Missense mutations of MLH1 and MSH2 genes detected in patients with gastrointestinal cancer are associated with exonic splicing enhancers and silencers

  • Authors: Ming Zhu, Hui‑Mei Chen, Ya‑Ping Wang
  • View Affiliations

  • Published online on: Monday, March 11, 2013
  • Pages: 1710-1718
  • DOI: 10.3892/ol.2013.1243

Abstract

The MLH1 and MSH2 genes in DNA mismatch repair are important in the pathogenesis of gastrointestinal cancer. Recent studies of normal and alternative splicing suggest that the deleterious effects of missense mutations may in fact be splicing‑related when they are located in exonic splicing enhancers (ESEs) or exonic splicing silencers (ESSs). In this study, we used ESE‑finder and FAS‑ESS software to analyze the potential ESE/ESS motifs of the 114 missense mutations detected in the two genes in East Asian gastrointestinal cancer patients. In addition, we used the SIFT tool to functionally analyze these mutations. The amount of the ESE losses (68) was 51.1% higher than the ESE gains (45) of all the mutations. However, the amount of the ESS gains (27) was 107.7% higher than the ESS losses (13). In total, 56 (49.1%) mutations possessed a potential exonic splicing regulator (ESR) error. Eighty‑one mutations (71.1%) were predicted to be deleterious with a lower tolerance index as detected by the Sorting Intolerant from Tolerant (SIFT) tool. Among these, 38 (33.3%) mutations were predicted to be functionally deleterious and possess one potential ESR error, while 18 (15.8%) mutations were predicted to be functionally deleterious and exhibit two potential ESR errors. These may be more likely to affect exon splicing. Our results indicated that there is a strong correlation between missense mutations in MLH1 and MSH2 genes detected in East Asian gastrointestinal cancer patients and ESR motifs. In order to correctly understand the molecular nature of mutations, splicing patterns should be compared between wild‑type and mutant samples.

Introduction

The incidence and mortality rates of gastric cancer and colorectal cancer are among the highest among malignant tumors in East Asia. Germline mutations of mismatch repair (MMR) genes are responsible for the majority of hereditary nonpolyposis colorectal cancer (HNPCC) cases. The MMR genes MSH2 (OMIM No. 609309) and MLH1 (OMIM No. 120436) are considered to be the two major genes implicated in HNPCC (1,2). Carriers of germline mutations of MSH2 and MLH1 genes have a 4-fold greater risk of gastric cancer compared with normal individuals, as well as a high risk of colorectal cancer. These two genes are associated with gastrointestinal cancer susceptibility.

Missense mutations are among the most common types of mutations underlying inherited human diseases. The deleterious effects of missense mutations are usually attributed to their effects on the structure or function of a protein. The assumption may be misleading, as the mutations that affect the sequences that are important for splicing modulation are likely to have a profound effect on the translated product. It has become increasingly clear that exonic point mutations located outside the splice sites may affect pre-mRNA splicing and thereby cause disease (3,4). Correct pre-mRNA splicing not only requires that the splice site sequences are present at the exon-intron borders, but is also critically dependent on additional intronic and exonic regulatory sequences (5). Those present in exons and with the capacity of enhancing splicing are called exonic splicing enhancers (ESEs) and those with the capacity of inhibiting the splicing are the exonic splicing silencers (ESSs). Generally, these classes of elements are called exonic splicing regulators (ESRs). Consequently, mutations located in ESE or ESS elements may affect splicing. The significance and prevalence of this phenomenon may have been significantly underestimated, as the majority of studies of disease-related genes are limited to the analysis of genomic DNA.

The majority of enhancer sequences within exons have been found to bind members of the serine/arginine-rich (SR) protein family, while many silencing elements are bound by members of the heterogeneous nuclear ribonuclearprotein (hnRNP) family (6). ESEs are discrete, degenerate motifs of 6–8 nts located inside exons (7,8). The study of normal splicing suggests that the majority of exons contain at least one functional ESE site (7,9). ESE-bound SR proteins promote exon definition by directly recruiting and stabilizing the splicing machinery through protein-protein interactions (10), and/or by antagonizing the function of nearby silencer elements (11). The cores of ESSs are considered to be relatively short (6–10 nts). ESS-bound hnRNPs are proposed to mediate silencing through direct antagonism of the splicing machinery or by direct competition for overlapping enhancer binding sites. The intrinsic strength by which the splice sites are recognized by the spliceosome, as well as the antagonistic dynamics of proteins binding ESEs and ESSs, control a large proportion of exon recognition and alternative splicing. Therefore, exonic splicing regulatory sequences are now increasingly recognized as a major target and a common mechanism for disease-causing mutations leading to exon skipping in functionally diverse genes.

In this study, we used ESE-finder (12,13) and FAS-ESS (14) software to analyze the missense mutations of MSH2 and MLH1 genes detected in East Asian gastrointestinal cancer patients, and to assess whether these mutations hit the predicted ESE/ESS motifs and affected gene splicing.

Materials and methods

Subjects

A total of 114 missense mutations, 52 of MSH2 and 62 of MLH1, detected in the gastrointestinal cancer patients, were serially collected for this study from published East Asian literature (1544) (Table I). The majority of the investigated mutations were exclusively reported in East Asia (China, Japan and Korea), and some of the mutations were detected in different ethnicities. The study was approved by the Ethics Committee of Nanjing University, Nanjing, China.

