Aaltonen et al.6 and Hampel et al.8 was half that in our primary set (4 percent) and 1/10th that in the replication set (23 percent), which probably is a reflection of the age groups studied (mean ages, 68 years, 62.9 years, and 34 years, respectively), and reinforces our rationale for studying early-onset cases. The sex-specific difference in the frequency of mutations (a ratio of 1:17 for men and 1:37 for women) is noteworthy and consistent with sex-dependent penetrance effects10,12 and environmental factors, such as hormonal protective effects and sex-linked modifier genes. Such modifiers may explain sex-based differences in the population risk of colorectal cancer.
A few patients had the same mutations; some of these patients were related to each other, whereas others may have carried founder mutations. The proportion of MSH6 mutations (18.4 percent) is higher than that previously reported,29,30 although it is in accord with findings in families with the Lynch syndrome with predominantly extracolonic or late-onset colorectal cancers.31 A minority of tumors from MSH6 carriers had a high degree of microsatellite instability, as noted previously.29,30,32 The presence of other DNA mismatch-repair defects may increase the risk of cancer that does not have a microsatellite-instability phenotype — the MLH1 D132H variant, for example.33 The absence of microsatellite instability in these carriers emphasizes the importance of systematic approaches, without prescreening, to the identification of carriers among patients with incident cases.
Our study population was not categorized according to family history or patterns of referral, reducing the likelihood of bias. In contrast, previous reports23,34,35 studied selected populations referred to genetic centers. Amsterdam criteria seem to be insufficiently sensitive (42 percent) for routine use in incident cases, supporting our previous observations.7 Furthermore, 18 patients who fulfilled the Amsterdam criteria had no identifiable mutation. Some of these patients may have had genomic rearrangements of MSH6, intronic or promoter mutations, or PMS2 mutations, but use of the criteria for identifying hereditary nonpolyposis colorectal cancer fails to detect a clinically significant number of carriers. Although the Bethesda criteria are highly sensitive for the identification of carriers (95 percent), they require the analysis of microsatellite instability of 64 percent of tumors and three times as many analyses of germ-line genes as does our stage 1 model combined with immunostaining.
We found no significant difference in survival between genotypes, perhaps because of the relatively small number of carriers, but any possible trend is small and clinically irrelevant. This result concurs with results of population-based studies of family history36-38 but conflicts with results of retrospective analyses of families with the Lynch syndrome.15-17,39 Lead-time and selection bias probably explain these discrepancies. Thus, families with the Lynch syndrome with several surviving affected relatives are more likely to be included in retrospective studies. Effects on reproductive fitness also mean that fewer patients with alleles associated with a poor prognosis would be recruited. In a similar way, highly penetrant alleles impart excess rates of death with each incident tumor, as well as an increased likelihood of having multiple fatal synchronous or metachronous tumors. This contrasts with cases involving families with the Lynch syndrome who have a survival benefit as a result of surveillance.40 In any case, our finding emphasizes the importance of early cancer detection and prevention in patients with germ-line mutations in DNA mismatch-repair genes, whether or not such patients fulfill the criteria of having the Lynch syndrome.
Supported by a grant (C348/A3758) from the Cancer Research UK Programme, grants (K/OPR/2, /2/D333, and CZB/4/94) from the Scottish Executive Chief Scientist Office, and a grant (G0000657-53203) from the Medical Research Council.
No potential conflict of interest relevant to this article was reported.
We are indebted to Andrea Leitch, Diana Reinhardt, Naila Haq, Kathryn Drew, Antonella Maffe, and Alistair Thomson; to the nursing and office staff employed by the Colorectal Cancer Genetics Susceptibility study and the Scottish Colorectal Cancer study for their work in recruitment, especially Ruth Wilson, Nicola Cartwright, Maureen Edwards, Sheena MacDonald, Polly Somerville, Cathy Johnston, Jackie Kerrigan, Marie Manzi, Janet Chauhan, and Lisa Ferguson; to Jon Warner, Nicola Dunlop, and Austin Diamond at the Clinical Genetics Laboratory at the Western General Hospital, Edinburgh; to Stuart Bayliss, Lee Murphy, Ewan McDowall, Paul Fineron, Alistair Lessells, David Goudie, Zosia Miedzybrodzka, Neva Haites, Rosemarie Davidson, Ian Finlay, David Harrison, Frank Carey, Duncan Jodrell, Chris Twelves, David Brewster, and Roger Black; and to the Wellcome Trust Clinical Research Facility at the Western General Hospital in Edinburgh, the Scottish Cancer Registry, the Scottish Cancer Intelligence Unit of the Information and Statistics Division, and the Practitioner Services Division of the Scottish National Health Service for their excellent collaborative relationships; and to the surgeons, oncologists, pathologists, and colorectal cancer nursing teams in every Scottish hospital who made the work possible.
Source Information
From the Colon Cancer Genetics Group, School of Molecular and Clinical Medicine (R.A.B., A.T., S.M.F., H.C., M.G.D.), and the Public Health Sciences (H.C.), University of Edinburgh; and the Medical Research Council Human Genetics Unit (R.A.B., A.T., S.M.F., H.C., M.G.D.) and the Clinical Genetics Department (R.C., M.E.P.), Western General Hospital — all in Edinburgh; and the Research Institute in Healthcare Science, School of Applied Sciences, University of Wolverhampton, Wolverhampton, United Kingdom (I.D.N.).
Address reprint requests to Dr. Dunlop at the Medical Research Council Human Genetics Unit, Western General Hospital, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, United Kingdom, or at malcolm.dunlop@hgu.mrc.ac.uk.
