Abstract
Background
Colorectal cancer (CRC) is the third most common cancer globally, with rising cases in Latin America. MSI-H and MMRd play key roles in CRC, but data on their prevalence in Hispanic/Latino populations are limited. This study evaluates these biomarkers in the region.
Methods
A systematic review and meta-analysis were conducted following PRISMA guidelinesin Medline, Virtual Health Library, Scopus, and Web of Science. Random-effects models were used to estimate pooled prevalence due to expected heterogeneity between studies. Studies (cohort and cross-sectional) that evaluated MMRd and/or MSI-H through IHC and PCR techniques in Hispanic/Latino individuals with colorectal cancer (whether sporadic, associated with Lynch Syndrome, or other forms), residing in Latin American countries or elsewhere, were included.
Results
A total of 52 studies including 10,596 patients were included. The pooled prevalence of mismatch repair deficiency (MMRd) and microsatellite instability-high (MSI-H) in Hispanic/Latino populations was 15% (95% CI: 10%–20%; I2 = 89.6%) and 18% (95% CI: 13%–24%; I2 = 84.0%), respectively. Costa Rica and Mexico had the highest MMRd prevalence (30% and 24%), while Uruguay showed the highest MSI-H prevalence (45%). MSI-H was significantly associated with female sex (OR: 1.83) and right-sided tumors (OR: 8.16). MMRd was associated with right-sided tumors compared with the rectum (OR: 1.73) and the left colon (OR: 5.65).
Conclusions
This meta-analysis underscores the unique prevalence of MMRd and MSI-H in Hispanics, highlighting regional variations and the need for broader representation.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00384-026-05146-2.
Keywords: MSI-high, Colorectal carcinoma, Mismatch repair, Hispanic/Latino population
Introduction
According to GLOBOCAN 2022, colorectal cancer (CRC) is the third most common cancer globally, with 1,926,425 new cases reported and an age-standardized rate of 18.4 per 100,000 people. It remains the second leading cause of cancer-related deaths, accounting for 903,859 fatalities in 2022. Notably, CRC incidence and mortality rates show significant geographical variation [1].
In Latin American countries, CRC mortality increased by 20.5% between 1990 and 2019, contrasting with declining rates in high-income countries [2]. Also, CRC incidence correlates with the Human Development Index (HDI), higher HDI levels are linked to greater incidence [3]. Although some Hispanic/Latino countries have achieved high HDI status due to economic progress, the region remains marked by income inequality and social vulnerability [2]. These disparities contribute to uneven access to biomarker technologies and treatments, creating significant heterogeneity in CRC diagnosis and management across the region [3].
Different biomarkers have been established for CRC, of which microsatellite instability (MSI) is one of the most recognized and clinically validated. MSI is crucial for screening hereditary syndromes, predicting prognosis, and guiding treatment decisions [4]. CRC can be classified based on MSI status into high microsatellite instability (MSI-H), low microsatellite instability (MSI-L), or microsatellite stable (MSS) [5]. MSI-H is a hypermutable phenotype caused by a defective DNA mismatch repair (MMR) system, often resulting from the inactivation of the MMR genes MSH2, MLH1, MSH6, and PMS2, which prevents the correction of insertion or deletion errors during DNA replication [6].
MSI-H CRC exhibits distinct histopathological features, including tumor-infiltrating lymphocytes (TILs), absence of dirty necrosis, Crohn-like reactions, right-sided tumor location, mucinous differentiation (focal or extensive), and either well- or poorly differentiated morphology. Additionally, MSI-H tumors are associated with a high neoantigen burden [7–9]. These characteristics render MSI-H CRC tumors highly responsive to immune checkpoint inhibitors, making them excellent candidates for immunotherapy [4, 10].
Approximately 15–17% of all CRC cases exhibit MSI-H. MSI can result from somatic alterations in MMR genes, such as pathogenic or likely pathogenic (P/LP) variants or MLH1 promoter methylation, which are commonly associated with sporadic CRC. Most of these cases (75%–80%) are linked to acquired MLH1 promoter methylation and the CpG island methylator phenotype (CIMP). Alternatively, MSI can arise from germline P/LP variants in MMR genes or EPCAM deletions, accounting for 2%–3% of CRC cases and characterizing Lynch syndrome [6].
Given the critical role of MSI in clinical decision-making for CRC, particularly in guiding chemotherapy and immunotherapy strategies, the American Society of Clinical Oncology (ASCO) underscores the importance of MSI testing. As a result, MSI status evaluation is now recommended for all CRC cases [10, 11].
MSI-H and MMR deficiency (MMRd) are closely related biomarkers that reflect defects in the DNA mismatch repair system in CRC. MSI can be assessed indirectly through MMR protein expression using immunohistochemistry (IHC), which screens for the loss of MMR proteins MLH1, MSH2, MSH6, and PMS2. MMRd is defined as the complete loss of at least one protein, while MMR proficiency (MMRp) is indicated by positive staining for all four proteins [12, 13]. Alternatively, MSI can be directly detected using polymerase chain reaction (PCR-MSI), which evaluates microsatellite markers such as BAT25, BAT26, D2S123, D5S346, and D17S2720. PCR is considered positive when instability is identified in at least two markers [14–17]. Although the MSI-H and MMRd are highly concordant, discordant results have been reported in a minority of cases due to technical and biological factors [4, 11, 12, 15, 18].
IHC is widely used for MSI detection due to its lower cost, faster turnaround time, and high accuracy, achieving a concordance rate of 98.4% between MSI-H and MMRd expression in CRC. [18] While PCR-MSI is part of the biomarker routine in some centers, it is primarily recommended for cases with discordant IHC results, as it provides a more detailed MSI assessment, particularly when discrepancies could influence treatment decisions [15, 19, 20]. Recently, Next Generation Sequencing (NGS-MSI) has gained attention with the increasing adoption of Comprehensive Genomic Profiling (CGP) in cancer biomarker analysis [12]. However, the 2022 CAP guidelines prioritize PCR and IHC-MMR over NGS-MSI for colorectal carcinoma, citing limited evidence for NGS, its high cost, and reduced accessibility in developing countries [21].
Some studies have reported varying biomarker prevalences across cancer types and patient populations [22–24]. Latin America and the Caribbean exhibit unique genetic backgrounds, cultural behaviors, environmental exposures, and socioeconomic heterogeneity, all of which may influence the prevalence of MSI alterations in CRC [25]. While studies suggest that the prevalence of MSI in CRC among Hispanic/Latino individuals is comparable to other ethnic groups [26, 27] comprehensive regional data remain scarce. This systematic review and meta-analysis aim to summarize the clinical characteristics and estimate the prevalence of MMRd and MSI-H biomarkers (MMRd/MSI-H) in CRC populations from Latin American countries and Hispanic individuals living outside the region.
Materials and methods
This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [28]. The protocol was registered in PROSPERO, the International Prospective Register of Systematic Reviews, under the identifier CRD42024573607.
Information sources and search strategy
A comprehensive search strategy was conducted across Medline, Virtual Health Library, Scopus, and Web of Science. The term Hispanic/Latino was defined to include individuals of Spanish ancestry in the United States and all Latin American countries, including Brazil. As a result, the search incorporated the term "Hispanic or Latino." Specific Medical Subject Headings (MeSH) terms such as "Colonic Neoplasms," "DNA Mismatch Repair," and "Microsatellite Instability" were also used (Supplementary Table 1). Grey literature was accessed through Google Scholar, and the final database search was completed on May 31, 2024. The language was restricted to English, Spanish and Portuguese. Additionally, a manual review of reference lists from selected articles was conducted.
Inclusion criteria
The inclusion criteria for this systematic review encompassed original cohort and cross-sectional studies that evaluated MMRd or MSI-H through IHC and PCR techniques in Hispanic/Latino individuals with colorectal cancer (whether sporadic, associated with Lynch Syndrome, or other forms), residing in Latin American countries or elsewhere. NGS-MSI was not included due to the pre-defined limitations in accessing NGS technologies in Hispanic/Latino populations. The studies required to have performed IHC and/or PCR-MSI testing on tumor tissue. There were no language restrictions, and the search was conducted up to May 2024.
For the purposes of this review, Hispanic/Latino populations were defined according to the classifications used in the original studies. This included individuals from Latin American countries as well as populations identified as Hispanic or Latino in studies conducted in other regions, particularly the United States (US). In most studies, ethnicity was determined by geographic origin or self-reported ethnicity. Given the complex genetic ancestry and admixture characteristic of Latin American populations, which includes varying contributions of Indigenous American, European, and African ancestries, the term Hispanic/Latino was used as reported by the original authors rather than representing a genetically homogeneous group [22, 25, 29].
Exclusion criteria
The exclusion criteria for this review were as follows: a) Studies that assessed fewer than 4 MMR proteins (MLH1, MSH2, MSH6, PMS2), b) Studies that presented inconsistencies between the text and the data reported in tables, c) Studies that did not differentiate molecular alteration information between Hispanic/Latino individuals and other ethnic groups, d) Studies that evaluated MMRd/MSI-H status exclusively in a subset of individuals with a specific molecular alteration.
Study selection
Articles selected were assessed by four primary reviewers (GGG, DMG, JCC, VCC) that independently screened the titles and abstracts of the studies to determine eligibility. The same reviewers then conducted a thorough assessment of the full texts of the selected articles, excluding those that did not meet the established criteria. References of identified studies were reviewed to find additional relevant articles. Discrepancies among the reviewers were resolved by a fifth author (RPM or JCR).
Data collection process and data extraction
The following information was extracted from each article, when available: authors, year of publication, country, study period, population size, age, sex, MMR/MSI assessment methods, prevalence of MMRd/MSI-H, affected MMR proteins, and tumor size, location, histological type, and stage.
Risk of bias and applicability
Risk of bias was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for cohort and cross-sectional studies was implemented [30]. Three authors (GGG, DFMG, RPM) answered eight questions for cross-sectional studies and eleven questions for cohort studies. Each question was rated as ‘yes’, no’, ‘unclear’, or ‘not applicable’. A scoring system was applied by calculating the proportion of “Yes” responses. Studies with ≥ 70% “Yes” responses were considered at low risk of bias, those with 50–69% at moderate risk, and those with < 50% at high risk.
