Abstract
The clinical features of sporadic mismatch repair deficiency (MMRd) and Lynch syndrome (LS) in Japanese patients with endometrial cancer (EC) were examined by evaluating the prevalence and prognostic factors of LS and sporadic MMRd in patients with EC. Targeted sequencing of five LS susceptibility genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) was carried out in 443 patients with EC who were pathologically diagnosed with EC at the National Cancer Center Hospital between 2011 and 2018. Pathogenic variants in these genes were detected in 16 patients (3.7%). Immunohistochemistry for MMR proteins was undertaken in 337 of the 433 (77.9%) EC patients, and 91 patients (27.0%) showed absent expression of at least one MMR protein. The 13 cases of LS with MMR protein loss (93.8%) showed a favorable prognosis with a 5‐year overall survival (OS) rate of 100%, although there was no statistically significant difference between this group and the sporadic MMRd group (p = 0.27). In the MMRd without LS group, the 5‐year OS rate was significantly worse in seven patients with an aberrant p53 expression pattern than in those with p53 WT (53.6% vs. 93.9%, log‐rank test; p = 0.0016). These results suggest that p53 abnormalities and pathogenic germline variants in MMR genes could be potential biomarkers for the molecular classification of EC with MMRd.
Keywords: endometrial cancer, immunohistochemistry, Lynch syndrome, mismatch repair deficiency, MLH1 promoter methylation, TP53
In this study, 3.7% of patients with Lynch syndrome were detected in our cohort. Patients with Lynch syndrome showed a favorable prognosis with a 5‐year overall survival rate of 100% despite the dominance of serous carcinoma and mixed carcinoma molecular subtypes in this group compared with the DNA mismatch repair (MMR) deficiency without Lynch syndrome and proficient MMR groups. For patients with MMR deficiency without Lynch syndrome, aberrant expression of p53 (overexpression or complete absence) was independently correlated with worse clinical outcomes.

1. INTRODUCTION
Lynch syndrome (LS), a common inherited disorder, 1 is caused by pathogenic variants of DNA mismatch repair (MMR)‐related genes such as MLH1, MSH2, MSH6, PMS2, and EPCAM. 2 The MMR system is responsible for identifying and repairing errors generated during DNA replication. Tumors that develop in LS carriers show high levels of microsatellite instability, which leads to the accumulation of large numbers of somatic mutations; the most common mutations are frameshift insertions/deletions within microsatellite loci. Carriers with pathogenic variants are at an increased risk for various malignancies, 3 and colorectal cancer and endometrial cancer (EC) are the most commonly associated tumors. 4 , 5 Endometrial cancer is often the sentinel cancer in women with LS, 6 and a diagnosis of LS at the time of EC diagnosis promotes earlier colorectal cancer surveillance, resulting in better survival benefits. 7 Therefore, diagnosing LS in EC patients is essential for the clinical management of patients.
In the classical methods for diagnosing LS, high‐risk individuals are identified by age, cancer history, and family cancer history according to the Amsterdam II criteria 8 or revised Bethesda guidelines. 9 After the preselection process, tumor testing, including immunohistochemistry (IHC) for MMR protein loss, microsatellite instability testing, or MLH1 promoter methylation testing is used as triage for germline testing to identify pathogenic variants in MMR genes. Universal screening for LS in patients with EC is widely accepted by experts and specialist societies. 10 The tumor‐based testing strategy is more sensitive than the classical strategy. 11 The use of triage systems in clinical practice has limited germline testing to a subset of patients with a strong suspicion of LS despite the fact that it is an essential method for diagnosing LS.
DNA MMR deficiency (MMRd) is not an exclusive feature of LS. Approximately 70% of MMRd ECs show somatic inactivation of MLH1 by promoter hypermethylation. 12 , 13 Cases without MLH1 promoter hypermethylation and no germline pathogenic variants in MMR genes are considered sporadic due to biallelic somatic MMR gene inactivation. 14 Although the clinicopathologic features and prognosis of colorectal cancers with LS and sporadic MMRd have been compared, 15 , 16 there are few studies investigating the prevalence and prognosis of LS and sporadic MMRd in selected EC populations after tumor triage. 17 , 18
The proportion of EC patients with LS varies widely among published studies, with an average of approximately 3%. 19 , 20 The screening criteria for EC patients with LS are controversial. Certain guidelines or studies recommend screening according to risk factors including age and family history. 21 , 22 However, universal screening is recommended by an increasing number of clinicians and guidelines, 23 , 24 , 25 including the Manchester International Consensus Group 10 and NICE guidelines in the UK. 26 A universal screening method for Japanese patients with EC remains to be established.
To determine the proportion and prognosis of EC patients with LS, targeted sequencing of five LS susceptibility genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) was carried out in 443 Japanese patients with EC. The clinicopathologic features of LS, MMRd without LS (non‐LS MMRd), and proficient MMR (pMMR) were compared, and prognostic factors were identified for each group.
