The variants c.306+5G>A and c.1865T>A (p.Leu622His) of the DNA repair gene MLH1 occur frequently in Spanish Lynch syndrome families. To understand their ancestral history and clinical effect, we performed functional assays and a penetrance analysis and studied their genetic and geographic origins. Detailed family histories were taken from 29 carrier families. Functional analysis included in silico and in vitro assays at the RNA and protein levels. Penetrance was calculated using a modified segregation analysis adjusted for ascertainment. Founder effects were evaluated by haplotype analysis. The identified MLH1 c.306+5G>A and c.1865T>A (p.Leu622His) variants are absent in control populations and segregate with the disease. Tumors from carriers of both variants show microsatellite instability and loss of expression of the MLH1 protein. The c.306+5G>A variant is a pathogenic mutation affecting mRNA processing. The c.1865T>A (p.Leu622His) variant causes defects in MLH1 expression and stability. For both mutations, the estimated penetrance is moderate (age-cumulative colorectal cancer risk by age 70 of 20.1% and 14.1% for c.306+5G>A and of 6.8% and 7.3% for c.1865T>A in men and women carriers, respectively) in the lower range of variability estimated for other pathogenic Spanish MLH1 mutations. A common haplotype was associated with each of the identified mutations, confirming their founder origin. The ages of c.306+5G>A and c.1865T>A mutations were estimated to be 53 to 122 and 12 to 22 generations, respectively. Our results confirm the pathogenicity, moderate penetrance, and founder origin of the MLH1 c.306+5G>A and c.1865T>A mutations. These findings have important implications for genetic counseling and molecular diagnosis of Lynch syndrome. Cancer Res; 70(19); 7379–91. ©2010 AACR.

Lynch syndrome (MIM 120435) is an autosomal-dominant condition caused by germline mutations in mismatch repair (MMR) genes MLH1, MSH2, MSH6, and PMS2 (1). It is characterized by early-onset colorectal cancer (CRC) and an increased risk of other cancers (1). At age 70, cumulative CRC risk has been estimated to be 27% to 66% for men and 22% to 47% for women; risk for endometrial cancer (EC) varies between 14% and 40% (25).

Several founder mutations have been described in MMR genes (6). In MLH1, founder mutations were identified in several populations (68), where they can explain a substantial fraction of Lynch syndrome occurrences (9, 10), facilitating genetic diagnosis. In Spain, founder mutations in MMR genes have only been identified in the MSH2 gene (11, 12).

MMR founder mutations reported thus far are heterogeneous in function and frequency (6). Most of them encode truncated proteins and are readily categorized as pathogenic mutations. However, founder MMR variants with uncertain pathogenicity have also been identified (11, 13, 14). To investigate the functional effect of MMR variants, numerous assays at the RNA and protein level have been developed (15, 16). The classification of a variant as a disease-causing mutation requires integration of data from different sources, including its frequency in control populations, its cosegregation with the disease in families, its clinicopathologic features, and its properties in functional studies (17).

We have identified and characterized two frequently occurring MLH1 variants in the Spanish population. To address their clinical significance, we examined their penetrance and performed functional studies. The founder effect hypothesis was further explored by haplotype analysis.

Patients and samples

A total of 57 families were included in this study. Twenty-nine families were carriers of c.306+5G>A or c.1865T>A MLH1 variants (17 and 12 families, respectively) and were assessed through Spanish genetic counseling and molecular diagnostic laboratories. Twenty-eight families were carriers of other pathogenic MLH1 germline mutations assessed at the Catalan Institute of Oncology (ICO). Detailed family histories from at least three generations and geographic origins were obtained. Clinical data collection included tumor location, age at diagnosis, microsatellite instability (MSI) testing, and immunohistochemistry of MMR proteins in tumors. Genealogic investigations based on interviews failed to identify relationships between individuals from different families. The study protocol was approved by the Human Research Ethics Committees of participating centers, and informed consent was obtained from all subjects evaluated.

Genomic DNA was extracted from whole blood using the FlexiGene DNA kit (Qiagen) or from formalin-fixed, paraffin-embedded tissues using the QIAamp DNA Mini kit (Qiagen). DNA samples from 325 cases and 309 controls in a hospital-based CRC case-control study conducted to assess gene-environment interactions in relation to CRC risk (18) were used.

Screening for the c.306+5G>A and c.1865T>A MLH1 mutations and loss of heterozygosity analysis

Screening for the c.306+5G>A and c.1865T>A MLH1 mutations was performed by conformation-sensitive capillary electrophoresis (CSCE) in DNA samples from the same CRC case-control study (Supplementary Table S1; conditions available on request; ref. 18). DNAs with patterns differing from those of controls were amplified using nonfluorescent primer and sequenced with BigDye Terminator v.3.1 Cycle Sequencing kit (Applied Biosystems). The methods for analysis of loss of heterozygosity (LOH) of the variant c.1865T>A of MLH1 in tumors are included in Supplementary Methods.

Computational methods

The following computational methods were used to predict modifications in splice-sites or exonic splicing enhancer sites: Spliceport (19), NNSplice (20), Rescue_ESE (21), and ESEfinder (22). The Polyphen (23) algorithm was used to predict the pathogenicity of p.Leu622His variant using default settings. The Clustalw program was used to align the amino acid sequence of MLH1 in 13 phylogenetically diverse species.

Effect of the c.306+5G>A and c.1865T>A MLH1 mutations on mRNA processing and stability

Total RNA was extracted from peripheral blood lymphocytes using Trizol (Invitrogen), and cDNA was synthesized using random primers (Invitrogen) and SuperScript II reverse transcriptase (Invitrogen). Specific primers were used to amplify the appropriate MLH1 coding region (Supplementary Table S1). The methods for allele-specific expression (ASE) analysis of the variant c.1865T>A of MLH1 are descibed in Supplementary Methods.

Site-directed mutagenesis and construction of p.Leu622His-MLH1

The pcDNA3.1+ vector containing wild-type (WT) MLH1 cDNA (Genbank accession no. NM_000249.2) was kindly provided by Dr. R. Kolodner (Ludwig Institute for Cancer Research, UC San Diego School of Medicine, La Jolla, USA). The mutant p.Leu622His-MLH1 cDNA was constructed using the QuikChange Site-Directed Mutagenesis kit (Stratagene) with primer 5′-AAGAAGAAGGCTGAGATGC(A)TGCAGACTATTTCTCTTTG-3′ (sense strand; mutagenesis site is in parentheses). Sequencing was used to verify the presence of the mutation. The cDNA insert between XhoI and BamHI sites was subcloned into WT MLH1-pcDNA3.

Cell culture and transfection

HCT116 [deficient for endogenous MLH1 (24)] and 293 cells were obtained from the American Type Culture Collection, resuscitated from stocks frozen at low passage within 6 months of purchase, and cultured as described (25, 26). Cell lines were routinely tested by Mycoplasma presence and verified by morphology, growth curve analysis, and expression of proteins (e.g., MLH1 and PMS2). HCT116 cells were transfected with pGFP (green fluorescent protein) and WT MLH1-pcDNA3.1 or p.Leu622His-MLH1-pcDNA3.1 vector using Lipofectamine 2000 (Invitrogen) and Plus (Invitrogen). Transfection efficiency was measured by cytometry 24 hours after transfection.

MLH1 and PMS2 protein expression and stability experiments

Protein extraction from peripheral blood lymphocytes and HCT116 and 293 cells was performed as described elsewhere (27). MLH1 and PMS2 expression levels were examined by SDS-PAGE, followed by Western blotting analysis with anti-MLH1 and anti-PMS2 antibodies (clones G168-15 and A16-4; BD Biosciences). β-Tubulin antibody (Sigma) was used to assess equal loading in all lanes. Band intensities were quantified using Quantity One software (Bio-Rad), and expression of MLH1 and PMS2 was normalized to β-tubulin expression. The decrease of protein expression was calculated by dividing the normalized protein expression in p.Leu622His-transfected cells by the expression in WT MLH1–transfected cells. The stability of WT and variant MLH1 was assessed by treating cells with cycloheximide, a global inhibitor of de novo protein synthesis, as described (25).

