Immunohistochemical Assessment of MLH1, MSH2, MSH6, and PMS2 Expression and Mismatch Repair Deficiency in Surgically Resected Colorectal Carcinomas

Abstract

Background

Deficiency of DNA mismatch repair (dMMR) in colorectal cancer (CRC) predicts prognosis and guides' therapy. Data on dMMR prevalence and predictors in Brazil remain limited.

Objective

To estimate the prevalence of dMMR in CRC resections and identify independent clinical-pathological predictors.

Materials and Methods

We retrospectively analyzed 330 adults who underwent resection for primary colorectal adenocarcinoma between January 2008 and December 2024 at a public hospital and a private clinic in Campinas, in the state of São Paulo, Brazil. The exclusion criteria were non-adenocarcinoma histology, complete pathologic response to neoadjuvant therapy, inflammatory bowel disease-associated CRC, polyposis syndromes, and inadequate tissue. Immunohistochemistry (IHC) for MLH1, MSH2, MSH6, and PMS2 was centralized; complete loss of any protein indicated dMMR. We recorded age, sex, tumor site, histological grade, and nodal status. Univariate analyses used the Fisher's exact and Mann-Whitney tests, and a multivariable logistic regression was conducted to identify independent dMMR predictors (p  <  0.05).

Results

The dMMR prevalence was 12.7% (42/330). In the multivariable analysis, proximal location (odds ratio [OR]: 2.51; 95%CI: 1.26–4.99; p  =  0.009) and high grade (OR: 3.79; 95%CI: 1.40–6.24; p  =  0.008) were independently associated with dMMR, but age was not (p  =  0.441). Node-positive tumors had higher dMMR rates than node-negative cases (17.1 % versus 11.0 %; p  =  0.045). The predominant IHC profile was MLH1 + PMS2 co-loss (47.6 % of dMMR cases).

Conclusions

Approximately one in eight CRCs in this Brazilian cohort is positive for dMMR. Tumor phenotype (proximal site, poor differentiation), rather than age, predicts dMMR.

Keywords

colorectal cancer - MMR - immunotherapy - colorectal surgery - MSI

Introduction

Colorectal cancer (CRC) remains a significant global health burden, ranking as the third most frequently diagnosed malignancy and the second leading cause of cancer-related death in many high-income nations. This persistent impact likely reflects demographic shifts, particularly population aging, as well as lifestyle factors such as adopting a diet rich in processed foods, low dietary fiber, and sedentary behavior.[1] In Brazil, the National Cancer Institute (INCA, Instituto Nacional de Câncer, in Portuguese) estimated that over 45 thousand new cases of CRC occurred in 2023, with a mortality rate of ∼ 8.1 per 100 thousand inhabitants.[2] Despite advances in colonoscopic screening, surgical techniques, and systemic therapies, ∼ 20% of patients still present with metastatic disease at diagnosis, when 5-year survival falls below 15%.[3]

Population studies indicate that up to 30% of all CRC cases may be linked to a hereditary component, such as high-impact mutations in DNA error-fixing genes or early-onset neoplastic syndromes.[4] A molecular subset of CRC characterized by microsatellite instability (MSI) arises from a DNA mismatch repair (MMR) system deficiency composed of proteins MLH1, MSH2, MSH6, and PMS2. Under normal conditions, the MutSα complex (MSH2-MSH6) identifies DNA replication errors, and the MutLα complex (MLH1-PMS2) orchestrates repair. Loss of any MMR component, due to inherited germline mutations in Lynch syndrome or somatic MLH1 promoter hypermethylation, leads to the accumulation of insertion-deletion errors in microsatellite regions, resulting in a hypermutation phenotype with a high neoantigenic load. These features trigger intense lymphocytic infiltration and confer sensitivity to immune checkpoint inhibitors targeting PD-1/PD-L1.[5] [6] [7] These gene inconsistencies also lead to their malfunction and a shortened adenoma-carcinoma sequence time.[8]

Colorectal cancer is a condition with effective prevention strategies, and the best outcome of treatment is closely linked to early diagnosis. However, despite this being an important issue, investigating the genetic causes of CRC rarely exceeds the application of clinical criteria, such as the Amsterdam or Bethesda criteria. It is estimated that less than 20% of families with genetic cancer syndromes are referred to specific tests and/or a specialty center.[9] Therefore, knowing the MMR status of CRC is of crucial importance regarding patients' treatment.[10] [11]

International cohorts report deficiency of MMR (dMMR) in 10 to 20% of sporadic CRCs, with higher rates in proximal tumors (up to 30%) and poorly-differentiated subtypes.[12] [13] [14] Mismatch repair status is associated with an improved overall prognosis, distinct metastatic patterns, phenotypes, and progression patterns, as well as specific chemosensitivity. In response, guidelines increasingly recommend universal dMMR screening by immunohistochemistry (IHC) for all CRCs, regardless of patient age or family history. Immunohistochemistry offers rapid, cost-effective triage with sensitivity and specificity of over 90% compared with other tests, such as next-generation sequencing (NGS) or PCR-based MSI testing.[15] [16]