2. MATERIALS AND METHODS
2.1. Study cohorts
The case study analyzed 433 consecutive patients with EC. Patients who had a pathological diagnosis of EC between 2011 and 2018 at the National Cancer Center Hospital and had available blood DNA for sequencing were enrolled. The Institutional Review Board of the National Cancer Center Research Institute approved this study (2015‐278 and 2017‐331). Informed consent for the use of samples in research was obtained from patients on their first visit to our hospital. The data obtained using samples collected after participants provided informed consent are summarized on the hospital's website. Patients were free to revoke the presumed consent at any time. Only samples from patients who did not revoke their consent were included in the study. Clinical data, including age, cancer stage (as defined by the International Federation of Gynecology and Obstetrics in 2008 16 ), pathological factors, and survival time after primary surgery, were retrospectively obtained for each patient. Overall survival (OS) was calculated from the date of primary surgery to the date of death from any cause. At least two gynecological pathologists confirmed the pathological diagnoses according to the 2020 WHO classification of female genital tumors. 27
2.2. Classification and detection of germline pathogenic and likely pathogenic variants
Five established LS predisposition genes (MLH1 [refGene: NM_001258271], MSH2 [refGene: NM_000251], MSH6 [refGene: NM_000179], PMS2 [refGene: NM_000535], and EPCAM [refGene: NM_002354]) were analyzed in all patients. 4 Variants were described according to the HGVS (Human Genome Variation Society) nomenclature guidelines. The experimental methods were described previously. 28 , 29 Genome mapping was undertaken using Parabricks version 3.1.3 (Nvidia). 30 The GRCh38 reference genome sequence was used. The pipeline used in this study implemented algorithms equivalent to those of BWA (version 0.7.15) 31 and GATK (version 4.1.0). The mapped data were outputted in BAM format. 32 Germline variants were called using GATK HaplotypeCaller.
The clinical significance of each variant was determined using the association results, known clinical significance in ClinVar, population data, computational data, and functional data according to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines. Germline variants were considered pathogenic if they met the following criteria: (1) global minor allele frequency <0.005 in ExAC 33 and/or Tohoku Medical Megabank Organization (ToMMo) 34 ; (2) null variants (nonsense, frameshift indel, and splice‐site variants) and missense variants classified as “pathogenic” or “likely pathogenic” in the ClinVar database 35 (https://www.ncbi.nlm.nih.gov/clinvar/); and (3) high‐impact variants, such as stop‐gain, stop‐loss, and start‐loss as defined by SnpEff version 4.3. 36 Variants that met these criteria were examined by an expert panel, which decided their final status. Pathogenic or likely pathogenic variants were further validated by Sanger sequencing.
2.3. Immunohistochemical analysis and interpretation
All IHC tests, including the detection of p53 (DO7, prediluted; Dako), PMS2 (EP51, prediluted; Dako/Agilent), MSH6 (EP49, prediluted; Dako/Agilent), MLH1 (ES05, prediluted; Dako/Agilent), and MSH2 (FE11, prediluted; Dako/Agilent) were carried out as described previously 37 , 38 , 39 in cases where tumor specimens were available at our institution. The term “aberrant p53 staining pattern (p53abn)” refers to either a strong and diffuse nuclear staining pattern (>80% of carcinoma cells) or an entirely negative (“null pattern”) staining pattern of carcinoma cells. Because IHC for PMS2 and MSH6 can be used instead of the four Ab panel (MLH1, MSH2, MSH6, and PMS2) for MMRd screening, 40 in this study, the MMRd status was first defined as the complete loss of nuclear staining for PMS2 or MSH6 proteins. After this process, IHC for MLH1 and MSH2 was added in cases of PMS2 loss and MSH6 loss, respectively. Internal positive controls with intact nuclear staining included the adjacent normal mucosa, stromal cells, and inflammatory cells.
2.4. DNA methylation analysis
Cases with MLH1 protein loss were subjected to DNA methylation analysis of the MLH1 promoter region using an Infinium HumanMethylationEPIC BeadChip array (Illumina), as previously reported. 41 , 42 The DNA methylation level of each individual probe was calculated as a β‐value that ranged from 0 (unmethylated) to 1 (fully methylated).
Region‐specific DNA methylation analysis was undertaken by bisulfite‐pyrosequencing using PyroMark Q24 Advanced (Qiagen). 43 Genomic DNA (100–1000 ng) was modified by sodium bisulfite using the EZ DNA Methylation Kit (Zymo Research Corp.). Ten microliters of modified DNA was used to amplify the target CpG site using biotinylated primers. The primer sequences for the target CpG sites and the PCR conditions are listed in Table S1. 44 The PCR product was annealed to 0.2 μM of the pyrosequencing primer, and pyrosequencing was carried out using the PyroMark Q24 Advanced system (Qiagen). The methylation level was obtained using PSQ Assay Design software (Qiagen). The corrected methylation level was calculated using the cancer cell fraction in the comprehensive methylation analysis and pyrosequencing. The cut‐off for the corrected methylation level was 0.6 in this study. Genomic regions were aligned according to the human reference genome hg38.
2.5. Statistical analysis
R 3.3.1 (R Foundation) and JMP version 8.0.1 (SAS Institute) were used for statistical analyses. The association between MMR status and clinicopathologic factors was analyzed using Fisher's exact test and R software. Cumulative survival was calculated using the Kaplan–Meier method, and survival was compared between groups using the log‐rank test. The cut‐off p value for statistical significance was <0.05. The effect of variables on OS was determined using univariate and multivariate analyses and the Cox proportional hazards model using JMP software. The analyses classified pathologic TNM stages as I–II or III–IV.