Estimation of age-specific cumulative risk

We used information on the occurrence of CRC and EC in relatives of MMR mutation-positive index cases to estimate age- and gender-specific incidences of CRC and EC (females) in MMR mutation carriers by maximum likelihood using modified segregation analysis (2). The method was implemented in MENDEL (v3.3.5; refs. 28, 29).

Relatives were assumed to be followed from 20 years of age and to be censored at the age of CRC diagnosis, at the age of death, at the age of last follow-up, or at age 70 years, whichever occurred earliest. We did not ignore the cases beyond age 70 but assigned them the same risk at age 70 to avoid the larger variances observed when only sparse data are available. In estimating the risk of CRC and EC, female relatives were censored at age of CRC or EC diagnosis, whichever was diagnosed first. Information on MMR mutation status in relatives was included whenever available. For individuals with missing age information, the age was imputed based on relationship with the proband, age of the proband, and deceased status at last follow-up (dead or alive).

To correct for ascertainment, we maximized the conditional likelihood of observing the phenotypes (CRC and/or EC) and genotypes (c.306+5G>A or c.1865T>A MLH1 variants) of the entire pedigree given the phenotypic and genotypic information of the index case (proband) and phenotypic information of the pedigree to account for multiplex ascertainment bias. Age-specific cumulative risks (penetrance) and hazard ratio (HR) estimates of CRC and EC risks in families with MMR gene variants were calculated assuming a proportional hazards model, with λ(t) = λ0(t)exp[g(t)], where λ0(t) is the background incidence. They were compared with the risks in the general population, which were assumed to follow the population incidence from the Spanish Cancer Registries (30). The age-specific relative risks in carriers compared with the population rates are modeled through the function exp[g(t)]. We estimated the age-specific log HR parameters for the two age intervals <50 and ≥50, assuming that

$g(t)=∑k=1nexp[βk]$
a piecewise constant HR in the kth age band k = 1, 2. In all analysis, cancer incidences in noncarriers were assumed to follow the population cohort–specific rates as obtained through the Spanish Cancer Registries.

To construct confidence intervals (CI) for the log(HR) estimates, we assumed that the maximum likelihood estimates of the parameters were asymptotically normally distributed with covariance matrix given by the inverse of the Fisher information matrix. Cumulative risk (e.g., penetrance) and its 95% CI were calculated from the cumulative incidence Λ(t) given by

$Λ(t)=∑k=1niktkexp[βk]$
where ik is the population incidence obtained from the Spanish Cancer Registries, tk is the length of the kth age interval, and βk is the log(RR) in the kth age interval k = 1, 2. The cumulative risk is given by F(t) = 1 − exp[−Λ(t)] and a 95% CI for F(t) is
$1−exp[−Λ(t)±1.96V⁢a⁢r(Λ(t))]$
, where

$V⁢a⁢r(Λ(t))=∑k=1nik2tk2V⁢a⁢r(βk)exp[2βk]+2∑j

Wald-type tests and CIs were then used based on the point estimate and the estimated SEs (28, 29).

The analysis accounted for both genotyped and ungenotyped relatives. Missing genotype information was handled by including the allele frequency as a parameter in the likelihood and then maximizing the marginal likelihood of the phenotype and genotype data of the entire pedigree, summing over all possible configurations of the unobserved genotype matrix, given the observed genotypes. Cumulative risks and HR for CRC and EC were estimated separately for males and females; risk of EC was estimated only for females.

Haplotype analysis

Haplotype analysis was performed using three MLH1 single-nucleotide polymorphisms and seven microsatellite markers (Supplementary Table S1; conditions available on request). One hundred and twenty-two DNA samples from members of the studied families and 50 control individuals randomly selected from the CRC case-control study (18) were analyzed, including individuals that come from the areas of origin of the founders. To deduce the mutation-associated haplotype, intrafamilial segregation analysis was performed under the assumption that the number of crossovers between adjacent markers was minimal. The frequency of disease haplotypes in the control population was estimated using PHASE2 (default settings; ref. 31).

Estimation of founder mutation age

We used a modification of the method of Schroeder and colleagues (32) to estimate the time to the most recent common ancestor (TMRCA) separately for the c.306+5G>A and c.1865T>A alleles. This method uses a count of the number of recombination events that have occurred on copies of the ancestral mutant haplotype, together with an estimate of the recombination map length of the haplotype, to estimate the total time length of the genealogy of sampled copies of a mutant allele in units of generations. In our application of the approach (32), to estimate TMRCA from the genealogy length, we relied on a multiplier c(n), a ratio of TMRCA to tree length that was estimated from coalescent simulations with sample size n. The TMRCA estimate was then taken as an estimate of the age of the mutation, and CIs were obtained by considering the uncertainty in converting the length estimate for the genealogy into an estimate of TMRCA. Because analysis of family history revealed no relationships among sampled families in the most recent three to five generations, our age estimation was performed from a reference point four generations in the past, so that at the end of the estimation process, the estimate was increased by four generations. See Supplementary Materials and Methods for further details.

Identification of frequently occurring germline MLH1 variants

Mutational screening of MMR genes performed in suspected Lynch syndrome patients at ICO led to the identification of two frequently occurring germline MLH1 variants: c.306+5G>A and c.1865T>A. No other alterations in MLH1 coding sequence or at exon-intron boundaries were detected in carriers. Of the 83 families with germline MMR alterations identified at ICO, 45 were carriers of an MLH1 alteration (28 pathogenic mutations and 17 variants of unknown significance). The c.306+5G>A and c.1865T>A variants were identified in nine and four families, constituting 20% and 9% of all MLH1 carrier families, respectively. An extended collaborative study with other referral centers (see legend of Table 1) enabled the identification of 16 additional carrier families. In all, we identified 17 families with c.306+5G>A and 12 with c.1865T>A MLH1 variants (Table 1). Neither of these two variants was detected by CSCE in a panel of paired CRC cases and controls, reducing the probability of being polymorphisms or CRC risk alleles.

Table 1.