However, robust data on dMMR prevalence and predictors in Brazilian populations are limited. Single-center Brazilian studies describe variable dMMR rates, often lacking adjustment for confounders such as age, tumor location, and differentiation grade.[9] [17] [18] [19] Few local data comprehensively describe the prevalence of dMMR in surgically resected CRC patients and its independent associations with demographic and tumor characteristics, hindering the development of evidence-based recommendations for universal IHC screening and tailored treatment strategies.[20] [21] [22]

The present study addressed this gap by conducting a retrospective cohort study of 330 patients with CRC from a public hospital and a private clinic in the city of Campinas, state of São Paulo, Brazil. We performed IHC for MLH1, MSH2, MSH6, and PMS2 on surgical specimens, determined dMMR status, and collected data on age at surgery, tumor anatomical site, and histological grade. We applied univariate analyses and multivariate logistic regression to identify independent predictors of dMMR. Our objectives were: 1) to establish the local prevalence of dMMR; 2) to determine its associations with clinical and pathological variables; and 3) to contribute to recommendations in universal IHC screening protocols and personalized therapeutic approaches in distinct healthcare settings.

Materials and Methods

Study Design and Patient Selection

The present retrospective cohort study included all adult patients (≥ 18 years) who underwent elective surgery with curative intention for primary colorectal adenocarcinoma between January 2008 and December 2024 at 2 institutions in Campinas: public Hospital Municipal Dr. Mário Gatti and one author's (GSP) private colorectal surgery clinic. Both have their patients listed in an electronic database. Exclusion criteria were applied, including non-adenocarcinoma histology, complete pathological response following neoadjuvant therapy, CRC arising from inflammatory bowel disease, adenomatous polyposis coli, as well as unavailable data, and inadequate tissue and samples for IHC.

Tissue Retrieval and Immunohistochemistry

Paraffin-embedded surgical specimens not previously submitted to IHC were gathered from multiple laboratories. All paraffin blocks were re-cut and processed centrally at the Immunopathology Laboratory of the Medical School at Universidade São Francisco to ensure methodological consistency. Four-micrometer sections underwent automated staining on the Dako Autostainer Link (Agilent Technologies using the EnVision FLEX platform (Agilent Technologies). After heat-induced epitope retrieval in EnVision FLEX Target Retrieval Solution (pH 9.0) at 97 °C for 20 minutes, sections were incubated with ready-to-use monoclonal antibodies for MLH1 (clone ES05), MSH2 (FE11), MSH6 (EP49), and PMS2 (EP51) for 20 minutes at room temperature. Detection employed the EnVision FLEX+ High pH polymer system, which utilizes diaminobenzidine as the chromogen and Mayer's hematoxylin as the counterstain. Complete loss of staining in tumor cells' nucleus, with intact staining in internal non-neoplastic controls ([Fig. 1]), defined dMMR) for each marker.

Fig. 1 Immunohistochemical examples of DNA mismatch repair (MMR) protein expression patterns (×200). (A, B) Proficient nuclear MLH1/PMS2 expression. (C, D) Lack of nuclear MLH1/PMS2 expression.

Data Collection and Variables

Clinical data (age at surgery, gender), pathological features (tumor location by subsite and tumor, node, metastasis [TNM] stage, histological grade), and IHC results for each MMR protein were abstracted from the database and pathology reports. Tumor subsites were evaluated separately and then grouped into proximal (cecum, ascending, transverse) versus distal (descending, sigmoid, rectum). Histological grade was studied individually and subsequently, and it was also clustered into two groups: low-grade (well-to-moderately differentiated) and high-grade (poorly differentiated, mucinous, or signet-ring).

Statistical Analysis

Descriptive statistics summarize demographic and tumor characteristics. Continuous variables are expressed as mean ± SD and compared using the Mann-Whitney U-test; categorical variables are presented as counts and percentages, with Fisher's exact test used for comparison. To adjust for potential confounders and identify independent predictors of dMMR, a multivariable logistic regression model was fitted, including age (continuous), tumor location (proximal versus distal), and histological grade (high versus low). Statistical modeling was performed using the IBM SPSS Statistics for Windows (IBM Corp.) software, version 26.0. Data management and exploratory analyses were conducted using OpenAI GPTs Data Analyst, o3 and o4-mini-high (OpenAI), ensuring reproducible code-driven data manipulation and model validation. Statistical significance was set at p < 0.05.

Ethical Considerations

The study was approved by the Research Ethics Committee of Universidade Estadual de Campinas (UNICAMP) (CAAE 80397518.0.0000.5404), with a waiver of informed consent due to its retrospective nature. No identifiable patient information was used.

Results

Data from 1,064 patients were revised. After the exclusion criteria were applied, 734 patients were excluded for the following reasons: incomplete data on the record: 67; familial adenomatous polyposis: 25; non-adenocarcinoma: 41; complete response to neoadjuvant therapy: 26; unavailable specimen or specimen without viable tissue for IHC: 575. A final analytic cohort of 330 patients remained after the exclusion criteria were applied ([Fig. 2]).

Fig. 2 Study sample.