3. RESULTS
3.1. Germline analysis of 433 patients with EC
The flowchart of the detection process for cases with LS or MMRd is shown in Figure 1. Sixteen pathogenic variants were identified in 433 patients (3.7%) as follows: three in MLH1, three in MSH2, nine in MSH6, one in PMS2, and none in EPCAM. The characteristics of the 16 patients with LS are summarized in Table 1. The mean age at diagnosis in patients with LS was 55 (28–77) years; the mean age was lower in the groups with pathogenic variants of MLH1 or MSH2 (45 and 43 years, respectively) than in those with other pathogenic variants and non‐LS cases (Table 2). Five of six patients (83%) carrying a pathogenic variant in MLH1 or MSH2 had a family history based on the revised Bethesda guidelines. Patients with pathogenic variants in MSH6 were approximately 50 years or older at the time of diagnosis, and more than 50% of patients with MSH6 mutation had no family history (Table 1). Of 16 patients with LS, four had a history of colorectal cancer and two were diagnosed with other cancers (colorectal cancer and gastric cancer) during the follow‐up period.
FIGURE 1.

Consort diagram showing the detection process for cases of endometrial cancer with Lynch syndrome or mismatch repair (MMR) deficiency. IHC, immunohistochemistry.
TABLE 1.
Characteristics of 16 Japanese patients with Lynch syndrome
| No. | Age (years) | BMI | Gene | HGVS.c | HGVS.p | Effect | Family history | IHC | Stage | Histology | IHC p53 status | Status |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 45 | 27.9 | MLH1 | c.519dupT | p.G174Wfs*18 | Frameshift variant | + | MMRd | IIIC | EMG1 | WT | NED |
| 2 | 28 | 17.7 | MLH1 | c.G677A | p.R226Q | Missense variant | + | MMRd | IIIC | Dediff | Diffuse | NED |
| 3 | 53 | 26.2 | MLH1 | c.C350T | p.T117M | Missense variant | − | N/A | IA | EMG1 | WT | NED |
| 4 | 72 | 18.7 | MSH2 | c.1441_1442insTAAG | p.R482Sfs*7 | Frameshift variant | + | MMRd | IVB | Serous | WT | AWD |
| 5 | 42 | 21.6 | MSH2 | c.C2038T | p.R680X | Stop gained | + | MMRd | IA | EMG2 | WT | NED |
| 6 | 43 | 23.9 | MSH2 | c.C1215A | p.Y405X | Stop gained | + | N/A | IA | EMG2 | WT | LOF |
| 7 | 63 | 19.7 | MSH6 | c.3514dupA | p.R1172Kfs*5 | Frameshift variant | + | MMRd | IA | Serous | Diffuse | NED |
| 8 | 56 | 17 | MSH6 | c.C2082A | p.C694X | Stop gained | + | MMRd | IVB | Mix (serous + EMG1) | Diffuse | NED |
| 9 | 52 | 20.4 | MSH6 | c.3254dupC | p.F1088Lfs*4 | Frameshift variant | − | MMRd | IB | EMG1 | WT | NED |
| 10 | 55 | 20.9 | MSH6 | c.3556+1G>T | N/A | Splice acceptor variant | + | MMRd | IIIA | EMG1 | WT | NED |
| 11 | 55 | 21.3 | MSH6 | c.2909delG | p.I972Lfs*24 | Frameshift variant | − | MMRd | IA | Mix (serous + EMG1) | WT | NED |
| 12 | 60 | 20.2 | MSH6 | c.1247dupT | p.K417fs*0 | Frameshift variant | − | MMRd | IA | Mix (serous + EM) | WT | NED |
| 13 | 77 | 22.1 | MSH6 | c.440delT | p.L148fs*0 | Frameshift variant | − | pMMR | IB | Carcinosarcoma | WT | DOD |
| 14 | 71 | 27.7 | MSH6 | c.C2872T | p.Q958X | Stop gained | − | MMRd | IA | EMG1 | WT | NED |
| 15 | 48 | 21.6 | MSH6 | c.4001delG | p.E1335Kfs*9 | Frameshift variant | + | MMRd | IA | EMG2 | WT | NED |
| 16 | 62 | 23.2 | PMS2 | c.251‐2A>G | N/A | Splice acceptor variant | − | MMRd | IIIC | Mix (serous + EMG2) | WT | NED |
Abbreviations: AWD, alive with disease; BMI, body mass index; Dediff, dedifferentiated adenocarcinoma; DOD, dead of disease; EM, endometrioid carcinoma; EMG1/2, endometrioid adenocarcinoma, grade 1/2; HGVS, Human Genome Variation Society; IHC, immunohistochemistry; LOF, loss of follow‐up; MMRd, mismatch repair deficiency; N/A, not applicable; NED, no evidence of disease; pMMR, proficient mismatch repair.
TABLE 2.