Table I

Pathogenic missense mutations analyzed in the splicing assay.

Table I

Pathogenic missense mutations analyzed in the splicing assay.

ESE findera
GeneExonNucleotide changeAmino acid changeSF2/ASFSC35SRp40SRp55FAS ESSbSIFT predictionEthnicityReference
MSH21c.14C>Ap.Pro5His−1/3DamagingChinese15
MSH21c.23C>Tp.Thr8Met−1/1=1+1/0ToleratedChinese; Japanese16, 17
MSH21c.49G>Tp.Val17Phe=1+1/0+1/0ToleratedKorean18
MSH22c.329A>Cp.Lys110Thr+1/0ToleratedJapanese19
MSH23c.380A>Tp.Asn127IleDamagingKorean20
MSH23c.505A>Gp.Ile169Val=1=1+1/0ToleratedChinese21
MSH23c.518T>Gp.Leu173Arg−1/1DamagingChinese21
MSH23c.529G>Ap.Glu177Lys=1DamagingChinese22
MSH23c.595T>Cp.Cys199ArgDamagingChinese23
MSH23c.619G>Tp.Ala207Ser−1/1=1−1/2ToleratedChinese24
MSH25c.884A>Gp.Asp295Gly=1+1/0DamagingKorean25
MSH26c.968C>Ap.Ser323Tyr=1−1/1ToleratedKorean18
MSH26c.1004C>Tp.Thr335IleDamagingKorean18
MSH26c.1012G>Ap.Gly338Arg−1/1−1/1−1/1DamagingChinese26
MSH27c.1108G>Ap.Ala370Thr=1ToleratedChinese27
MSH27c.1145G>Ap.Arg382His=1DamagingChinese28
MSH27c.1168C>Tp.Leu390Phe−1/1−1/1DamagingChinese21
MSH27c.1223A>Gp.Tyr408Cys+1/0=1DamagingChinese21
MSH27c.1225C>Ap.Gln409Lys+1,−1/1DamagingChinese28
MSH27c.1255C>Ap.Gln419Lys=1ToleratedChinese21
MSH27c.1261C>Ap.Leu421Met−1/1+1/0DamagingChinese21
MSH210c.1516G>Tp.Asp506Tyr=1DamagingKorean29
MSH210c.1571G>Tp.Arg524Leu+1/0−1/1DamagingChinese30
MSH211c.1688A>Cp.Tyr563Ser=1−1/1DamagingChinese31
MSH212c.1799C>Tp.Ala600Val−1/1+2/0DamagingJapanese32
MSH212c.1807G>Tp.Asp603Tyr−1/1DamagingChinese33
MSH212c.1808A>Gp.Asp603Gly−1/1+1/0DamagingChinese34
MSH212c.1886A>Gp.Gln629Arg+1/0ToleratedChinese; Korean18, 35
MSH212c.1916A>Gp.His639Arg+1/0DamagingJapanese19
MSH212c.1917T>Ap.His639Gln=1DamagingChinese30
MSH212c.1939G>Ap.Glu647LysDamagingJapanese19
MSH212c.1955C>Ap.Pro652His−1/1+1/0DamagingChinese30
MSH212c.1966T>Cp.Tyr656His−1/1ToleratedJapanese19
MSH213c.2036T>Cp.Ile679Thr+1/0DamagingJapanese19
MSH213c.2047G>Ap.Gly683Arg+1,−1/1−1/1+2/2DamagingChinese30
MSH213c.2064G>Ap.Met688Ile−1/1−2/2+1/0DamagingKorean36
MSH213c.2087C>Tp. Pro696LeuDamagingChinese27
MSH213c.2089T>Cp.Cys697Arg+1/0+1/0+1/0DamagingKorean37
MSH213c.2108C>Ap.Ser703Tyr=1−1/1+1/0DamagingChinese22
MSH213c.2128G>Tp.Ala710Ser−1/1−1/1DamagingChinese26
MSH213c.2141C>Tp.Ala714Val=1+4/0DamagingKorean18
MSH213c.2168C>Tp.Ser723Phe=1DamagingJapanese32
MSH213c.2185A>Gp.Met729Val+1/0=1+1/0DamagingJapanese19
MSH213c.2195C>Tp.Thr732IleDamagingJapanese19
MSH214c.2425G>Ap.Glu809Lys−1/1+1/0ToleratedChinese27
MSH215c.2479G>Ap.Gly827Arg−1/2DamagingChinese33
MSH215c.2516A>Gp.His839Arg=1ToleratedChinese16
MSH215c.2533A>Gp.Lys845GluDamagingJapanese17
MSH215c.2564A>Cp.Gln855Pro+1/0+2/0+2, −1/1ToleratedKorean25
MSH216c.2649T>Gp.Ile883MetToleratedKorean38
MSH216c.2651T>Cp.Ile884Thr+1/0+1/1DamagingKorean25
MSH216c.2792A>Cp.Lys931Thr−1/1DamagingChinese15
MLH11c.107T>Ap.Ile36AsnDamagingChinese30
MLH12c.122AT>TAp.Asp41Val+1/0+1/1DamagingChinese27
MLH12c.137G>Tp.Ser46Ile−1/1=1ToleratedChinese22
MLH12c.158A>Cp.Glu53Ala+1/0ToleratedJapanese19
MLH12c.194G>Ap.Gly65Asp+2,−1/1DamagingChinese15