- References
References
1
Croitoru ME ,Cleary SP ,Di Nicola N , et al. Association between biallelic and monoallelic germline MYH gene mutations and colorectal cancer risk. J Natl Cancer Inst 2004;96:1631-1634
CrossRef | Web of Science | Medline2
Farrington SM ,Tenesa A ,Barnetson R , et al. Germline susceptibility to colorectal cancer due to base-excision repair gene defects. Am J Hum Genet 2005;77:112-119
CrossRef | Web of Science | Medline3
Umar A ,Boland CR ,Terdiman JP , et al. Revised Bethesda Guidelines for hereditary nonpolyposis colorectal cancer (Lynch syndrome) and microsatellite instability. J Natl Cancer Inst 2004;96:261-268
CrossRef | Web of Science | Medline4
Vasen HF ,Watson P ,Mecklin JP ,Lynch HT . New clinical criteria for hereditary nonpolyposis colorectal cancer (HNPCC, Lynch syndrome) proposed by the International Collaborative group on HNPCC. Gastroenterology 1999;116:1453-1456
CrossRef | Web of Science | Medline5
de la Chapelle A . Genetic predisposition to colorectal cancer. Nat Rev Cancer 2004;4:769-780
CrossRef | Web of Science | Medline6
Aaltonen LA ,Salovaara R ,Kristo P , et al. Incidence of hereditary nonpolyposis colorectal cancer and the feasibility of molecular screening for the disease. N Engl J Med 1998;338:1481-1487
Full Text | Web of Science | Medline7
Farrington SM ,Lin-Goerke J ,Ling J , et al. Systematic analysis of hMSH2 and hMLH1 in young colon cancer patients and controls. Am J Hum Genet 1998;63:749-759
CrossRef | Web of Science | Medline8
Hampel H ,Frankel WL ,Martin E , et al. Screening for the Lynch syndrome (hereditary nonpolyposis colorectal cancer). N Engl J Med 2005;352:1851-1860
Full Text | Web of Science | Medline9
Dunlop MG ,Farrington SM ,Nicholl I , et al. Population carrier frequency of hMSH2 and hMLH1 mutations. Br J Cancer 2000;83:1643-1645
CrossRef | Web of Science | Medline10
Dunlop MG ,Farrington SM ,Carothers AD , et al. Cancer risk associated with germline DNA mismatch repair gene mutations. Hum Mol Genet 1997;6:105-110
CrossRef | Web of Science | Medline11
Aarnio M ,Sankila R ,Pukkala E , et al. Cancer risk in mutation carriers of DNA-mismatch-repair genes. Int J Cancer 1999;81:214-218
CrossRef | Web of Science | Medline12
Quehenberger F ,Vasen HF ,van Houwelingen HC . Risk of colorectal and endometrial cancer for carriers of mutations of the hMLH1 and hMSH2 gene: correction for ascertainment. J Med Genet 2005;42:491-496
CrossRef | Web of Science | Medline13
Southey MC ,Jenkins MA ,Mead L , et al. Use of molecular tumor characteristics to prioritize mismatch repair gene testing in early-onset colorectal cancer. J Clin Oncol 2005;23:6524-6532
CrossRef | Web of Science | Medline14
Terdiman JP ,Gum JR Jr ,Conrad PG , et al. Efficient detection of hereditary nonpolyposis colorectal cancer gene carriers by screening for tumor microsatellite instability before germline genetic testing. Gastroenterology 2001;120:21-30
CrossRef | Web of Science | Medline15
Sankila R ,Aaltonen LA ,Jarvinen HJ ,Mecklin JP . Better survival rates in patients with MLH1-associated hereditary colorectal cancer. Gastroenterology 1996;110:682-687
CrossRef | Web of Science | Medline16
Aarnio M ,Mustonen H ,Mecklin JP ,Jarvinen HJ . Prognosis of colorectal cancer varies in different high-risk conditions. Ann Med 1998;30:75-80
CrossRef | Web of Science | Medline17
Watson P ,Lin KM ,Rodriguez-Bigas MA , et al. Colorectal carcinoma survival among hereditary nonpolyposis colorectal carcinoma family members. Cancer 1998;83:259-266
CrossRef | Web of Science | Medline18
Lothe RA ,Peltomaki P ,Meling GI , et al. Genomic instability in colorectal cancer: relationship to clinicopathological variables and family history. Cancer Res 1993;53:5849-5852
Web of Science | Medline19
Bubb VJ ,Curtis LJ ,Cunningham C , et al. Microsatellite instability and the role of hMSH2 in sporadic colorectal cancer. Oncogene 1996;12:2641-2649
Web of Science | Medline20
Gryfe R ,Kim H ,Hsieh ETK , et al. Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer. N Engl J Med 2000;342:69-77
Full Text | Web of Science | Medline21
Lynch HT ,Lynch PM . Molecular screening for the Lynch syndrome -- better than family history? N Engl J Med 2005;352:1920-1922
Full Text | Web of Science | Medline22
Liu B ,Farrington SM ,Petersen GM , et al. Genetic instability occurs in the majority of young patients with colorectal cancer. Nat Med 1995;1:348-352
CrossRef | Web of Science | Medline23
Wijnen JT ,Vasen HF ,Khan PM , et al. Clinical findings with implications for genetic testing in families with clustering of colorectal cancer. N Engl J Med 1998;339:511-518
Full Text | Web of Science | Medline24
Boland CR ,Thibodeau SN ,Hamilton SR , et al. A National Cancer Institute Workshop on Microsatellite Instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer. Cancer Res 1998;58:5248-5257
Web of Science | Medline25
Colon Cancer Genetics Group. Prediction of DNA mismatch repair gene mutation probability status in incident colorectal cancer cases. Edinburgh: University of Edinburgh, MRC Human Genetics Unit, 2006. (Accessed June 2, 2006, at http://www1.hgu.mrc.ac.uk/Softdata/MMRpredict.php.)