Clinicopathologic characteristics of 339 patients with Lynch syndrome (LS), non‐LS mismatch repair deficiency (MMRd), and proficient mismatch repair (pMMR) using tumor specimens
| Category | LS | Non‐LS MMRd | pMMR | p value |
|---|---|---|---|---|
| Number of patients | 14 | 78 | 245 | – |
| Age, years; median (range) | 55 (28–77) | 56 (44–89) | 58 (28–84) | 0.95 |
| BMI, median (range) | 21.1 (17–27.9) | 21.9 (15.6–41.1) | 22.6 (14.9–40.1) | 0.23 |
| FIGO stage (2008) | 0.58 | |||
| I | 8 (57.1) | 57 (73) | 167 (68) | – |
| II | 0 (0.0) | 6 (7.7) | 21 (8.6) | – |
| III | 4 (28.6) | 10 (12.8) | 35 (14.3) | – |
| IV | 2 (14.3) | 5 (6.4) | 16 (6.5) | – |
| Unknown | – | – | 6 (2.5) | – |
| Histology | <0.001 | |||
| Endometrioid (G1, G2) | 6 (42.9) | 50 (64.1) | 172 (70.2) | – |
| Endometrioid (G3) | 0 (0.0) | 20 (25.6) | 12 (4.9) | – |
| Serous | 2 (14.3) | 2 (2.6) | 17 (6.9) | – |
| Clear | 0 (0.0) | 0 (0.0) | 5 (2.0) | – |
| Mixed | 4 (28.6) | 3 (3.8) | 2 (0.8) | – |
| Carcinosarcoma | 1 (7.1) | 2 (2.6) | 31 (12.7) | – |
| Others | 1 (7.1) | 1 (1.3) | 3 (1.2) | – |
Note: Data are shown as n (%) unless otherwise indicated.
Abbreviation: BMI, body mass index.
3.2. Immunohistochemical analysis
Of 433 participants, formalin‐fixed, paraffin‐embedded specimens for IHC were available in 337 (77.9%) patients. In the IHC analysis of these cases, 91 patients (27.0%) showed loss of expression of at least one of the MMR proteins. Of the 16 patients with germline pathogenic variants, 14 were analyzed by IHC staining. All cases showed MMR protein loss except for one case of stage IB carcinosarcoma (Table 1). Sixty‐five of 91 (71.4%) patients with the MMRd phenotype showed MLH1 loss. Two cases of MLH1 loss had concurrent loss of MLH1, PMS2, and MSH6. Excluding MLH1, loss of MSH2 was the most common alteration (13.2%), followed by loss of MSH6 (12.1%) and PMS2 (3.3%) (Table 3). Of the 91 patients with MMR protein loss, 10 patients showed p53abn. Seven of 10 patients with p53abn had no germline pathogenic variants.
TABLE 3.
Patterns of mismatch repair (MMR) protein loss in patients with Lynch syndrome (LS) and non‐LS MMR deficiency (MMRd)
| Patterns of MMR protein loss | Total (n = 91) | LS (n = 13) | Non‐LS MMRd (n = 78) |
|---|---|---|---|
| MLH1 (MLH1 and PMS2) | 63 (69.2%) | 2 | 61 |
| MSH2 (MSH2 and MSH6) | 12 (13.2%) | 3 | 9 |
| MSH6 (MSH6 only) | 11 (12.1%) | 6 | 5 |
| PMS2 (PMS2 only) | 3 (3.3%) | 1 | 2 |
| MLH1, PMS2, and MSH6 | 2 (2.2%) | 1 | 1 |
3.3. DNA methylation analysis
MLH1 promoter methylation levels were analyzed by pyrosequencing in 65 samples with negative MLH1 protein expression on IHC. Eighteen samples were excluded because of poor DNA quality, and pyrosequencing data were obtained for 47 of the 65 initial and additional samples. Of the 47 samples, four were excluded because the cancer cell fraction was low (10%). Of the remaining 43 samples, four were excluded because of low copy number. Finally, 39 samples underwent methylation analysis, and 32 (82.1%) had methylation levels >0.6 by pyrosequencing.
3.4. Clinicopathologic factors of the LS, non‐LS MMRd, and pMMR groups
The characteristics of patients in the LS, non‐LS MMRd, and pMMR groups are shown in Table 2. There were significant differences in histology, whereas no differences in age, body mass index, or FIGO 2008 stage were observed between the three groups. Of the 16 LS cases, two (12.5%) were serous carcinoma and four (25%) were mixed carcinoma (serous and endometrioid grade 1/2 components); these tumors occurred at a significantly higher rate in the LS group than in the non‐LS MMRd and pMMR groups. By contrast, endometrioid adenocarcinoma grade 3 was the dominant histological type in the non‐LS MMRd group (25.6%), and carcinosarcoma was the dominant tumor in the pMMR group (12.7%). The median follow‐up period of all patients was 60 months (range, 2–113 months).
3.5. Correlation among clinical outcomes and groups with LS, non‐LS MMRd, and pMMR
The 13 cases of LS with MMR protein loss showed favorable prognoses, with a 5‐year OS rate of 100%. However, there were no significant differences in 5‐year OS between the LS and non‐LS MMRd groups (100% vs. 89.5%, log‐rank test; p = 0.27). In addition, the survival curves of the non‐LS MMRd and pMMR groups were almost the same and the 5‐year OS rates were 89.5% and 89.2%, respectively (Figure 2). In the non‐LS MMRd group, the 5‐year OS rate was significantly worse in seven patients with p53abn than in patients with p53 WT tumors (53.6% vs. 93.9%, log‐rank test; p = 0.0016) (Figure 3A). Previously reported prognostic factors, such as pathological stage (I–II vs. III–IV), histology (endometrioid vs. non‐endometrioid), and lymphovascular invasion, were used as adjustment factors in the Cox proportional hazards analysis. The p53abn molecular subtype was correlated with worse OS in patients with non‐LS MMRd (hazard ratio = 8.27, p = 0.02; Table 4). By contrast, there was no correlation between histology and OS (log‐rank test; p = 0.08) (Figure 3B). In terms of the pMMR group, the 5‐year OS rate was significantly worse in 37 patients with p53abn than in patients with p53 WT tumors (68.8% vs. 94.7%, log‐rank test; p = 0.0007) (Figure S1A). However, unlike the non‐LS MMRd group, there was a strong correlation between p53 status and histological type, with histological type being the most potent prognostic factor. The 5‐year OS rate of patients with nonendometrioid carcinoma was significantly worse than that of patients with endometrioid carcinoma (56.6% vs. 98.7%, log‐rank test; p < 0.0001) (Figure S1B).