Patient Characteristics

A total of 330 patients met the inclusion criteria. The mean age was 62.3 ± 12.4 years. There were 180 men (54.5%) and 150 women (45.5%). Tumors were in the proximal colon in 117 cases (35.5%) and in the distal colon/rectum in 213 cases (64.5%), detailed in [Table 1]. Histological grading identified 264 low-grade (well/moderately differentiated; 80.0%) and 66 rtablehigh-grade (poorly differentiated, mucinous, or signet-ring; 20.0%) tumors.

Table 1 Baseline characteristics of the cohort (n = 330)

		Total (n)	dMMR (n)	pMMR (n)	dMLH1 (n)	dMSH2 (n)	dMSH6 (n)		dPMS2 (n)
Age (years)	< 30	4	1	3	1	0	0		1
	30–34	3	0	3	0	0	0		0
	35–39	13	0	13	0	0	0		0
	40–44	16	2	14	1	0	1		1
	45–49	17	4	13	0	2	2		2
	50–54	32	4	28	3	0	0		3
	55–59	44	5	39	4	0	0		5
	60–64	40	0	40	0	0	0		0
	65–69	65	8	57	5	0	2		7
	70–74	42	8	34	6	3	2		6
	75–80	32	4	28	2	0	2		2
	80–84	13	3	10	3	0	0		2
	> 85	9	3	6	2	0	0		3
Gender	Female	167	24	139	16	1	5	18	0.408
	Male	163	18	145	11	4	4	14
Site	Anal canal	1	0	1	0	0	0	0
	Cecum	30	2	28	0	1	0	0
	Ascending	44	15	28	0	12	1	3	0.001
	Descending	19	3	15	0	1	1	1
	Rectum	120	8	112	0	4	2	2
	Sigmoid	81	7	72	0	4	1	1
	Transverse	20	5	15	0	4	0	2
	More than one site	15	2	13	0	1	0	0

Abbreviations: dMMR, DNA mismatch repair deficiency; pMMR, DNA mismatch repair proficiency; dMLH1, MLH1 deficiency; dMSH2, MSH2 deficiency; dMSH6, MSH6 deficiency; dPMS2, PMS2 deficiency.

Prevalence of dMMR

Overall, 42 of 330 tumors (12.7%) demonstrated deficiency of at least one MMR protein by IHC. Breakdown by protein was: MLH1 loss in 27 cases (8.2%), PMS2 loss in 32 (9.7%), MSH6 loss in 9 (2.7%), and MSH2 loss in 5 (1.5%). Exactly 1 protein was absent from 15 patients (4.5%), and from 27 patients (8.2%), 2 or more proteins were lost ([Table 2]).

Table 2 Frequency of MMR protein loss

Deficiency profile	Frequency (n)	dMMR cases (%)
MLH1 only	3	7.1
PMS2 only	8	19.0
MSH6 only	3	7.1
MSH2 only	1	2.4
MLH1 + PMS2	20	47.6
MLH1 + MSH2	1	2.4
MSH2 + MSH6	2	4.8
MSH6 + PMS2	1	2.4
MLH1 + MSH2 + PMS2	1	2.4
MLH1 + MSH6 + PMS2	2	4.8
MLH1 + MSH2 + MSH6 + PMS2	1	2.4

Abbreviation: dMMR, DNA mismatch repair deficiency.

An analysis of protein-expression patterns by age group revealed no statistically significant differences. Proficient MMR tumors were evenly distributed across all age intervals. The combined MLH1 + PMS2-loss profile was observed in every age group but showed a non-significant concentration among patients aged 55 to 74. Isolated loss of MLH1 or MSH2 was rare and occurred sporadically only in older age groups. The prevalence of dMMR was 13.5% in patients < 50 years (7/52) and 12.6% in those ≥ 50 years (35/278; p = 0.825).

Regarding tumor site, the ascending colon was the most frequent dMMR site (34.1%), as shown in [Table 3], but when the location was grouped in proximal (cecum, ascending colon, and transverse colon) and compared with distal lesions (sigmoid, rectum, descending colon, and anal canal), 22 of 98 right-sided cases (22.4%) showed MMR deficiency. In contrast, only 20 of 232 left-sided cases (8.6%) displayed this profile ([Table 4]). Mismatch repair deficiency was significantly more common in proximal tumors than in distal ones (p = 0.001).

Table 3 Sites of tumor occurrence and MMR status

Site	Total (n)	dMMR (n)	pMMR (n)	dMMR (%)	p-value
Rectum	120	8	112	6.7	0.015
Sigmoid	81	7	74	8.6	0.251
Ascending	44	15	29	34.1	0.001
Cecum	30	2	28	6.7	0.398
Transverse	20	5	15	25	0.155
Descending	19	3	16	15.8	0.72
More than one site	15	2	13	13.3	1
Anal canal	1	0	1	0	1

Abbreviations: dMMR, DNA mismatch repair deficiency; pMMR, DNA mismatch repair proficiency.

Table 4 Relationship between MMR status and laterality

	Total (n)	dMMR (n)	pMMR (n)	dMMR (%)	p-value
Right side	97	22	75	22.7	0.001
Left side	229	20	209	8.7

Abbreviations: dMMR, DNA mismatch repair deficiency; pMMR, DNA mismatch repair proficiency.