Summary measures
The primary outcomes of this study were the prevalence of MMRd/MSI-H tumors among cases of colorectal cancer in Hispanic/Latino individuals. Prevalence was calculated as the proportion of MMRd/MSI-H cases relative to the total number of tests conducted, with country-specific prevalence also determined. Furthermore, ORs for MMRd/MSI-H were calculated in relation to age, gender, tumor stage, location, and histological subtype.
Data synthesis and analysis
Quantitative analyses of the included studies were conducted in R version 4.3.1 using the meta and metafor packages. Two separate meta-analyses with a random-effects model were performed to estimate the prevalence of MMRd/MSI-H among Hispanic/Latino individuals with colorectal cancer. Additionally, we employed ORs with corresponding confidence intervals to assess the correlation between MMRd/MSI-H and various clinicopathological features. Meta-analyses were conducted using Review Manager 5.4.1 software from the Cochrane Collaboration. A random-effects model was selected expecting substantial clinical and methodological heterogeneity across studies. Heterogeneity was assessed with Cochran's Q and quantified with the I2 statistic, interpreted as low (≤ 25%), moderate (25–75%), or high (> 75%). A significance level of 5% was used, and heterogeneity was assessed according to sample size, country, and study design. Geographic heterogeneity was explored descriptively through country-based subgroups displayed in the forest plots. Formal subgroup or meta-regression analyses according to diagnostic modality, tumor stage, or Lynch syndrome inclusion were not performed because the required study-level data were incomplete, inconsistently reported, or not directly comparable across reports.
MMRd and MSI-H were conceptually grouped as complementary markers of mismatch repair dysfunction in colorectal cancer, because both are used to identify tumors with defective mismatch repair biology and have relevance for molecular classification, Lynch syndrome screening, prognosis, and therapeutic decision-making [31, 32]. However, they were analyzed separately because they are not identical biomarkers, and clinically meaningful discordance has been documented despite their high overall concordance [15]. Discordant cases could not be reclassified at the review level because the primary studies did not consistently report paired assay-level results or explicit adjudication algorithms; therefore, cases were synthesized according to the endpoint reported by the original authors [15, 32].
Sensitivity analysis
To assess the robustness of the pooled prevalence estimates in the presence of substantial heterogeneity, we performed leave-one-out sensitivity analyses for both the MMRd and MSI-H meta-analyses using the metafor package in R. Each study was sequentially omitted, and the random-effects model was re-estimated using restricted maximum likelihood (REML) under the same analytical assumptions as in the primary analyses. The leave-one-out analyses were presented as Figure S1 (MMRd) and Figure S2 (MSI-H).
Results
Results of the search and screening
The PRISMA flow diagram, shown in Fig. 1 summarizes the search process. After removing duplicates, 591 records were screened based on their titles and abstracts. Following this initial screening, 101 articles were selected for full-text assessment, and 49 studies were excluded because they did not meet the inclusion criteria. Finally, 52 studies were included in the review, 40 cross-sectional studies and 12 cohort studies. Of these, 22 studies evaluated MMR only, 24 focused on MSI only, and 4 assessed both MMR and MSI. Most of the studies were from Brazil, with 18 articles, followed by 7 studies on Hispanic individuals living in the United States. The countries of the other participants were Chile (n = 5), Colombia (n = 5), Puerto Rico (n = 5), Argentina (n = 3), Mexico (n = 3), Peru (n = 4), Dominican Republic (n = 1), Costa Rica (n = 1), Ecuador (n = 1), and Paraguay (n = 1).
Fig. 1.
Search strategy
General clinical information
Clinical data were extracted from 52 articles, encompassing a total of 10,596 individuals. Among studies evaluating MMRd, the mean age of participants was 58.71 years. Of these, 63.4% (1928/3041) were male, 69.7% (1667/2391) had tumors located in the left colon or rectum, 52.2% (70/134) presented with non-mucinous adenocarcinoma histology, and 55.8% (663/1188) had stage III-IV tumors (Table 1). In studies assessing MSI status, the mean age was 64.17 years. Of the participants, 71.8% (1039/1448) were male, 67.4% (807/1198) had tumors in the left colon or rectum, 72.6% (98/135) displayed a non-mucinous adenocarcinoma histological subtype, and 53.9% (96/178) had stage III-IV tumors (Table 2).
Table 1.
Clinical characteristics of patients included with MMR status by country
| MMR Status | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Author/Year | Country/Region | Type of study | Type of test performed | Mean age | Total | Gender | Location | |||||||
| dMMR | pMMR | Male | Female | Right colon | Left colon/Rectum | |||||||||
| dMMR | pMMR | dMMR | pMMR | dMMR | pMMR | dMMR | pMMR | |||||||
| Antelo et al. 2019 [33] | Argentina | Cross-sectional | PCR & IHC | 34.52 | 21 | 81 | 10 | 41 | 11 | 40 | 12 | 14 | 9 | 67 |
| Schmitz et al. 2014 [34] | Argentina | Cross-sectional | IHC | 57 | 16 | 41 | 10 | 56 | 6 | 43 | - | - | - | - |
| Azambuja et al. 2023 [35] | Brazil | Cohort | PCR & IHC | 64 | 8 | 55 | - | - | - | - | - | - | - | - |
| Berardinelli et al. 2018 [36] | Brazil | Cohort | PCR & IHC | 57.8 | 102 | 886 | 528 | - | - | - | 238 | - | 520 | - |
| De Freitas et al. 2015 [37] | Brazil | Cross-sectional | PCR & IHC | 68 | 8 | 53 | 8 | - | 4 | - | - | 6 | 5 | - |
| Germini et al. 2019 [38] | Brazil | Cohort | PCR & IHC | 65.4 | 4 | 57 | - | - | - | - | - | - | - | - |
| Gomes et al. 2021 [39] | Brazil | Cross-sectional | IHC | 56.8 | 78 | 920 | - | - | - | - | - | - | - | - |
| Alex et al. 2017 [40] | Brazil | Cross-sectional | IHC | 52 | 41 | 84 | 28 | 38 | 13 | 46 | 26 | 21 | 15 | 63 |
| Paula Simedan Vila et al. 2023 [41] | Brazil | Cross-sectional | IHC | 60 | 43 | 327 | 20 | 179 | 23 | 148 | - | - | - | - |
| Sunagua Aruquipa et al. 2024 [42] | Brazil | Cross-sectional | PCR & IHC | 63,7 | 14 | 844 | - | - | - | - | - | - | - | - |
| Gómez-Rodríguez et al. 2021 [43] | Colombia | Cross-sectional | IHC | 69 | 12 | 74 | 9 | 36 | 3 | 38 | 8 | 37 | 2 | 37 |
| Shamek et al. 2016 [44] | Colombia & USA | Cross-sectional | IHC | 63 | 11 | 52 | 6 | 18 | 5 | 16 | - | - | - | - |
| Allan et al. 2020 [45] | Costa Rica | Cohort | IHC | 66.5 | 165 | 388 | 120 | 268 | 47 | 120 | 72 | 42 | 92 | 346 |
| Quezada-Diaz et al. 2022 [46] | Chile | Cross-sectional | IHC | - | 8 | 57 | - | - | - | - | 5 | 16 | 3 | 41 |
| Bacilio et al. 2018 [47] | Ecuador | Cross-sectional | IHC | 66.2 | 182 | 58 | 71 | 20 | 111 | 38 | - | - | - | - |
| Lopez-Correa et al. 2018 [48] | Mexico | Cross-sectional | IHC | 59 | 43 | 159 | 24 | 95 | 19 | 64 | 17 | 18 | 22 | 140 |
| De De Mexico et al. 2022 [49] | Mexico | Cross-sectional | IHC | 65 | 39 | 105 | 21 | 57 | 18 | 48 | 27 | 35 | 12 | 70 |
| Fleitas-Kanonnikoff et al. 2019 [50] | Paraguay | Cohort | IHC | 52 | 5 | 31 | 2 | 21 | 3 | 10 | 2 | 12 | 3 | 19 |
| Egoavil et al. 2011 [51] | Peru | Cross-sectional | IHC | 59.3 | 35 | 54 | - | - | - | - | - | - | - | - |
| Carbajal et al. 2014 [52] | Peru | Cross-sectional | IHC | - | 1 | 2 | - | - | - | - | - | - | - | - |
| De Jesus-Monge et al. 2010 [53] | Puerto Rico | Cross-sectional | PCR & IHC | 59.9 | 7 | 157 | 3 | 67 | 4 | 90 | - | - | - | - |
| Sierra et al. 2021 [54] | Puerto Rico | Cross-sectional | IHC & PCR (Only MMR reported) | 65,8 | 3 | 26 | 11 | 161 | 24 | 121 | 25 | 91 | 10 | 191 |
| Cruz-Correa et al. 2015 [55] | Puerto rico & Dominican Republic | Cross-sectional | PCR & IHC | - | 13 | 45 | - | - | - | - | - | - | - | - |
| Barrows et al. 2017 [56] | U.S.A hispanics | Cross-sectional | IHC | 53,9 | 14 | 88 | - | - | - | - | - | - | - | - |
| Berera et al. 2016 [57] | U.S.A hispanics | Cross-sectional | IHC | 60 | 13 | 90 | - | - | - | - | - | - | - | - |
| Ricker et al. 2017 [58] | U.S.A hispanics | Cross-sectional | PCR & IHC | 53,7 | 21 | 140 | - | - | - | - | - | - | - | - |
| Fangman et al. 2021 [59] | U.S.A hispanics | Cohort | IHC | 42 | 28 | 106 | - | - | - | - | - | - | - | - |
| Gupta et al. 2010 [27] | U.S.A hispanics | Cohort | PCR & IHC | 57 | 14 | 85 | - | - | - | - | - | - | - | - |
| Hoffman et al. 2018 [60] | U.S.A hispanics | Cross-sectional | IHC | 61.3 | 4 | 35 | - | - | - | - | - | - | - | - |
| Reverón et al. 2018 [61] | U.S.A hispanics | Cross-sectional | IHC | - | 6 | 89 | - | - | - | - | - | - | - | - |
| MMR Status | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Author/Year | Histology subtype | Stage | ||||||||||
| Mucinous adenocarcinoma | Conventional adenocarcinoma | I | II | III | IV | |||||||
| dMMR | pMMR | dMMR | pMMR | dMMR | pMMR | dMMR | pMMR | dMMR | pMMR | dMMR | pMMR | |
| Antelo et al. 2019 [33] | - | - | - | - | I—II: MMRd = 11, MMRp = 26, III—IV: MMRd = 10, MMRp = 55 | |||||||