FIGURE 2.

Kaplan–Meier survival curves for all stages of endometrial cancer in Japanese patients. Overall survival of patients with Lynch syndrome (LS; red line), non‐LS mismatch repair deficiency (MMRd; blue line), and proficient mismatch repair (pMMR; green line).
FIGURE 3.

Kaplan–Meier survival curves of Japanese patients with endometrial cancer according to (A) p53 status and (B) histology in patients with mismatch repair deficiency without Lynch syndrome (non‐LS MMRd). (A) Overall survival of patients with p53 WT (red line) and p53 aberrant expression pattern (diffuse or null) (blue line). (B) Overall survival of endometrioid adenocarcinoma (red line) and nonendometrioid adenocarcinoma (blue line) in patients with non‐LS MMRd.
TABLE 4.
Correlation between mismatch repair deficiency without Lynch syndrome (non‐LS MMRd) and overall survival in patients with non‐LS MMRd
| Variable | n | Univariate | Multivariate | ||
|---|---|---|---|---|---|
| HR (95% CI) | p value | HR (95% CI) | p value | ||
| Stage (I, II vs. IIII, IV) | 63/15 | 8.28 (1.77–38.71) | 0.0087 | 5.28 (0.72–38.43) | 0.090 |
| Histology (EM vs. non‐EM) | 70/8 | 3.87 (0.74–20.13) | 0.15 | 1.37 (0.13–14.21) | 0.79 |
| p53 status (absence vs. presence) | 71/7 | 7.69 (1.72–34.47) | 0.018 | 8.27 (1.53–44.60) | 0.020 |
| Lymphovascular invasion (absence vs. presence) | 31/37 | 6.45 (1.34–55.51) | 0.046 | 3.37 (0.32–35.68) | 0.28 |
Abbreviations: CI, confidence interval; EM, endometrioid carcinoma; HR, hazard ratio.
4. DISCUSSION
Lynch syndrome was detected in 3.7% of the patients in the cohort. Patients with LS had a favorable prognosis, with a 5‐year OS rate of 100%. Serous carcinoma and mixed carcinoma were the predominant histological types in LS compared with the non‐LS MMRd and pMMR groups. In patients with non‐LS MMRd, aberrant p53 expression (overexpression or complete absence) was independently correlated with worse clinical outcomes.
The frequency of LS (3.7%) identified in this study did not differ significantly from that reported previously. 20 However, not all cases with LS showed MMRd (13 of 14 cases). We investigated the prognostic value of LS compared with non‐LS MMRd. The present findings are consistent with those of previous studies showing that patients with LS tend to have a better prognosis and a higher risk for second cancers than patients with non‐LS MMRd. 17 , 18 The prognosis of patients with LS is considered favorable regardless of race. The OS of patients with EC with MMRd, including a large number of cases with MLH1 promoter hypermethylation, is worse than that of patients with EC with POLE mutation in the molecular classification of The Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE). 39 , 45 , 46 In this study, survival analysis showed that patients with LS had better OS than patients with non‐LS MMRd, as in “POLE mutated endometrial cancer”. In this study, the categorization of patients with LS into the “true MMRd group” remained unclear because we did not evaluate POLE mutation status. However, a previous study showed that the proportion of patients with POLE mutation and MMRd as a dual classifier is extremely low at 0.9%. 47 Thus, most patients with LS were categorized into the MMRd group. Similar results were reported in a study that showed better relapse‐free survival in 36 patients with LS than in 275 cases with MLH1 promoter hypermethylation. 17 Survival analyses of patients with colorectal cancer show that patients with LS have better OS than sporadic MMRd patients or MLH1 promoter methylated MMRd patients. 16 , 48 In this study, non‐LS MMRd patients were not divided into two groups, namely, methylated MMRd and other MMRd because of inconclusive results in eight cases with a low pathological cancer cell fraction or low copy number, which made it difficult to determine whether the methylation level was truly <0.6 or the results were due to poor sample quality. Further studies including subgroup analysis of EC cases with non‐LS MMRd are needed.
In the present study, patients with p53abn had worse OS than patients with p53 WT in the non‐LS MMRd group. Endometrial cancers with the double feature p53abn and MMRd were classified into the upstream branching group, MMRd, as previously reported in the ProMisE classification. 49 However, in this study, non‐LS MMRd patients with p53abn had a significantly poorer clinical outcome than those with p53 WT (53.6% vs. 93.9%, log‐rank test; p = 0.0016). These results indicated that ECs with both MMR‐d and p53abn may be classified into the single‐classifier p53abn group.
Regarding histology, serous carcinoma and mixed carcinoma (serous and endometrioid grade 1/2 components) were statistically significantly dominant in patients with LS despite showing a favorable prognosis. In a previous study, 50% of mixed serous and endometrioid grade 1/2 component cases showed MMRd and LS. 50 Conlon et al. reported that intratumoral morphological heterogeneity is prominent in MMRd cancers, and such cases have at times been categorized as having a serous carcinoma component because of the level of cytological atypia present. 51 The present data support these previous reports, and histology in patients with MMRd was not correlated with clinical outcomes.