Most tumors were moderately differentiated (82.4%). In that category, the dMMR rate was 11%, similar to that of well-differentiated tumors. By contrast, poorly-differentiated and mucinous carcinomas showed markedly higher dMMR frequencies—41.7% and 40%, respectively. In undifferentiated tumors, the rate reached 25% ([Table 5]).

Table 5 Frequency of dMMR according to tumor grade

Differentiation	n	% (n = 330)	dMMR (n)	pMMR (n)	dMMR (%)	p-value
Well-differentiated	37	11.20	4	33	10.8
Moderately differentiated	272	82.40	30	242	11.0
Poorly differentiated	12	3.60	5	7	41.7
Undifferentiated	4	1.20	1	3	25.0
Mucinous	5	1.50	2	3	40.0

Abbreviations: dMMR, DNA mismatch repair deficiency; pMMR, DNA mismatch repair proficiency.

The link between loss of differentiation and dMMR is made clear when pooling undifferentiated, poorly differentiated, and mucinous tumors into a single high-grade group (n = 21) and comparing them with the combined low-grade group (moderately and well-differentiated) tumors (n = 309) yielded a Fisher's exact p-value of 0.002. Thus, high-grade tumors displayed dMMR in 38.1% of cases, compared with 11.0% among low-grade tumors, a statistically significant difference ([Table 6]).

Table 6 Frequency of dMMR according to tumor grade (pooled in high and low grade)

Differentiation (pooled)	n	% (n = 330)	dMMR (n)	pMMR (n)	dMMR (%)
High-grade (undifferentiated + poorly differentiated + mucinous)	21	6.4	8	13	38.1	0.002
Low-grade (moderately + well-differentiated)	309	93.6	34	275	11.0

Abbreviations: dMMR, DNA mismatch repair deficiency; pMMR, DNA mismatch repair proficiency.

In a multivariate logistic-regression model assessing features of dMMR CRC, including age, location, and grade ([Table 7]), right-sided (proximal) tumors were 2.5 times more likely to exhibit dMMR after adjustment for age and grade (odds ratio [OR] = 2.51; p = 0.009). High-grade tumors (poorly differentiated, undifferentiated, or mucinous) were associated with a 3.8-fold increase in dMMR probability when other variables were controlled (OR = 3.79; p = 0.008). Age did not emerge as an independent predictor (p = 0.441), underscoring its lack of association with MMR status.

Table 7 Multivariable logistic regression model for predictors of dMMR

Variable	β-coefficient	Standard error	p-value	Adjusted odds ratio (95%CI)
Proximal location (right sided)	0.922	0.353	0.009	2.51 (1.26–5.02)
High-grade (poorly differentiated/undifferentiated/mucinous)	1.333	0.505	0.008	3.79 (1.41–10.20)
Age (per additional year)	0.010	0.013	0.441	1.01 (0.9–1.04)

Abbreviation: dMMR, mismatch repair deficiency.

These results confirm that proximal location and poor differentiation are independent features associated with increased predictive value of dMMR. In contrast, patient age contributes to no additional predictive value in this series once the multivariable adjustment is applied.

Regarding disease stage, 22 of 200 (11.0%) stage I and II (node-negative, N0) patients showed MMR deficiency, whereas 22 of 130 (17.1%) node-positive (stages III and IV) patients (N1–N2) displayed this profile. The Fisher's exact test yielded a p-value of 0.045, indicating a statistically significant difference in dMMR prevalence between patients with and without lymph node metastasis ([Table 8]).

Table 8 Prevalence of dMMR in patients with and without lymph node metastasis

Lymph-node status	Total patients (n)	dMMR-positive (n)	dMMR (%)	p-value
N0 (no metastasis)	200	22	11.0	0.045
N1–N2 (with metastasis)	130	22	17.1	—

Abbreviation: dMMR, mismatch repair deficiency.

According to the tumor stage, the prevalence of loss of each protein (or combination thereof) is shown in [Table 9]. There were no significant findings regarding individual MMR protein expression and staging.

Table 9 Distribution of tumor stage according to immunohistochemical protein-expression deficiency profile

Deficiency profile	I	IIA	IIB	IIIA	IIIB	IIIC	IV	Total
MSH6 only	0	0	2	0	1	0	0	3
MLH1 + MSH6 + PMS2	1	0	0	0	1	0	0	2
MLH1 + PMS2	3	10	0	0	3	2	2	20
PMS2 only	1	3	1	0	1	2	0	8
MLH1 only	1	1	0	0	1	0	0	3
Total	6	14	3	0	6	4	2	42

Discussion

Prevalence of dMMR

In this cohort of 330 CRC resections, we found a 12.7 % rate of dMMR by IHC, which is well within the 10  to 20 % range reported in large Western series.[14] [23] This finding confirms that, despite genetic and environmental differences, the CRC population in the present study exhibits similar overall dMMR rates, mirroring the relevance of global epidemiological data to our Brazilian context.[9] [20] [21] [22] Notably, our combined public-private design encompasses a broad spectrum of healthcare delivery models, which may support the generalizability of these findings across diverse clinical settings.