Clinical features of affected carriers

FamilyReferral centerCriteria metAffected carrierGenderTumor typeAge of onsetMSIIHCCRC locationCRC stage: TNM/Dukes
MLH1MSH2MSH6
A. c.306+5G>A families
A1 ICO, Barcelona AC A1.1 CRC 38 − T4N0M0
A1.2 CRC 41     T2N0M0
A1.3 CRC 69 − T3N0M0
A2 ICO, Barcelona BC A2.1 CRC 28 − Rc T2N0M0
A2.2 CRC 51 − T3N0M0
A3 ICO, Barcelona BC A3.1 CRC 38
A3.8 CRC 52     T2N0M0
A3.10 CRC 52
GC 70
A4 ICO, Barcelona AC A4.1 CRC 38 NV T3N1Mx
A4.2 CRC 60 NV T4NxMx
A5 ICO, Barcelona BC A5.1 CRC 50 − T2NxM0
DC 68
CRC 80     Rc T3N0M0
A6 ICO, Barcelona BC A6.1 CRC 38 NV NV T4N1Mx
A6.2 CRC 49     T2N0Mx
A7 ICO, Barcelona BC A7.1 CRC 52 − T1N0M0
A8 HCSC, Madrid/HULB, Zaragoza BC A8.1 BC* 48
3CRC 50 NV R,R,L B1,B1,B2
A9 HCSC, Madrid AC A9.1 CRC 20 −   T3N2Mx
A10 CNIO, Madrid BC A10.1 CRC 30    B1
A11 H. Cruces, Bizkaia BC A11.1 CRC 59     T2N0M0
A11.2 CRC 48     T3N0M0
A12 H. Cruces, Bizkaia BC A12.1 EC 51
TC* 65
A13 ICO, Barcelona AC A13.1 EC 42
2CRC 42  − R,R T3N0M0,T3N0M0
A14 ICO, Barcelona AC A14.2 CRC 45
CRC 49
A15 IBGM, Valladolid AC A15.1 CRC 27 − Rc T4N0M0
A15.2 CRC 50
A15.8 CRC 39     T3N0Mx
A16 IBGM, Valladolid AC A16.1 CRC 59 −
A17 H. Clinic, Barcelona/HVC Pamplona AC A17.10 CRC 58 − B2
A17.11 CRC 35  −
B. c.1865T>A families
B1 ICO, Barcelona BC B1.1 CRC 27 − T3N0M0
CRC 39     T1N0M0
B2 H. St Joan, Reus AC B2.1 2CRC 56     R,L T1N0M0
B2.2 CRC 24 − NV T3N0M0
B3 H. St Pau, Barcelona AC B3.1 CRC 43 − NV T3N0M0
B3.2 CRC 28     T3M1N0
B4 ICO, Barcelona AC B4.1 CRC 33 − NV T3N2Mx
B4.2 CRC 42     T3N0M0
OC* 58
B5 ICO, Girona AC B5.1 CRC 42 − T3N0M0
B6 HCSC, Madrid AC B6.1 CRC 38 −
B6.2 EC 53 −
CRC 65
B6.3 EC 55 −
B6.4 CRC 32     T3N2Mx
B7 HCSC, Madrid BC B7.1 CRC 59 −
B8 IOC, Barcelona BC B8.2 CRC 43  −
B9 HVH, Barcelona BC B9.1 CRC 55 −
B10 ICO, Barcelona AC B10.1 EC 54 NV
B11 CNIO, Madrid AC B11.1 CRC 56
B12 CNIO, Madrid AC B12.5 EC 38
BC* 79
B12.7 CRC 48
B12.8 2CRC 51
FamilyReferral centerCriteria metAffected carrierGenderTumor typeAge of onsetMSIIHCCRC locationCRC stage: TNM/Dukes
MLH1MSH2MSH6
A. c.306+5G>A families
A1 ICO, Barcelona AC A1.1 CRC 38 − T4N0M0
A1.2 CRC 41     T2N0M0
A1.3 CRC 69 − T3N0M0
A2 ICO, Barcelona BC A2.1 CRC 28 − Rc T2N0M0
A2.2 CRC 51 − T3N0M0
A3 ICO, Barcelona BC A3.1 CRC 38
A3.8 CRC 52     T2N0M0
A3.10 CRC 52
GC 70
A4 ICO, Barcelona AC A4.1 CRC 38 NV T3N1Mx
A4.2 CRC 60 NV T4NxMx
A5 ICO, Barcelona BC A5.1 CRC 50 − T2NxM0
DC 68
CRC 80     Rc T3N0M0
A6 ICO, Barcelona BC A6.1 CRC 38 NV NV T4N1Mx
A6.2 CRC 49     T2N0Mx
A7 ICO, Barcelona BC A7.1 CRC 52 − T1N0M0
A8 HCSC, Madrid/HULB, Zaragoza BC A8.1 BC* 48
3CRC 50 NV R,R,L B1,B1,B2
A9 HCSC, Madrid AC A9.1 CRC 20 −   T3N2Mx
A10 CNIO, Madrid BC A10.1 CRC 30    B1
A11 H. Cruces, Bizkaia BC A11.1 CRC 59     T2N0M0
A11.2 CRC 48     T3N0M0
A12 H. Cruces, Bizkaia BC A12.1 EC 51
TC* 65
A13 ICO, Barcelona AC A13.1 EC 42
2CRC 42  − R,R T3N0M0,T3N0M0
A14 ICO, Barcelona AC A14.2 CRC 45
CRC 49
A15 IBGM, Valladolid AC A15.1 CRC 27 − Rc T4N0M0
A15.2 CRC 50
A15.8 CRC 39     T3N0Mx
A16 IBGM, Valladolid AC A16.1 CRC 59 −
A17 H. Clinic, Barcelona/HVC Pamplona AC A17.10 CRC 58 − B2
A17.11 CRC 35  −
B. c.1865T>A families
B1 ICO, Barcelona BC B1.1 CRC 27 − T3N0M0
CRC 39     T1N0M0
B2 H. St Joan, Reus AC B2.1 2CRC 56     R,L T1N0M0
B2.2 CRC 24 − NV T3N0M0
B3 H. St Pau, Barcelona AC B3.1 CRC 43 − NV T3N0M0
B3.2 CRC 28     T3M1N0
B4 ICO, Barcelona AC B4.1 CRC 33 − NV T3N2Mx
B4.2 CRC 42     T3N0M0
OC* 58
B5 ICO, Girona AC B5.1 CRC 42 − T3N0M0
B6 HCSC, Madrid AC B6.1 CRC 38 −
B6.2 EC 53 −
CRC 65
B6.3 EC 55 −
B6.4 CRC 32     T3N2Mx
B7 HCSC, Madrid BC B7.1 CRC 59 −
B8 IOC, Barcelona BC B8.2 CRC 43  −
B9 HVH, Barcelona BC B9.1 CRC 55 −
B10 ICO, Barcelona AC B10.1 EC 54 NV
B11 CNIO, Madrid AC B11.1 CRC 56
B12 CNIO, Madrid AC B12.5 EC 38
BC* 79
B12.7 CRC 48
B12.8 2CRC 51

NOTE: A. Clinical features of affected carriers of variant c.306+5G>A of MLH1. B. Clinical features of affected carriers of variant c.1865T>A of MLH1.

Abbreviations: ICO, Institut Català d'Oncologia; HCSC, Hospital Clínico San Carlos; CNIO, Centro Nacional de Investigaciones Oncológicas; H. Cruces, Hospital de Cruces; HVH, Hospital Vall d'Hebron; H. St Joan, Hospital Universitari Sant Joan; H. St Pau, Hospital de la Santa Creu i Sant Pau; IDOC, Institut d'Oncologia Corachan; IBGM, Instituto de Biología y Genética Molecular; H. Clinic, Hospital Clinic; HVC, Hospital Virgen del Camino; HULB, Hospital Universatario Lozano Blesa; AC, Amsterdam criteria; BC, Bethesda criteria; M, male; F, female; BC, breast cancer; CRC, colorectal cancer; DC, duodenal cancer; EC, endometrial cancer; GC, gastric cancer; OC, otorhinolaryngological cancer; TC, thyroid cancer; IHC, immunohistochemical analysis of MMR proteins in tumor tissue; NV, not evaluable result; R, right; L, left; Rc, rectum.

*Tumor type not included in Lynch syndrome tumor spectrum.

Familial clinical features

Most of the included families fulfilled the modified Amsterdam criteria (Table 1). The majority of tumors diagnosed in carriers belonged to the Lynch syndrome spectrum. The median age at diagnosis was 49.5 years (range, 20–80) for c.306+5G>A carriers and 45.5 years (range, 24–79) for c.1865T>A carriers. CRC and EC tested were microsatellite unstable (MSI+), and informative cases showed loss of expression of the MLH1 protein (Table 1).

Both c.306+5G>A and c.1865T>A MLH1 variants cosegregated with cancer in 29 and 21 affected members, respectively, and were absent in 37 and 18 unaffected members, respectively. The c.306+5G>A variant was also identified in 21 unaffected members (median age, 34.0; range, 22–63), and c.1865T>A in 21 unaffecteds (median age, 29.0; range, 18–41).