| Schmitz et al. 2014 [34] | - | - | - | - | - | - | - | - | - | - | - | - |
| Azambuja et al. 2023 [35] | - | - | - | - | - | - | - | - | - | - | - | - |
| Berardinelli et al. 2018 [36] | - | - | - | - | - | - | - | - | - | - | - | - |
| De Freitas et al. 2015 [37] | 1 | - | - | - | 3 | - | 4 | - | - | - | 2 | - |
| Germini et al. 2019 [38] | - | - | - | - | - | - | - | - | - | - | - | - |
| Gomes et al. 2021 [39] | - | - | - | - | - | - | - | - | - | - | - | - |
| Alex et al. 2017 [40] | 17 | 13 | - | - | - | - | - | - | - | - | - | - |
| Paula Simedan Vila et al. 2023 [41] | - | - | - | - | - | - | - | - | - | - | - | - |
| Sunagua Aruquipa et al. 2024 [42] | - | - | - | - | - | - | - | - | - | - | - | - |
| Gómez-Rodríguez et al. 2021 [43] | 3 | 10 | 8 | 62 | - | - | - | - | - | - | - | - |
| Shamekh et al. 2016 [44] | - | - | - | - | - | - | - | - | - | - | - | - |
| Allan et al. 2020 [45] | - | - | - | - | 20 | 12 | 36 | 163 | 58 | 141 | 52 | 72 |
| Quezada-Diaz et al. 2022 [46] | - | - | - | - | - | 2 | 2 | 20 | 5 | 23 | 1 | 12 |
| Bacilio et al. 2018 [47] | - | - | - | - | 27 | 9 | 54 | 22 | 45 | 14 | 56 | 13 |
| Lopez-Correa et al. 2018 [48] | 6 | 14 | - | - | 5 | 8 | 11 | 15 | 9 | 21 | 4 | 10 |
| De De Mexico et al. 2022 [49] | - | - | - | - | - | - | - | - | - | - | - | - |
| Fleitas-Kanonnikoff et al. 2019 [50] | - | - | - | - | - | - | - | - | - | - | - | - |
| Egoavil et al. 2011 [51] | - | - | - | - | - | - | - | - | - | - | - | - |
| Carbajal et al. 2014 [52] | - | - | - | - | - | - | - | - | - | - | - | - |
| De Jesus-Monge et al. 2010 [53] | - | - | - | - | - | 9 | 3 | 63 | 3 | 43 | 1 | 13 |
| Sierra et al. 2021 [54] | - | - | - | - | - | - | - | - | - | - | - | - |
| Cruz-Correa et al. 2015 [55] | - | - | - | - | - | - | - | - | - | - | - | - |
| Barrows et al. 2017 [56] | - | - | - | - | - | - | - | - | - | - | - | - |
| Berera et al. 2016 [57] | - | - | - | - | - | - | - | - | - | - | - | - |
| Ricker et al. 2017 [58] | - | - | - | - | - | - | - | - | - | - | - | - |
| Fangman et al. 2021 [59] | - | - | - | - | - | - | - | - | - | - | - | - |
| Gupta et al. 2010 [27] | - | - | - | - | - | - | - | - | - | - | - | - |
| Hoffman et al. 2018 [60] | - | - | - | - | - | - | - | - | - | - | - | - |
| Reverón et al. 2018 [61] | - | - | - | - | - | - | - | - | - | - | - | - |
Table 2.
Clinical characteristics of patients included with MSI status by country
| MSI Status | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Author/Year | Country/Region | Type of study | Type of test performed | Mean age | Total | Sex | Location | |||||||
| MSI | MSS | Male | Female | Right colon | Left colon | |||||||||
| MSI | MSS | MSI | MSS | MSI | MSS | MSI | MSS | |||||||
| Lerda et al. 2019 [62] | Argentina | Cross-sectional | PCR | 60.6 | 4 | 27 | 3 | 16 | 1 | 11 | - | - | - | - |
| Sánchez et al. 2020 [63] | Argentina | Cross-sectional | PCR & IHC | - | 11 | 99 | - | - | - | - | - | - | - | - |
| Anacleto et al. 2005 [64] | Brazil | Cross-sectional | PCR | 63 | 14 | 92 | - | - | - | - | 13 | 9 | 5 | 65 |
| Berardinelli et al. 2018 [36] | Brazil | Cohort | PCR & IHC | 57.8 | 106 | 907 | 528 | - | - | - | - | 238 | 520 | - |
| da Silva et al. 2015 [65] | Brazil | Cross-sectional | PCR | - | 43 | 123 | - | - | - | - | - | - | - | - |
| De Freitas et al. 2015 [37] | Brazil | Cross-sectional | PCR & IHC | 68 | 12 | 49 | 8 | - | 4 | - | 6 | - | 5 | - |
| de Oliveira et al. 2023 [66] | Brazil | Cross-sectional | PCR & IHC | - | 10 | 112 | 7 | 57 | 55 | 3 | 40 | 8 | 2 | 72 |
| dos Santos et al. 2019 [67] | Brazil | Cohort | PCR | 61 | 12 | 78 | - | - | - | - | - | - | - | - |
| Moraes Losso et al. 2012 [68] | Brazil | Cross-sectional | PCR | - | 16 | 22 | - | - | - | - | - | - | - | - |
| Leite et al. 2010 [69] | Brazil | Cross-sectional | PCR | - | 15 | 51 | - | - | - | - | - | - | - | - |
| Proença et al. 2018 [70] | Brazil | Cross-sectional | PCR | 63 | 7 | 36 | - | - | - | - | - | - | - | - |
| Rasuck et al. 2012 [71] | Brazil | Cross-sectional | PCR & MLPA | - | 16 | 61 | - | - | - | - | - | - | - | - |
| Santos et al. 2024 [72] | Brazil | Cohort | PCR & Sanger | - | 7 | 200 | 5 | 110 | 2 | 94 | - | 4 | 3 | - |
| Afanador et al. 2022 [73] | Colombia | Cross-sectional | PCR | - | 12 | 32 | - | - | - | - | - | - | - | - |
| Cardenas et al. 2008 [74] | Colombia | Cross-sectional | PCR | - | 3 | 8 | 5 | - | 6 | - | - | - | - | - |
| Montenegro et al. 2006 [75] | Colombia | Cross-sectional | PCR | - | 11 | 30 | - | - | - | - | - | - | - | - |
| Alvarez et al. 2021 [76] | Chile | Cohort | PCR | - | 74 | 342 | 5 | 110 | 2 | 94 | 4 | - | 3 | - |
| Hurtado et al. 2015 [77] | Chile | Cross-sectional | PCR | - | 15 | 43 | 7 | 21 | 8 | 22 | 11 | - | 4 | - |
| MAríA Wielandt et al. 2017 [78] | Chile | Cross sectional | PCR & IHC | 70 | 9 | 44 | 4 | 25 | 5 | 19 | 12 | 8 | 1 | 32 |
| Wielandt et al. 2020 [79] | Chile | Cohort | PCR | 66 | 15 | 88 | 8 | 59 | 7 | 29 | 20 | 13 | 2 | 68 |
| Jordi et al. n.d. [80] | Mexico | Cross-sectional | PCR | - | 10 | 20 | - | - | - | - | 5 | 0 | 5 | 20 |
| Ortiz et al. 2016 [81] | Peru | Cross-sectional | Electrophoresis and PCR | - | 11 | 17 | - | - | - | - | - | - | - | - |
| Perez-Mayoral et al. 2023 [82] | Puerto Rico | Cross-sectional | PCR & IHC | - | 6 | 186 | - | - | - | - | - | - | - | - |
| Sierra et al. 2021 [54] | Puerto Rico | Cross-sectional | PCR & IHC | - | 3 | 26 | - | - | - | - | - | - | - | - |
| Cruz-Correa et al. 2015 [55] | Puerto rico & Dominican Republic | Cross-sectional | PCR & IHC | - | 8 | 22 | - | - | - | - | - | - | - | - |
| Vital et al. 2023 [83] | Uruguay | Cross-sectional | PCR | 61.7 | 54 | 54 | 31 | 30 | 23 | 24 | - | - | - | - |
| Antelo et al. 2019 [33] | U.S.A hispanics | Cross-sectional | PCR & IHC | - | 54 | 48 | - | - | - | - | - | - | - | - |
| Gupta et al. 2010 [27] | U.S.A hispanics | Cohort | PCR & IHC | - | 11 | 100 | - | - | - | - | - | - | - | - |
| MSI Status | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Author/Year | Histology subtype | Stage | ||||||||||
| Mucinous adenocarcinoma | Conventional adenocarcinoma | I | II | III | IV | |||||||
| MSI | MSS | MSI | MSS | MSI | MSS | MSI | MSS | MSI | MSS | MSI | MSS | |
| Lerda et al. 2019 [62] | - | - | - | - | - | - | - | - | - | - | - | - |
| Sánchez et al. 2020 [63] | - | - | - | - | - | - | - | - | - | - | - | - |
| Anacleto et al. 2005 [64] | - | - | - | - | - | - | - | - | - | - | - | - |
| Berardinelli et al. 2018 [36] | - | - | - | - | - | - | - | - | - | - | - | - |
| da Silva et al. 2015 [65] | - | - | - | - | - | - | - | - | - | - | - | - |
| De Freitas et al. 2015 [37] | 1 | - | - | - | 3 | 4 | - | - | - | 2 | - | |
| de Oliveira et al. 2023 [66] | 3 | 18 | 6 | 92 | - | - | - | - | - | - | - | - |
| dos Santos et al. 2019 [67] | - | - | - | - | - | - | - | - | - | - | - | - |
| Moraes Losso et al. 2012 [68] | - | - | - | - | - | - | - | - | - | - | - | - |
| Leite et al. 2010 [69] | - | - | - | - | - | - | - | - | - | - | - | - |
| Proença et al. 2018 [70] | - | - | - | - | - | - | - | - | - | - | - | - |
| Rasuck et al. 2012 [71] | - | - | - | - | - | - | - | - | - | - | - | - |
| Santos et al. 2024 [72] | - | - | - | - | - | - | 5 | - | 3 | - | - | - |
| Afanador et al. 2022 [73] | - | - | - | - | - | - | - | - | - | - | - | - |
| Cardenas et al. 2008 [74] | - | - | - | - | - | - | - | - | - | - | - | - |
| Montenegro et al. 2006 [75] | - | - | - | - | - | - | - | - | - | - | - | - |
| Alvarez et al. 2021 [76] | - | - | - | - | - | - | - | - | - | - | - | - |
| Hurtado et al. 2015 [77] | - | - | - | - | - | - | - | - | - | - | - | - |
| MAríA Wielandt et al. 2017 [78] | 4 | 11 | - | - | - | - | - | - | - | - | - | - |
| Wielandt et al. 2020 [79] | - | - | - | - | - | - | - | - | - | - | - | - |
| Jordi et al. n.d. [80] | - | - | - | - | - | - | - | - | - | - | - | - |
| Ortiz et al. 2016 [81] | - | - | - | - | - | - | - | - | - | - | - | - |
| Perez-Mayoral et al. 2023 [82] | - | - | - | - | - | - | - | - | - | - | - | - |
| Sierra et al. 2021 [54] | - | - | - | - | - | - | - | - | - | - | - | - |
| Cruz-Correa et al. 2015 [55] | - | - | - | - | - | - | - | - | - | - | - | - |
| Vital et al. 2023 [83] | - | - | - | - | 6 | 3 | 20 | 17 | 22 | 31 | 6 | 3 |
| Antelo et al. 2019 [33] | - | - | - | - | - | - | - | - | - | - | - | - |
| Gupta et al. 2010 [27] | - | - | - | - | - | - | - | - | - | - | - | - |
Altered markers were analyzed in 348 individuals from the MMRd group and 156 individuals assessed for MSI. In the MMRd group, the most frequent protein expression losses observed via IHC were MLH1/PMS2 in combination (156/348, 44.8%), followed by MSH2/MSH6 in combination (72/348, 20.7%). Other losses included MSH2 individually (40/348, 11.5%), MLH1 individually (35/348, 10.1%), PMS2 individually (23/348, 6.6%), and MSH6 individually (21/348, 6.0%). The least common marker was the combined loss of MSH2, MSH6, and MLH1 (1/348, 0.3%). Due to incomplete reporting of the microsatellites included in PCR-MSI panels or missing information in some studies, it was not possible to confirm the consistency of MSI results across studies.