The diversity of protein deficiency profiles, ranging from isolated losses to complex co-deficiencies, underscores the need for refined classification. The combined loss MLH1 + PMS2 was dominant, consistent with PMS2's dependence on MLH1 for heterodimer stability. Rare profiles (such as MSH2 + MSH6) may indicate distinct mutational mechanisms or secondary somatic events.[12] BRAF V600E and MLH1 methylation assays, along with NGS panel testing, would enable differentiation between sporadic and Lynch-associated dMMR, thereby optimizing genetic counseling and surveillance strategies.[14]

Our reliance on IHC alone precluded a definitive distinction between hereditary and somatic dMMR; in 50 % of MLH1-deficient cases, we infer the somatic methylation of MLH1 may represent sporadic methylation rather than Lynch syndrome.[17] Subgroup analyses of rare profiles (e.g., isolated MSH2 or MSH6 loss) were underpowered.

Age and Screening

Contrary to expectations drawn from hereditary CRC registries, we found no significant difference in dMMR prevalence between patients younger than 50 years (13.5%) and those aged 50 years or older (12.6%).[17] [24] While a younger age is a hallmark of Lynch syndrome, our data suggest that other causes of MLH1 deficiency may also be present, such as sporadic MLH1 promoter methylation syndrome, which predominates among sporadic dMMR tumors, thereby diluting the age effect.[17] This observation reinforces recommendations for universal dMMR IHC screening in all CRC patients rather than age-restricted testing.[25]

Tumor Phenotypes

In our multivariable logistic model, proximal location (OR = 2.51; 95%CI = 1.26–4.99; p = 0.009) and high histological grade (OR = 3.79; 95%CI = 1.40–6.24; p = 0.008) were independently associated with dMMR status. Proximal (right-sided) tumors demonstrated a significantly higher dMMR frequency than distal lesions (22.2% versus 8.0%; p = 0.001). This 2-to-3-fold enrichment aligns with the underlying molecular pathogenesis of the microsatellite instability (MSI) pathway and its known predilection for the cecum, and the ascending and transverse colon.[2]

High-grade histology (poorly-differentiated and mucinous subtypes) also showed a marked frequency of dMMR (38.1% versus 6.8% in low-grade tumors; p < 0.001), reflecting the strong association with poor differentiation that may reflect the link between hypermutation and aggressive morphological features.[26] [27] [28]

In a multivariable logistic regression analysis, adjusting for age, location, and grade, the proximal site remained an independent predictor of dMMR, whereas age did not. These results confirm that tumor phenotypes, such as location and differentiation, outweigh patient demographics in predicting MMR status and underscore the limited utility of age as a screening criterion.[29] [30]

Nodal Status

Tumors with lymph node involvement (N1–N2) exhibited a higher rate of dMMR (17.1 %) compared with node-negative tumors (11.0 %; p  =  0.045). This 6.1% difference is an unexpected finding in our dataset and contrasts with the expectation that microsatellite-unstable cancers would exhibit less nodal spread.[31] Within our cohort, this finding may reflect heterogeneity among dMMR tumors, among which subsets still possess mechanisms—undetected by IHC alone—that allow for lymphatic dissemination. Future work should correlate dMMR status with measures of local immune infiltration and detailed molecular profiling (for example, PDL-1 expression or other immune-regulatory alterations) to determine which dMMR subsets are prone to nodal metastasis.[32]

Clinical Issues

In our cohort of 330 resected colorectal adenocarcinomas, standard IHC identified dMMR in 12.7% of cases. Notably, a considerable share of dMMR tumors lies outside conventional “high-risk” subsets, underscoring the limitations of selective testing.

Clinically, the identification of dMMR has immediate implications. Microsatellite instability-high status predicts poor response to 5-fluorouracil monotherapy in stage-II CRC but confers sensitivity to PD-1 inhibitors in metastatic disease.[7] [33] [34] [35] Our findings support the integration of IHC results into multidisciplinary treatment planning, which guides the selection of adjuvant regimens and determines immunotherapy eligibility. Moreover, early recognition of Lynch syndrome through comprehensive IHC and molecular triage facilitates cascade testing, enabling at-risk relatives to undergo targeted surveillance and risk-reducing interventions.[14] [16]

We, therefore, endorse universal MMR-protein screening—both in endoscopic biopsies and surgical specimens—for every newly-diagnosed case of CRC, and we encourage guideline committees worldwide to update their recommendations accordingly, as did the National Comprehensive Cancer Network guidelines, which recommended MSI to be tested in all newly-diagnosed CRCs, since 2018.[14] [16] Early detection of dMMR on biopsy not only accelerates appropriate referral for Lynch syndrome evaluation but also informs preoperative therapeutic decisions, such as neoadjuvant immunotherapy in locally advanced dMMR tumors.[7] [35] [36] Systematic dMMR detection enhances patient care on multiple fronts: it refines individual and familial surveillance strategies, reinforces the choice of adjuvant therapy (particularly immune-checkpoint blockade), and triggers timely genetic counseling for possible Lynch syndrome.