MLH12c.199G>Ap.Gly67Arg=1+1/0DamagingChinese16
MLH12c.205A>Gp.Arg69GlyDamagingJapanese19
MLH13c.229T>Cp.Cys77Arg+1/0DamagingChinese27
MLH13c.242C>Tp.Thr81Ile−1/2−1/2DamagingJapanese19
MLH13c.250A>Gp.Lys84Glu+1/0DamagingChinese27
MLH14c.318C>Gp.Ser106Arg−1/1−1/1DamagingKorean18
MLH14c.327T>Gp.His109Gln−1/1+1/0DamagingKorean18
MLH14c.332C>Tp.Ala111Val−1/1=1−1/1+1/0DamagingJapanese17
MLH14c.350C>Tp.Thr117Met=1DamagingChinese27
MLH16c.498A>Cp.Leu166PheToleratedChinese30
MLH17c.572G>Tp.Ser191Ile−4/4DamagingChinese30
MLH18c.637G>Tp.Val213Leu−2/2−1/1ToleratedChinese16
MLH18c.649C>Tp.Arg217Cys−1/1DamagingJapanese; Korean29, 32
MLH18c.655A>Gp.Ile219Val=1=1ToleratedChinese; Japanese17; 21
MLH18c.677 G>Ap.Arg226Gln−1/1DamagingKorean25
MLH19c.701A>Gp.Glu234Gly−1/1−1/1+3/0ToleratedKorean18
MLH19c.790C>Tp.His264TyrDamagingChinese33
MLH110c.793C>Tp.Arg265Cys=1DamagingChinese27
MLH110c.845C>Gp.Ala282Gly−1/1=1ToleratedKorean39
MLH111c.908T>Ap.Val303Glu=1DamagingChinese30
MLH111c.949C>Ap.Leu317Met−1/1−1/1DamagingChinese30
MLH111c.962G>Tp.Ser321Ile−1/1−1/1ToleratedKorean18
MLH111c.985C>Ap.His329Asn+1/0−1/2ToleratedChinese22
MLH111c.1038G>Tp. Gln346His=1DamagingChinese27
MLH112c.1151T>Ap.Val384Asp=1−1/1−2/2DamagingChinese40
MLH112c.1178T>Cp.Leu393ProDamagingChinese27
MLH112c.1186T>Ap.Phe396Ile−1/1=1−1/1DamagingKorean25
MLH112c.1198C>Gp.Leu400Val+1,−1/1=1−1/1ToleratedChinese31
MLH112c.1246A>Gp.Lys416GluToleratedChinese30
MLH113c.1453G>Cp.Asp485His=1ToleratedKorean18
MLH114c.1561C>Ap.Leu521Ile−1/1−1/1DamagingJapanese19
MLH114c.1576C>Tp.His526Tyr=1DamagingJapanese19
MLH114c.1625A>Tp.Gln542Leu=1=1−1/2DamagingJapanese; Korean39, 41
MLH114c.1646T>Cp.Leu549ProDamagingKorean29
MLH115c.1681T>Cp.Tyr561His+1/0=1+1, −1/1DamagingChinese22
MLH115c.1721T>Cp.Leu574Pro=1+1/1=1+1/0DamagingJapanese; Korean39, 41
MLH116c.1742C>Tp.Pro581Leu−2/2+1/0ToleratedChinese42
MLH116c.1744C>Gp.Leu582Val=2+1/0ToleratedJapanese41
MLH116c.1763T>Cp.Leu588Pro+1/0DamagingJapanese17
MLH116c.1799A>Gp.Glu600Gly=1DamagingChinese22
MLH116c.1823C>Ap.Ala608AspDamagingChinese30
MLH117c.1900G>Ap.Gly634ArgDamagingJapanese19
MLH117c.1905C>Gp.Asn635Lys−1/1ToleratedKorean18
MLH117c.1907T>Cp.Leu636Pro−1/1−1/1DamagingKorean39
MLH117c.1918C>Tp.Pro640Ser−1/1DamagingKorean39
MLH117c.1942C>Tp.Pro648Ser−1/1+1/0+1/0DamagingChinese22
MLH117c.1984A>Cp.Thr662Pro+1/0=1−1/1ToleratedKorean38
MLH117c.1988A>Cp.Glu663Ala=1ToleratedChinese30
MLH118c.2038T>Cp.Cys680Arg+1/0DamagingChinese30
MLH118c.2041G>Ap.Ala681ThrDamagingChinese43
MLH118c.2042C>Tp.Ala681Val+1/0DamagingChinese44
MLH118c.2059C>Tp.Arg687Trp−2/2DamagingJapanese32
MLH118c.2101C>Ap.Gln701Lys=1+1/0ToleratedChinese21
MLH119c.2168C>Ap.Ala723Asp+1/0DamagingKorean39
MLH119c.2170T>Ap.Leu724MetToleratedKorean39
MLH119c.2210A>Tp.Asp737Val=1−1/1DamagingJapanese19
MLH119c.2263A>Gp.Arg755Gly+1,−1/1+3/0DamagingChinese27

a Number of ESE motifs added or abrogated from the mutation/number of ESE motifs in the normal allele.

b Number of ESS motifs added or abrogated from the mutation/number of ESS motifs in the normal allele.