This study has several limitations. First, this was a single‐center study with a retrospective design. However, in comparison with the general Japanese cases of EC in the patient annual report for 2018, 52 our cohort is considered nearly equivalent in terms of the proportion of patients at each stage and with each histology. Therefore, the clinical features of sporadic MMRd and LS in this study are valuable standard Japanese data. Second, the sample size was small. Only seven cases (9%) of non‐LS MMRd with p53abn were analyzed, and the role of p53abn in predicting an unfavorable prognosis may be relatively minor. Further studies are needed to validate the effect of p53 status in non‐LS MMRd patients.
Considering the favorable prognosis of LS with MMRd and the risk of developing a second cancer, genetic testing of EC patients with MMRd is important to design personalized treatments and to ensure surveillance for second cancers. Pathogenic variants in LS‐related genes may be prognostic and predictive biomarkers. The present results indicate that the double/dual classifier EC with both MMR‐d and p53abn may be categorized as the single‐classifier p53abn in the ProMisE classification.
AUTHOR CONTRIBUTIONS
Mayumi Kobayashi Kato: Data curation; investigation; writing – original draft. Erisa Fujii: Data curation; investigation; writing – review and editing. Yuka Asami: Data curation; investigation; writing – review and editing. Yukihide Momozawa: Funding acquisition; supervision; writing – review and editing. Kengo Hiranuma: Data curation; investigation; writing – review and editing. Masaaki Komatsu: Funding acquisition; writing – review and editing. Ryuji Hamamoto: Funding acquisition; supervision; writing – review and editing. Takahiro Ebata: Formal analysis; methodology; writing – review and editing. Koji Matsumoto: Supervision; writing – review and editing. Mitsuya Ishikawa: Supervision; writing – review and editing. Takashi Kohno: Project administration; resources; supervision; writing – review and editing. Tomoyasu Kato: Supervision; writing – review and editing. Hiroshi Yoshida: Data curation; funding acquisition; project administration; supervision; writing – review and editing. Kouya Shiraishi: Conceptualization; project administration; supervision; writing – review and editing.
FUNDING INFORMATION
This work was supported by the Japan Agency for Medical Research and Development (AMED) (20ck0106554h0001 and 23ama221520h0001), the Grant‐in‐Aid for Young Scientists (B) Number 20K18207 and 19K16572, Grant‐in‐Aid for Scientific Research (B) 20H03695, Grant‐in‐Aid for Scientific Research (C) Number 20K09636, BRIDGE (programs for bridging the gap between R&D and the ideal society (Society 5.0) and generating economic and social value), and National Cancer Center Research and Development Fund (2022‐A‐20, 2023‐J‐2, NCC Biobank, and NCC Core Facility).
CONFLICT OF INTEREST STATEMENT
Dr. Takashi Kohno and Dr. Ryuji Hamamoto are associate editors of Cancer Science. The other authors have no conflict of interest.
ETHICS STATEMENT
Approval of the research protocol by an institutional review board: The Institutional Review Board of the National Cancer Center Research Institute approved this study.
Informed consent: All patients provided written informed consent.
Registry and registration no. of the study/trial: N/A.
Animal studies: N/A.
Supporting information
Figure S1.
Table S1.
ACKNOWLEDGMENTS
The authors thank Hitoshi Ichikawa, Maiko Matsuda, Yoko Shimada, Sachiyo Mitani, and other physicians and staff members at the National Cancer Center and other hospitals for their assistance and support. We thank BioEdit Ltd for assistance with English language editing.
Kato MK, Fujii E, Asami Y, et al. Clinical features and impact of p53 status on sporadic mismatch repair deficiency and Lynch syndrome in uterine cancer. Cancer Sci. 2024;115:1646‐1655. doi: 10.1111/cas.16121
Contributor Information
Hiroshi Yoshida, Email: hiroyosh@ncc.go.jp.
Kouya Shiraishi, Email: kshirais@ncc.go.jp.