Limitations

Operationally, centralizing IHC processing in a reference laboratory was critical to ensure consistency across specimens sourced from multiple pathology providers. The period between surgery and IHC testing, however, is sometimes much more extended than what is considered adequate in literature. The impossibility of reprocessing some paraffin-embedded specimens, protein denaturation, and the inadequate staining of the specimens is a genuine concern. Although some proteins can be lost in older specimens, leading to inaccurate results,[37] [38] standardized antigen retrieval, antibody clones, and detection systems minimized inter-laboratory variability and improved assay reproducibility. Whenever there was doubt about the quality of the IHC result, it was not used.

Other limitations of our study include the lack of germline genetic confirmation and a weak analysis of rare dMMR profiles.

Finally, the absence of clinical outcomes data limits the assessment of dMMR's prognostic and predictive value in this cohort.

Future implications

Future prospective work should layer MLH1-promoter methylation assays onto the IHC workflow to more accurately distinguish between sporadic and hereditary cases, while correlating dMMR status with clinical outcomes, such as survival and treatment response,[24] [34] [39] [40] as well as evaluating the effectiveness of universal screening in diverse healthcare settings.

Knowing a tumor's MMR profile before surgery enables more informed operative planning, and the prospect of dMMR-targeted vaccines provides yet another incentive for the adoption of global screening.[41] [42] Finally, artificial intelligence models that predict microsatellite instability and the benefits of immunotherapy are emerging, but they require robust, multicenter validation before being used in routine clinical practice.[43]

Ultimately, universal MMR testing represents a critical step toward precision oncology in CRC,[25] ensuring that all patients benefit from accurate molecular diagnosis and tailored therapeutic strategies.[44]

As a practical suggestion for targeted screening implantation, considering costs, literature evidence,[14] [16] [32] [45] [46] [47] [48] results from this study, expected results, and treatment optimization, a flowchart has been adapted from Giardiello et al.[48] and Syngal et al.,[45] as shown in [Fig. 3].

Fig. 3 Suggested targeted cancer screening flowchart for MMR patients. Adapted from Giardiello et al.[48] and Syngal et al.[45]

In conclusion, the present study confirms that dMMR affects approximately one in eight CRCs in the studied population, and that proximal tumor sites and less differentiated tumors are more prone to dMMR, consistent with other published series.

Conflict of Interests

The authors have no conflict of interests to declare.