Potential ESE motif analysis

To identify the ESE motifs that were recognized by individual SR proteins, a PCR-based systematic evolution of ligands by exponential enrichment (SELEX) was used. During this approach, a natural splicing enhancer in a minigene was replaced by short, random sequences derived from an oligonucleotide library. The generated pool of minigenes was transfected into cultured cells, and spliced mRNAs were amplified by RT-PCR and sequenced (7). On the basis of the frequencies of the individual nucleotides at each position, a score matrix for each nucleotide in each position was calculated. This score matrix may be used to predict SR protein-specific ESEs (ESE-finder) (12,13).

We analyzed wild-type or mutant exon sequences from MLH1 and MSH2 genes in Table I with ESE-finder software using SR protein score matrices and threshold values, essentially as described previously (ESE-finder: http://rulai.cshl.edu/tools/ESE/) (12). Sequence motifs for the same or different SR proteins may overlap. We considered only the wild type or mutant sequence motifs with scores greater than or equal to the value of the threshold for the corresponding SR protein. The threshold values were as follows: SF2/ASF (IgM-BRCA1) heptamer motif, 1.867; SC35 octamer motif, 2.383; SRp40 heptamer motif, 2.670 and SRp55 hexamer motif, 2.676.

Potential ESS motif analysis

To systematically identify ESS motifs, an in vivo splicing reporter system was developed to screen a library of random decanucleotides. The resulting library was transfected into cultured human 293 cells, and stably transfected cells were combined and sorted for GFP-expressing cells by fluorescence activated cell sorting (FACS) analysis. The fluorescence-activated screen for exonic splicing silencers (FAS-ESS, or FAS for short) yielded 176 ESS hexamers (FAS-hex2 set) (14).

We analyzed wild-type or mutant exon sequences from MLH1 and MSH2 genes in Table I with FAS-ESS software using a FAS-hex2 set (176 ESS hexamers), essentially as described previously (FAS-ESS: http://genes.mit.edu/fas-ess/) (14).

SIFT analysis

Sorting Intolerant from Tolerant (SIFT) tool (accessible at http://sift.jcvi.org/) was applied to detect deleterious missense mutations (45,46). SIFT compiles a dataset of functionally linked protein sequences by searching the protein database using a PSI-BLAST algorithm. Subsequently, it builds an alignment from the homologous sequences with the query sequence and scans all positions in the alignment, as well as calculating the probabilities for amino acids at that position. The substitution at each position with normalized probabilities of a tolerance index or SIFT score of <0.05 are predicted to be deleterious or intolerant, while those ≥0.05 are predicted to be tolerant (45). In this study, reference sequence (RefSeq) ID or GenInfo Identifier (GI) number and substitutions were provided as inputs to the SIFT blink program (46). A total of 52 missense mutations in the MSH2 gene (GI: 4557761) and 62 in the MLH1 gene (GI, 463989) were analyzed for identification of deleterious variants.

Results

Potential ESE/ESS analysis of the mutations in MLH1 and MSH2 genes

We analyzed wild-type or mutant exon sequences from MLH1 and MSH2 genes in Table I using SR protein score matrices and threshold values, essentially as described. Potential ESE motifs found in the mutations in the two genes are listed in Table I (Fig. 1). Some of the mutations may load in different potential ESE motifs. Of the 114 mutations analyzed, 47 (41.2%) mutations resulted in 68 ESE motif scores (24 SF2/ASF [IgM-BRCA1], 13 SC35, 19 SRp40 and 12 SRp55) being eliminated. However, 38 (33.3%) mutations created 45 ESE motif scores (12 SF2/ASF [IgM-BRCA1], 8 SC35, 14 SRp40 and 11 SRp55).

We analyzed wild-type or mutant exon sequences from MLH1 and MSH2 genes in Table I with FAS-ESS using the FAS-hex2 set (176 ESS hexamers), essentially as described previously. Potential ESS motifs found in the mutations in the two genes are listed in Table I (Fig. 2). Of the 114 mutations assessed, 9 (7.9%) mutations resulted in 13 ESS motif scores being eliminated. However, 17 (14.9%) mutations created 27 ESS motif scores.

Eliminating the potential ESE motif and creating the potential ESS motif have the same effect on exon exclusion. We named these mutations as potential ESR error mutations. In total, 56 (49.1%) mutations possessed a potential ESR error (Table II).

Table II

Potential ESR errors detected in the mutations of the two genes.

Table II

Potential ESR errors detected in the mutations of the two genes.