MMRd/MSI-H prevalence in Hispanic/Latinos
Among the 28 articles reporting the prevalence of MMRd, a total of 6,475 individuals with available tests were included from Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Mexico, Paraguay, Peru, Puerto Rico, and Hispanic individuals in the U.S. The pooled MMRd prevalence was found to be 15% (95% CI: 10%−20%), with heterogeneity (I2 = 92%, P < 0.001) (Fig. 2). In the 28 articles that reported the prevalence of MSI-H, involving a total of 3,760 individuals with available tests from Argentina, Brazil, Chile, Colombia, Mexico, Peru, Puerto Rico, the Dominican Republic, Uruguay, and Hispanic individuals in the U.S, the pooled MSI-H prevalence was 18% (95% CI: 13%−24%) (Fig. 3).
Fig. 2.
Meta-analysis of MMRd frequency
Fig. 3.
Meta-analysis of MSI-H frequency
Country-based subgroup differences were statistically significant in both analyses (MMRd: χ2 = 63.19, P < 0.001; MSI-H: χ2 = 56.72, P < 0.001). Country-specific assessments revealed that Costa Rica had the highest MMRd prevalence at 30% (95% CI: 26%−34%), followed by Mexico at 24% (95% CI: 19%−30%). In contrast, Puerto Rico exhibited the lowest MMRd prevalence at only 8% (95% CI: 5%−15%). For MSI-H, Uruguay had the highest prevalence 45% (95% CI: 27%−64%), followed by Peru at 42% (95% CI: 32%−52%) and Mexico at 33% (95% CI: 17%−53%). Puerto Rico had the lowest MSI-H prevalence at 5% (95% CI: 2%−16%) (Fig. 4).
Fig. 4.
Prevalence of MMRd and MSI-H in Latin American countries
Clinicopathological features correlated with MMRd/MSI-H status
A second meta-analysis was conducted to evaluate the relationship between clinicopathological features and MMRd/MSI-H (Supplementary Table 2). The results indicated that MSI-H was significantly associated with females, with an OR of 1.83 (1.40–2.39). Additionally, MMRd was significantly associated with tumors in the right colon compared to the rectum (OR: 1.73, 1.39–2.16) and with right-sided tumors compared to the left colon (OR: 5.65, 4.20–7.60). Similarly, MSI-H was more frequent in right-sided tumors compared to the left colon, with an OR of 8.16 (5.40–12.33).
In this study, no significant associations were observed between MMRd and sex or between MSI-H and tumor stage. This finding is likely due to the inclusion of these variables for descriptive purposes only, as they did not meet the inclusion criteria for the meta-analysis due to insufficient or inconsistent data across studies. Moreover, limitations in available data on histological type and TNM classification prevented a proper meta-analysis of these variables.
In the MMRd meta-analysis, the primary pooled proportion was 0.1315 (95% CI 0.1045–0.1642), with substantial heterogeneity (I2 = 89.6%; tau2 = 0.4289). Leave-one-out analysis showed only modest variation in the pooled estimate; the greatest change was observed after omission of Aruquipa et al. 2024 (Brazil) (33), which increased the pooled proportion to 0.1407 (95% CI 0.1151–0.1708) and reduced tau2 to 0.3624, while heterogeneity remained high.
In the MSI-H meta-analysis, the primary pooled proportion was 0.1946 (95% CI 0.1571–0.2385), also with substantial heterogeneity (I2 = 84.0%; tau2 = 0.3739). Sequential omission of individual studies again produced only modest changes in the pooled estimate. The largest change was observed after omission of Perez-Mayoral et al. 2023 (Puerto Rico) [82], which increased the pooled proportion to 0.2035 (95% CI 0.1671–0.2455) and reduced tau2 to 0.2974 and I2 to 81.0%. Influence diagnostics identified this study as the most influential observation in the MSI-H model; however, its exclusion did not materially change the overall interpretation, supporting the robustness of the pooled estimate despite persistent between-study heterogeneity.
Quality assessment
A total of 52 articles underwent quality assessment. Most studies met the JBI criteria for cross-sectional (n = 41) and cohort studies (n = 11). However, among the cross-sectional studies, many did not account for confounding factors (n = 35), and a few did not report the statistical methods used (n = 4). In the cohort study group, some studies also failed to identify confounding factors (n = 5), and others did not address strategies for managing incomplete follow-up (n = 6). All included studies were classified as having a low risk of bias. Therefore, no studies were excluded based on quality assessment, and additional sensitivity analyses excluding high-risk studies were not considered necessary. The quality assessment for each study is detailed in Supplementary Table 3A and B.
Discussion
Latin America is a highly diverse region with significant genetic variation, influenced by Native American (NAT), European (EUR), and African (AFR) ancestries. This makes it a unique area for studying colorectal cancer (CRC) biomarkers. Some studies suggest that genetic ancestry does not significantly affect the prevalence of MSI-H tumors [26, 84], while others report a higher prevalence of MSI-H tumors in European and African populations. A recent study by Matejcic et al. (2024), using whole-genome sequencing (NGS-MSI), found that NAT ancestry is associated with a lower frequency of MSI-H tumors compared to microsatellite-stable tumors (OR = 0.45, 95% CI = 0.21–0.99, p = 0.048) [32]. This highlights the relationship between genetic ancestry and tumor prevalence in the region.
In Hispanic/Latino populations, a recent meta-analysis of 201 studies from Europe, Asia, and North America reported prevalences of 11.7% for MMRd and 10.2% for MSI-H [85]. In our study of Hispanic/Latino populations, MMRd, detected by IHC, was present in 15% of cases, while MSI-H tumors were found in 18% of cases. These rates are higher than those reported by Ashktorab et al. (2016), who found an overall MSI prevalence of 12% across six studies focusing on Hispanic populations [26].
A country-by-country analysis showed notable differences in MMRd and MSI-H prevalence. This heterogeneity was also reflected in the meta-analysis (I2 = 86%), indicating substantial variability between studies. Costa Rica had the highest prevalence of MMRd at 30%, followed by Mexico at 24%, while Uruguay and Peru had the highest prevalence of MSI-H at (45% and 24% respectively). The high European ancestry in Costa Rica and Mexico, due to colonial and post-colonial migrations [42, 82, 84, 86], may explain their higher prevalence of MSI-H. On the other hand, both Mexico and Peru have high NAT ancestry [87–89], which was linked to lower MSI-H tumor frequencies in the study by Matejcic et al. [86]. These differences could be due to the methods used, as our study employed PCR-MSI and IHC-MSI, while Matejcic et al. used NGS-MSI. However, these country-specific differences highlight the genetic diversity within Hispanic/Latino populations and show the complexity of how ancestry influences MSI prevalence.
Several studies have suggested that differences in MMRd/MSI-H prevalence between Hispanic/Latino populations and other groups may be due to the higher rate of germline pathogenic/likely pathogenic (P/LP) variants in MMR genes (Lynch Syndrome) [27, 90, 91]. Hispanic/Latino individuals have a higher frequency of germline P/LP variants in MMR genes compared to Black/African American and White individuals (18.1% vs. 9.5% and 8.1%, respectively). Among individuals with CRC, Hispanic/Latino populations also show higher rates of P/LP variants compared to White, Asian, and Black individuals (18% vs. 16.2%, 12.6%, and 6.7%, respectively) [92]. A meta-analysis found that around 2.2% of all CRC cases carry germline P/LP variants in MMR genes across populations from Oceania, Europe, Asia, and North America [93]. In contrast, these variants account for 5–8% of CRC cases in Colombia [94] and 3.7% in Mexico [95]. In Brazil, germline P/LP variants in MMRd tumors were reported at 49% [42], much higher than the 33% observed in the U.S [96]. and 12.2% in Australia [97].
Additionally, Ricker et al. [91] reported that 13.0% of CRC tumors in Latino individuals exhibited MMRd, with 61.9% of these cases attributed to germline mutations in MMR genes. Across all age groups, CRC patients with germline variants, especially in MLH1, were often younger than 50 years, which is typical for Lynch syndrome. This suggests that sporadic MSI CRC may be less common in Hispanic individuals, and a significant proportion of MSI cases may be linked to Lynch syndrome [27].