Authors' Contributions

• References

• 1 Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021; 71 (03) 209-249 PubMed
• 2 Intituto Nacional de Câncer (INCA) [Internet]. Rio de Janeiro: INCA; 2022 [update 2025 Apr 03; cited 2025 Apr 6]. Estatísticas de câncer. Available from: https://www.gov.br/inca/pt-br/assuntos/cancer/numeros
• 3 Siegel RL, Miller KD, Sauer AG, Fedewa SA, Butterly LF, Anderson JC. et al. Colorectal cancer statistics, 2020. CA Cancer J Clin 2020; 70 (03) 145-164 PubMed
• 4 Stoffel EM, Mangu PB, Limburg PJ. American Society of Clinical Oncology, European Society for Medical Oncology. Hereditary colorectal cancer syndromes: American Society of Clinical Oncology clinical practice guideline endorsement of the familial risk-colorectal cancer: European Society for Medical Oncology clinical practice guidelines. J Oncol Pract 2015; 11 (03) e437-e441
• 5 Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD. et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N Engl J Med 2015; 372 (26) 2509-2520
• 6 Boland CR, Goel A. Microsatellite instability in colorectal cancer. Gastroenterology 2010; 138 (06) 2073-2087.e3
• 7 Cercek A, Foote MB, Rousseau B, Smith JJ, Shia J, Sinopoli J. et al. Nonoperative Management of Mismatch Repair-Deficient Tumors. N Engl J Med 2025; 392 (23) 2297-2308
• 8 Kuipers EJ, Grady WM, Lieberman D, Seufferlein T, Sung JJ, Boelens PG. et al. Colorectal cancer. Nat Rev Dis Primers 2015; 1 (01) 15065
• 9 Kozak VN, Ribeiro EMdSF, Kozonoe MM, Ioshii SO, Rocha JCCd. When guidelines face reality - Lynch syndrome screening in the setting of public health system in a developing country. J Community Genet 2022; 13 (01) 19-29
• 10 Sevá-Pereira G, Coy CSR, Martinez CAR. Updates on DNA Repair Gene Deficiency in Colorectal Cancer (dMMR). J Coloproctol (Rio J) 2025; 45 (01) s00451805009
• 11 Chalabi M, Verschoor YL, Tan PB, Balduzzi S, Van Lent AU, Grootscholten C. et al. Neoadjuvant Immunotherapy in Locally Advanced Mismatch Repair-Deficient Colon Cancer. N Engl J Med 2024; 390 (21) 1949-1958 PubMed
• 12 Guinney J, Dienstmann R, Wang X, Reyniès Ad, Schlicker A, Soneson C. et al. The consensus molecular subtypes of colorectal cancer. Nat Med 2015; 21 (11) 1350-1356
• 13 Guastadisegni C, Colafranceschi M, Ottini L, Dogliotti E. Microsatellite instability as a marker of prognosis and response to therapy: a meta-analysis of colorectal cancer survival data. Eur J Cancer 2010; 46 (15) 2788-2798
• 14 Hodan R, Gupta S, Weiss JM, Axell L, Burke CA, Chen LM. et al. Genetic/Familial High-Risk Assessment: Colorectal, Endometrial, and Gastric, Version 3.2024, NCCN Clinical Practice Guidelines In Oncology. J Natl Compr Canc Netw 2024; 22 (10) 695-711
• 15 Shia J. Immunohistochemistry versus microsatellite instability testing for screening colorectal cancer patients at risk for hereditary nonpolyposis colorectal cancer syndrome. Part I. The utility of immunohistochemistry. J Mol Diagn 2008; 10 (04) 293-300
• 16 Weiss JM, Gupta S, Burke CA, Axell L, Chen LM, Chung DC. et al. NCCN Guidelines® Insights: Genetic/Familial High-Risk Assessment: Colorectal, Version 1.2021. J Natl Compr Canc Netw 2021; 19 (10) 1122-1132
• 17 Vos JR, Fakkert IE, Spruijt L, Willems RW, Langenveld S, Mensenkamp AR. et al; FINAL Group. Evaluation of yield and experiences of age-related molecular investigation for heritable and nonheritable causes of mismatch repair deficient colorectal cancer to identify Lynch syndrome. Int J Cancer 2020; 147 (08) 2150-2158
• 18 Sinicrope FA, Rego RL, Halling KC, Foster N, Sargent DJ, La Plant B. et al. Prognostic impact of microsatellite instability and DNA ploidy in human colon carcinoma patients. Gastroenterology 2006; 131 (03) 729-737
• 19 Rosa RCA, Santis JO, Teixeira LA, Molfetta GA, Santos JTTd, Ribeiro VdS. et al. Lynch syndrome identification in a Brazilian cohort of endometrial cancer screened by a universal approach. Gynecol Oncol 2020; 159 (01) 229-238
• 20 Oliveira JW, Moraes RA, Mehanna SH, Linhares JC. COLORECTAL CANCER: HISTOPATHOLOGICAL PROFILE AND PREVALENCE OF DNA REPAIR SYSTEM DEFICIENCY IN PATIENTS SUBMITTED TO SURGICAL TREATMENT IN A UNIVERSITY HOSPITAL. Arq Bras Cir Dig 2023; 36: e1771
• 21 Paula AEd, Galvão HCR, Bonatelli M, Sabato C, Fernandes GC, Berardinelli GN. et al. Clinicopathological and molecular characterization of Brazilian families at risk for Lynch syndrome. Cancer Genet 2021; 254-255: 82-91
• 22 Schneider NB, Pastor T, Paula AEd, Achatz MI, Santos ARd, Vianna FSL. et al; Brazilian Lynch Syndrome Study Group. Germline MLH1, MSH2 and MSH6 variants in Brazilian patients with colorectal cancer and clinical features suggestive of Lynch Syndrome. Cancer Med 2018; 7 (05) 2078-2088
• 23 Mulet-Margalef N, Linares J, Badia-Ramentol J, Jimeno M, Monte CS, Mozo JLM, Calon A. Challenges and Therapeutic Opportunities in the dMMR/MSI-H Colorectal Cancer Landscape. Cancers (Basel) 2023; 15 (04) 1022
• 24 Flecchia C, Zaanan A, Lahlou W, Basile D, Broudin C, Gallois C. et al. MSI colorectal cancer, all you need to know. Clin Res Hepatol Gastroenterol 2022; 46 (09) 101983
• 25 Eikenboom EL, Van der Werf-'t Lam AS, Rodríguez-Girondo M, Asperen CJV, Dinjens WNM, Hofstra RMW. et al. Universal immunohistochemistry for Lynch Syndrome: a systematic review and meta-analysis of 58,580 colorectal carcinomas. Clin Gastroenterol H. 2021; 20 (03) e496-e507 PubMed