Total mutationsESE eliminatedESS createdESR errorTwo ESRs error
Total mutations114 (100.0%)47 (41.2%)17 (14.9%)56 (49.1%)25 (21.9%)
SIFT deleterious81 (71.1%)32 (28.1%)13 (11.4%)38 (33.3%)18 (15.8%)

[i] ESR error; mutations that have lost one ESE motif or gained one ESS motif. Two ESRs error; mutations that have eliminated at least two potential ESE motifs, or created at least two potential ESS motifs, or eliminated one or more potential ESE motifs and created one or more potential ESS motifs. ESR, exonic splicing regulator; ESE, exonic splicing enhancer; ESS, exonic splicing silencer.

Deleterious missense mutations predicted by the SIFT server

Eighty-one missense mutations (71.1%) were predicted to be deleterious with a tolerance index <0.05; the lower the tolerance score, the greater the functional consequence an amino acid residue substitution is expected to have (Table I). Additionally, 32 (28.1%) mutations were predicted to be deleterious with potential ESE motif losses, while 13 (11.4%) mutations were predicted to be deleterious with potential ESS motif gains. In total, 38 (33.3%) mutations were predicted to be deleterious with potential ESR errors (Table II).

Discussion

The incidence and mortality rates of gastrointestinal cancer are among the highest malignant tumors in East Asia. MMR genes MLH1 and MSH2 have been known to play an important role in the pathogenesis of gastrointestinal cancer. At present, the majority of databases contain annotation data that are primarily or exclusively derived from genomic DNA analysis, and the effect of a mutation on the mRNA or on the encoded protein is usually predicted from the primary sequence, rather than by experimentally determining the mRNA expression and splicing patterns. Therefore, the majority of reported disease-associated alleles of these genes are small insertions, deletions or splice-site mutations that result in protein truncation. Thus, only a small number of amino acid substitutions in either gene have been described as deleterious missense mutations, yet a very large number of different unclassified variant alleles are routinely encountered in clinical and research laboratories. It is therefore necessary to functionally define these unclassified variants as deleterious alleles, low-penetrance alleles or benign polymorphisms.

In this study, we selected 114 missense mutations of MSH2 and MLH1 genes detected from East Asian gastrointestinal cancer patients in published studies. The ethnic group included Chinese, Japanese and Korean individuals. The missense mutations contribute to certain forms of cancer susceptibility in East Asian populations, but it was unclear whether these were the definite pathogenic mutations in gastrointestinal cancer.

The consequences of splicing unclassified variants found in the MLH1 or the MSH2 genes may be studied directly at the patient RNA level. However, the number of variants that may be tested for splicing alterations using patient RNA is limited by the difficulty of obtaining blood samples suitable for RNA extraction. The bioinformatic tools, the ESE-finder and FAS-ESS, may enable prediction of the splicing defect of the mutations. These tools have already been used successfully to predict ESEs/ESSs and their disruption in a variety of genes, including ACF, BRCA1, BRCA2, FBN1, IGF1, PDHA1, SMN1, SMN2, TNFRSF5, CFTR, MlH1, MSH2, Tp53, MCAD and others (3,7,4752). Auclair et al conducted a systematic RNA screening of a series of 60 western patients who carried unrelated exonic or intronic mutations in the MLH1 or MSH2 genes (53). In addition, it was found that the potential correlation between aberrant splicing and prediction of ESE by the ESE-finder demonstrated a sensitivity of 80% and a specificity of 42%.

Under the conditions of the null hypothesis, there is no correlation between ESEs and mutations; the amount of ESE motif scores eliminated or created should be equal. However, in the present study, the amount of ESE losses (68) was 51.1% higher than ESE gains (45). This suggested that the mutations loaded in the potential ESE motifs were more likely to eliminate the ESE motif score, and that they affected gene splicing. Additionally, under the conditions of the null hypothesis, there is no correlation between ESSs and mutations; the amount of ESS motif scores eliminated or created should be equal. Conversely, in the present study, the amount of ESS gains (27) was 107.7% higher than the amount of ESS losses (13). This suggested that the mutations were more likely to create the ESS motif score and that they affected gene splicing, indicating that there is a strong association between missense mutations in MLH1 and MSH2 genes and ESE/ESS motifs. Some of the mutations should be splicing-related deleterious alleles.

As an upper limit for the estimate of the proportion of ESR-related mutations, we suggest that 56 (49.1%) mutations, which have lost ESE or gained ESS motifs, were deleterious for the reason that they disturbed functional splicing enhancers or or created functional splicing silencers, respectively. This approach was likely to overestimate the proportion of ESR-related pathogenic mutations. This is due to the fact that not all ESR motifs are true functional ESRs, and not all nucleotide substitutions in functional ESRs disturb their function.

According to previous studies, no extensive functional analysis was available for these mutations. We used the SIFT tool to functionally analyze the missense mutations. SIFT is a program that predicts the effect of amino acid substitutions on protein function, on the basis of sequence conservation during evolution and the nature of the amino acids substituted in a gene of interest. In total, 81 missense mutations (71.1%) were predicted to be deleterious with a tolerance index <0.05. Among them, 38 (33.3%) mutations were predicted to be deleterious and have at least one potential ESR error. Some of these may be pathogenic with exon exclusion.