Most studies reviewed here reported an average age of over 50 years for individuals with MMRd and MSI-H, except for Antelo M et al. [33] and Fangman BD et al. [59] in the MMR group (Table 1). Our study also found a significant association between female gender, right-sided tumors, and MSI-H, consistent with findings by Liang et al., who reported similar patterns in Asian populations (female: 54.1%, right-sided: 63.9% in IHC-MSI tumors) [98].
While the right-sided tumor pattern aligns with the clinical presentation of Lynch syndrome, the gender distribution contrasts with Lynch syndrome, which is more common in males, with higher lifetime risks (54–74%) compared to females (30–52%) [99]. The earlier onset of CRC in males compared to females further complicates the understanding of whether germline variants account for most MMRd/MSI-H cases in our cohort, making it difficult to generalize.
CIMP is the most frequent cause of sporadic MSI-H CRC [29]. Differences in MLH1 methylation between populations may help explain the variations in MMRd/MSI-H prevalence across ancestries and countries, supporting our findings. In Hispanic/Latino populations, MLH1 silencing remains high. Moreno-Ortiz et al. reported a methylation frequency of 25% in Mexican CRC patients, with a higher prevalence in women (71%) [100]. Similar frequencies have been reported in Brazil (23%), Colombia (24%), and Peru (38.4%) [43]. By contrast, a study in Slovakia found a higher MLH1 methylation prevalence of 45.8% [101], while studies in Asia showed much lower rates, such as 10.1% [102]. In the U.S., MLH1 promoter methylation was found in 20.3% of CRC patients, which is similar to Hispanic/Latino populations. Specifically, among U.S. Hispanic/Latino individuals, MLH1 silencing was reported at 12.6% [43].
Therefore, the higher prevalence of MMRd/MSI-H in the Hispanic/Latino populations in our study is likely due to both the higher frequency of Lynch syndrome and the significant prevalence of MLH1 promoter methylation in this group, including the U.S. Hispanic/Latino cohort. However, due to data limitations, we could not distinguish between sporadic and hereditary CRC cases.
The most common protein expression losses observed in this study via IHC-MSI were MLH1 and PMS2, followed by MSH2 and MSH6. This pattern aligns with findings from Asian populations [66, 86]. In 2019, Lizhu Chen et al. found that MLH1 and PMS2 were the most frequent protein loss combination in MMRd CRC cases, occurring in 41% of cases, while MSH2 and MSH6 losses were found in 20% of cases [103]. Less common combinations included losses of MSH6 and PMS2 or all four proteins [103].
Although MSI-H prevalence differs between Hispanic/Latino and Asian populations, our findings on protein expression losses are consistent. This may reflect shared genetic histories, as migration waves into East Asia, especially through Southeast Asia, contributed to the genetic diversity in both East Asian and Hispanic/Latino populations [43, 101, 102]. This genetic legacy may help explain the elevated rates of MLH1 silencing in Hispanic/Latino populations [104, 105] and the similarities in actionable somatic alterations between populations with NAT ancestry and South Asian patients [22].
No significant correlation was found between stage and MMRd/MSI-H due to data limitations, available studies indicate that 69.4% of MMRd/MSI-H CRC cases in Hispanic/Latino populations were diagnosed at stage I-II, while only 25.9% were stage IV. This is consistent with previous evidence showing that Hispanic/Latino individuals are more likely to be diagnosed with stage II and III CRC compared to Asian, White, and Black individuals [106]. Additionally, MSI-H tumors are more common in stage II and III (around 34%) and rare in stage IV (around 4%) [107]. This pattern may be explained by the less aggressive nature of MSI-H tumors, which have high mutational burdens that generate neoantigens, promoting immune cell infiltration and potentially limiting tumor growth and progression to later stages. However, Asian, White, and Black populations show a higher proportion of stage I tumors, suggesting that the higher prevalence of MSI-H in Hispanic/Latino populations may also be linked to later overall diagnosis [106].
The methodological quality of the included studies was assessed using the JBI critical appraisal tool for case series [30]. While most studies demonstrated acceptable methodological quality, several had notable limitations, including incomplete reporting of patient selection criteria, potential confounding factors, or a lack of standardized diagnostic approaches. These methodological differences may have contributed to the heterogeneity observed in prevalence estimates and should be considered when interpreting pooled results.
One key issue is the underrepresentation of many Hispanic/Latino countries, meaning the available data may not reflect the broader population, especially in regions with limited research or incomplete data collection. Additionally, many of the studies included did not evaluate populations using a complete set of MSI microsatellite markers or did not report this information. In several cases, MMRd/MSI-H status was assessed in only a subset of patients, limiting the inclusion of additional studies. These disparities highlight the need for standardized approaches to MMRd/MSI-H testing and reporting.
Limitations
A potential limitation of this review is assay-related measurement bias, which may introduce some outcome misclassification across studies [108]. Importantly, this should be interpreted as a source of residual methodological variability rather than as a threat to the validity of the included estimates, because both MMR immunohistochemistry and PCR-based MSI testing are accepted, guideline-supported approaches for colorectal cancer and generally show high concordance [109]. However, these methods interrogate different levels of mismatch repair dysfunction, and discordant classifications may occur because of tumor heterogeneity, low tumor cell content, retained expression of non-functional proteins, unusual staining patterns, or other test-specific interpretative challenges [108, 110]. Therefore, a small proportion of the between-study variability may reflect differences in biomarker ascertainment rather than true underlying prevalence alone [110].
Conclusion
This systematic review and meta-analysis provide a comprehensive evaluation of the prevalence, clinical features, and molecular markers associated with MMRd and MSI-H status among Hispanic/Latino populations. The overall prevalence of MMRd and MSI-H was 15% and 18%, respectively, with notable variations across countries. Costa Rica and Mexico demonstrated the highest MMRd prevalence, while Uruguay exhibited the highest MSI-H prevalence. Conversely, Puerto Rico consistently showed the lowest prevalence for both markers. These values differ from those seen in other populations and may be partly explained by differences in germline mutations, MLH1 methylation, and the tumor stage at diagnosis in Hispanic/Latino patients. Moreover, clinicopathological analyses revealed significant associations between MMRd/MSI-H and a predilection for tumors in the right colon. Additionally, MSI-H was more frequently observed in females. The participation and reporting of the rest of Latin American countries is warranted to address gaps in data and provide a deeper understanding of these molecular markers in diverse populations.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary file2 Leave-one-out sensitivity analysis and influence diagnostics for the MMRd prevalence meta-analysis (PDF 143 KB)
Supplementary file3 Leave-one-out sensitivity analysis and influence diagnostics for the MSI-H prevalence meta-analysis (PDF 163 KB)
Author contributions
Conception and design: R Parra-Medina; (II) Administrative support: All authors (III) Provision of study materials or patients: All Authors; (IV) Collection and assembly of data: All authors; (V) Data analysis and interpretation: All Authors; (VI) Manuscript writing: All Authors; (VII) Final approval of manuscript: All Authors.
Funding
Open Access funding provided by Colombia Consortium.
Data availability
All relevant data are within the manuscript and its Supporting Information files.
Declarations
Ethical approval
Not applicable. This study synthesizes published data only.
Consent to participate
Not applicable. This study synthesizes published data only.
Consent for publication
Not applicable. This study synthesizes published data only.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Bray F, Laversanne M, Sung H et al (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 74(3):229–263. 10.3322/caac.21834 [DOI] [PubMed] [Google Scholar]
- 2.Muzi CD, Banegas MP, Guimarães RM (2023) Colorectal cancer disparities in Latin America: mortality trends 1990–2019 and a paradox association with human development. PLoS ONE 18(8):e0289675. 10.1371/journal.pone.0289675 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Bray F, Jemal A, Grey N et al (2012) Global cancer transitions according to the Human Development Index (2008-2030): a population-based study. Lancet Oncol 13(8):790–801. 10.1016/S1470-2045(12)70211-5 [DOI] [PubMed] [Google Scholar]
- 4.Battaglin F, Naseem M, Lenz HJ et al (2018) Microsatellite instability in colorectal cancer: overview of its clinical significance and novel perspectives. Clin Adv Hematol Oncol 16(11):735–745 [PMC free article] [PubMed] [Google Scholar]