REFERENCES
- 1. Idos G, Valle L. Lynch syndrome. In: Adam MP, Mirzaa GM, Pagon RA, et al., eds. GeneReviews((R)). The University of Washington; 1993. [PubMed] [Google Scholar]
- 2. Zhao S, Chen L, Zang Y, et al. Endometrial cancer in Lynch syndrome. Int J Cancer. 2022;150:7‐17. [DOI] [PubMed] [Google Scholar]
- 3. Barrow E, Robinson L, Alduaij W, et al. Cumulative lifetime incidence of extracolonic cancers in Lynch syndrome: a report of 121 families with proven mutations. Clin Genet. 2009;75:141‐149. [DOI] [PubMed] [Google Scholar]
- 4. Lynch HT, Lynch PM, Lanspa SJ, Snyder CL, Lynch JF, Boland CR. Review of the Lynch syndrome: history, molecular genetics, screening, differential diagnosis, and medicolegal ramifications. Clin Genet. 2009;76:1‐18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Barrow E, Hill J, Evans DG. Cancer risk in Lynch syndrome. Fam Cancer. 2013;12:229‐240. [DOI] [PubMed] [Google Scholar]
- 6. Lu KH, Dinh M, Kohlmann W, et al. Gynecologic cancer as a "sentinel cancer" for women with hereditary nonpolyposis colorectal cancer syndrome. Obstet Gynecol. 2005;105:569‐574. [DOI] [PubMed] [Google Scholar]
- 7. Dehghani Soufi M, Rezaei Hachesu P, Ferdousi R. Oncology informatics for Lynch syndrome research and care: a literature review. JCO Clin Cancer Inform. 2022;6:e2200087. [DOI] [PubMed] [Google Scholar]
- 8. Vasen HF, Moslein G, Alonso A, et al. Guidelines for the clinical management of Lynch syndrome (hereditary non‐polyposis cancer). J Med Genet. 2007;44:353‐362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. 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;293:1986‐1994. [DOI] [PubMed] [Google Scholar]
- 10. Crosbie EJ, Ryan NAJ, Arends MJ, et al. The Manchester international consensus group recommendations for the management of gynecological cancers in Lynch syndrome. Genet Med. 2019;21:2390‐2400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Forman A, Sotelo J. Tumor‐based genetic testing and familial cancer risk. Cold Spring Harb Perspect Med. 2020;10(8):1‐18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Stelloo E, Jansen AML, Osse EM, et al. Practical guidance for mismatch repair‐deficiency testing in endometrial cancer. Ann Oncol. 2017;28:96‐102. [DOI] [PubMed] [Google Scholar]
- 13. Goodfellow PJ, Billingsley CC, Lankes HA, et al. Combined microsatellite instability, MLH1 methylation analysis, and immunohistochemistry for Lynch syndrome screening in endometrial cancers from GOG210: An NRG oncology and gynecologic oncology group study. J Clin Oncol. 2015;33:4301‐4308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Lefol C, Sohier E, Baudet C, et al. Acquired somatic MMR deficiency is a major cause of MSI tumor in patients suspected for "Lynch‐like syndrome" including young patients. Eur J Hum Genet. 2021;29:482‐488. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Poulogiannis G, Frayling IM, Arends MJ. DNA mismatch repair deficiency in sporadic colorectal cancer and Lynch syndrome. Histopathology. 2010;56:167‐179. [DOI] [PubMed] [Google Scholar]
- 16. Liu GC, Liu RY, Yan JP, et al. The heterogeneity between Lynch‐associated and sporadic MMR deficiency in colorectal cancers. J Natl Cancer Inst. 2018;110:975‐984. [DOI] [PubMed] [Google Scholar]
- 17. Post CCB, Stelloo E, Smit V, et al. Prevalence and prognosis of Lynch syndrome and sporadic mismatch repair deficiency in endometrial cancer. J Natl Cancer Inst. 2021;113:1212‐1220. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Dominguez‐Valentin M, Sampson JR, Seppala TT, et al. Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the prospective Lynch syndrome database. Genet Med. 2020;22:15‐25. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Hampel H, Frankel W, Panescu J, et al. Screening for Lynch syndrome (hereditary nonpolyposis colorectal cancer) among endometrial cancer patients. Cancer Res. 2006;66:7810‐7817. [DOI] [PubMed] [Google Scholar]
- 20. Ryan NAJ, Glaire MA, Blake D, Cabrera‐Dandy M, Evans DG, Crosbie EJ. The proportion of endometrial cancers associated with Lynch syndrome: a systematic review of the literature and meta‐analysis. Genet Med. 2019;21:2167‐2180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Wang Y, Wang Y, Li J, et al. Lynch syndrome related endometrial cancer: clinical significance beyond the endometrium. J Hematol Oncol. 2013;6:22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Buchanan DD, Tan YY, Walsh MD, et al. Tumor mismatch repair immunohistochemistry and DNA MLH1 methylation testing of patients with endometrial cancer diagnosed at age younger than 60 years optimizes triage for population‐level germline mismatch repair gene mutation testing. J Clin Oncol. 2014;32:90‐100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Mills AM, Liou S, Ford JM, Berek JS, Pai RK, Longacre TA. Lynch syndrome screening should be considered for all patients with newly diagnosed endometrial cancer. Am J Surg Pathol. 2014;38:1501‐1509. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Dillon JL, Gonzalez JL, DeMars L, Bloch KJ, Tafe LJ. Universal screening for Lynch syndrome in endometrial cancers: frequency of germline mutations and identification of patients with Lynch‐like syndrome. Hum Pathol. 2017;70:121‐128. [DOI] [PubMed] [Google Scholar]
- 25. Frolova AI, Babb SA, Zantow E, et al. Impact of an immunohistochemistry‐based universal screening protocol for Lynch syndrome in endometrial cancer on genetic counseling and testing. Gynecol Oncol. 2015;137:7‐13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Stinton C, Jordan M, Fraser H, et al. Testing strategies for Lynch syndrome in people with endometrial cancer: systematic reviews and economic evaluation. Health Technol Assess. 2021;25:1‐216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Lokuhetty DWVA, Watanabe R. Female genital tumors. 5th ed. Internal Agency for Research on Cancer (IARC); 2020. [Google Scholar]