Eliminating and creating the potential ESE motif has the same effect on exon exclusion. One mutation may eliminate one or more potential ESE motifs. The greater the number of potential ESE motifs eliminated, the more likely the mutation was to affect the ESE motifs. However, one mutation may create one or more potential ESS motifs. The greater the number of potential ESS motifs created, the more likely the mutation was to affect the ESS motifs. In total, 25 (21.9%) mutations eliminated at least two potential ESE motifs, or created at least two potential ESS motifs, or eliminated one or more potential ESE motifs and created one or more potential ESS motifs. These may be more likely to affect exon splicing. Among these, 18 (15.8%) mutations, c.1012G>A, c.1168C>T, c.1799C>T, c.1808A>G, c.2047G>A, c.2064G>A, c.2108C>A, c.2128G>T, c.2141C>T in MSH2; c.242C>T, c.318C>G, c.327T>G, c.332C>T, c.1186T>A, c.1561C>A, c.1907T>C, c.2059C>T, c.2263A>G in MLH1, were predicted to be deleterious in the SIFT analysis. These were the mutations that most likely affected exon splicing, and were denoted as ESR-relevant mutations. We proposed that some of these disrupted functional ESEs or created functional ESSs, leading to the creation of a misspliced message predicted to encode a truncated, non-functional protein. However, these data did not allow us to determine which of the SR protein/hnRNPs motifs were functional. Although it is unlikely that each motif was able to be recognized simultaneously, due to the overlap between them, it is possible that each motif was important in a different cell type, depending on the relative expression levels of SR protein/hnRNPs.

Several putative ESR sequences have been found in exons where they have been sought systematically, raising the possibility of functional redundancy. This may diminish the potential exon-skipping effect of a mutation in any one ESR. However, in cases where 3–10 putative ESE sequences occur within a single exon, a single ESE-disrupting base substitution may lead to efficient exon skipping. Fackenthal et al found that BRCA2 T2722R was a deleterious allele that caused BRCA2 exon 18 skipping (48), and Pagenstecher et al found a silent mutation MLH1 c.1731G>A caused MLH1 exon 15 skipping (54). However, a single ESS-creating base substitution may lead to efficient exon skipping. Oliveira et al found that POMGNT1 c.636C>T created a new ESS and caused POMGNT1 exon 7 skipping (55), and Raponi et al found that BRCA1 c.231G>T created a new ESS and caused BRCA1 exon 6 skipping (56). This suggests that, at least in certain cases, individual ESRs may be critical for splicing even when other ESRs are present in the same exon. However, the splice mutations of MLH1 and MSH2 have been underestimated. The strong correlation between missense mutations with splicing enhancer/silencer motifs found in this study also suggested that splicing-related mutations in the two genes may be relatively common. The computer predictions do not always correlate with in vivo splicing defects. The predictable ESR error mutations require experimental analysis for validation in a further study.

In conclusion, our results indicated that there is a strong correlation between missense mutations in MLH1 and MSH2 genes detected in East Asian gastrointestinal cancer patients and ESR motifs. In total, 38 (33.3%) mutations were predicted to be functionally deleterious and possess one potential ESR error, while 18 (15.8%) mutations were predicted to be functionally deleterious with two potential ESR errors. These may be more likely to affect exon splicing. To truly understand the molecular nature of mutations, splicing patterns should be compared between wild-type and mutant samples.

Acknowledgements

This study was supported by the National Natural Science Foundation of China (Grant Nos. 81270152, 81070273 and 30972535).

References

1 

Peltomäki P and Vasen HF: Mutations predisposing to hereditary nonpolyposis colorectal cancer: database and results of a collaborative study. The International Collaborative Group on hereditary nonpolyposis colorectal cancer. Gastroenterology. 113:1146–1158. 1997.

2 

Lynch HT and de la Chapelle A: Genetic susceptibility to non-polyposis colorectal cancer. J Med Genet. 36:801–818. 1999.

3 

Cartegni L, Chew SL and Krainer AR: Listening to silence and understanding nonsense: exonic mutations that affect splicing. Nat Rev Genet. 3:285–298. 2002.

4 

Pagani F and Baralle FE: Genomic variants in exons and introns: identifying the splicing spoilers. Nat Rev Genet. 5:389–396. 2004.

5 

Shapiro MB and Senapathy P: RNA splice junctions of different classes of eukaryotes: sequence statistics and functional implications in gene expression. Nucleic Acids Res. 15:7155–7174. 1987.

6 

Jurica MS and Moore MJ: Pre-mRNA splicing: awash in a sea of proteins. Mol Cell. 12:5–14. 2003.

7 

Liu HX, Zhang M and Krainer AR: Identification of functional exonic splicing enhancer motifs recognized by individual SR proteins. Genes Dev. 12:1998–2012. 1998.

8 

Blencowe BJ: Exonic splicing enhancers: mechanism of action, diversity and role in human genetic diseases. Trends Biochem Sci. 25:106–110. 2000.

9 

Hastings ML and Krainer AR: Pre-mRNA splicing in the new millennium. Curr Opin Cell Biol. 13:302–309. 2001.

10 

Zuo P and Maniatis T: The splicing factor U2AF35 mediates critical protein-protein interactions in constitutive and enhancer-dependent splicing. Genes Dev. 10:1356–1368. 1996.

11 

Kan JL and Green MR: Pre-mRNA splicing of IgM exons M1 and M2 isdirected by a juxtaposed splicing enhancer and inhibitor. Genes Dev. 13:462–471. 1999.