- 5.Li K, Luo H, Huang L et al (2020) Microsatellite instability: a review of what the oncologist should know. Cancer Cell Int. 10.1186/s12935-019-1091-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Vacante M, Borzì AM, Basile F et al (2018) Biomarkers in colorectal cancer: current clinical utility and future perspectives. World J Clin Cases 6(15):869–881. 10.12998/wjcc.v6.i15.869 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Greenson JK, Huang SC, Herron C et al (2009) Pathologic predictors of microsatellite instability in colorectal cancer. Am J Surg Pathol 33(1):126–133. 10.1097/PAS.0b013e31817ec2b1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Baracaldo Ayala RL, Peña Carvajalino LF, Gómez Rodríguez O et al (2020) Características histopatológicas del carcinoma colorrectal con inestabilidad microsatelital (IMS). Repert Med Cir 29(1). 10.31260/repertmedcir.v29.n1.2020.172
- 9.Vanderwalde A, Spetzler D, Xiao N et al (2018) Microsatellite instability status determined by next-generation sequencing and compared with PD-L1 and tumor mutational burden in 11,348 patients. Cancer Med 7(3):746–756. 10.1002/cam4.1372 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Vikas P, Messersmith H, Compton C et al (2023) Mismatch repair and microsatellite instability testing for immune checkpoint inhibitor therapy: ASCO endorsement of College of American Pathologists guideline. J Clin Oncol 41(10):1943–1948. 10.1200/JCO.22.02462 [DOI] [PubMed] [Google Scholar]
- 11.Kawakami H, Zaanan A, Sinicrope FA (2015) Microsatellite instability testing and its role in the management of colorectal cancer. Curr Treat Options Oncol 16(7):30. 10.1007/s11864-015-0348-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ali-Fehmi R, Krause HB, Morris RT et al (2024) Analysis of concordance between next-generation sequencing assessment of microsatellite instability and immunohistochemistry-mismatch repair from solid tumors. JCO Precis Oncol 8:e2300648. 10.1200/PO.23.00648 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Svrcek M, Lascols O, Cohen R et al (2019) MSI/MMR-deficient tumor diagnosis: which standard for screening and for diagnosis? Diagnostic modalities for the colon and other sites: differences between tumors. Bull Cancer 106(2):119–128. 10.1016/j.bulcan.2018.12.008 [DOI] [PubMed] [Google Scholar]
- 14.McCracken J, Neff JL. (2018) Discordant IHC/PCR test results for mismatch repair status in colorectal adenocarcinoma [conference abstract]. 10.26226/morressier.578f37f9d462b8028d88f705
- 15.Chen J, Yan Q, Sun J et al (2023) Microsatellite status detection of colorectal cancer: evaluation of inconsistency between PCR and IHC. J Cancer 14(7):1132–1140. 10.7150/jca.81675 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sun BL (2021) Current microsatellite instability testing in management of colorectal cancer. Clin Colorectal Cancer 20(1):e12–e20. 10.1016/j.clcc.2020.08.001 [DOI] [PubMed] [Google Scholar]
- 17.Fan WX, Su F, Zhang Y et al (2024) Oncological characteristics, treatments and prognostic outcomes in MMR-deficient colorectal cancer. Biomark Res. 10.1186/s40364-024-00640-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Ye M, Ru G, Yuan H et al (2023) Concordance between microsatellite instability and mismatch repair protein expression in colorectal cancer and their clinicopathological characteristics: a retrospective analysis of 502 cases. Front Oncol 13:1178772. 10.3389/fonc.2023.1178772 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Nádorvári ML, Lotz G, Kulka J et al (2024) Microsatellite instability and mismatch repair protein deficiency: equal predictive markers? Pathol Oncol Res. 10.3389/pore.2024.1611719 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zito Marino F, Amato M, Ronchi A et al (2022) Microsatellite status detection in gastrointestinal cancers: PCR/NGS is mandatory in negative/patchy MMR immunohistochemistry. Cancers (Basel) 14(9):2204. 10.3390/cancers14092204 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Bartley AN, Mills AM, Konnick E et al (2022) Mismatch repair and microsatellite instability testing for immune checkpoint inhibitor therapy: guideline from the College of American Pathologists in collaboration with the Association for Molecular Pathology and Fight Colorectal Cancer. Arch Pathol Lab Med 146(10):1194–1210. 10.5858/arpa.2021-0632-CP [DOI] [PubMed] [Google Scholar]
- 22.Arora K, Tran TN, Kemel Y et al (2022) Genetic ancestry correlates with somatic differences in a real-world clinical cancer sequencing cohort. Cancer Discov 12(11):2552–2565. 10.1158/2159-8290.CD-22-0312 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Carrot-Zhang J, Chambwe N, Damrauer JS et al (2020) Comprehensive analysis of genetic ancestry and its molecular correlates in cancer. Cancer Cell 37(5):639–54.e6. 10.1016/j.ccell.2020.04.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Arora K, Suehnholz SP, Zhang H et al (2025) Genetic ancestry-based differences in biomarker-based eligibility for precision oncology therapies. JAMA Oncol. 10.1001/jamaoncol.2024.5794 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Ruíz-Patiño A, Rojas L, Zuluaga J et al (2024) Genomic ancestry and cancer among Latin Americans. Clin Transl Oncol 26(8):1856–1871. 10.1007/s12094-024-03415-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Ashktorab H, Ahuja S, Kannan L et al (2016) A meta-analysis of MSI frequency and race in colorectal cancer. Oncotarget 7(23):34546–34557. 10.18632/oncotarget.8945 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Gupta S, Ashfaq R, Kapur P et al (2010) Microsatellite instability among individuals of Hispanic origin with colorectal cancer. Cancer 116(21):4965–4972. 10.1002/cncr.25486 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372:n71. 10.1136/bmj.n71 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Donehower LA, Creighton CJ, Schultz N et al (2013) MLH1-silenced and non-silenced subgroups of hypermutated colorectal carcinomas have distinct mutational landscapes. J Pathol 229(1):99–110. 10.1002/path.4087 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Munn Z, Barker TH, Moola S et al (2020) Methodological quality of case series studies: an introduction to the JBI critical appraisal tool. JBI Evid Synth 18(10):2127–2133. 10.11124/JBISRIR-D-19-00099 [DOI] [PubMed] [Google Scholar]
- 31.Luchini C, Bibeau F, Ligtenberg MJL et al (2019) ESMO recommendations on microsatellite instability testing for immunotherapy in cancer, and its relationship with PD-1/PD-L1 expression and tumour mutational burden: a systematic review-based approach. Ann Oncol 30(8):1232–1243. 10.1093/annonc/mdz116 [DOI] [PubMed] [Google Scholar]
- 32.Evrard C, Tachon G, Randrian V et al (2019) Microsatellite instability: diagnosis, heterogeneity, discordance, and clinical impact in colorectal cancer. Cancers (Basel) 11(10):1567. 10.3390/cancers11101567 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Antelo M, Golubicki M, Roca E et al (2019) Lynch-like syndrome is as frequent as Lynch syndrome in early-onset nonfamilial nonpolyposis colorectal cancer. Int J Cancer 145(3):705–713. 10.1002/ijc.32160 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Schmitz L, Moretti L, Marino L, Gimenez L, Rojas Bilbao E (2014) Estudio fenotípico de inestabilidad microsatelital en cáncer colorrectal. Correlación con parámetros histológicos y clínicos. Revista Española de Patología 47(4):204–209. 10.1016/J.PATOL.2013.10.002
- 35.Azambuja D de B, e Gloria H de C, Montenegro G eS, Kalil AN, Hoffmann JS, Leguisamo NM, Saffi J (2023) High expression of MRE11A is associated with shorter survival and a higher risk of death in CRC patients. Genes 14(6):1270. 10.3390/GENES14061270/S1 [DOI] [PMC free article] [PubMed]
- 36.Berardinelli GN, Scapulatempo-Neto C, Durães R, de Oliveira MA, Guimarães D, Reis RM (2018) Advantage of HSP110 (T17) marker inclusion for microsatellite instability (MSI) detection in colorectal cancer patients. Oncotarget 9(47):28691. 10.18632/ONCOTARGET.25611 [DOI] [PMC free article] [PubMed]
- 37.de Freitas IN, de Campos FGCM, Alves VAF, Cavalcante JM, Carraro D, Coudry R de A, Diniz MA, Nahas SC, Ribeiro U (2015) Proficiency of DNA repair genes and microsatellite instability in operated colorectal cancer patients with clinical suspicion of lynch syndrome. J Gastrointest Oncol 6(6):628–637. 10.3978/J.ISSN.2078-6891.2015.089 [DOI] [PMC free article] [PubMed]
- 38.Germini DE, Franco MIF, Fonseca FLA, de Sousa Gehrke F, da Costa Aguiar Alves Reis B, Cardili L, Oshima CTF, Theodoro TR, Waisberg J (2019) Association of expression of inflammatory response genes and DNA repair genes in colorectal carcinoma. Tumor Biol 42(4). 10.1177/1010428319843042 [DOI] [PubMed]
- 39.Gomes AAD, Macedo MP, Torrezan GT, Zenun GR, Aguiar S, Begnami MD, Carraro DM, Formiga MN (2021) DNA mismatch repair–deficient colorectal carcinoma: referral rate for genetic cancer risk assessment in a brazilian cancer center. J Gastrointest Cancer 52(3):997–1002. 10.1007/s12029-020-00467-z [DOI] [PubMed]
- 40.Alex AK, Siqueira S, Coudry R, Santos J, Alves M, Hoff PM, Riechelmann RP (2017) Response to chemotherapy and prognosis in metastatic colorectal cancer with dna deficient mismatch repair. Clin Colorectal Cancer 16(3):228–239. 10.1016/j.clcc.2016.11.001 [DOI] [PubMed]
- 41.Paula Simedan Vila A, Helena Rodrigues G, Leite Marzochi L, Garcia de Oliveira-Cucolo J, Lívia Silva Galbiatti-Dias A, Felipe Maciel Andrade R, de Santi Neto D, Gomes Netinho J, Castiglioni L, Cristina Pavarino É, Maria Goloni-Bertollo E (2023) Epidemiological and molecular evaluation of BRAF, KRAS, NRAS genes and MSI in the development of colorectal cancer. Gene 870:147395. 10.1016/J.GENE.2023.147395 [DOI] [PubMed]