- 28. Fujita M, Liu X, Iwasaki Y, et al. Population‐based screening for hereditary colorectal cancer variants in Japan. Clin Gastroenterol Hepatol. 2022;20:2132‐2141.e9. [DOI] [PubMed] [Google Scholar]
- 29. Momozawa Y, Akiyama M, Kamatani Y, et al. Low‐frequency coding variants in CETP and CFB are associated with susceptibility of exudative age‐related macular degeneration in the Japanese population. Hum Mol Genet. 2016;25:5027‐5034. [DOI] [PubMed] [Google Scholar]
- 30. Franke KR, Crowgey EL. Accelerating next generation sequencing data analysis: an evaluation of optimized best practices for genome analysis toolkit algorithms. Genomics Inform. 2020;18:e10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Li H, Durbin R. Fast and accurate short read alignment with burrows‐wheeler transform. Bioinformatics. 2009;25:1754‐1760. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Danecek P, Bonfield JK, Liddle J, et al. Twelve years of SAMtools and BCFtools. Gigascience. 2021;10:10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Lek M, Karczewski KJ, Minikel EV, et al. Analysis of protein‐coding genetic variation in 60,706 humans. Nature. 2016;536:285‐291. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Nagasaki M, Yasuda J, Katsuoka F, et al. Rare variant discovery by deep whole‐genome sequencing of 1,070 Japanese individuals. Nat Commun. 2015;6:8018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Landrum MJ, Lee JM, Benson M, et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 2018;46:D1062‐D1067. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Cingolani P, Platts A, Wang le L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso‐2; iso‐3. Fly (Austin). 2012;6:80‐92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Kato MK, Yoshida H, Uehara T, et al. Unique prognostic features of grade 3 endometrioid endometrial carcinoma: findings from 101 consecutive cases at a Japanese tertiary cancer center. Taiwan J Obstet Gynecol. 2021;60:238‐244. [DOI] [PubMed] [Google Scholar]
- 38. Kato MK, Yoshida H, Tanase Y, Uno M, Ishikawa M, Kato T. Loss of ARID1A expression as a favorable prognostic factor in early‐stage grade 3 endometrioid endometrial carcinoma patients. Pathol Oncol Res. 2021;27:598550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Asami Y, Kobayashi Kato M, Hiranuma K, et al. Utility of molecular subtypes and genetic alterations for evaluating clinical outcomes in 1029 patients with endometrial cancer. Br J Cancer. 2023;128:1582‐1591. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Hall G, Clarkson A, Shi A, et al. Immunohistochemistry for PMS2 and MSH6 alone can replace a four antibody panel for mismatch repair deficiency screening in colorectal adenocarcinoma. Pathology. 2010;42:409‐413. [DOI] [PubMed] [Google Scholar]
- 41. Ueda S, Yamashita S, Watanabe SI, et al. Influence of degree of DNA degradation in formalin‐fixed and paraffin‐embedded tissue samples on accuracy of genome‐wide DNA methylation analysis. Epigenomics. 2021;13:565‐576. [DOI] [PubMed] [Google Scholar]
- 42. Ebata T, Yamashita S, Takeshima H, et al. DNA methylation marker to estimate ovarian cancer cell fraction. Med Oncol. 2022;39:78. [DOI] [PubMed] [Google Scholar]
- 43. Irie T, Yamada H, Takeuchi C, et al. The methylation level of a single cancer risk marker gene reflects methylation burden in gastric mucosa. Gastric Cancer. 2023;26:667‐676. [DOI] [PubMed] [Google Scholar]
- 44. Sugai T, Yoshida M, Eizuka M, et al. Analysis of the DNA methylation level of cancer‐related genes in colorectal cancer and the surrounding normal mucosa. Clin Epigenetics. 2017;9:55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Cancer Genome Atlas Research N , Kandoth C, Schultz N, et al. Integrated genomic characterization of endometrial carcinoma. Nature. 2013;497:67‐73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Stelloo E, Nout RA, Osse EM, et al. Improved risk assessment by integrating molecular and clinicopathological factors in early‐stage endometrial cancer‐combined analysis of the PORTEC cohorts. Clin Cancer Res. 2016;22:4215‐4224. [DOI] [PubMed] [Google Scholar]
- 47. Leon‐Castillo A, Britton H, McConechy MK, et al. Interpretation of somatic POLE mutations in endometrial carcinoma. J Pathol. 2020;250:323‐335. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Haraldsdottir S, Hampel H, Wu C, et al. Patients with colorectal cancer associated with Lynch syndrome and MLH1 promoter hypermethylation have similar prognoses. Genet Med. 2016;18:863‐868. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Leon‐Castillo A, Gilvazquez E, Nout R, et al. Clinicopathological and molecular characterisation of ‘multiple‐classifier’ endometrial carcinomas. J Pathol. 2020;250:312‐322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Conlon N, Da Cruz Paula A, Ashley CW, et al. Endometrial carcinomas with a "serous" component in Young women are enriched for DNA mismatch repair deficiency, Lynch syndrome, and POLE exonuclease domain mutations. Am J Surg Pathol. 2020;44:641‐648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Garg K, Soslow RA. Strategies for distinguishing low‐grade endometrioid and serous carcinomas of endometrium. Adv Anat Pathol. 2012;19:1‐10. [DOI] [PubMed] [Google Scholar]
- 52. Nagase S, Ohta T, Takahashi F, Yamagami W, Yaegashi N, Board Members of the 2020 Committee on Gynecologic Oncology of the Japan Society of Obstetrics and Gynecology . Annual report of the committee on gynecologic oncology, the Japan Society of Obstetrics and Gynecology: annual patient report for 2018 and annual treatment report for 2013. J Obstet Gynaecol Res. 2022;48:541‐552. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1.
Table S1.