26
Herman JG ,Umar A ,Polyak K , et al. Incidence and functional consequences of hMLH1 promoter hypermethylation in colorectal carcinoma. Proc Natl Acad Sci U S A 1998;95:6870-6875
CrossRef | Web of Science | Medline27
Carethers JM ,Chauhan DP ,Fink D , et al. Mismatch repair proficiency and in vitro response to 5-fluorouracil. Gastroenterology 1999;117:123-131
CrossRef | Web of Science | Medline28
Ribic CM ,Sargent DJ ,Moore MJ , et al. Tumor microsatellite-instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for colon cancer. N Engl J Med 2003;349:247-257
Full Text | Web of Science | Medline29
Kolodner RD ,Tytell JD ,Schmeits JL , et al. Germ-line msh6 mutations in colorectal cancer families. Cancer Res 1999;59:5068-5074
Web of Science | Medline30
Wijnen J ,de Leeuw W ,Vasen H , et al. Familial endometrial cancer in female carriers of MSH6 germline mutations. Nat Genet 1999;23:142-144
CrossRef | Web of Science | Medline31
Plaschke J ,Engel C ,Kruger S , et al. Lower incidence of colorectal cancer and later age of disease onset in 27 families with pathogenic MSH6 germline mutations compared with families with MLH1 or MSH2 mutations. J Clin Oncol 2004;22:4486-4494
CrossRef | Web of Science | Medline32
Wu Y ,Berends MJ ,Mensink RG , et al. Association of hereditary nonpolyposis colorectal cancer-related tumors displaying low microsatellite instability with MSH6 germline mutations. Am J Hum Genet 1999;65:1291-1298
CrossRef | Web of Science | Medline33
Lipkin SM ,Rozek LS ,Rennert G , et al. The MLH1 D132H variant is associated with susceptibility to sporadic colorectal cancer. Nat Genet 2004;36:694-699
CrossRef | Web of Science | Medline34
Kim JC ,Kim HC ,Roh SA , et al. hMLH1 and hMSH2 mutations in families with familial clustering of gastric cancer and hereditary non-polyposis colorectal cancer. Cancer Detect Prev 2001;25:503-510
Web of Science | Medline35
Millar AL ,Pal T ,Madlensky L , et al. Mismatch repair gene defects contribute to the genetic basis of double primary cancers of the colorectum and endometrium. Hum Mol Genet 1999;8:823-829
CrossRef | Web of Science | Medline36
Kee F ,Collins BJ ,Patterson CC . Prognosis in familial non-polyposis colorectal cancer. Gut 1991;32:513-516
CrossRef | Web of Science | Medline37
Slattery ML ,Kerber RA . The impact of family history of colon cancer on survival after diagnosis with colon cancer. Int J Epidemiol 1995;24:888-896
CrossRef | Web of Science | Medline38
Bertario L ,Russo A ,Sala P , et al. Survival of patients with hereditary colorectal cancer: comparison of HNPCC and colorectal cancer in FAP patients with sporadic colorectal cancer. Int J Cancer 1999;80:183-187
CrossRef | Web of Science | Medline39
Lin KM ,Shashidharan M ,Ternent CA , et al. Colorectal and extracolonic cancer variations in MLH1/MSH2 hereditary nonpolyposis colorectal cancer kindreds and the general population. Dis Colon Rectum 1998;41:428-433
CrossRef | Web of Science | Medline40
Jarvinen HJ ,Aarnio M ,Mustonen H , et al. Controlled 15-year trial on screening for colorectal cancer in families with hereditary nonpolyposis colorectal cancer. Gastroenterology 2000;118:829-834
CrossRef | Web of Science | Medline
- Citing Articles (122)
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1
K. M. Landsbergen, J. B. Prins, H. G. Brunner, P. Duijvendijk, F. M. Nagengast, J. H. Krieken, M. Ligtenberg, N. Hoogerbrugge. (2012) Psychological distress in newly diagnosed colorectal cancer patients following microsatellite instability testing for Lynch syndrome on the pathologist’s initiative. Familial Cancer
CrossRef2
Emily Steinhagen, Jinru Shia, Arnold J. Markowitz, Zsofia K. Stadler, Erin E. Salo-Mullen, Junting Zheng, Steven A. Lee-Kong, Garrett M. Nash, Kenneth Offit, José G. Guillem. (2012) Systematic Immunohistochemistry Screening for Lynch Syndrome in Early Age-of-Onset Colorectal Cancer Patients Undergoing Surgical Resection. Journal of the American College of Surgeons 214:1, 61-67
CrossRef3
William K. Funkhouser, Ira M. Lubin, Federico A. Monzon, Barbara A. Zehnbauer, James P. Evans, Shuji Ogino, Jan A. Nowak. (2012) Relevance, Pathogenesis, and Testing Algorithm for Mismatch Repair–Defective Colorectal Carcinomas. The Journal of Molecular Diagnostics
CrossRef4
S. K. Warrier, A. H. Trainer, A. C. Lynch, C. Mitchell, R. Hiscock, S. Sawyer, A. Boussioutas, A. G. Heriot. (2011) Preoperative Diagnosis of Lynch Syndrome With DNA Mismatch Repair Immunohistochemistry on a Diagnostic Biopsy. Diseases of the Colon & Rectum 54:12, 1480-1487
CrossRef5
Xavier Llor. (2011) When should we suspect a hereditary colorectal cancer syndrome?. Clinical Gastroenterology and Hepatology
CrossRef6
Omar Khan, Amie Blanco, Peggy Conrad, Cassandra Gulden, Tovah Z Moss, Olufunmilayo I Olopade, Sonia S Kupfer, Jonathan Terdiman. (2011) Performance of Lynch Syndrome Predictive Models in a Multi-Center US Referral Population. The American Journal of Gastroenterology 106:10, 1822-1827
CrossRef7
Oana M. Radu, Marina N. Nikiforova, Linda M. Farkas, Alyssa M. Krasinskas. (2011) Challenging cases encountered in colorectal cancer screening for Lynch syndrome reveal novel findings: nucleolar MSH6 staining and impact of prior chemoradiation therapy. Human Pathology 42:9, 1247-1258
CrossRef8
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CrossRef9
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CrossRef10
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CrossRef11
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CrossRef12
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CrossRef13