- 42.SunaguaAruquipa M, D’AlpinoPeixoto R, Jacome A et al (2024) Association of KRAS G12C status with age at onset of metastatic colorectal cancer. Curr Issues Mol Biol 46(2):1374–1382. 10.3390/cimb46020088 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Gómez-Rodríguez O, Baracaldo-Ayala R, Polo JF et al (2021) Microsatellite instability in Colombian patients with colorectal adenocarcinoma. Rev Colomb Gastroenterol 36:349–356. 10.22516/25007440.686 [Google Scholar]
- 44.Shamekh R, Cives M, Mejia J, Coppola D (2016) Higher frequency of isolated PMS2 loss in colorectal tumors in Colombian population: preliminary results. Pathol Lab Med Int 8:37–41. 10.2147/plmi.s94771
- 45.Allan RE, Luis RP, Juan P (2020) Microsatellite instability in Costa Rican patients with colorectal adenocarcinoma and its association with overall survival and response to fluoropyrimidine-based chemotherapy. Cancer Epidemiol 65. 10.1016/j.canep.2020.101680 [DOI] [PubMed]
- 46.Quezada-Diaz F, Gomez J, Fulle A, Irarrazaval MJ, Torres J, Bellolio F (2022) Results of an immunohistochemistry-based universal screening strategy for Lynch syndrome in patients with colorectal cancer treated in a public hospital from Latin-America. Surgery Open Digestive Advance 5. 10.1016/j.soda.2022.100041
- 47.Bacilio M del RM, Gonzalez AMP, Martínez FGC, Pesantez MIL, Murillo GEP (2018) Inestabilidad de los microsatélites en cáncer colo-rectal y su distribución de acuerdo a factores pronósticos en SOLCA Cuenca 2004-2014. Revista de La Facultad de Ciencias Médicas de La Universidad de Cuenca 36(1):9–16. https://publicaciones.ucuenca.edu.ec/ojs/index.php/medicina/article/view/2422
- 48.López-Correa PE, Lino-Silva LS, Gamboa-Domínguez A, Zepeda-Najar C, Salcedo-Hernández RA (2018) Frequency of defective mismatch repair system in a series of consecutive cases of colorectal cancer in a national cancer center. J Gastrointest Cancer 49(3):379–384. 10.1007/s12029-018-0132-1 [DOI] [PubMed]
- 49.De De Mexico R, Gastroenterologia´ G, Rios-Valencia J, Cruz-Reyes C, Galindo-García TA, Rosas-Camargo V, Gamboa-Domínguez A (2022) Mismatch repair system in colorectal cancer. Frequency, cancer phenotype, and follow-up. In: Revista de Gastroenterología de México, vol 87. https://doi.org/www.elsevier.es/rgmx [DOI] [PubMed]
- 50.Fleitas-Kanonnikoff T, Martinez-Ciarpaglini C, Ayala J, Gauna C, Denis R, Yoffe I, Sforza S, Martínez MT, Pomata A, Ibarrola-Villava M, Arevshatyan S, Burriel V, Boscá D, Pastor O, Ferrer-Martinez A, Carrasco F, Mongort C, Navarro S, Ribas G, Cervantes A (2019) Molecular profile in Paraguayan
- 51.Egoavil CM, Montenegro P, Soto JL, Casanova L, Sanchez-Lihon J, Castillejo MI, Martinez-Canto A, Perez-Carbonell L, Castillejo A, Guarinos C, Barbera VM, Jover R, Paya A, Alenda C (2011) Clinically important molecular features of Peruvian colorectal tumours: high prevalence of DNA mismatch repair deficiency and low incidence of KRAS mutations. Pathology 43(3):228–233. 10.1097/PAT.0b013e3283437613 [DOI] [PubMed]
- 52.Carbajal CÑ, Sánchez Renteria F, Lettiero B, Wernhoff P, Domínguez-Valentin M (2014) Caracterización molecular de cáncer colorrectal hereditario en Perú Molecular characterization of hereditary colorectal cancer in Peru. In Rev Gastroenterol Peru, vol 34, no 4 [PubMed]
- 53.De Jesus-Monge WE, Gonzalez-Keelan C, Zhao R, Hamilton SR, Rodriguez-Bigas M, Cruz-Correa M (2010) Mismatch repair protein expression and colorectal cancer in Hispanics from Puerto Rico. Familial Cancer 9(2):155–166. 10.1007/s10689-009-9310-4 [DOI] [PMC free article] [PubMed]
- 54.Sierra I, Pérez-Mayoral J, Rosado K, Maldonado V, Alicea-Zambrana K, Reyes JS, Torres M, Tous L, Lopéz-Acevedo N, Diaz-Algorrí Y, Carlo-Chevere V, Rodriguez-Quilichini S, Cruz-Correa M (2021) Implementation of Universal colorectal cancer screening for lynch syndrome in hispanics living in Puerto Rico. J Racial Ethn Health Disparities 8(5):1185–1191. 10.1007/s40615-020-00876-7 [DOI] [PMC free article] [PubMed]
- 55.Cruz-Correa M, Diaz-Algorri Y, Pérez-Mayoral J, Suleiman-Suleiman W, del Mar Gonzalez-Pons M., Bertrán C, Casellas N, Rodríguez N, Pardo S, Rivera K, Mosquera R, Rodriguez-Quilichini S (2015) Clinical characterization and mutation spectrum in Caribbean Hispanic families with Lynch syndrome. Familial Cancer 14(3):415–425. 10.1007/s10689-015-9795-y [DOI] [PMC free article] [PubMed]
- 56.Barrows DB, Zarrin-Khameh N (2017) Variability in the prevalence of microsatellite instability in colon cancer
- 57.Berera S, Koru-Sengul T, Miao F, Carrasquillo O, Nadji M, Zhang Y, Hosein PJ, McCauley JL, Abreu MT, Sussman DA (2016) Colorectal tumors from different racial and ethnic minorities have similar rates of mismatch repair deficiency. Clin Gastroenterol Hepatol 14(8):1163–1171. 10.1016/j.cgh.2016.03.037 [DOI] [PubMed]
- 58.Ricker CN, Hanna DL, Peng C, Nguyen NT, Stern MC, Schmit SL, Idos GE, Patel R, Tsai S, Ramirez V, Lin S, Shamasunadara V, Barzi A, Lenz HJ, Figueiredo JC (2017) DNA mismatch repair deficiency and hereditary syndromes in Latino patients with colorectal cancer. Cancer 123(19):3732–3743. 10.1002/cncr.30790 [DOI] [PMC free article] [PubMed]
- 59.Fangman BD, Goksu SY, Chowattukunnel N et al (2021) Disparities in characteristics, access to care, and oncologic outcomes in young-onset colorectal cancer at a safety-net hospital. JCO Oncology Practice 17(5):e614–e622. 10.1200/OP.20.00777 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Hoffman SJ, Wu ML-C (2018) Phenotypic and genotypic differences in colorectal carcinoma among Caucasians, Asians, and Hispanics lack statistical significance. Pathol Res Pract 214(5):720–726. 10.1016/j.prp.2018.03.008 [DOI] [PubMed]
- 61.Reverón D, López C, Gutiérrez S, Sayegh ZE, Antonia T, Dutil J, Malafa M, Coppola D (2018) Frequency of mismatch repair protein deficiency in a puerto rican population with colonic adenoma and adenocarcinoma. Cancer Genom Proteom 15(4):265–271. 10.21873/cgp.20084 [DOI] [PMC free article] [PubMed]
- 62.Lerda D, Pellicioni P, Biaggi M, Labrador J, Illescas E, Bella S, Llugdar J, Cortes M (2019) Consejo genético y detección de vías moleculares en pacientes con cáncer hereditario. Methodo Investigación Aplicada a Las Ciencias Biológicas 4(3):71–80. 10.22529/me.2019.4(3)02
- 63.Sánchez AG, Juaneda I, Eynard H, Basquiera AL, Palazzo E, Calafat P, Palla V, Romagnoli PA, Alvarellos T (2020) CAT25 defines microsatellite instability in colorectal cancer by high-resolution melting PCR. Br J Biomed Sci 77(3):105–111. 10.1080/09674845.2020.1730625 [DOI] [PubMed]
- 64.Anacleto C, Leopoldino AM, Rossi B, Soares FA, Lopes A, Rocha JCC, Caballero O, Camargo AA, Simpson AJG, Pena SDJ (2005) Colorectal cancer “methylator phenotype”: fact or artifact? Neoplasia 7(4):331–335. 10.1593/neo.04502 [DOI] [PMC free article] [PubMed]
- 65.Da Silva FC, De Oliveira Ferreira JR, Torrezan GT, Figueiredo MCP, Santos EMM, Nakagawa WT, Brianese RC, De Oliveira LP, Begnani MD, Aguiar-Junior S, Rossi BM, De Oliveira Ferreira F, Carraro DM (2015) Clinical and molecular characterization of brazilian patients suspected to have lynch syndrome. PLoS ONE 10(10). 10.1371/journal.pone.0139753 [DOI] [PMC free article] [PubMed]
- 66.de Oliveira TC, Secolin R, Lopes-Cendes I (2023) A review of ancestrality and admixture in Latin America and the Caribbean focusing on Native American and African descendant populations. Front Genet 14. 10.3389/fgene.2023.1091269 [DOI] [PMC free article] [PubMed]
- 67.dos Santos W, Sobanski T, de Carvalho AC, Evangelista AF, Matsushita M, Berardinelli GN, de Oliveira MA, Reis RM, Guimarães DP (2019) Mutation profiling of cancer drivers in Brazilian colorectal cancer. Sci Rep 9(1). 10.1038/s41598-019-49611-1 [DOI] [PMC free article] [PubMed]
- 68.Moraes Losso G, da Silveira Moraes R, Gentili AC, Taborda Messias-Reason I, Moraes Losso G (2012) Microsatellite instability-msi markers (BAT26, BAT25, D2S123, D5S346, D17S250) IN RECTAL CANCER. In ABCD Arquivos Brasileiros de Cirurgia Digestiva, vol 25, no 4 [DOI] [PubMed]
- 69.Leite SMO, Gomes KB, Pardini VC, Ferreira ACS, Oliveira VC, Cruz GMG (2010) Assessment of microsatellite instability in colorectal cancer patients from Brazil. Mol Biol Rep 37(1):375–380. 10.1007/s11033-009-9807-9 [DOI] [PubMed]
- 70.Proença MA, Biselli JM, Succi M, Severino FE, Berardinelli GN, Caetano A, Reis RM, Hughes DJ, Silva AE (2018) Relationship between fusobacterium nucleatum, inflammatory mediators and microRNAs in colorectal carcinogenesis. World J Gastroenterol 24(47):5351–5365. 10.3748/wjg.v24.i47.5351 [DOI] [PMC free article] [PubMed]
- 71.Rasuck CG, Leite SMO, Komatsuzaki F, Ferreira ACS, Oliveira VC, Gomes KB (2012) Association between methylation in mismatch repair genes, V600E BRAF mutation and microsatellite instability in colorectal cancer patients. Mol Biol Rep 39(3):2553–2560. 10.1007/s11033-011-1007-8 [DOI] [PubMed]
- 72.Santos FA, Reis RM, Barroti LC, Pereira AAL, Matsushita MM, de Carvalho AC, Datorre JG, Berardinelli GN, Araujo RLC (2024) Overall survival, BRAF, RAS, and MSI status in patients who underwent cetuximab after refractory chemotherapy for metastatic colorectal cancer. J Gastrointest Cancer 55(1):344–354. 10.1007/S12029-023-00964-X [DOI] [PubMed]
- 73.Afanador CH, Palacio KA, Isaza LF, Ahumada E, Ocampo CM, Muñetón CM (2022) Molecular characterization of colorectal cancer patients. Biomedica 42:154–171. 10.7705/biomedica.5957 [DOI] [PMC free article] [PubMed]
- 74.Cárdenas W, Castillo A, Vargas C, Moreno O, Insuasti J (2008) Análisis de la inestabilidad de microsatélites mediante el marcador BAT-26 en una muestra de pacientes del Hospital Universitario de Santander con diagnóstico de cáncer gástrico o colorrectal. Colombia Médica 39:41–51. http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S1657-95342008000600007&lng=en&nrm=iso&tlng=es
- 75.Montenegro Y, Luis Ramírez-Castro J, Fernando Isaza L, Bedoya G, Muñetón-Peña CM (2006) Análisis genético en pacientes con cáncer colorrectal. In: Revista Médica de Chile, vol 134 [DOI] [PubMed]