• 26 Mei WJ, Mi M, Qian J, Xiao N, Yuan Y, Ding PR. Clinicopathological characteristics of high microsatellite instability/mismatch repair-deficient colorectal cancer: A narrative review. Front Immunol 2022; 13: 1019582
• 27 Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin 2019; 69 (01) 7-34
• 28 Mao J, He Y, Chu J, Hu B, Yao Y, Yan Q, Han S. Analysis of clinical characteristics of mismatch repair status in colorectal cancer: a multicenter retrospective study. Int J Colorectal Dis 2024; 39 (01) 100
• 29 Chen H, Yin S, Xiong Z, Li X, Zhang F, Chen X. et al. Clinicopathologic characteristics and prognosis of synchronous colorectal cancer: a retrospective study. BMC Gastroenterol 2022; 22 (01) 120
• 30 Altshuler E, Franke AJ, Skelton IV WP, Feely M, Wang Y, Lee JH. et al. Impact of Institutional Universal Microsatellite-Instability (MSI) Reflex Testing on Molecular Profiling Differences Between Younger and Older Patients with Colorectal Cancer. Clin Colorectal Cancer 2023; 22 (01) 153-159
• 31 Toh JWT, Phan K, Reza F, Chapuis P, Spring KJ. Rate of dissemination and prognosis in early and advanced stage colorectal cancer based on microsatellite instability status: systematic review and meta-analysis. Int J Colorectal Dis 2021; 36 (08) 1573-1596
• 32 Lenz HJ, Overman MJ, Cutsem EV, Limon ML, Wong MK, Hendlisz A. et al. First-line (1L) nivolumab (NIVO) + ipilimumab (IPI) in patients (pts) with microsatellite instability-high/mismatch repair deficient (MSI-H/dMMR) metastatic colorectal cancer (mCRC): 64-month (mo) follow-up from CheckMate 142. J Clin Oncol 2024; 42 (03) 97-97
• 33 Zhang H, Huang J, Xu H, Yin N, Zhou L, Xue J, Ren M. Neoadjuvant immunotherapy for DNA mismatch repair proficient/microsatellite stable non-metastatic rectal cancer: a systematic review and meta-analysis. Front Immunol 2025; 16: 1523455
• 34 Han K, Tang JH, Liao LE, Jiang W, Sui QQ, Xiao BY. et al. Neoadjuvant Immune Checkpoint Inhibition Improves Organ Preservation in T4bM0 Colorectal Cancer With Mismatch Repair Deficiency: A Retrospective Observational Study. Dis Colon Rectum 2023; 66 (10) e996-e1005
• 35 Cercek A. Neoadjuvant Treatment of Mismatch Repair-Deficient Colon Cancer - Clinically Meaningful?. N Engl J Med 2024; 390 (21) 2024-2025
• 36 Cercek A, Fernandes GdS, Roxburgh CS, Ganesh K, Ng S, Sanchez-Vega F. et al. Mismatch Repair-Deficient Rectal Cancer and Resistance to Neoadjuvant Chemotherapy. Clin Cancer Res 2020; 26 (13) 3271-3279
• 37 Xie R, Chung JY, Ylaya K, Williams RL, Guerrero N, Nakatsuka N. et al. Factors influencing the degradation of archival formalin-fixed paraffin-embedded tissue sections. J Histochem Cytochem 2011; 59 (04) 356-365
• 38 Grillo F, Pigozzi S, Ceriolo P, Calamaro P, Fiocca R, Mastracci L. Factors affecting immunoreactivity in long-term storage of formalin-fixed paraffin-embedded tissue sections. Histochem Cell Biol 2015; 144 (01) 93-99
• 39 Taieb J, Svrcek M, Cohen R, Basile D, Tougeron D, Phelip JM. Deficient mismatch repair/microsatellite unstable colorectal cancer: Diagnosis, prognosis and treatment. Eur J Cancer 2022; 175: 136-157
• 40 Zhang X, Wu T, Cai X, Dong J, Xia C, Zhou Y. et al. Neoadjuvant Immunotherapy for MSI-H/dMMR Locally Advanced Colorectal Cancer: New Strategies and Unveiled Opportunities. Front Immunol 2022; 13: 795972
• 41 Sei S, Ahadova A, Keskin DB, Bohaumilitzky L, Gebert J, Doeberitz MvK. et al. Lynch syndrome cancer vaccines: A roadmap for the development of precision immunoprevention strategies. Front Oncol 2023; 13: 1147590
• 42 Hernandez-Sanchez A, Grossman M, Yeung K, Sei SS, Lipkin S, Kloor M. Vaccines for immunoprevention of DNA mismatch repair deficient cancers. J Immunother Cancer 2022; 10 (06) e004416
• 43 Hildebrand LA, Pierce CJ, Dennis M, Paracha M, Maoz A. Artificial Intelligence for Histology-Based Detection of Microsatellite Instability and Prediction of Response to Immunotherapy in Colorectal Cancer. Cancers (Basel) 2021; 13 (03) 391
• 44 Ryan E, Sheahan K, Creavin B, Mohan HM, Winter DC. The current value of determining the mismatch repair status of colorectal cancer: A rationale for routine testing. Crit Rev Oncol Hematol 2017; 116: 38-57
• 45 Syngal S, Brand RE, Church JM, Giardiello FM, Hampel HL, Burt RW. American College of Gastroenterology. ACG clinical guideline: Genetic testing and management of hereditary gastrointestinal cancer syndromes. Am J Gastroenterol 2015; 110 (02) 223-262 , quiz 263
• 46 Gupta S, Provenzale D, Llor X, Halverson AL, Grady W, Chung DC. et al. NCCN Guidelines Insights: Genetic/Familial High-Risk Assessment: Colorectal, Version 2.2019. J Natl Compr Canc Netw 2019; 17 (09) 1032-1041
• 47 Giardiello FM, Allen JI, Axilbund JE, Boland CR, Burke CA, Burt RW. et al; US Multi-Society Task Force on Colorectal Cancer. Guidelines on genetic evaluation and management of Lynch syndrome: a consensus statement by the US Multi-Society Task Force on colorectal cancer. Gastroenterology 2014; 147 (02) 502-526
• 48 Giardiello FM, Allen JI, Axilbund JE, Boland CR, Burke CA, Burt RW. et al. Guidelines on genetic evaluation and management of Lynch syndrome: a consensus statement by the US Multi-Society Task Force on Colorectal Cancer. Dis Colon Rectum 2014; 57 (08) 1025-1048

Publication History

Received: 04 October 2024

Accepted: 04 August 2025

Article published online:
31 December 2025