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CrossRef14
Maria S Pino, Daniel C Chung. (2011) Microsatellite instability in the management of colorectal cancer. Expert Review of Gastroenterology & Hepatology 5:3, 385-399
CrossRef15
Ryan E. Wiegand. (2011) Reply to comments on ‘performance of using multiple stepwise algorithms for variable selection’. Statistics in Medicine 30:8, 894-896
CrossRef16
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CrossRef17
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CrossRef18
Angus D. Thomson, Raymond Kwok, Martin D. Weltman. (2011) Genetic Evaluation of Polyposis. Current Colorectal Cancer Reports 7:1, 8-15
CrossRef19
Frank A Sinicrope, Zhineng Jayson Yang. (2011) Prognostic and predictive impact of DNA mismatch repair in the management of colorectal cancer. Future Oncology 7:3, 467-474
CrossRef20
Scott M. Weissman, Cecelia Bellcross, Christina Chimera Bittner, Mary E. Freivogel, Joy Larsen Haidle, Pardeep Kaurah, Anna Leininger, Selvi Palaniappan, Kelle Steenblock, Thuy M. Vu, Molly S. Daniels. (2011) Genetic Counseling Considerations in the Evaluation of Families for Lynch Syndrome—A Review. Journal of Genetic Counseling 20:1, 5-19
CrossRef21
Manuel Ferrer Márquez, Ángel Reina Duarte, Vanesa Maturana Ibáñez, Ricardo Belda Lozano, Francisco Rubio Gil, Isabel Blesa Sierra, María del Mar Rico Morales. (2011) Lynch syndrome: Genetics and surgery. Cirugía Española (English Edition) 89:1, 3-9
CrossRef22
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CrossRef23
Kandelaria Rumilla, Karen V. Schowalter, Noralane M. Lindor, Brittany C. Thomas, Kara A. Mensink, Steven Gallinger, Spring Holter, Polly A. Newcomb, John D. Potter, Mark A. Jenkins, John L. Hopper, Tiffany I. Long, Daniel J. Weisenberger, Robert W. Haile, Graham Casey, Peter W. Laird, Loic Le Marchand, Stephen N. Thibodeau. (2011) Frequency of Deletions of EPCAM (TACSTD1) in MSH2-Associated Lynch Syndrome Cases. The Journal of Molecular Diagnostics 13:1, 93-99
CrossRef24
María Dolores Giráldez. (2011) Avances en la etiopatogenia, identificación y manejo clínico de las formas hereditarias y familiares de cáncer colorrectal. Gastroenterología y Hepatología 34, 70-75
CrossRef25
Jeffrey N. Weitzel, Kathleen R. Blazer, Deborah J. MacDonald, Julie O. Culver, Kenneth Offit. (2011) Genetics, genomics, and cancer risk assessment. CA: A Cancer Journal for Cliniciansn/a-n/a
CrossRef26
Manuel Ferrer Márquez, Ángel Reina Duarte, Vanesa Maturana Ibáñez, Ricardo Belda Lozano, Francisco Rubio Gil, Isabel Blesa Sierra, María del Mar Rico Morales. (2011) Síndrome de Lynch: genética y cirugía. Cirugía Española 89:1, 3-9
CrossRef27
Fay Kastrinos, Sapna Syngal. (2011) Inherited Colorectal Cancer Syndromes. The Cancer Journal 17:6, 405-415
CrossRef28
Margot G.F. van Lier, Celine H.M. Leenen, Anja Wagner, Dewkoemar Ramsoekh, Hendrikus J. Dubbink, Ans M.W. van den Ouweland, Pieter J Westenend, Eelco J.R. de Graaf, Leonieke M.M. Wolters, Wietske W. Vrijland, Ernst J Kuipers, Monique E. van Leerdam, Ewout W. Steyerberg, Winand N.M. Dinjens, . (2011) Yield of routine molecular analyses in colorectal cancer patients ≤ 70 years to detect underlying Lynch syndrome. The Journal of Pathologyn/a-n/a
CrossRef29
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CrossRef30
, Maija Kohonen-Corish, Thomas K. Weber, Annika Lindblom, Finlay Macrae. (2010) Report of the Combined Meeting of the International Society for Gastrointestinal Hereditary Tumours, the Human Variome Project and the National Cancer Institute Colon Cancer Family Registry, Duesseldorf, Germany, 24 June 2009. Familial Cancer 9:4, 705-711
CrossRef31
M. Nielsen, L. N. van Steenbergen, N. Jones, S. Vogt, H. F. A. Vasen, H. Morreau, S. Aretz, J. R. Sampson, O. M. Dekkers, M. L. G. Janssen-Heijnen, F. J. Hes. (2010) Survival of MUTYH-Associated Polyposis Patients With Colorectal Cancer and Matched Control Colorectal Cancer Patients. JNCI Journal of the National Cancer Institute 102:22, 1724-1730
CrossRef32
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CrossRef33
C. Zhang, Z. Fang, Y. Xiong, J. Li, L. Liu, M. Li, W. Zhang, J. Wan. (2010) Copy number increase of aurora kinase A in colorectal cancers: a correlation with tumor progression. Acta Biochimica et Biophysica Sinica 42:11, 834-838
CrossRef34
Elena M. Stoffel, Anu Chittenden. (2010) Genetic Testing for Hereditary Colorectal Cancer: Challenges in Identifying, Counseling, and Managing High-Risk Patients. Gastroenterology 139:5, 1436-1441.e1
CrossRef35
David J. Gallagher, James D. Smith, Kenneth Offit, Zsofia K. Stadler. (2010) Diagnosing Hereditary Colorectal Cancer. Clinical Colorectal Cancer 9:4, 205-211
CrossRef36
Derek G. Power, Emily Gloglowski, Steven M. Lipkin. (2010) Clinical Genetics of Hereditary Colorectal Cancer. Hematology/Oncology Clinics of North America 24:5, 837-859
CrossRef37
Steven A. Lee-Kong, Arnold J. Markowitz, Emily Glogowski, Christopher Papadopoulos, Zsofia Stadler, Martin R. Weiser, Larissa K. Temple, José G. Guillem. (2010) Prospective Immunohistochemical Analysis of Primary Colorectal Cancers for Loss of Mismatch Repair Protein Expression. Clinical Colorectal Cancer 9:4, 255-259
CrossRef38
A. Lièvre. (2010) Vers un traitement personnalisé du cancer colorectal: facteurs pronostiques et prédictifs. Oncologie 12:10, 584-592
CrossRef39
Elena M Stoffel, Rowena C Mercado, Wendy Kohlmann, Beth Ford, Shilpa Grover, Peggy Conrad, Amie Blanco, Kristen M Shannon, Mark Powell, Daniel C Chung, Jonathan Terdiman, Stephen B Gruber, Sapna Syngal. (2010) Prevalence and Predictors of Appropriate Colorectal Cancer Surveillance in Lynch Syndrome. The American Journal of Gastroenterology 105:8, 1851-1860
CrossRef40
Maria S Pino, Daniel C Chung. (2010) Application of molecular diagnostics for the detection of Lynch syndrome. Expert Review of Molecular Diagnostics 10:5, 651-665
CrossRef41
C. Richard Boland, Moshe Shike. (2010) Report From the Jerusalem Workshop on Lynch Syndrome-Hereditary Nonpolyposis Colorectal Cancer. Gastroenterology 138:7, 2197.e1-2197.e7
CrossRef42
Reetesh K. Pai, Rish K. Pai. (2010) Molecular Testing in Colorectal Carcinoma. Surgical Pathology Clinics 3:2, 429-445
CrossRef43
, L. I. Overbeek, R. P. Hermens, J. H. Krieken, E. M. Adang, M. Casparie, F. M. Nagengast, M. J. Ligtenberg, N. Hoogerbrugge. (2010) Electronic reminders for pathologists promote recognition of patients at risk for Lynch syndrome: cluster-randomised controlled trial. Virchows Archiv 456:6, 653-659
CrossRef44
Pedro Pérez Segura, Carmen Guillén Alonso, Teresa Ramón y Cajal, Raquel Serrano Blanch, Enrique Aranda. (2010) TTD consensus document on the diagnosis and management of hereditary colorectal cancer. Clinical and Translational Oncology 12:5, 356-366
CrossRef45
J. Balmana, A. Castells, A. Cervantes, . (2010) Familial colorectal cancer risk: ESMO Clinical Practice Guidelines. Annals of Oncology 21:Supplement 5, v78-v81
CrossRef46
Madeleine Hewish, Christopher J. Lord, Sarah A. Martin, David Cunningham, Alan Ashworth. (2010) Mismatch repair deficient colorectal cancer in the era of personalized treatment. Nature Reviews Clinical Oncology 7:4, 197-208
CrossRef47
Isela Quispe, Judith Balmaña. (2010) Desarrollo y aplicación de modelos predictivos en el síndrome de Lynch. Medicina Clínica 134:9, 412-417
CrossRef48
L. Baglietto, N. M. Lindor, J. G. Dowty, D. M. White, A. Wagner, E. B. Gomez Garcia, A. H. J. T. Vriends, , N. R. Cartwright, R. A. Barnetson, S. M. Farrington, A. Tenesa, H. Hampel, D. Buchanan, S. Arnold, J. Young, M. D. Walsh, J. Jass, F. Macrae, Y. Antill, I. M. Winship, G. G. Giles, J. Goldblatt, S. Parry, G. Suthers, B. Leggett, M. Butz, M. Aronson, J. N. Poynter, J. A. Baron, L. Le Marchand, R. Haile, S. Gallinger, J. L. Hopper, J. Potter, A. de la Chapelle, H. F. Vasen, M. G. Dunlop, S. N. Thibodeau, M. A. Jenkins. (2010) Risks of Lynch Syndrome Cancers for MSH6 Mutation Carriers. JNCI Journal of the National Cancer Institute 102:3, 193-201
CrossRef49
Emma Barrow, Emma Jagger, Judith Brierley, Andrew Wallace, Gareth Evans, James Hill, Ray McMahon. (2010) Semiquantitative assessment of immunohistochemistry for mismatch repair proteins in Lynch syndrome. Histopathology 56:3, 331-344
CrossRef50
Mercy Mvundura, Scott D. Grosse, Heather Hampel, Glenn E. Palomaki. (2010) The cost-effectiveness of genetic testing strategies for Lynch syndrome among newly diagnosed patients with colorectal cancer. Genetics in Medicine 12:2, 93-104
CrossRef51
Margot G.F. Van Lier, Anja Wagner, Monique E. Van Leerdam, Katharina Biermann, Ernst J. Kuipers, Ewout W. Steyerberg, Hendrikus Jan Dubbink, Winand N.M. Dinjens. (2010) A review on the molecular diagnostics of Lynch syndrome: a central role for the pathology laboratory. Journal of Cellular and Molecular Medicine 14:1-2, 181-197
CrossRef52
Ryan E. Wiegand. (2010) Performance of using multiple stepwise algorithms for variable selection. Statistics in Medicinen/a-n/a
CrossRef53
Hiromu Naruse, Noriko Ikawa, Kiyoshi Yamaguchi, Yusuke Nakamura, Masami Arai, Chikashi Ishioka, Kokichi Sugano, Kazuo Tamura, Naohiro Tomita, Nagahide Matsubara, Teruhiko Yoshida, Yoshihiro Moriya, Yoichi Furukawa. (2009) Determination of splice-site mutations in Lynch syndrome (hereditary non-polyposis colorectal cancer) patients using functional splicing assay. Familial Cancer 8:4, 509-517
CrossRef54
Floor J. Backes, Heather Hampel, Katherine A. Backes, Luis Vaccarello, George Lewandowski, Jeffrey A. Bell, Gary C. Reid, Larry J. Copeland, Jeffrey M. Fowler, David E. Cohn. (2009) Are prediction models for Lynch syndrome valid for probands with endometrial cancer?. Familial Cancer 8:4, 483-487
CrossRef55
Wade S. Samowitz, Karen Curtin, Roger K. Wolff, Sheryl R. Tripp, Bette J. Caan, Martha L. Slattery. (2009) Microsatellite instability and survival in rectal cancer. Cancer Causes & Control 20:9, 1763-1768
CrossRef56
Heather Hampel. (2009) Genetic Testing for Hereditary Colorectal Cancer. Surgical Oncology Clinics of North America 18:4, 687-703
CrossRef57
Mark A. Jenkins. (2009) Role of MSH6 and PMS2 in the DNA Mismatch Repair Process and Carcinogenesis. Surgical Oncology Clinics of North America 18:4, 625-636
CrossRef58
Daniel B. Eisen, Daniel J. Michael. (2009) Sebaceous lesions and their associated syndromes: Part II. Journal of the American Academy of Dermatology 61:4, 563-578
CrossRef59
Ya-shuang Zhao, Fu-lan Hu, Fan Wang, Bing Han, Dan-dan Li, Xiang-wei Li, Sui Zhu. (2009) Meta-Analysis of MSH6 Gene Mutation Frequency in Colorectal and Endometrial Cancers. Journal of Toxicology and Environmental Health, Part A 72:11-12, 690-697
CrossRef60
Fay Kastrinos, John I Allen, David H Stockwell, Elena M Stoffel, Earl F Cook, Muthoka L Mutinga, Judith Balmaña, Sapna Syngal. (2009) Development and Validation of a Colon Cancer Risk Assessment Tool for Patients Undergoing Colonoscopy. The American Journal of Gastroenterology 104:6, 1508-1518
CrossRef61
Albert Tenesa, Malcolm G. Dunlop. (2009) New insights into the aetiology of colorectal cancer from genome-wide association studies. Nature Reviews Genetics 10:6, 353-358
CrossRef62
Thibaud Koessler, Elizabeth M. Azzato, Barbara Perkins, Robert J. Macinnis, David Greenberg, Douglas F. Easton, Paul D.P. Pharoah. (2009) Common germline variation in mismatch repair genes and survival after a diagnosis of colorectal cancer. International Journal of Cancer 124:8, 1887-1891
CrossRef63
Shilpa Grover, Sapna Syngal. (2009) Genetic testing in gastroenterology: Lynch syndrome. Best Practice & Research Clinical Gastroenterology 23:2, 185-196
CrossRef64
Renée C. Niessen, Jan H. Kleibeuker, Helga Westers, Paul O. J. Jager, Dennie Rozeveld, Krista K. Bos, Wytske Boersma-van Ek, Harry Hollema, Rolf H. Sijmons, Robert M. W. Hofstra. (2009) PMS2 involvement in patients suspected of Lynch syndrome. Genes, Chromosomes and Cancer 48:4, 322-329
CrossRef65
Mark A. Jenkins, James G. Dowty, John L. Hopper, Melissa C. Southey. (2009) Molecular screening of all colorectal tumors diagnosed before age 50 years followed by genetic testing efficiently identifies Lynch syndrome cases. International Journal of Cancer 124:5, x-xi
CrossRef66
R. C. Green, P. S. Parfrey, M. O. Woods, H. B. Younghusband. (2009) Prediction of Lynch Syndrome in Consecutive Patients With Colorectal Cancer. JNCI Journal of the National Cancer Institute 101:5, 331-340
CrossRef67
Ranjit Manchanda, Usha Menon, Rachel Michaelson-Cohen, Uziel Beller, Ian Jacobs. (2009) Hereditary non-polyposis colorectal cancer or Lynch syndrome: the gynaecological perspective. Current Opinion in Obstetrics and Gynecology 21:1, 31-38
CrossRef68
Carolien M Kets, Nicoline Hoogerbrugge, Joannes H J M van Krieken, Monique Goossens, Han G Brunner, Marjolijn J L Ligtenberg. (2009) Compound heterozygosity for two MSH2 mutations suggests mild consequences of the initiation codon variant c.1A>G of MSH2. European Journal of Human Genetics 17:2, 159-164
CrossRef69
E Barrow, L Robinson, W Alduaij, A Shenton, T Clancy, F Lalloo, J Hill, DG Evans. (2009) Cumulative lifetime incidence of extracolonic cancers in Lynch syndrome: a report of 121 families with proven mutations. Clinical Genetics 75:2, 141-149
CrossRef70
C. J. Pouchet, N. Wong, G. Chong, M. J. Sheehan, G. Schneider, B. Rosen-Sheidley, W. Foulkes, M. Tischkowitz. (2009) A comparison of models used to predict MLH1, MSH2 and MSH6 mutation carriers. Annals of Oncology 20:4, 681-688
CrossRef71
Kjetil Søreide, Aida Slewa, Pål J. Stokkeland, Bianca van Diermen, Emiel A. M. Janssen, Jon Arne Søreide, Jan P. A. Baak, Hartwig Kørner. (2009) Microsatellite instability and DNA ploidy in colorectal cancer. Cancer 115:2, 271-282
CrossRef72
Guy Rosner, Hana Strul. (2009) Microsatellite instability in the evaluation of hereditary nonpolyposis colorectal cancer. Current Colorectal Cancer Reports 5:1, 40-47
CrossRef73
Jose G. Monzon, Carol Cremin, Linlea Armstrong, Jennifer Nuk, Sean Young, Doug E. Horsman, Kristy Garbutt, Chris D. Bajdik, Sharlene Gill. (2009) Validation of predictive models for germline mutations in DNA mismatch repair genes in colorectal cancer. International Journal of CancerNA-NA
CrossRef74
Rish K. Pai, Rebecca Wilcox, John Hart. 2009. Molecular Gastrointestinal, Liver, and Pancreatic Pathology. , 269-295.
CrossRef75
Glenn E. Palomaki, Monica R. McClain, Stephanie Melillo, Heather L. Hampel, Stephen N. Thibodeau. (2009) EGAPP supplementary evidence review: DNA testing strategies aimed at reducing morbidity and mortality from Lynch syndrome. Genetics in Medicine 11:1, 42-65
CrossRef76
E. Tulupova, R. Kumar, M. Hanova, J. Slyskova, B. Pardini, V. Polakova, A. Naccarati, L. Vodickova, J. Novotny, J. Halamkova, K. Hemminki, P. Vodicka. (2008) Do polymorphisms and haplotypes of mismatch repair genes modulate risk of sporadic colorectal cancer?. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 648:1-2, 40-45
CrossRef77
R. J. Mitchell, R. K. Ferguson, A. Macdonald, M. G. Dunlop, H. Campbell, M. E. Porteous. (2008) Cascade genetic testing for mismatch repair gene mutations. Familial Cancer 7:4, 293-301
CrossRef78
Catherine Julié, Christophe Trésallet, Antoine Brouquet, Céline Vallot, Ute Zimmermann, Emmanuel Mitry, François Radvanyi, Etienne Rouleau, Rosette Lidereau, Florence Coulet, Sylviane Olschwang, Thierry Frébourg, Philippe Rougier, Bernard Nordlinger, Pierre Laurent-Puig, Christophe Penna, Catherine Boileau, Brigitte Franc, Christine Muti, Hélène Hofmann-Radvanyi. (2008) Identification in Daily Practice of Patients With Lynch Syndrome (Hereditary Nonpolyposis Colorectal Cancer): Revised Bethesda Guidelines-Based Approach Versus Molecular Screening. The American Journal of Gastroenterology 103:11, 2825-2835
CrossRef79
Stacey A. DaCosta Byfield, Sapna Syngal. (2008) Clinical Guidelines Versus Universal Molecular Testing: Are We Ready to Choose an Optimal Strategy for Lynch Syndrome Identification?. The American Journal of Gastroenterology 103:11, 2837-2840
CrossRef80
Francesc Balaguer, Teresa Ocaña, Imma Garrell, Ángel Ferrández. (2008) Atención en clínicas de alto riesgo: un nuevo concepto de prevención del cáncer colorrectal. Medicina Clínica 131:10, 382-386
CrossRef81
Brindusa Truta, Yunn-Yi Chen, Amie M. Blanco, Guoren Deng, Peggy G. Conrad, Yong Ho Kim, Eun Taek Park, Sanjay Kakar, Young S. Kim, Fernando Velayos, Marvin H. Sleisenger, Jonathan P. Terdiman. (2008) Tumor histology helps to identify Lynch syndrome among colorectal cancer patients. Familial Cancer 7:3, 267-274
CrossRef82
E Barrow, W Alduaij, L Robinson, A Shenton, T Clancy, F Lalloo, J Hill, DG Evans. (2008) Colorectal cancer in HNPCC: cumulative lifetime incidence, survival and tumour distribution. A report of 121 families with proven mutations. Clinical Genetics 74:3, 233-242
CrossRef83
Miki Ohta, Takafumi Sugimoto, Motoko Seto, Dai Mohri, Yoshinari Asaoka, Motohisa Tada, Yasuo Tanaka, Yutaka Yamaji, Fumihiko Kanai, Takao Kawabe, Masao Omata. (2008) Genetic alterations in colorectal cancers with demethylation of insulin-like growth factor II. Human Pathology 39:9, 1301-1308
CrossRef84
Wigdan Al-Sukhni, Melyssa Aronson, Steven Gallinger. (2008) Hereditary Colorectal Cancer Syndromes: Familial Adenomatous Polyposis and Lynch Syndrome. Surgical Clinics of North America 88:4, 819-844
CrossRef85
Tawakalitu Oseni, Ismail Jatoi. (2008) An Overview of the Role of Prophylactic Surgery in the Management of Individuals with a Hereditary Cancer Predisposition. Surgical Clinics of North America 88:4, 739-758
CrossRef86
Lucia I. H. Overbeek, Marjolijn J. L. Ligtenberg, Riki W. Willems, Rosella P. M. G. Hermens, Willeke A. M. Blokx, Stefan V. Dubois, Hans van der Linden, Jos W. R. Meijer, Maria L. Mlynek-Kersjes, Nicoline Hoogerbrugge, Konnie M. Hebeda, Joannes H. J. M. van Krieken. (2008) Interpretation of Immunohistochemistry for Mismatch Repair Proteins is Only Reliable in a Specialized Setting. The American Journal of Surgical Pathology 32:8, 1246-1251
CrossRef87
Lucia I. H. Overbeek, Nicoline Hoogerbrugge, Joannes H. J. M. van Krieken, Fokko M. Nagengast, Theo J. M. Ruers, Marjolijn J. L. Ligtenberg, Rosella P. M. G. Hermens. (2008) Most Patients with Colorectal Tumors at Young Age Do Not Visit a Cancer Genetics Clinic. Diseases of the Colon & Rectum 51:8, 1249-1254
CrossRef88
Janice S. Kwon, Charlotte C. Sun, Susan K. Peterson, Kristin G. White, Molly S. Daniels, Stephanie G. Boyd‐Rogers, Karen H. Lu. (2008) Cost‐effectiveness analysis of prevention strategies for gynecologic cancers in Lynch syndrome. Cancer 113:2, 326-335
CrossRef89
Jinru Shia. (2008) Immunohistochemistry versus Microsatellite Instability Testing For Screening Colorectal Cancer Patients at Risk For Hereditary Nonpolyposis Colorectal Cancer Syndrome. The Journal of Molecular Diagnostics 10:4, 293-300
CrossRef90
Marion Harris, . (2008) WHY ALL YOUNG BOWEL CANCER PATIENTS SHOULD BE SCREENED FOR LYNCH SYNDROME. ANZ Journal of Surgery 78:7, 531-532
CrossRef91
Elizabeth C. Chao, Jonathan L. Velasquez, Mavee S.L. Witherspoon, Laura S. Rozek, David Peel, Pauline Ng, Stephen B. Gruber, Patrice Watson, Gad Rennert, Hoda Anton-Culver, Henry Lynch, Steven M. Lipkin. (2008) Accurate classification of MLH1/MSH2 missense variants with multivariate analysis of protein polymorphisms-mismatch repair (MAPP-MMR). Human Mutation 29:6, 852-860
CrossRef92
Antoni Castells. (2008) Oncología digestiva. ¿Cómo podemos identificar a los pacientes con cáncer colorrectal afectados de un síndrome de Lynch?. Gastroenterología y Hepatología 31:6, 390-391
CrossRef93
Richard T. Penson. (2008) Cycles within cycles. Menopause 15:3, 412-413
CrossRef94
Albert Tenesa, Susan M Farrington, James G D Prendergast, Mary E Porteous, Marion Walker, Naila Haq, Rebecca A Barnetson, Evropi Theodoratou, Roseanne Cetnarskyj, Nicola Cartwright, Colin Semple, Andrew J Clark, Fiona J L Reid, Lorna A Smith, Kostas Kavoussanakis, Thibaud Koessler, Paul D P Pharoah, Stephan Buch, Clemens Schafmayer, Jürgen Tepel, Stefan Schreiber, Henry Völzke, Carsten O Schmidt, Jochen Hampe, Jenny Chang-Claude, Michael Hoffmeister, Hermann Brenner, Stefan Wilkening, Federico Canzian, Gabriel Capella, Victor Moreno, Ian J Deary, John M Starr, Ian P M Tomlinson, Zoe Kemp, Kimberley Howarth, Luis Carvajal-Carmona, Emily Webb, Peter Broderick, Jayaram Vijayakrishnan, Richard S Houlston, Gad Rennert, Dennis Ballinger, Laura Rozek, Stephen B Gruber, Koichi Matsuda, Tomohide Kidokoro, Yusuke Nakamura, Brent W Zanke, Celia M T Greenwood, Jagadish Rangrej, Rafal Kustra, Alexandre Montpetit, Thomas J Hudson, Steven Gallinger, Harry Campbell, Malcolm G Dunlop. (2008) Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nature Genetics 40:5, 631-637
CrossRef95
M Dolores Giráldez, Sergi Castellví-Bel, Francesc Balaguer, Victòria Gonzalo, Teresa Ocaña, Antoni Castells. (2008) Lynch syndrome in colorectal cancer patients. Expert Review of Anticancer Therapy 8:4, 573-583
CrossRef96
Rebecca A. Barnetson, Nicola Cartwright, Annelot van Vliet, Naila Haq, Kate Drew, Susan Farrington, Nicola Williams, Jon Warner, Harry Campbell, Mary E. Porteous, Malcolm G. Dunlop. (2008) Classification of ambiguous mutations in DNA mismatch repair genes identified in a population-based study of colorectal cancer. Human Mutation 29:3, 367-374
CrossRef97
Tusar K. Desai, Donald Barkel. (2008) Syndromic Colon Cancer: Lynch Syndrome and Familial Adenomatous Polyposis. Gastroenterology Clinics of North America 37:1, 47-72
CrossRef98
Kathleen Y Yang, Lee-may Chen. (2008) Gynecologic decisions for women at risk for Lynch syndrome. Expert Review of Obstetrics & Gynecology 3:2, 231-237
CrossRef99
C.M. Kets, J.H.J.M. van Krieken, P.E.J. van Erp, T. Feuth, Y.H.A Jacobs, H.G. Brunner, M.J.L. Ligtenberg, N. Hoogerbrugge. (2008) Is early-onset microsatellite and chromosomally stable colorectal cancer a hallmark of a genetic susceptibility syndrome?. International Journal of Cancer 122:4, 796-801
CrossRef100
Francesc Balaguer, Judith Balmaña, Sergi Castellví–Bel, Ewout W. Steyerberg, Montserrat Andreu, Xavier Llor, Rodrigo Jover, Sapna Syngal, Antoni Castells. (2008) Validation and Extension of the PREMM1,2 Model in a Population-Based Cohort of Colorectal Cancer Patients. Gastroenterology 134:1, 39-46
CrossRef101
Guido T. Bommer, Eric R. Fearon. 2008. Molecular Abnormalities in Colon and Rectal Cancer. , 409-421.
CrossRef102
Ji Won Park, Hee Jin Chang, Kyung Hae Jung, Dae Yong Kim, Dae Kyung Sohn, Kyung Soo Han, Chang Won Hong, Seok-Byung Lim, Hyo Seong Choi, Seung-Yong Jeong, Sang-Jeon Lee. (2008) Clinicopathologic Features of Sporadic Colorectal Cancer with MLH1/MSH2 Loss of Expression - Reduced Likelihood of Metastases. Journal of the Korean Society of Coloproctology 24:3, 175
CrossRef103
Francesc Balaguer, Sergi Castellví-Bel, Victòria Gonzalo, M. Dolores Giráldez, Teresa Ocaña, Antoni Castells. (2008) Who requires genetic testing?. Current Colorectal Cancer Reports 4:1, 48-54
CrossRef104
Ewout W. Steyerberg, Judith Balmaña, David H. Stockwell, Sapna Syngal. (2007) Data reduction for prediction: A case study on robust coding of age and family history for the risk of having a genetic mutation. Statistics in Medicine 26:30, 5545-5556
CrossRef105
Maurizio Ponz de Leon, Lucio Bertario, Maurizio Genuardi, Giovanni Lanza, Cristina Oliani, Guglielmina Nadia Ranzani, Giovanni Battista Rossi, Liliana Varesco, Tiziana Venesio, Alessandra Viel. (2007) Identification and Classification of Hereditary Nonpolyposis Colorectal Cancer (Lynch Syndrome): Adapting Old Concepts to Recent Advancements. Report from the Italian Association for the Study of Hereditary Colorectal Tumors Consensus Group. Diseases of the Colon & Rectum 50:12, 2126-2134
CrossRef106
D. RAMSOEKH, M. E. VAN LEERDAM, A. WAGNER, E. J. KUIPERS. (2007) Review article: detection and management of hereditary non-polyposis colorectal cancer (Lynch syndrome). Alimentary Pharmacology & Therapeutics 26, 101-111
CrossRef107
Sining Chen, David M. Euhus, Giovanni Parmigiani. (2007) Quantitative models for predicting mutations in Lynch syndrome genes. Current Colorectal Cancer Reports 3:4, 206-211
CrossRef108
D. Gareth Evans, Sheila Walsh, James Hill, Raymond T. McMahon. (2007) Strategies for Identifying Hereditary Nonpolyposis Colon Cancer. Seminars in Oncology 34:5, 411-417
CrossRef109
Päivi Peltomäki. (2007) Tracking mutations in a family: Recognizing indicators of germline mutation in Lynch syndrome. Current Colorectal Cancer Reports 3:4, 199-205
CrossRef110
Nita Ahuja, Stephen B. Baylin. (2007) Subclassification of microsatellite-unstable tumors in colorectal cancer. Current Colorectal Cancer Reports 3:4, 212-219
CrossRef111
Mark A. Jenkins, Shinichi Hayashi, Anne-Marie O’Shea, Lawrence J. Burgart, Tom C. Smyrk, David Shimizu, Paul M. Waring, Andrew R. Ruszkiewicz, Aaron F. Pollett, Mark Redston, Melissa A. Barker, John A. Baron, Graham R. Casey, James G. Dowty, Graham G. Giles, Paul Limburg, Polly Newcomb, Joanne P. Young, Michael D. Walsh, Stephen N. Thibodeau, Noralane M. Lindor, Loïc LeMarchand, Steven Gallinger, Robert W. Haile, John D. Potter, John L. Hopper, Jeremy R. Jass. (2007) Pathology Features in Bethesda Guidelines Predict Colorectal Cancer Microsatellite Instability: A Population-Based Study. Gastroenterology 133:1, 48-56
CrossRef112
L I H Overbeek, C M Kets, K M Hebeda, D Bodmer, E van der Looij, R Willems, M Goossens, N Arts, H G Brunner, J H J M van Krieken, N Hoogerbrugge, M J L Ligtenberg. (2007) Patients with an unexplained microsatellite instable tumour have a low risk of familial cancer. British Journal of Cancer 96:10, 1605-1612
CrossRef113
Mark A. Jenkins, Melissa C. Southey, Graham G. Giles, John L. Hopper. (2007) Rationale for, and approach to, studying modifiers of risk in persons with a genetic predisposition to colorectal cancer. Current Oncology Reports 9:3, 202-207
CrossRef114
Y. Nancy You, Vipul T. Lakhani, Samuel A. Wells. (2007) The Role of Prophylactic Surgery in Cancer Prevention. World Journal of Surgery 31:3, 450-464
CrossRef115
H. T. Lynch, J. F. Lynch, P. M. Lynch. (2007) Toward a Consensus in Molecular Diagnosis of Hereditary Nonpolyposis Colorectal Cancer (Lynch Syndrome). JNCI Journal of the National Cancer Institute 99:4, 261-263
CrossRef116
M.L. Kochman. (2007) Identification and Survival of Carriers of Mutations in DNA Mismatch-Repair Genes in Colon Cancer. Yearbook of Gastroenterology 2007, 71-72
CrossRef117
Vladimir Baltić. (2007) Application of Genomics in Clinical Oncology. Journal of Medical Biochemistry 26:2, 79-93
CrossRef118
C M Kets, J H J M van Krieken, K M Hebeda, S J Wezenberg, M Goossens, H G Brunner, M J L Ligtenberg, N Hoogerbrugge. (2006) Very low prevalence of germline MSH6 mutations in hereditary non-polyposis colorectal cancer suspected patients with colorectal cancer without microsatellite instability. British Journal of Cancer 95:12, 1678-1682
CrossRef119
Mark A. Jenkins, Melissa C. Southey, Graham G. Giles, John L. Hopper. (2006) Rationale for, and approach to, studying modifiers of risk in persons with a genetic predisposition to colorectal cancer. Current Colorectal Cancer Reports 2:4, 173-178
CrossRef120
Dimitrios H Roukos, Michael Fatouros, Epameinondas Tsianos, Angelos M Kappas. (2006) Does a new model improve decisions about mismatch-repair genetic testing and Lynch syndrome identification?. Nature Clinical Practice Oncology 3:12, 656-657
CrossRef121
(2006) Model identifies DNA mismatch-repair mutations in patients with colorectal cancer. Nature Clinical Practice Oncology 3:10, 529-529
CrossRef122
Boland, C. Richard, . (2006) Decoding Hereditary Colorectal Cancer. New England Journal of Medicine 354:26, 2815-2817
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