Pathogenicity assessment of the c.306+5G>A and c.1865T>A MLH1 variants

For the c.306+5G>A variant, splicing prediction programs predicted the creation of a new donor site 5 bp upstream. Reverse transcription-PCR (RT-PCR) analysis on RNA from lymphocytes of carriers confirmed the generation of this aberrant mRNA transcript, r.303_307delugagg, expected to generate a truncated protein. This transcript was associated with an increased amount of the r.208_306del alternative constitutional transcript, corresponding to the in-frame skipping of MLH1 exon 3 (Fig. 1). Although the variant c.306+5G>A is pathogenic at the RNA level, neither abnormal bands nor differences in MLH1 protein expression were observed in lymphocytes from c.306+5G>A carriers, as assessed by Western blotting (data not shown).

Figure 1.

Characterization of the c.306+5G>A MLH1 variant. A, schematic overview of MLH1 exons 2 to 4 with a representation of the normal and aberrant transcripts caused by the c.306+5G>A mutation. Black arrows represent primers used for RT-PCR amplification. B, acrylamide gel showing RT-PCR products obtained from c.306+5G>A carriers and a noncarrier. On the right, direct sequencing of the RT-PCR products is shown.

Figure 1.

Characterization of the c.306+5G>A MLH1 variant. A, schematic overview of MLH1 exons 2 to 4 with a representation of the normal and aberrant transcripts caused by the c.306+5G>A mutation. Black arrows represent primers used for RT-PCR amplification. B, acrylamide gel showing RT-PCR products obtained from c.306+5G>A carriers and a noncarrier. On the right, direct sequencing of the RT-PCR products is shown.

Close modal

The MLH1 c.1865T>A variant is predicted to generate the missense change p.Leu622His, which was classified as pathogenic by the Polyphen algorithm and MAPP-MMR and SIFT predictions (33, 34). The affected amino acid residue is highly conserved and is located at the interaction domain for MutL (the homologue of MLH1 in Escherichia coli; ref. 35). Spliceport and NNSplice did not predict any effect on mRNA processing, whereas ESEfinder and Rescue_ESE predicted the creation of a new potential binding site for SRp proteins. In lymphocytes of c.1865T>A carriers, differences neither at the mRNA level [as assessed by RT-PCR (data not shown) and allele-specific expression analysis (Supplementary Fig. S1)] nor at the protein expression level (data not shown) were observed. The transient transfection of the p.Leu622His variant into the HCT116 cell line (24), which lacks endogenous MLH1, resulted in diminished MLH1 expression when compared with WT MLH1–transfected cells (Fig. 2A). MLH1 heterodimerizes with PMS2, stabilizing its expression (25). As expected, the diminished p.Leu622His expression was associated with lower PMS2 expression compared with WT MLH1–transfected cells (Fig. 2A). After cycloheximide treatment, MLH1 expression was lower in both p.Leu622His-transfected cells and WT MLH1–transfected cells. However, the effect was greater in p.Leu622His-transfected cells, indicating that p.Leu622His protein was less stable than WT MLH1 (Fig. 2B). Five of the six tumors analyzed from c.1865T>A carriers lost the MLH1 WT allele (Supplementary Fig. S1), suggesting a growth advantage associated with loss of the WT protein. Together, these lines of evidence support the notion that the variant c.1865T>A is a pathogenic mutation via a mechanism in which MLH1 protein expression is decreased.

Figure 2.

Expression and stability of the p.Leu622His variant of MLH1 in HCT116 cells. A, time course of expression of WT MLH1 and p.Leu622His (L622H) variants. Top and middle, cell lysates probed with anti-PMS2 and anti-MLH1 antibodies; bottom, to verify equal protein loading, cell lysates were probed with anti-tubulin antibody. Untransfected HCT116 and 293 cells were used as controls. One representative experiment among three is shown. The ranges of decrease in MLH1 expression at 24, 48, and 72 h were 35% to 55%, 42% to 75%, and 81% to 100%, respectively. The ranges of decrease in PMS2 expression at 24, 48, and 72 h were 57% to 89%, 48% to 55%, and 43% to 64%, respectively. B, stability of WT MLH1 and p.Leu622His variant as assessed by cycloheximide (CHX) treatment. “+” and “−” represent treatment with cycloheximide or DMSO as vehicle, respectively. The decrease in expression at 1, 4, 6, and 9 h after cycloheximide treatment was 39%, 64%, 55%, and 61% in WT MLH1 and 47%, 97%, 99%, and 100% in p.Leu622His, respectively. One representative experiment among three is shown.

Figure 2.

Expression and stability of the p.Leu622His variant of MLH1 in HCT116 cells. A, time course of expression of WT MLH1 and p.Leu622His (L622H) variants. Top and middle, cell lysates probed with anti-PMS2 and anti-MLH1 antibodies; bottom, to verify equal protein loading, cell lysates were probed with anti-tubulin antibody. Untransfected HCT116 and 293 cells were used as controls. One representative experiment among three is shown. The ranges of decrease in MLH1 expression at 24, 48, and 72 h were 35% to 55%, 42% to 75%, and 81% to 100%, respectively. The ranges of decrease in PMS2 expression at 24, 48, and 72 h were 57% to 89%, 48% to 55%, and 43% to 64%, respectively. B, stability of WT MLH1 and p.Leu622His variant as assessed by cycloheximide (CHX) treatment. “+” and “−” represent treatment with cycloheximide or DMSO as vehicle, respectively. The decrease in expression at 1, 4, 6, and 9 h after cycloheximide treatment was 39%, 64%, 55%, and 61% in WT MLH1 and 47%, 97%, 99%, and 100% in p.Leu622His, respectively. One representative experiment among three is shown.

Close modal

Cumulative risks and HRs derived from the penetrance analysis

A total of 1,936 individuals were included in the penetrance analysis, 57 of which were probands and 388 of which were first-degree relatives of probands (Table 2). Age-specific cumulative risks of CRC by decade compared with risks in Spanish Cancer Registries (30) are shown in Table 3A. For c.306+5G>A carriers, the risk of CRC by age 50 significantly exceeds the cumulative risk in the general population. Risk of CRC continues to increase, and by age 70, lifetime risk for CRC is estimated at 20.1% (95% CI, 1.4–35.9%) for men and 14.1% for women (95% CI, 1.2–25.2%). The overall HR for CRC is 7.7 (95% CI, 2.9–20.6) for males and 9.0 (95% CI, 3.6–22.6) for females (Table 3B). The age-specific HR estimates in the age intervals 20 to 49 and 50 to 69 clearly indicate much higher relative risk compared with the general population, declining in the age range from 50 to 69 years. Cumulative risk for EC also exceeds that of the general population at age 70 years, equaling 7.2% (95% CI, 0–16.9%) with HR of 6.3 (95% CI, 1.4–27.9; Table 3).

Table 2.