12 

Cartegni L, Wang J, Zhu Z, Zhang MQ and Krainer AR: ESE finder: a web resource to identify exonic splicing enhancers. Nucleic Acid Research. 31:3568–3571. 2003.

13 

Smith PJ, Zhang C, Wang J, Chew SL, Zhang MQ and Krainer AR: An increased specificity score matrix for the prediction of SF2/ASF-specific exonic splicing enhancers. Hum Mol Genet. 15:2490–2508. 2006.

14 

Wang Z, Rolish ME, Yeo G, Tung V, Mawson M and Burge CB: Systematic identification and analysis of exonic splicing silencers. Cell. 119:831–845. 2004.

15 

Cai Q, Sun MH, Fu G, et al: Mutation analysis of hMSH2 and hMLH1 genes in Chinese hereditary nonpolyposis colorectal cancer families. Zhonghua Bing Li Xue Za Zhi. 32:323–328. 2003.(In Chinese).

16 

Wang XL, Yuan Y, Zhang SZ, Cai SR, Huang YQ, Jiang Q and Zheng S: Clinical and genetic characteristics of Chinese hereditary nonpolyposis colorectal cancer families. World J Gastroenterol. 12:4074–4077. 2006.

17 

Nomura S, Sugano K, Kashiwabara H, et al: Enhanced detection of deleterious and other germline mutations of hMSH2 and hMLH1 in Japanese hereditary nonpolyposis colorectal cancer kindreds. Biochem Biophys Res Commun. 271:120–129. 2000.

18 

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. 25:503–510. 2001.

19 

Nakahara M, Yokozaki H, Yasui W, Dohi K and Tahara E: Identification of concurrent germline mutations in hMSH2 and/or hMLH1 in Japanese hereditary nonpolyposis colorectal cancer kindreds. Cancer Epidemiol Biomarkers Prev. 6:1057–1064. 1997.

20 

Park SJ, Lee KA, Park TS, Kim NK, Song J, Kim BY and Choi JR: A novel missense MSH2 gene mutation in a patient of a Korean family with hereditary nonpolyposis colorectal cancer. Cancer Genet Cytogenet. 182:136–139. 2008.

21 

Fan Y, Liu X, Zhang H, et al: Variations in exon 7 of the MSH2 gene and susceptibility to gastrointestinal cancer in a Chinese population. Cancer Genet Cytogenet. 170:121–128. 2006.

22 

Yan HL, Hao LQ, Jin HY, et al: Clinical features and mismatch repair genes analyses of Chinese suspected hereditary non-polyposis colorectal cancer: a cost-effective screening strategy proposal. Cancer Sci. 99:770–780. 2008.

23 

Leung SY, Chan TL, Chung LP, et al: Microsatellite instability and mutation of DNA mismatch repair genes in gliomas. Am J Pathol. 153:1181–1188. 1998.

24 

Wu MS, Lee CW, Shun CT, et al: Distinct clinicopathologic and genetic profiles in sporadic gastric cancer with different mutator phenotypes. Genes Chromosomes Cancer. 27:403–411. 2000.

25 

Kim YM, Choe CG, Cho SK, Jung IH, Chang WY and Cho M: Three novel germline mutations in MLH1 and MSH2 in families with Lynch syndrome living on Jeju island, Korea. BMB Rep. 43:693–697. 2010.

26 

Zhao C, Tang WZ, Gao F and Li W: Study on hMSH2 gene mutation in the carcinogenesis of sporadic colorectal carcinoma. Journal of Guangxi Medical University. 27:11–14. 2010.

27 

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. 75:334–345. 2009.

28 

Jin HY, Liu X, Li VK, et al: Detection of mismatch repair gene germline mutation carrier among Chinese population with colorectal cancer. BMC Cancer. 8:442008.

29 

Han HJ, Yuan Y, Ku JL, et al: Germline mutations of hMLH1 and hMSH2 genes in Korean hereditary nonpolyposis colorectal cancer. J Natl Cancer Inst. 88:1317–1319. 1996.

30 

Sheng JQ, Fu L, Sun ZQ, et al: Mismatch repair gene mutations in Chinese HNPCC patients. Cytogenet Genome Res. 122:22–27. 2008.

31 

Cui L, Jin HY, Cheng HY, Yan YD, Meng RG and Yu DH: Genetic detection of Chinese hereditary nonpolyposis colorectal cancer. World J Gastroenterol. 10:209–213. 2004.

32 

Furukawa T, Konishi F, Shitoh K, Kojima M, Nagai H and Tsukamoto T: Evaluation of screening strategy for detecting hereditary nonpolyposis colorectal carcinoma. Cancer. 94:911–920. 2002.

33 

Yuen ST, Chan TL, Ho JW, et al: Germline, somatic and epigenetic events underlying mismatch repair deficiency in colorectal and HNPCC-related cancers. Oncogene. 21:7585–7592. 2002.

34 

Zhang CH, He YL, Wang FJ, et al: Detection of hMSH2 and hMLH1 mutations in Chinese hereditary non-polyposis colorectal cancer kindreds. World J Gastroenterol. 14:298–302. 2008.