- 76.Alvarez K, Cassana A, De La Fuente M, Canales T, Abedrapo M, López-Köstner F (2021) Clinical, pathological and molecular characteristics of chilean patients with early-, intermediate-and late-onset colorectal cancer. Cells 10(3):1–10. 10.3390/cells10030631 [DOI] [PMC free article] [PubMed]
- 77.Hurtado C, Wielandt AM, Zárate AJ, Kronberg U, Castro M, Yamagiwa K, Ito T, Eishi Y, Contreras L, López-Köstner F (2015) Análisis molecular del cáncer de colon esporádico. Revista Médica de Chile 143(3):310–319. 10.4067/S0034-98872015000300005 [DOI] [PubMed]
- 78.MAríA WielAndt A, VillArroel C, hurtAdo C, SiMiAn dAniel A, ZAMorAno diego MArtíne Z, Ma CAStro Ma, tereSA ViAl Ma, Kronberg udo, lópeZ-KoStner F (2017) Caracterización de pacientes con cáncer colorrectal esporádico basado en la nueva subclasificación molecular de consenso Characterization of patients with sporadic colorectal cancer following the new Consensus Molecular Subtypes (CMS). In: Revista Médica de Chile, vol 145 [DOI] [PubMed]
- 79.Wielandt AM, Hurtado C, Moreno CM, Villarroel C, Castro M, Estay M, Simian D, Martinez M, Vial MT, Kronberg U, López-Köstner F (2020) Characterization of Chilean patients with sporadic colorectal cancer according to the three main carcinogenic pathways: microsatellite instability, CpG island methylator phenotype and Chromosomal instability. Tumor Biol 42(7). 10.1177/1010428320938492 [DOI] [PubMed]
- 80.Jordi G-C, Rodrigo Fernando R-S, Rocío Pamela M-V, Jairo Aaron R-C, Lucía T-C, Rocío del Carmen B-C, Chards Sonia C-C, Jorge G-H, Andrea G-A, Itzel Ariadna H-D, Ayala Adriana D, Rafael C-C, Karina E-F, Mario E-G, Jesús Miguel L-L (n.d.) Microsatellite instability incidence in recurrent colon cancer stage II and III. In: Journal of Medical Research and Surgery, vol 1
- 81. Ortiz C, Dongo-Pflucker K, Martín-Cruz L, Barletta Carrilo C, Mora-Alferez P, Arias A (2016) Microsatellite instability in patients diagnosed with colorectal cancer. Revista de Gastroenterología del Perú 36(1):15–22. Retrieved on May 8, 2026, from http://www.scielo.org.pe/scielo.php?script=sci_arttext&pid=S1022-51292016000100002&lng=es&tlng=es [PubMed]
- 82.Perez-Mayoral J, Gonzalez-Pons M, Centeno-Girona H et al (2023) Molecular and sociodemographic colorectal cancer disparities in Latinos living in Puerto Rico. Genes (Basel) 14(4):894. 10.3390/genes14040894 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Vital M, Carusso F, Vergara C, Neffa F, Della Valle A, Esperón P (2023) Genetic and epigenetic characteristics of patients with colorectal cancer from Uruguay. Pathol Res Pract 241. 10.1016/j.prp.2022.154264 [DOI] [PubMed]
- 84.Myer PA, Lee JK, Madison RW et al (2022) The genomics of colorectal cancer in populations with African and European ancestry. Cancer Discov 12(5):1282–1293. 10.1158/2159-8290.CD-21-0813 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Kang YJ, O’Haire S, Franchini F et al (2022) A scoping review and meta-analysis on the prevalence of pan-tumour biomarkers (dMMR, MSI, high TMB) in different solid tumours. Sci Rep. 10.1038/s41598-022-23319-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Matejcic M, Teer JK, Hoehn HJ et al. (2024) Spectrum of somatic mutational features of colorectal tumors in ancestrally diverse populations. medRxiv. 10.1101/2024.03.11.24303880.
- 87.Sohail M, Palma-Martínez MJ, Chong AY et al (2023) Mexican Biobank advances population and medical genomics of diverse ancestries. Nature 622(7984):775–783. 10.1038/s41586-023-06560-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Sandoval JR, Salazar-Granara A, Acosta O et al (2013) Tracing the genomic ancestry of Peruvians reveals a major legacy of pre-Columbian ancestors. J Hum Genet 58(9):627–634. 10.1038/jhg.2013.73 [DOI] [PubMed] [Google Scholar]
- 89.Haraldsdottir S, Hampel H, Wu C et al (2016) Patients with colorectal cancer associated with Lynch syndrome and MLH1 promoter hypermethylation have similar prognoses. Genet Med 18(9):863–868. 10.1038/gim.2015.184 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Seagle HM, Keller SR, Tavtigian SV et al (2023) Clinical multigene panel testing identifies racial and ethnic differences in germline pathogenic variants among patients with early-onset colorectal cancer. J Clin Oncol 41(26):4279–4289. 10.1200/JCO.22.02378 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Ricker CN, Hanna DL, Peng C et al (2017) DNA mismatch repair deficiency and hereditary syndromes in Latino patients with colorectal cancer. Cancer 123(19):3732–3743. 10.1002/cncr.30790 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92.Uson PLS, Riegert-Johnson D, Boardman L et al (2022) Germline cancer susceptibility gene testing in unselected patients with colorectal adenocarcinoma: a multicenter prospective study. Clin Gastroenterol Hepatol 20(3):e508–e528. 10.1016/j.cgh.2021.04.013 [DOI] [PubMed] [Google Scholar]
- 93.Abu-Ghazaleh N, Kaushik V, Gorelik A et al (2022) Worldwide prevalence of Lynch syndrome in patients with colorectal cancer: systematic review and meta-analysis. Genet Med 24(5):971–985. 10.1016/j.gim.2022.01.014 [DOI] [PubMed] [Google Scholar]
- 94.Serrano D, Arteaga CE (2016) Molecular diagnosis of hereditary nonpolyposis colorectal cancer (Lynch syndrome). Rev Fac Med 64:537–542. 10.15446/revfacmed.v64n3.48458 [Google Scholar]
- 95.Nieto Z, Valenzuela AK, Huitzil Melendez FD et al (2018) First results of universal screening for Lynch syndrome in a Mexican cohort of colorectal cancer patients. J Clin Oncol 36(4_suppl):590. 10.1200/JCO.2018.36.4_suppl.590 [Google Scholar]
- 96.Marquez E, Geng Z, Pass S et al (2013) Implementation of routine screening for Lynch syndrome in university and safety-net health system settings: successes and challenges. Genet Med 15(12):925–932. 10.1038/gim.2013.45 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 97.de Paula AE, Galvão HdCR, Bonatelli M et al (2021) Clinicopathological and molecular characterization of Brazilian families at risk for Lynch syndrome. Cancer Genet 254–255:82–91. 10.1016/j.cancergen.2021.02.003 [DOI] [PubMed] [Google Scholar]
- 98.Liang Y, Cai X, Zheng X et al (2021) Analysis of the clinicopathological characteristics of stage I-III colorectal cancer patients deficient in mismatch repair proteins. Onco Targets Ther 14:2203–2212. 10.2147/OTT.S278029 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Schneider R, Schneider C, Jakobeit C et al (2014) Gender-specific aspects of Lynch syndrome and familial adenomatous polyposis. Viszeralmedizin 30(2):82–88. 10.1159/000360839 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Moreno-Cc JM, Jiménez-García J, Gutiérrez-Angulo M et al (2021) Elevada frecuencia de metilación del promotor de MLH1 mediada por sexo y edad en tumores colorrectales de pacientes mexicanos. Gac Med Mex 157(6). 10.24875/GMM.21000293 [DOI] [PubMed]
- 101.Kašubov I, Kalman M, Jašek K et al (2019) Stratification of patients with colorectal cancer without the recorded family history. Oncol Lett. 10.3892/ol.2019.10018 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102.Wong JJL, Hawkins NJ, Ward RL et al (2011) Methylation of the 3p22 region encompassing MLH1 is representative of the CpG island methylator phenotype in colorectal cancer. Mod Pathol 24(3):396–411. 10.1038/modpathol.2010.212 [DOI] [PubMed] [Google Scholar]
- 103.Chen L, Chen G, Zheng X et al (2019) Expression status of four mismatch repair proteins in patients with colorectal cancer: clinical significance in 1238 cases. Int J Clin Exp Pathol 12(10):3685–3699 [PMC free article] [PubMed] [Google Scholar]
- 104.Tagore D, Aghakhanian F, Naidu R et al (2021) Insights into the demographic history of Asia from common ancestry and admixture in the genomic landscape of present-day Austroasiatic speakers. BMC Biol. 10.1186/s12915-021-00981-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 105.Skoglund P, Jakobsson M (2011) Archaic human ancestry in East Asia. Proc Natl Acad Sci U S A 108(45):18301–18306. 10.1073/pnas.1108181108 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 106.Rhead B, Hein DM, Pouliot Y et al (2024) Association of genetic ancestry with molecular tumor profiles in colorectal cancer. Genome Med 16(1):99. 10.1186/s13073-024-01373-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 107.Vilar E, Gruber SB (2010) Microsatellite instability in colorectal cancer-the stable evidence. Nat Rev Clin Oncol 7(3):153–162. 10.1038/nrclinonc.2009.237 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108.van der Werf-’t Lam AS, Terlouw D, Tops CM et al (2023) Discordant staining patterns and microsatellite results in tumors of MSH6 pathogenic variant carriers. Mod Pathol 36(9):100240. 10.1016/j.modpat.2023.100240 [DOI] [PubMed] [Google Scholar]
- 109.Zhang P, Wang A, Bian C et al (2024) Evaluation of mismatch-repair and microsatellite-instability status in a Chinese colorectal cancer cohort. Asian J Surg 47(2):959–967. 10.1016/j.asjsur.2023.12.176 [DOI] [PubMed] [Google Scholar]
- 110.Guyot D’Asnières De Salins A, Tachon G, Cohen R et al (2021) Discordance between immunochemistry of mismatch repair proteins and molecular testing of microsatellite instability in colorectal cancer. ESMO Open 6(3):100120. 10.1016/j.esmoop.2021.100120 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary file2 Leave-one-out sensitivity analysis and influence diagnostics for the MMRd prevalence meta-analysis (PDF 143 KB)
Supplementary file3 Leave-one-out sensitivity analysis and influence diagnostics for the MSI-H prevalence meta-analysis (PDF 163 KB)
Data Availability Statement
All relevant data are within the manuscript and its Supporting Information files.