Characteristics of the study population by mutation type

c.306+5G>Ac.1865T>AOther MLH1 mutations
No. probands/pedigrees 17 12 28
Total no. individuals 514 447 975
No. females 257 204 444
No. males 240 221 486
No. individuals with missing gender information 17 22 45
No. individuals with missing age information 226 208 442
No. first-degree relatives 89 106 193
No. subjects genotyped 88 60 174
No. tested mutation-positive subjects 50 42 88
Percentage of mutation-positive subjects among subjects genotyped 56.8 70.0 50.5
Median age at diagnosis of CRC in men (range) 52 (38–80) 43 (20–65) 41 (25–80)
Median age at diagnosis of CRC in women (range) 50 (20–80) 48 (23–87) 44 (18–77)
Percentage of CRC diagnosed before age 50 among affected subjects 38.3 57.1 73.7
Percentage of CRC or EC affected subjects among carriers 56.0 47.6 64.8
Percentage of CRC or EC affected subjects among noncarriers 2.6
Percentage of CRC or EC affected subjects among nontested individuals 10.1 12.1 7.5
c.306+5G>Ac.1865T>AOther MLH1 mutations
No. probands/pedigrees 17 12 28
Total no. individuals 514 447 975
No. females 257 204 444
No. males 240 221 486
No. individuals with missing gender information 17 22 45
No. individuals with missing age information 226 208 442
No. first-degree relatives 89 106 193
No. subjects genotyped 88 60 174
No. tested mutation-positive subjects 50 42 88
Percentage of mutation-positive subjects among subjects genotyped 56.8 70.0 50.5
Median age at diagnosis of CRC in men (range) 52 (38–80) 43 (20–65) 41 (25–80)
Median age at diagnosis of CRC in women (range) 50 (20–80) 48 (23–87) 44 (18–77)
Percentage of CRC diagnosed before age 50 among affected subjects 38.3 57.1 73.7
Percentage of CRC or EC affected subjects among carriers 56.0 47.6 64.8
Percentage of CRC or EC affected subjects among noncarriers 2.6
Percentage of CRC or EC affected subjects among nontested individuals 10.1 12.1 7.5

NOTE: Blood- and nonblood-related relatives are included.

Table 3.

Age-specific cumulative risk and HR estimates for CRC and EC in carriers of c.306+5G>A, c.1865T>A, and other pathogenic MLH1 mutations

A
Age (y)CRC (males)CRC (females)
% Cumulative risk population% Cumulative risk MLH1 carriers (95% CI)% Cumulative risk population% Cumulative risk MLH1 carriers (95% CI)
c.306+5G>Ac.1865T>AOther MLH1 mutationsc.306+5G>Ac.1865T>AOther MLH1 mutations
20
30 0.01 0.08 0.02 0.10 0.01 0.09 0.04 0.05
40 0.06 0.46 0.14 0.63 0.06 0.54 0.27 0.33
50 0.28 2.14 (0.04–4.20) 0.68 (0–1.64) 2.90 (0.78–4.96) 0.24 2.14 (0.17–4.06) 1.07 (0–2.54) 1.3 (0–2.59)
60 1.00 7.46 2.40 10.00 0.72 6.29 3.18 3.85
70 2.87 20.13 (1.42–35.95) 6.80 (0–15.80) 26.32 (7.85–41.07) 1.67 14.05 (1.20–25.23) 7.26 (0–16.50) 10.74 (0–16.80)

EC (females)  CRC and EC (females)
20
30 0.01 0.12 0.04 0.06
40 0.02 0.13 0.06 0.11 0.08 0.97 0.35 0.46
50 0.13 0.82 (0–2.02) 0.38 (0–1.16) 0.74 (0–1.54) 0.37 4.41 (1.25–7.47) 1.63 (0–3.50) 2.10 (0.43–3.74)
60 0.55 3.42 1.60 3.1 1.27 14.41 5.50 7.07
70 1.17 7.16 (0–16.88) 3.37 (0–10.05) 6.5 (0–13.12) 2.84 29.58 (9.34–45.29) 11.98 (0–24.24) 16.24 (3.32–25.67)

B
Age (y) HR (95% CI)
CRC (males) CRC (females)
c.306+5G>A c.1865T>A Other MLH1 mutations c.306+5G>A c.1865T>A Other MLH1 mutations
20–49 14.89 (3.03–73.23) 4.10 (0.18–95.72) 32.42 (12.57–83.57) 13.36 (2.93–60.94) 9.56 (1.33–68.44) 12.63 (3.49–45.62)
50–69 5.37 (1.47–19.72) 1.89 (0.325–10.95) 3.21 (0.88–11.70) 6.88 (1.95–24.28) 1 (NA) 2.30 (0.48–11.05)
Overall HR 7.72 (2.89–20.59) 2.42 (0.57–10.23) 10.48 (5.04–21.81) 8.99 (3.58–22.56) 4.48 (1.11–18.01) 5.42 (1.97–14.93)

EC (females) CRC and EC (females)
20–49 20.00 (2.77–144.19) 5.22 (0.15–185.08) 16.02 (3.19–80.42) 22.52 (7.49–67.70) 9.13 (1.62–51.61) 20.30 (7.84–52.27)
50–69 3.67 (0.55–24.51) 2.17 (0.15–32.45) 2.98 (0.55–15.92) 8.41 (3.10–22.78) 1.73 (0.16–18.49) 1.99 (0.54–7.34)
Overall HR 6.32 (1.43–27.94) 2.92 (0.36–23.57) 5.71 (1.91–17.02) 12.17 (5.92–25.01) 4.43 (1.37–14.36) 5.73 (2.59–12.71)
A
Age (y)CRC (males)CRC (females)
% Cumulative risk population% Cumulative risk MLH1 carriers (95% CI)% Cumulative risk population% Cumulative risk MLH1 carriers (95% CI)
c.306+5G>Ac.1865T>AOther MLH1 mutationsc.306+5G>Ac.1865T>AOther MLH1 mutations
20
30 0.01 0.08 0.02 0.10 0.01 0.09 0.04 0.05
40 0.06 0.46 0.14 0.63 0.06 0.54 0.27 0.33
50 0.28 2.14 (0.04–4.20) 0.68 (0–1.64) 2.90 (0.78–4.96) 0.24 2.14 (0.17–4.06) 1.07 (0–2.54) 1.3 (0–2.59)
60 1.00 7.46 2.40 10.00 0.72 6.29 3.18 3.85
70 2.87 20.13 (1.42–35.95) 6.80 (0–15.80) 26.32 (7.85–41.07) 1.67 14.05 (1.20–25.23) 7.26 (0–16.50) 10.74 (0–16.80)

EC (females)  CRC and EC (females)
20
30 0.01 0.12 0.04 0.06
40 0.02 0.13 0.06 0.11 0.08 0.97 0.35 0.46
50 0.13 0.82 (0–2.02) 0.38 (0–1.16) 0.74 (0–1.54) 0.37 4.41 (1.25–7.47) 1.63 (0–3.50) 2.10 (0.43–3.74)
60 0.55 3.42 1.60 3.1 1.27 14.41 5.50 7.07
70 1.17 7.16 (0–16.88) 3.37 (0–10.05) 6.5 (0–13.12) 2.84 29.58 (9.34–45.29) 11.98 (0–24.24) 16.24 (3.32–25.67)

B
Age (y) HR (95% CI)
CRC (males) CRC (females)
c.306+5G>A c.1865T>A Other MLH1 mutations c.306+5G>A c.1865T>A Other MLH1 mutations
20–49 14.89 (3.03–73.23) 4.10 (0.18–95.72) 32.42 (12.57–83.57) 13.36 (2.93–60.94) 9.56 (1.33–68.44) 12.63 (3.49–45.62)
50–69 5.37 (1.47–19.72) 1.89 (0.325–10.95) 3.21 (0.88–11.70) 6.88 (1.95–24.28) 1 (NA) 2.30 (0.48–11.05)
Overall HR 7.72 (2.89–20.59) 2.42 (0.57–10.23) 10.48 (5.04–21.81) 8.99 (3.58–22.56) 4.48 (1.11–18.01) 5.42 (1.97–14.93)

EC (females) CRC and EC (females)
20–49 20.00 (2.77–144.19) 5.22 (0.15–185.08) 16.02 (3.19–80.42) 22.52 (7.49–67.70) 9.13 (1.62–51.61) 20.30 (7.84–52.27)
50–69 3.67 (0.55–24.51) 2.17 (0.15–32.45) 2.98 (0.55–15.92) 8.41 (3.10–22.78) 1.73 (0.16–18.49) 1.99 (0.54–7.34)
Overall HR 6.32 (1.43–27.94) 2.92 (0.36–23.57) 5.71 (1.91–17.02) 12.17 (5.92–25.01) 4.43 (1.37–14.36) 5.73 (2.59–12.71)

NOTE: A. Age-specific cumulative risk of CRC and EC for male and female carriers of MLH1 mutations compared with corresponding values for the population incidences as reported in the Spanish Cancer Registries (95% CIs are provided for cumulative risk at ages 50 and 70). B. Age-specific and overall HR for CRC and EC for male and female carriers of MLH1 mutations (95% Wald CI is provided for the HR parameters).

Abbreviation: NA, not available.

Although the cumulative risk of CRC for c.1865T>A carriers exceeds the risk in the general population by age 60 years, it is lower than for c.306+5G>A. Risk of CRC continues to increase and by age 70 is 6.8% (95% CI, 0–15.8%) for males and 7.3% (95% CI, 0–16.5%) for females. The overall HR for CRC is 2.4 (95% CI, 06–10.2) for males and 4.5 (95% CI, 1.1–18.0) for females. Risk for EC tends to exceed that of the general population at age 70 years, equaling 3.4% (95% CI, 0–10.0%) with HR of 2.9 (95% CI, 0.4–23.6; Table 3).

In carriers of other Spanish MLH1 pathogenic mutations, estimated lifetime risk for CRC is 26.3% (95% CI, 7.8–41.1%) for men and 10.7% for women (95% CI, 0–16.8%), with HR of 10.5 (95% CI, 5.0–21.8) for males and 5.4 (95% CI, 2.0–14.9) for females, and cumulative risk for EC is 6.5% (95% CI, 0–13.1%) with HR of 5.7 (95% CI, 1.9–17.0; Table 3). Therefore, both c.306+5G>A and c.1865T>A mutations show a penetrance within the range of variability estimated in families with other MLH1 mutations, with a nonsignificant trend to lower penetrance for the c.1865T>A mutation.

Haplotype analysis and estimation of mutation age

Ancestors of families carrying the c.306+5G>A mutation came from the Ebro river valley in northern Spain, whereas ancestors of families with the c.1865T>A mutation originated from the region of Jaén in southern Spain (Fig. 3). Common geographic origins of carrier families suggested that each of the two mutations could have occurred as a unique event in a single founder individual. This hypothesis was confirmed by haplotype analysis (Table 4).

Figure 3.

Map of Spain showing locations where Lynch syndrome families with the c. 306+5G>A mutation (white circles) and the c.1865T>A mutation (black circles) originated. For six families (four c.306+5G>A and two c.1865T>A), the original location is not known. The Ebro valley is highlighted in dark gray. The insert shows a larger-scale map of the Jaén province.

Figure 3.

Map of Spain showing locations where Lynch syndrome families with the c. 306+5G>A mutation (white circles) and the c.1865T>A mutation (black circles) originated. For six families (four c.306+5G>A and two c.1865T>A), the original location is not known. The Ebro valley is highlighted in dark gray. The insert shows a larger-scale map of the Jaén province.

Close modal
Table 4.

Haplotypes associated with the c.306+5G>A (A) and c.1865T>A (B) mutations in carrier families

NOTE: The “/” symbol indicates that the phase of the disease haplotype cannot be established. The “//” symbol indicates that recombination has likely occurred within a family. Intragenic MLH1 markers are shown in a box. Dark gray shading indicates nonrecombinant haplotypes. The sizes of the minimum and maximum conserved haplotypes are shown at the bottom. Inferred haplotypes of subjects in the fifth generation in each family are in bold. The frequencies of disease-associated alleles among a panel of control DNAs are shown at the bottom.

The existence of a clear shared haplotype in carrier individuals permitted estimation of mutation age. In this estimation for the c.306+5T>A mutation, we considered disease haplotypes in the region extending from D3S2369 to D3S1298 (D3S1612 to D3S1298 for c.1865T>A; Table 4), which has a recombination map length of 0.9796 cM (2.2578 cM for c.1865T>A). In the control population, the estimated frequency of the identified minimum common haplotype, excluding the disease mutation, was 0.069 for c.306+5T>A and 0.048 for c.1865T>A (Supplementary Table S2).

To estimate the age of the mutation, we relied on an estimate of the number of recombination events that occurred on the ancestral disease haplotype for each disease mutation. At the 5′ end of the common haplotype of c.306+5G>A, a likely recombination event at marker D3S2369 was detected in family A10; at the 3′ end (D3S1298), the common haplotype was lost in 6 of the 17 families, likely in two separate recombination events (Table 4A). Therefore, for c.306+5T>A, we counted a minimum of three recombination events necessary to explain all disease haplotypes in the region. For c.1865T>A, we counted a minimum of one event, which occurred at the 3′ end (D3S1298) and which explained the loss of the common haplotype by 5 of the 12 families (Table 4B).

From the map lengths (r) and recombination counts (k), we estimated genealogy lengths (L) using the formula

$LĮ=k/r$
⁠. We obtained
$LĮE⁢b⁢r⁢o=3/0.009796=306$
generations and
$LĮJ⁢aeĭn=1/0.022578=44$
generations. To estimate TMRCA from these lengths, we required an estimate of the ratio c (see Supplementary Materials and Methods). By simulating 5 × 107 trees under a coalescent model of constant population size with n = 17 lineages representing 17 families, we estimated
$cĮE⁢b⁢r⁢o=0.2324$
, which gives an estimate of
$HĮE⁢b⁢r⁢o=cĮE⁢b⁢r⁢oLĮE⁢b⁢r⁢o+4=75$
generations (1,879 years assuming 25 years per generation) for the c.306+5G>A mutation. Similarly, using n = 12 lineages, we estimated
$cĮJ⁢aeĭn=0.2569$
, producing an age estimate of
$HĮJ⁢aeĭn=cĮJ⁢aeĭnLĮJ⁢aeĭn=4=15$
generations (384 years assuming 25 years per generation) for c.1865T>A. The 95% CI for
$HĮE⁢b⁢r⁢o$
is 53 to 122 generations, and the corresponding interval for
$HĮJ⁢aeĭn$
is 12 to 22 generations (Supplementary Table S2).

We have identified and characterized two frequent MLH1 variants, c.306+5G>A and c.1865T>A (p.Leu622His), among Spanish Lynch syndrome families. They represent the first founder MLH1 mutations identified in the Spanish population.

The predicted effect of the previously reported MLH1 variant c.306+5G>A (36) on splicing was confirmed, consistent with observations on the nearby mutations c.306+2dupT and c.306+4A>G (37, 38). At the protein level, no differences in expression were observed in mutation carriers when compared with controls, presumably because of a lack of stability of mutated MLH1 proteins or due to the limitations of the Western blotting assay.

The c.1865T>A variant (p.Leu622His) was previously described as a germline MLH1 mutation in two Spanish families (39, 40). Prior functional assays for p.Leu622His were inconclusive to assess its pathogenicity: In yeast-based assays, it was deficient in MMR activity (33, 41), whereas HCT116 cells cotransfected with MLH1 and PMS2 retained partial MMR activity (69.2%). The effect on protein expression levels was inconclusive (33). In vitro expression studies in MLH1-transfected HCT116 cells indicated that this mutation may substantially reduce MLH1 expression by affecting its stability, which in turn leads to a reduction in the expression of its counterpart PMS2. A pathogenic role for the p.Leu622His mutation was further supported by the frequent loss of the MLH1 WT allele observed in tumors (42). An additional effect of the mutation on the capacity to bind PMS2 or on the intracellular trafficking of MLH1/PMS2 could not be ruled out.

Once the functional effect of the founder mutations was shown, we explored whether penetrance estimates differed from other MLH1 mutations. The estimated penetrance of Spanish MLH1 mutations was moderate and consistent with data reported for Dutch families (5). The penetrance of founder mutations was within the range of variability of penetrance observed for Spanish MLH1 mutations. The penetrance for c.1865T>A missense mutation may be lower, a fact that may be attributed to the observed decrease in MLH1 expression. The penetrance estimates are sensitive to the type of ascertainment correction, and elevate with use of an unconditional likelihood or likelihood conditioned only on the proband, a phenomenon also noted in (2). Of note, penetrance estimates for Spanish Lynch syndrome families are lower than those reported in North American populations (2, 3). The fact that we have used the same method as Stoffel and colleagues (2) and that similar cumulative risks are observed in the United States and Spain suggests that geographic differences in cancer risk might exist in Lynch syndrome carriers. Several factors including lifestyle, environmental factors, mutational spectrum, or, as recently reported, the existence of distinct weak alleles capable of producing polygenic effects (43) may account for this observation.

Founder mutations in MMR genes have an important effect in traditional “founder populations”: Four different mutations in MLH1 and MSH2 genes in Finland, Newfoundland, and in Ashkenazi Jews account for between 25% and 50% of all Lynch syndrome cases in these populations (9, 10, 13, 44). Before our report, two founder mutations in the MSH2 gene had been identified in Spanish Lynch syndrome families, although their frequencies were low in our population (11, 12). In the cohort of Lynch syndrome families from ICO, the identified c.306+5G>A and c.1865T>A mutations account for 28.8% of the 45 families carrying MLH1 alterations (13 founders and 32 nonfounders) and represent 17.6% (13 of 74) of all families with mutations in MMR genes. In addition, the c.306+5G>A founder accounts for up to 25% of MLH1 mutations identified in the Ebro basin area (data not shown).

Our detection of founder mutations in MLH1 supports the view that they can occur not only in groups commonly viewed as founder populations but also in geographically localized subsets of larger populations. These two founder mutations were not detected in a prior study of 1,222 incident cases of CRC in Spain (EPICOLON; ref. 45). This study identified 11 germline MMR mutations, 4 in MLH1. The lack of detection of founder mutations may be due to the low number of identified mutations or the relatively low coverage of the areas of origin.

Families carrying the c.306+5G>A mutation cluster within the Ebro river basin, in northern Spain, and we estimate that the mutation arose ∼1,879 years ago. Taking into account the fact that the river valley is geographically isolated by mountain ranges, and the Ebro river was navigable until the 19th century, we hypothesize that the mutation arose somewhere in the valley and was distributed along the river over the years (Fig. 3). The c.1865T>A mutation is younger (384 years) than c.306+5G>A, and its distribution is restricted to the mountainous province of Jaén. It is noteworthy that probands have been identified in Madrid and Barcelona, frequent destinations of internal migratory movements during the period 1960 to 1970. Thus, the origin of the MLH1 founder mutations can be linked to specific geographic areas, and their current distribution can be explained by migration patterns. Allele age estimation is generally imprecise (46) due to several factors, including uncertainty in the count of recombination events on ancestral haplotypes, the accuracy with which the recombination count predicts the true genealogy length, and the accuracy with which TMRCA reflects allele age. However, the relatively recent values obtained are sensible for rare mutations restricted to relatively isolated geographic areas.

The high prevalence and moderate penetrance of the c.306+5G>A and c.1865T>A variants have implications for molecular and clinical approaches to founder mutations in many settings. In specific populations such as the Spanish population, initial screening for founder mutations increases the efficiency of testing of molecular diagnostic labs. Even more importantly, careful clinical characterization of founder mutations can lead to mutation-specific counseling and improved clinical care.

No potential conflicts of interest were disclosed.

We thank the staff at the Genetic Counseling Units who have participated in this study and Michael DeGiorgio for helpful discussions about the mutation age estimates.

Grant Support: Fundació La Caixa grant BM 04-107-0; Fundació Gastroenterologia Dr. Francisco Vilardell grant F05-01; Ministerio de Educación y Ciencia grants AGL2004-07579-04, SAF 06-6084, and SAF09-7319; Spanish Networks RTICCC grants RD06/0020/1050, 1051, 0021, and 0028; Acción en Cáncer (Instituto de Salud Carlos III); Fundació Roses Contra el Càncer; Fondo de Investigación Sanitaria (CP 03-0070); and NIH grant CA81488.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1
Lynch
HT
,
Lynch
JF
,
Lynch
PM
,
Attard
T
.
Hereditary colorectal cancer syndromes: molecular genetics, genetic counseling, diagnosis and management
.
Fam Cancer
2008
;
7
:
27
39
.
2
Stoffel
E
,
Mukherjee
B
,
Raymond
VM
, et al
.
Calculation of risk of colorectal and endometrial cancer among patients with lynch syndrome
.
Gastroenterology
2009
;
137
:
1621
7
.
3
Choi
YH
,
Cotterchio
M
,
McKeown-Eyssen
G
, et al
.
Penetrance of colorectal cancer among MLH1/MSH2 carriers participating in the colorectal cancer familial registry in Ontario
.
Hered Cancer Clin Pract
2009
;
7
:
14
.
4
Alarcon
F
,
Lasset
C
,
Carayol
J
, et al
.
Estimating cancer risk in HNPCC by the GRL method
.
Eur J Hum Genet
2007
;
15
:
831
6
.
5
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
6
.
6
Pineda
M
,
Gonzalez
S
,
Lazaro
C
,
Blanco
I
,
Capella
G
.
Detection of genetic alterations in hereditary colorectal cancer screening
.
Mutat Res
2009
.
7
Chong
G
,
Jarry
J
,
Marcus
V
, et al
.
High frequency of exon deletions and putative founder effects in French Canadian Lynch syndrome families
.
Hum Mutat
2009
;
30
:
E797
812
.
8
Tang
R
,
Hsiung
C
,
Wang
JY
, et al
.
Germ line MLH1 and MSH2 mutations in Taiwanese Lynch syndrome families: characterization of a founder genomic mutation in the MLH1 gene
.
Clin Genet
2009
;
75
:
334
45
.
9
Nystrom-Lahti
M
,
Kristo
P
,
Nicolaides
NC
, et al
.
Founding mutations and Alu-mediated recombination in hereditary colon cancer
.
Nat Med
1995
;
1
:
1203
6
.
10
Moisio
AL
,
Sistonen
P
,
Weissenbach
J
,
de la Chapelle
A
,
Peltomaki
P
.
Age and origin of two common MLH1 mutations predisposing to hereditary colon cancer
.
Am J Hum Genet
1996
;
59
:
1243
51
.
11
Medina-Arana
V
,
Barrios
Y
,
Fernandez-Peralta
A
, et al
.
New founding mutation in MSH2 associated with hereditary nonpolyposis colorectal cancer syndrome on the Island of Tenerife
.
Cancer Lett
2006
;
244
:
268
73
.
12
Menéndez
M
,
Castellví-Bel
S
,
Pineda
M
, et al
.
Founder effect of a pathogenic MSH2 mutation identified in Lynch syndrome Spanish families
.
Clin Genet
2010
;
78
:
186
90
.
13
Foulkes
WD
,
Thiffault
I
,
Gruber
SB
, et al
.
The founder mutation MSH2*1906G→C is an important cause of hereditary nonpolyposis colorectal cancer in the Ashkenazi Jewish population
.
Am J Hum Genet
2002
;
71
:
1395
412
.
14
Cederquist
K
,
Emanuelsson
M
,
Wiklund
F
,
Golovleva
I
,
Palmqvist
R
,
Gronberg
H
.
Two Swedish founder MSH6 mutations, one nonsense and one missense, conferring high cumulative risk of Lynch syndrome
.
Clin Genet
2005
;
68
:
533
41
.
15
Spurdle
AB
,
Couch
FJ
,
Hogervorst
FB
,
P
,
Sinilnikova
OM
.
Prediction and assessment of splicing alterations: implications for clinical testing
.
Hum Mutat
2008
;
29
:
1304
13
.
16
Couch
FJ
,
Rasmussen
LJ
,
Hofstra
R
,
Monteiro
AN
,
Greenblatt
MS
,
de Wind
N
.
Assessment of functional effects of unclassified genetic variants
.
Hum Mutat
2008
;
29
:
1314
26
.
17
Goldgar
DE
,
Easton
DF
,
Byrnes
GB
,
Spurdle
AB
,
Iversen
ES
,
Greenblatt
MS
.
Genetic evidence and integration of various data sources for classifying uncertain variants into a single model
.
Hum Mutat
2008
;
29
:
1265
72
.
18
Moreno
V
,
Gemignani
F
,
Landi
S
, et al
.
Polymorphisms in genes of nucleotide and base excision repair: risk and prognosis of colorectal cancer
.
Clin Cancer Res
2006
;
12
:
2101
8
.
19
Dogan
RI
,
Getoor
L
,
Wilbur
WJ
,
Mount
SM
.
SplicePort—an interactive splice-site analysis tool
.
Nucleic Acids Res
2007
;
35
:
W285
91
.
20
Reese
MG
,
Eeckman
FH
,
Kulp
D
,
Haussler
D
.
Improved splice site detection in Genie
.
J Comput Biol
1997
;
4
:
311
23
.
21
Fairbrother
WG
,
Yeh
RF
,
Sharp
PA
,
Burge
CB
.
Predictive identification of exonic splicing enhancers in human genes
.
Science
2002
;
297
:
1007
13
.
22
Cartegni
L
,
Wang
J
,
Zhu
Z
,
Zhang
MQ
,
Krainer
AR
.
ESEfinder: a web resource to identify exonic splicing enhancers
.
Nucleic Acids Res
2003
;
31
:
3568
71
.
23
Ramensky
V
,
Bork
P
,
Sunyaev
S
.
Human non-synonymous SNPs: server and survey
.
Nucleic Acids Res
2002
;
30
:
3894
900
.
24
Boyer
JC
,
Umar
A
,
Risinger
JI
, et al
.
Microsatellite instability, mismatch repair deficiency, and genetic defects in human cancer cell lines
.
Cancer Res
1995
;
55
:
6063
70
.
25
Perera
S
,
Bapat
B
.
The MLH1 variants p.Arg265Cys and p.Lys618Ala affect protein stability while p.Leu749Gln affects heterodimer formation
.
Hum Mutat
2008
;
29
:
332
.
26
Pelletier
R
,
Farrell
BT
,
Miret
JJ
,
Lahue
RS
.
Mechanistic features of CAG*CTG repeat contractions in cultured cells revealed by a novel genetic assay
.
Nucleic Acids Res
2005
;
33
:
5667
76
.
27
Lutzen
A
,
de Wind
N
,
Georgijevic
D
,
Nielsen
FC
,
Rasmussen
LJ
.
Functional analysis of HNPCC-related missense mutations in MSH2
.
Mutat Res
2008
;
645
:
44
55
.
28
Antoniou
A
,
Pharoah
PD
,
Narod
S
, et al
.
Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: a combined analysis of 22 studies
.
Am J Hum Genet
2003
;
72
:
1117
30
.
29
Lange
K
,
Weeks
D
,
Boehnke
M
.
Programs for pedigree analysis: MENDEL, FISHER, and dGENE
.
Genet Epidemiol
1988
;
5
:
471
2
.
30
MP
,
Edwards
B
,
Shin
HR
, editors.
Cancer incidence in five continents, vol. IX. IARC Scientific Publications No. 160
.
Lyon
:
IARC
;
2007
.
31
Stephens
M
,
Donnelly
P
.
A comparison of Bayesian methods for haplotype reconstruction from population genotype data
.
Am J Hum Genet
2003
;
73
:
1162
9
.
32
Schroeder
KB
,
Jakobsson
M
,
Crawford
MH
, et al
.
Haplotypic background of a private allele at high frequency in the Americas
.
Mol Biol Evol
2009
;
26
:
995
1016
.
33
Takahashi
M
,
Shimodaira
H
,
Andreutti-Zaugg
C
,
Iggo
R
,
Kolodner
RD
,
Ishioka
C
.
Functional analysis of human MLH1 variants using yeast and in vitro mismatch repair assays
.
Cancer Res
2007
;
67
:
4595
604
.
34
Chao
EC
,
Velasquez
JL
,
Witherspoon
MS
, et al
.
Accurate classification of MLH1/MSH2 missense variants with multivariate analysis of protein polymorphisms-mismatch repair (MAPP-MMR)
.
Hum Mutat
2008
;
29
:
852
60
.
35
Guarne
A
,
Ramon-Maiques
S
,
Wolff
EM
, et al
.
Structure of the MutL C-terminal domain: a model of intact MutL and its roles in mismatch repair
.
EMBO J
2004
;
23
:
4134
45
.
36
Becouarn
Y
,
Rullier
A
,
Gorry
P
, et al
.
Value of microsatellite instability typing in detecting hereditary non-polyposis colorectal cancer. A prospective multicentric study by the Association Aquitaine Gastro
.
Gastroenterol Clin Biol
2005
;
29
:
667
75
.
37
Pagenstecher
C
,
Wehner
M
,
Friedl
W
, et al
.
Aberrant splicing in MLH1 and MSH2 due to exonic and intronic variants
.
Hum Genet
2006
;
119
:
9
22
.
38
Tournier
I
,
Vezain
M
,
Martins
A
, et al
.
A large fraction of unclassified variants of the mismatch repair genes MLH1 and MSH2 is associated with splicing defects
.
Hum Mutat
2008
;
29
:
1412
24
.
39
Godino
J
,
de La Hoya
M
,
Diaz-Rubio
E
,
Benito
M
,
Caldes
T
.
Eight novel germline MLH1 and MSH2 mutations in hereditary non-polyposis colorectal cancer families from Spain
.
Hum Mutat
2001
;
18
:
549
.
40
Palicio
M
,
Balmana
J
,
Gonzalez
S
, et al
.
Mismatch repair gene analysis in Catalonian families with colorectal cancer
.
J Med Genet
2002
;
39
:
E29
.
41
Wanat
JJ
,
Singh
N
,
Alani
E
.
The effect of genetic background on the function of Saccharomyces cerevisiae mlh1 alleles that correspond to HNPCC missense mutations
.
Hum Mol Genet
2007
;
16
:
445
52
.
42
Tuupanen
S
,
Karhu
A
,
Jarvinen
H
,
Mecklin
JP
,
Launonen
V
,
Aaltonen
LA
.
No evidence for dual role of loss of heterozygosity in hereditary non-polyposis colorectal cancer
.
Oncogene
2007
;
26
:
2513
7
.
43
Martinez
SL
,
Kolodner
RD
.
Functional analysis of human mismatch repair gene mutations identifies weak alleles and polymorphisms capable of polygenic interactions
.
Proc Natl Acad Sci U S A
2010
;
107
:
5070
5
.
44
Froggatt
NJ
,
Green
J
,
Brassett
C
, et al
.
A common MSH2 mutation in English and North American HNPCC families: origin, phenotypic expression, and sex specific differences in colorectal cancer
.
J Med Genet
1999
;
36
:
97
102
.
45
Pinol
V
,
Castells
A
,
Andreu
M
, et al
.
Accuracy of revised Bethesda guidelines, microsatellite instability, and immunohistochemistry for the identification of patients with hereditary nonpolyposis colorectal cancer
.
JAMA
2005
;
293
:
1986
94
.
46
Slatkin
M
,
Rannala
B
.
Estimating allele age
.
Annu Rev Genomics Hum Genet
2000
;
1
:
225
49
.