35 

Zhang Y, Liu X, Fan Y, et al: Germline mutations and polymorphic variants in MMR, E-cadherin and MYH genes associated with familial gastric cancer in Jiangsu of China. Int J Cancer. 119:2592–2596. 2006.

36 

Yuan Y, Han HJ, Zheng S and Park JG: Germline mutations of hMLH1 and hMSH2 genes in patients with suspected hereditary nonpolyposis colorectal cancer and sporadic early-onset colorectal cancer. Dis Colon Rectum. 41:434–440. 1998.

37 

Yoon SN, Ku JL, Shin YK, et al: Hereditary nonpolyposis colorectal cancer in endometrial cancer patients. Int J Cancer. 122:1077–1081. 2008.

38 

Sinn DH, Chang DK, Kim YH, et al: Effectiveness of each Bethesda marker in defining microsatellite instability when screening for Lynch syndrome. Hepatogastroenterology. 56:672–676. 2009.

39 

Shin YK, Heo SC, Shin JH, et al: Germline mutations in MLH1, MSH2 and MSH6 in Korean hereditary non-polyposis colorectal cancer families. Hum Mutat. 24:3512004.

40 

Zhang XM, Li JT, Zhu M, Wu XL, Gao P, Zhou P and Wang YP: Study on the relationship between genetic polymorphism Val384Asp in hMLH1 gene and the risk of four different carcinomas. Zhonghua Liu Xing Bing Xue Za Zhi. 25:978–981. 2004.(In Chinese).

41 

Han HJ, Maruyama M, Baba S, Park JG and Nakamura Y: Genomic structure of human mismatch repair gene, hMLH1, and its mutation analysis in patients with hereditary non-polyposis colorectal cancer (HNPCC). Hum Mol Genet. 4:237–242. 1995.

42 

Wang CF, Zhou XY, Sun MH, et al: Two novel germline mutations of MLH1 in hereditary nonpolyposis colorectal cancer family. Zhonghua Bing Li Xue Za Zhi. 35:68–72. 2006.(In Chinese).

43 

Sheng JQ, Chan TL, Chan YW, et al: Microsatellite instability and novel mismatch repair gene mutations in northern Chinese population with hereditary non-polyposis colorectal cancer. Chin J Dig Dis. 7:197–205. 2006.

44 

Wei W, Liu F, Liu L, et al: Distinct mutations in MLH1 and MSH2 genes in hereditary non-polyposis colorectal cancer (HNPCC) families from China. BMB Rep. 44:317–322. 2011.

45 

Ng PC and Henikoff S: Predicting deleterious amino acid substitutions. Genome Res. 11:863–874. 2001.

46 

Kumar P, Henikoff S and Ng PC: Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc. 4:1073–1082. 2009.

47 

Liu HX, Cartegni L, Zhang MQ and Krainer AR: A mechanism for exon skipping caused by nonsense or missense mutations in BRCA1 and other genes. Nat Genet. 27:55–58. 2001.

48 

Fackenthal JD, Cartegni L, Krainer AR and Olopade OI: BRCA2 T2722R is a deleterious allele that causes exon skipping. Am J Hum Genet. 71:625–631. 2002.

49 

Gorlov IP, Gorlova OY, Frazier ML and Amos CI: Missense mutations in hMLH1 and hMSH2 are associated with exonic splicing enhancers. Am J Hum Genet. 73:1157–1161. 2003.

50 

Gorlov IP, Gorlova OY, Frazier ML and Amos CI: Missense mutations in cancer suppressor gene TP53 are colocalized with exonic splicing enhancers (ESEs). Mutat Res. 554:175–183. 2004.

51 

Nielsen KB, Sørensen S, Cartegni L, et al: Seemingly neutral polymorphic variants may confer immunity to splicing-inactivating mutations: a synonymous SNP in exon 5 of MCAD protects from deleterious mutations in a flanking exonic splicing enhancer. Am J Hum Genet. 80:416–432. 2007.

52 

Cartegni L and Krainer AR: Disruption of an SF2/ASF dependent exonic splicing enhancer in SMN2 causes spinal muscular atrophy in the absence of SMN1. Nat Genet. 30:377–384. 2002.

53 

Auclair J, Busine MP, Navarro C, et al: Systematic mRNA analysis for the effect of MLH1 and MSH2 missense and silent mutations on aberrant splicing. Hum Mutat. 27:145–154. 2006.

54 

Pagenstecher C, Wehner M, Friedl W, et al: Aberrant splicing in MLH1 and MSH2 due to exonic and intronic variants. Hum Genet. 119:9–22. 2006.

55 

Oliveira J, Soares-Silva I, Fokkema I, et al: Novel synonymous substitution in POMGNT1 promotes exon skipping in a patient with congenital muscular dystrophy. J Hum Genet. 53:565–572. 2008.

56 

Raponi M, Kralovicova J, Copson E, et al: Prediction of single-nucleotide substitutions that result in exon skipping: identification of a splicing silencer in BRCA1 exon 6. Hum Mutat. 32:436–444. 2011.

Journal Cover

May 2013
Volume 5 Issue 5

Print ISSN: 1792-1074
Online ISSN:1792-1082

2013 Impact Factor: 0.987
Ranked #149/202 Oncology
(total number of cites)

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation