Literature DB >> 28874130

A survey of the clinicopathological and molecular characteristics of patients with suspected Lynch syndrome in Latin America.

Benedito Mauro Rossi1, Edenir Inêz Palmero2, Francisco López-Kostner3, Carlos Sarroca4, Carlos Alberto Vaccaro5, Florencia Spirandelli6, Patricia Ashton-Prolla7, Yenni Rodriguez8, Henrique de Campos Reis Galvão9, Rui Manuel Reis10,11, André Escremim de Paula2, Luis Gustavo Capochin Romagnolo9, Karin Alvarez3, Adriana Della Valle4, Florencia Neffa4, Pablo German Kalfayan5, Enrique Spirandelli6, Sergio Chialina6, Melva Gutiérrez Angulo12, Maria Del Carmen Castro-Mujica13, Julio Sanchez de Monte14, Richard Quispe15, Sabrina Daniela da Silva16,17, Norma Teresa Rossi18, Claudia Barletta-Carrillo13, Susana Revollo15, Ximena Taborga15, L Lena Morillas19, Hélène Tubeuf20,21, Erika Maria Monteiro-Santos1, Tamara Alejandra Piñero22, Constantino Dominguez-Barrera23, Patrik Wernhoff24, Alexandra Martins20, Eivind Hovig25,26, Pål Møller25,27,28, Mev Dominguez-Valentin29.   

Abstract

BACKGROUND: Genetic counselling and testing for Lynch syndrome (LS) have recently been introduced in several Latin America countries. We aimed to characterize the clinical, molecular and mismatch repair (MMR) variants spectrum of patients with suspected LS in Latin America.
METHODS: Eleven LS hereditary cancer registries and 34 published LS databases were used to identify unrelated families that fulfilled the Amsterdam II (AMSII) criteria and/or the Bethesda guidelines or suggestive of a dominant colorectal (CRC) inheritance syndrome.
RESULTS: We performed a thorough investigation of 15 countries and identified 6 countries where germline genetic testing for LS is available and 3 countries where tumor testing is used in the LS diagnosis. The spectrum of pathogenic MMR variants included MLH1 up to 54%, MSH2 up to 43%, MSH6 up to 10%, PMS2 up to 3% and EPCAM up to 0.8%. The Latin America MMR spectrum is broad with a total of 220 different variants which 80% were private and 20% were recurrent. Frequent regions included exons 11 of MLH1 (15%), exon 3 and 7 of MSH2 (17 and 15%, respectively), exon 4 of MSH6 (65%), exons 11 and 13 of PMS2 (31% and 23%, respectively). Sixteen international founder variants in MLH1, MSH2 and MSH6 were identified and 41 (19%) variants have not previously been reported, thus representing novel genetic variants in the MMR genes. The AMSII criteria was the most used clinical criteria to identify pathogenic MMR carriers although microsatellite instability, immunohistochemistry and family history are still the primary methods in several countries where no genetic testing for LS is available yet.
CONCLUSION: The Latin America LS pathogenic MMR variants spectrum included new variants, frequently altered genetic regions and potential founder effects, emphasizing the relevance implementing Lynch syndrome genetic testing and counseling in all of Latin America countries.

Entities:  

Keywords:  Latin America; Lynch syndrome; Mmr; Variants

Mesh:

Year:  2017        PMID: 28874130      PMCID: PMC5586063          DOI: 10.1186/s12885-017-3599-4

Source DB:  PubMed          Journal:  BMC Cancer        ISSN: 1471-2407            Impact factor:   4.430


Background

LS is caused by a defective mismatch repair (MMR) system, due to the presence of germline defects in at least one of the MMR genes, MLH1, MSH2, MSH6, PMS2, or to deletions of the 3′ portion of the EPCAM gene [1]. Such variants are here referred to as path_MMR and, when specifying one of the genes, as path_MLH1, path_MSH2, path_MSH6, path_PMS2 or path_EPCAM [2, 3]. LS is clinically classified according to the Amsterdam (AMS) criteria and/or the Bethesda guidelines, both relying in clinical information and family history. The Bethesda guidelines also takes into account the microsatellite instability (MSI) tumor marker, which is a signature characteristic of MMR-deficient tumors [4-7]. MSI or immuno-histochemical (IHC) testing of tumors are strategies to select patients for subsequent germline diagnostic testing in blood [8]. LS patients have an increased lifetime risk of colorectal cancer (CRC) (70–80%), endometrial cancer (50–60%), stomach cancer (13–19%), ovarian cancer (9–14%), cancer of the small intestine, the biliary tract, brain as well as carcinoma of the ureters and renal pelvis [9]. The cumulative incidence of any cancer at 70 years of age is 72% for path_MLH1 and path_MSH2 carriers but lower in path_MSH6 (52%) and path_PMS2 (18%) carriers. Path_MSH6 and path_PMS2 carriers do not have an increased risk for cancer before 40 years of age [2, 3]. The identification of LS patients is a goal because an early diagnosis and intensive screening may predict the disease and/or improve the disease prognosis [2]. The path_MMR variant spectrum of LS has been widely studied in CRC patients from North America, Europe, Australia and Asia. In the past decade, significant advances have been made in molecular testing and genetic counseling for LS in several Latin America countries [10-51]. A broad definition of Latin America is that all countries of the Americas south of the United States are included, with Mexico, Cuba, Puerto Rico and all the countries located in South America as well as the Caribbean Islands. Latin America presents with genetically somewhat different populations, where European and African immigrants have a concentration of the Caucasian population in the southern regions of the continent, whereas in the northern region, the population is predominantly Mestizo (a mixture of European and Amerindian) [52]. Among LS patients, the prevalence of path_MLH1 is 42%, path_MSH2 is 33%, path_MSH6 is 18% and path_PMS2 is 8% [53]. However, recent studies in Latin America LS families described the predominance of path_MSH2 (46%- 66%), followed by path_MLH1 (25%–43%), path_MSH6 (7%–8%), path_PMS2 (2%) and path_EPCAM (2%) [32, 36, 47]. Some Latin America LS variant spectrum included variants that have not previously been reported and potential founder effects which are useful for future development of genetic testing in these populations. It enables the comparison of LS characteristics and MMR variants across genetic ancestry background differences among these populations [12, 20, 23, 26, 32, 36, 40]. The clinical, molecular and MMR variant spectrum of LS has not been fully studied in all Latin America countries. Our study aims to combine both unpublished register data and published data in order to better describe the LS molecular profile and to update the previously described South American path_MMR variant spectrum study [32].

Methods

Unpublished data from hereditary cancer registries and published data from patients with suspected LS from Latin America have been included in this work. Through research collaborations, data from the Latin America hereditary cancer registers are available following direct contact with the register. The data include results from germline DNA testing, tumor testing (based on MSI analysis and/or IHC) and family history (Fig. 1).
Fig. 1

Flowchart depicting the groups of patients with suspected LS in Latin America included in the study. We included unpublished register data and published data from germline MMR testing, tumor testing and family history

Flowchart depicting the groups of patients with suspected LS in Latin America included in the study. We included unpublished register data and published data from germline MMR testing, tumor testing and family history

Hereditary cancer registries

Families that fulfilled the AMSII criteria [4, 5], the Bethesda guidelines [6] and/or other criteria i.e. families suggestive of a dominant CRC inheritance syndrome were selected from 11 hereditary cancer registries from 8 countries: Hospital Italiano (Buenos Aires, Argentina), Hospital Español de Rosario (Rosario, Argentina), Hospital Privado Universitario de Cordoba (Cordoba, Argentina), Centro de Enfermedades Neoplasicas Oncovida (La Paz, Bolivia), Barretos Cancer Hospital (Barretos, Brazil), Hospital de Clinicas de Porto Alegre (Rio Grande do Sul, Brazil), Clinica Las Condes (Santiago, Chile), Clinica del Country (Bogota, Colombia), Instituto Nacional de Cancerologia (Mexico City, Mexico), Instituto Nacional de Enfermedades Neoplasicas (Lima, Peru) and Hospital de las Fuerzas Armadas (Montevideo, Uruguay). Patients were informed about their inclusion into the registries, which generally contained data on family history, clinical information, age at onset and results of DNA testing or tumor screening in the diagnosis of LS. Written informed consent was obtained from all participants during genetic counseling sessions.

LS databases

A systematic review was performed in order to identify published reports on MMR variants in LS or hereditary CRC by querying the PubMed, SciELO and Google databases using specific key words (focusing on clinical, tumor or genetic testing information associated with the MMR genes) and taking into account publications in three languages, namely Spanish, English and Portuguese, up to July 2016. The search terms were “Lynch syndrome”, “hereditary colorectal cancer”, “hereditary colorectal cancer and Latin America” and “Lynch syndrome and Latin America”. We also used keywords in association with the names of Latin America countries (e.g., “Lynch syndrome and Colombia”). The results of the search were subsequently screened for the presence of path_MMR variants or tumor screening, clinical diagnosis and family history. We found 34 LS reports from 12 countries including Argentina [10, 14, 17, 18], Brazil [11, 15, 19, 22, 25, 28, 29, 37, 38, 43], Chile [20, 31], Colombia [12, 16, 23, 48], Mexico [27, 44, 49, 51], El Salvador and Guatemala [51], Paraguay [50], Peru [24, 33, 35, 45], Puerto Rico and Dominican Republic [21, 36], South America [26, 32, 47] and Uruguay [13].

Germline DNA testing

Genetic testing was generally based on Sanger sequencing of MLH1, MSH2, MSH6 and/or PMS2 and/or EPCAM in 7 participating centers from Argentina (Hospital Italiano de Buenos Aires and Hospital Español de Rosario), Brazil (Barretos Cancer Hospital and Hospital de Clinicas de Porto Alegre), Chile (Clinica Las Condes), Colombia (Clinica del Country) and Uruguay (Hospital de Las Fuerzas Armadas). Multiplex Ligation-dependent Probe Amplification (MLPA) was used to analyze genomic rearrangements in MMR and EPCAM genes (SALSA kit P003, MRC-Holland, Amsterdam, Netherland). For PMS2 analysis, especially for exons 12 to 15, to ensure the correct analysis of PMS2 and to avoid pseudogene co-amplification, a long-range PCR followed by a nested PCRs strategy was adopted. After amplification, sequencing was performed according to the manufacturer’s instructions. In addition, we took into consideration the results of germline DNA testing described in 15 previously published LS reports [10, 13, 17, 18, 20, 23, 26, 31, 32, 36, 37, 44, 47, 48, 51].

Tumor testing

Methods to assess tumor MMR status, e.g. MSI analysis and/or MMR protein staining are being currently used in Cordoba (Argentina), Lima (Peru), La Paz (Bolivia) and Mexico City (Mexico) as an approach to identify potential carriers of germline path_MMR variants. Germline MMR testing is then mandatory to confirm LS cases. Families from Peru (Instituto Nacional de Enfermedades Neoplasicas) were evaluated for MSI using a 5-mononucleotide marker panel (BAT-25, BAT-26, D2S123, D17S250 and D5S346). Tumors were classified into three categories and defined as MSI high (MSI-H) when ≥2 markers were unstable, MSI low (MSI-L) when one marker was unstable and microsatellite stable (MSS) when none of the markers were unstable. In Bolivia (Centro de Enfermedades Neoplasicas Oncovida), MSI analysis was evaluated by 1-mononucleotide marker panel (BAT-26). IHC analysis for MMR protein expression was performed on paraffin-embedded tumor tissue sections, as previously described [32]. In Argentina (Hospital Privado Universitario de Cordoba), Mexico (Instituto Nacional de Cancerologia) and Peru, IHC was evaluated using 4-MMR proteins (MLH1, PMS2, MSH2 and MSH6). Besides the information directly retrieved from these participating centers, we also collected MSI and/or IHC data from 15 LS published reports [14–16, 18, 21, 22, 24, 25, 27, 28, 31, 35, 38, 43, 45].

Family history

Available data of family history of patients with CRC included 4 published reports from Brazil [19], Mexico [49], Paraguay [50] and Peru [33].

MMR variants nomenclature and classification

The nomenclature guidelines of the Human Genome Variation Society (HGVS) were used to describe the detected MMR variants [54]. Variants were described by taking into account the following reference sequences: NM_000249.2 (MLH1), NM_000251.2 (MSH2), NM_000179.2 (MSH6), and NM_001322014.1 (PMS2). The recurrence or novelty of the identified variants was established by interrogating four databases (in their latest releases as of August 2016): the International Society of Gastrointestinal Hereditary Tumors (InSIGHT) database (accessed via the Leiden Open Variation Database/LOVD), the Universal Mutation Database (UMD), ClinVar, and the Human Gene Mutation Database (HGMD). The MMR variants were classified according to the 5-tier classification system into the following categories: class 5 (pathogenic), class 4 (likely pathogenic), class 3 (uncertain variants), class 2 (likely not pathogenic) and class 1 (not pathogenic) [55]. Novel MMR variants were considered class 5 if they: a) introduced a premature stop codon in the protein sequence (nonsense or frameshift); b) occurred at the most conserved positions of donor or acceptor splice sites (i.e. IVS ± 1, IVS ± 2); or c) represented whole-exon deletions or duplications. Well established polymorphisms, Class 1 variants and Class 2 variants were considered normal variants and not included in this study, except for the MSH6 c.733A > T, which has conflicting interpretations of pathogenicity. We focused on Class 3, Class 4 and Class 5 variants in this study. In addition, we updated our previous South American LS study [32] according to the 5-tier classification system, with InSiGHT updates [55].

Splicing-dedicated bioinformatics analysis

The potential impact on RNA splicing induced by the MMR variants was evaluated by focusing on alterations of donor and acceptor splice sites. We took into consideration both the potential impairment of reference splice sites and the possibility of creation of de novo splice sites. The analysis was performed by using the MaxEntScan algorithm [56] interrogated by using the Alamut software (Interactive Biosoftware, France) [57, 58]. For stratification purposes, negative alterations of reference splice sites were deemed important when MaxEntScan scores showed ≥15% decrease relative to corresponding wild-type splice sites [57]. The possibility of variant-induced de novo splice sites was assessed by annotating all increments in local MaxEntScan scores and comparing their values with those of reference splice sites as well as of nearby cryptic splice sites. In this case and for exonic variants, only scores equal or higher to those of the corresponding reference splice site within the same exon (as well as of local cryptic sites) were considered worth noting. In the case of intronic variants, only scores equal or higher to those of the weakest corresponding reference splice site within the same gene (as well as of local cryptic splice sites) were considered as potentially creating de novo splice sites.

Statistical analysis

Clinical characteristics were described using frequency distributions for categorical variables and summary measures for quantitative variables. To assess comparability of study groups, chi-square test or Fisher’s exact test was used for categorical variables and Student’s t test or Mann-Whitney to compare quantitative variables. The statistical analyses were performed using the statistical software package IBM SPSS Statistics 20 (SPSS©, Chicago, IL, USA) and STATA 12© (StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP).

Results

Path_MMR variants

By combining data provided by 7 participating centers, we identified suspected LS in a total of 881 Latin America individuals belonging to 344 unrelated families (Table 1, Fig. 1). Path_MMR genes were identified in 47% (range 39–64% depending on the participating countries/registries) of the families that fulfilled the AMSII criteria and/or the Bethesda guidelines and/or other criteria (Table 1). When the AMSII criteria were considered, the path_MMR genes detection raised to 64% (91/142), whereas 32% (54/170) and 23% (11/47) fulfilled the Bethesda guidelines and other criteria, respectively. The range of the mean age at diagnosis was 32–45 years for CRC and 43–51 years for endometrial cancer depending on the countries/registries (Table 1). Of the 410 path_MMR carriers, MLH1 was affected in 53.9% (221/410) of the cases, MSH2 in 32.4% (133/410), MSH6 in 9.5% (39/410), PMS2 in 3.4% (14/410) and EPCAM in 0.8% (3/410) (Table 1).
Table 1

Summary of hereditary cancer registries from Latin America LS families

Latin American InstitutionsNumber of familiesNumber of individualsFamilies fulfillinga Path_MMR carriers (%)Path_MMR families fulfillingAge at CRC diagnosis (mean ± SD)Age at endometrial cancer diagnosis (mean ± SD)
AMSIIRevised BethesdaOther criteriaPath_MMR carriersPath_MMR non-carriers Path_MLH1 carriers Path_MSH2 carriers Path_MSH6 carriers Path_PMS2 carriers Path_EPCAM carriersAMSIIRevised BethesdaOther criteria
Barretos Cancer Hospital (São Paulo, Brazil)125369159530172 (46.6)197 (53.4)79 (45.9)51 (29.7)32 (18.6)10 (5.8)0124810nana
Clinica Las Condes (Santiago, Chile)1002124447982 (38.7)130 (61.3)63 (76.8)14 (17.1)02 (2.4)3 (3.7)244040 (10.5)48.8 (11.5)
Hospital de las Fuerzas Armadas (Montevideo, Uruguay)291772612101 (57.1)76 (42.9)55 (54.5)39 (38.6)7 (6.9)00190039.9 (9.6)44.4 (11.9)
Hospital Italiano (Buenos Aires, Argentina)54753514526 (34.7)49 (65.3)11 (42.3)15 (57.7)000180045.8 (7.01)43.8 (7.08)
Hospital Español de Rosario (Rosario, Argentina)132567016 (64)9 (36)5 (31.3)10 (62.5)01 (6.2)062040.4 (10.4)51 (na)
Hospital das Clinicas (Porto Alegre, Brazil)1818126011(61.1)7 (38.9)8 (72.7)3 (27.3)0na0110042.1 (7.8)na
Clinica del Country (Bogota, Colombia)554012 (40)3 (60)01 (50)01 (50)010132 (na)na
Total34488114217047410 (46.5)471 (53.5)221 (53.9)133 (32.4)39 (9.5)14 (3.4)3 (0.8)915411

asome families meet more than one clinical criteria; LS: Lynch syndrome; CRC: colorectal cancer; MMR: mismatch repair; SD: standard deviation; na: not applied; Path_MMR: Pathogenic (disease-causing) variant of an MMR gene; path_MLH1: pathogenic variant of the MLH1 gene; path_MSH2: pathogenic variant of the MSH2 gene; path_MSH6: pathogenic variant of the MSH6 gene; path_PMS2: pathogenic variant of the PMS2 gene

Summary of hereditary cancer registries from Latin America LS families asome families meet more than one clinical criteria; LS: Lynch syndrome; CRC: colorectal cancer; MMR: mismatch repair; SD: standard deviation; na: not applied; Path_MMR: Pathogenic (disease-causing) variant of an MMR gene; path_MLH1: pathogenic variant of the MLH1 gene; path_MSH2: pathogenic variant of the MSH2 gene; path_MSH6: pathogenic variant of the MSH6 gene; path_PMS2: pathogenic variant of the PMS2 gene Fifteen published data from Argentina, Brazil, Chile, Colombia, Dominican Republic, El Salvador, Guatemala, Mexico, Puerto Rico, South America and Uruguay contained information about 962 tested individuals belonging to 1514 suspected LS families (Table 2, Fig. 1). Path_MMR variants were identified in 40% (389/962) (range 25–100% in the different databases/countries) of the families that fulfilled the AMSII criteria and/or the Bethesda guidelines and/or other criteria. The range of the mean age at diagnosis was 35–45 years for CRC and 41–49 years for endometrial cancer in the different databases (Table 2). Of the 389 path_MMR carriers, MLH1 was affected in 52.4% (204/389), MSH2 in 42.7% (166/389), MSH6 in 3.6% (14/389), PMS2 in 0.8% (3/389) and EPCAM in 0.5% (2/389) (Table 2).
Table 2

Summary of published data from Latin America LS families

Latin America LS published databasesNumber of familiesNumber of individualsAge at CRC diagnosis (mean ± SD)Age at endometrial cancer diagnosis (mean ± SD)AMSIIRevised BethesdaOther criteriaPath_MMR carriers (%)Path_MMR non- carriers (%) Path_MLH1 carriers (%) Path_MSH2 carriers (%) Path_MSH6 carriers (%) Path_PMS2 carriers (%) Path_EPCAM carriers (%)
Mendoza, Argentina [10]117nana1009(52.9)8(47.1)09100)nanana
Sao, Paulo, Brazil [11]252545.7(na)na618110(40)15(60)8(80)2(20)nanana
Montevideo, Uruguay [13]121245na12nana3(25)9(75)2(67)1(33)0nana
Bogota, Colombia [12, 48]2323nana1112na11(47.8)12(52.2)10(91)1(9)nanana
Buenos Aires, Argentina [17]4311nana430na5(45.5)6 (54.5)2(40)3(60)nanana
Mexico, El Salvador and Guatemala [51]131438.7(na)na59na11(78.6)3(21.4)7(64)4 (36)nanana
Santiago, Chile [20]2120nana147na9(45)11(55)6(30)3(15)nanana
Antioquia, Colombia [23]120nana1nana7(35)13(65)7(100)0nanana
Southeastern Brazil, Buenos Aires and Montevideo [26]123123nana5766na34(27.6)89(72.4)20(59)14(41)nanana
Santiago, Chile [31]3535nana1916na21(60)14(40)14(67)5(24)2(9)nana
South America [32]267267147120na99(37.1)168(62.9)59(60)40(40)nanana
Buenos Aires, Argentina 28na44.3(6.2)46.3(5.5)
Montevideo, Uruguay 25na35.1(7.6)41.5(8.3)
Santiago, Chile 50na35.7(10.7)41.1(8.8)
Barretos, Brazil) 23na39.4(13.8)49.8(5.3)
Colombia 13nanana
Southeastern Brazil 128na42.3(11.4)48.8(2.4)
Puerto Rico and Dominican Republic [36]783144.4(na)44 (na)nanana22(71)9 (29)8(36)13(59)1(5)nana
Southeastern Brazil [37]11611642.4(na)46 (na)4967na45(38.8)71(61)15(33)25(56)4(9)1(2)na
Jalisco, Mexico [44]3537.7(na)na30na5(100)04(80)1(20)nanana
South America [47]243243nanana98(40.3)145 (56.7)42(43)45(46)7(7)2(2)2(2)
Buenos Aires, Argentina 48na44(na)45(na)
Montevideo, Uruguay 16na42.3(na)48.8(na)
Santiago, Chile 27na41.3(na)43.6(na)
Barretos, Brazil) 23na39.4(na)49.8(na)
Colombia 13nanana
Southeastern Brazil 116na42.4(na)46(na)
Total 15149623683151389 (40.4)573 (59.6)204 (52.4)166 (42.7)14 (3.6)3 (0.8)2 (0.5)

LS: Lynch syndrome; CRC: colorectal cancer; MMR: mismatch repair; SD: standard deviation; na: not applied; Path_MMR: Pathogenic (disease-causing) variant of an MMR gene; path_MLH1: pathogenic variant of the MLH1 gene; path_MSH2: pathogenic variant of the MSH2 gene; path_MSH6: pathogenic variant of the MSH6 gene; path_PMS2: pathogenic variant of the PMS2 gene

Summary of published data from Latin America LS families LS: Lynch syndrome; CRC: colorectal cancer; MMR: mismatch repair; SD: standard deviation; na: not applied; Path_MMR: Pathogenic (disease-causing) variant of an MMR gene; path_MLH1: pathogenic variant of the MLH1 gene; path_MSH2: pathogenic variant of the MSH2 gene; path_MSH6: pathogenic variant of the MSH6 gene; path_PMS2: pathogenic variant of the PMS2 gene

Latin America MMR variants

In total, 220 unique alterations were identified, including 71 frameshift variants, 50 missense variants, 40 nonsense variants, 36 intronic variants and 23 large deletions/duplications. Frameshift and missense variants were the most common alterations (32% and 23%, respectively), followed by nonsense variants (18%), intronic variants (16%) and large deletions/duplications (11%) (Fig. 2, Table 3).
Fig. 2

Type of MMR variants in Latin America LS families

Table 3

Spectrum of MMR variants in Latin America LS families

GenecNomenclaturepNomenclatureExonReported/Current Study classificationReferencesCountryNumber of familiesRNA splicing-dedicated in silico analysis
WT MaxEntScan scoreVariant MaxEntScan scoreDifference in MaxEntScan score between variant and WT (%)
MLH1 c.(?_-198)_116 +?del1Class 5InSIGHTChile2ndndnd
c.83C > Tp.Pro28Leu1Class 5InSIGHTBrazil28.608.600
c.91_92delinsTGp.Ala31Cys1Class 3InSIGHTUruguay18.608.600
c.116G > Ap.Cys39Tyr1Class 4InSIGHTArgentina18.602.61−70
c.117-1G > T1iClass 5HGMDBrazil17.220.00−100
c.117-?_207 +?delp.Cys39* 2Class 5InSIGHTBrazil1ndndnd
c.117-691_306 + 1011delp.Cys39Trpfs*62–3Class 5InSIGHTMexico17.227.220
c.119delTp.Leu40* 2Class 5InSIGHTUruguay17.227.250
c.122A > Gp.Asp41Gly2Class 3InSIGHTBrazil17.227.220
c.199G > Ap.Gly67Arg2Class 5InSIGHTArgentina110.4510.450
c.211G > Tp.Glu71* 3Class 5InSIGHTBrazil18.118.110
c.225delT p.Ile75Metfs3Not reported/Class 5Current studyBrazil18.118.110
c.289 T > Gp.Tyr97Asp3Class 332Uruguay29.859.850
c.306 + 5G > A3iClass 5UMD, HGMDBrazil19.857.20−27
c.307-2A > G1iClass 5UMD (modified from 51)Guatemala110.900.00−100
c.332C > Tp.Ala111Val4Class 4InSIGHTBrazil110.9010.900
C.336 T > Ap.His112Gln4Class 332Argentina110.9010.900
c.350C > Tp.Thr117Met4Class 5InSIGHTUruguay, Argentina58.738.730
c.421C > Gp.Pro141Ala5Class 312Colombia110.6510.650
c.454-501_546-1098delp.Glu153Phefs*85iClass 5InSIGHTUruguay16.396.390
c.503dupAp.Asn168Lysfs*46Class 5InSIGHTChile18.688.680
c.503delAp.Glu172Asnfs*306Class 532Brazil18.688.680
c.545 + 3A > Gp.Glu153Valfs*96iClass 5InSIGHTBrazil28.684.95−43
c.588 + 2 T > Ab 7iClass 426Brazil19.720.00−100
c.588 + 5G > C7iClass 3InSIGHTBrazil19.724.33 −55
c.588 + 5G > T 7iNot reportedCurrent studyArgentina19.723.64 −63
c.665delAp.Asn222Metfs*78Class 5InSIGHTUruguay49.229.220
c.676C > Tp.Arg226* 8Class 5InSIGHTArgentina, Mexico29.227.12−23
c.677G > Ac p.Gln197Argfs*88Class 5InSIGHTArgentina, Brazil29.225.00−46
c.677 + 1G > A8iClass 4InSIGHTBrazil29.220.00−100
c.677 + 5G > A8iClass 4UMDChile, Argentina29.224.42−52
c.779 T > Gp.Leu260Arg9Class 5InSIGHTBrazil110.4310.430
c.790 + 1G > Ap.Glu227_Ser295del9iClass 5InSIGHTChile, Colombia310.430.00−100
c.791–4_795delTTAGATCGT10Class 526Brazil29.420.00−100
c.794G > C d p.Arg265Pro10Not reported80Chile19.429.420
c.884 + 5 T > C 10iNot reportedCurrent studyArgentina19.4310.5212
c.888_890delAGAinsC p.Leu296Phefs11Not reported/Class 5Current studyBrazil110.4610.460
c.901C > Tp.Gln301* 11Class 5InSIGHTChile110.4610.460
c.911delA p.Asp304Valfs*6311Not reported/Class 5Current studyUruguay110.4610.460
c.997_1000delAAGCp.Lys333Serfs*3311Class 578Chile17.207.200
c.1013A > Gp.Asn338Ser11Class 3InSIGHTBrazil17.207.200
c.1023delGp.Met342Cysfs*2511Class 5InSIGHTPuerto Rico27.207.200
c.1038 + 1G > Tp.Thr347PhefsX1411iClass 531Chile17.200.00−100
c.1039-6delT 11iNot reportedCurrent studyArgentina27.509.1322
c.1039-8T_1558?896Tdupp.520Vfs564X12–13Class 523Colombia2ndndnd
c.1105dupT12Class 5Modified from 51Mexico17.507.500
c.1225_1259delp.Gln409* 12Class 5UMDMexico19.999.990
c.1276C > Tp.Gln426* 12Class 5InSIGHTBrazil79.999.990
c.1333C > Tp.Gln445* 12Class 568Brazil19.999.990
c.1360G > Cp.Gly454Arg12Class 3InSIGHTUruguay19.999.990
c.1459C > Tp.Arg487* 13Class 5InSIGHTBrazil111.6611.660
c.1500_1502delCATc,d p.Ile501del13Class 311Brazil19.159.150
c.1558 + 1G > Tp.Val520Glyfs*313iClass 5InSIGHTBrazil19.150.00−100
c.1559-2A > Cb p.Leu521Lysfs*3413iClass 4InSIGHTChile110.440.00−100
c.1559-?_1731 +?delp.Val520Glyfs*714–15Class 531Chile1ndndnd
c.1639_1643dupTTATAp.Leu549Tyrfs*4414Class 5InSIGHTBrazil16.626.620
c.1681dupT p.Tyr561Leufs11Not reported/Class 5Current studyBrazil18.178.170
c.1690_1693delCTCAp.Leu564PhefsTer2615Class 5InSIGHTBrazil18.178.170
c.1724G > Ap.Arg575Lys15Class 332Argentina111.7811.780
c.1731 + 3A > Tb p.(Ser556Argfs*14)15iClass 420Chile111.785.63−52
c.1732-?_1896 +?delp.Pro579_Glu633del16–17Class 5InSIGHTBrazil1ndndnd
c.1763 T > Cp.Leu588Pro16Class 3InSIGHTChile19.349.340
c.1852_1854 delAAGd p.Lys618del16Class 5InSIGHTArgentina, El Salvador, Mexico63.513.510
c.1853delAinsTTCTTp.Lys618Ilefs*416Class 526Brazil23.513.510
c.1855delGd p.Ala619Leufs*1816Class 512, 36Colombia, Puerto Rico33.513.510
c.1863delG p.Met621Ilefs16Not reported/Class 5Current studyBrazil13.513.510
c.1890dupc p.Asp631* 16Class 326Argentina13.513.510
c.1897-?_1989 +?delp.Glu633_Glu663del17Class 5InSIGHTBrazil1ndndnd
c.1897-?_2271 +?del17–19Class 5InSIGHTBrazil4ndndnd
c.1918C > Tp.Pro640Ser17Class 3InSIGHTColombia16.536.530
c.1975C > Tp.Arg659* 17Class 5InSIGHTBrazil27.707.700
c.1990–93 C > T 17iNot reportedCurrent studyArgentina15.345.340
c.1998G > Ap.Trp666* 18Class 511Brazil15.345.340
c.2027 T > Cc p.Leu676Pro18Class 326Brazil15.345.340
c.2041G > A* p.Ala681Thr18Class 5UMDChile, Brazil, Colombia75.345.340
c.2044_2045delp.Met682Valfs*1118Class 534, 36Puerto Rico25.345.340
c.2059C > Tp.Arg687Trp18Class 5InSIGHTBrazil18.688.680
c.2093C > Gp.Ser698* 18Class 5InSIGHTEl Salvador18.688.680
c.2092_2093delTCp.Ser698Argfs*518Class 520Chile18.688.680
c.2103 + 1G > C18iClass 4InSIGHTMexico18.680.00−100
c.2104-?_(*193_?)delp.S702_X757del19Class 531Chile2ndndnd
c.2224C > Tp.Gln742* 19Class 526Brazil17.827.820
c.2252_2253dupAAp.Val752Lysfs*3219Class 3InSIGHTBrazil17.827.820
c.2252_2253delAAp.Lys751Serfs*319Class 5InSIGHTArgentina17.827.820
MSH2 c. * 32 G > C 3’UTRNot reportedCurrent studyArgentina16.116.110
c.71delAp.Gln24Argfs*401Class 532Brazil110.0710.070
c.96dupC p.Thr33Hisfs*491Not reported/Class 5Current studyBrazil110.0710.070
c.112G > T p.Asp38Tyr1Not reportedCurrent studyChile110.0710.070
c.138C > Gp.His46Gln1Class 3InSIGHTUruguay110.0710.070
c.166G > Tp.Glu56*1Class 5InSIGHTArgentina110.0710.070
c.174dupCd p.Lys59Glnfs*231Class 532Brazil310.0710.070
c.181C > Tp.Gln61*1Class 513Uruguay110.0710.070
c.187delGp.Val63*1Class 5InSIGHTBrazil110.0710.070
c.(?_-68)_211 +?del1Class 5InSIGHTArgentina1ndndnd
c.(?_-68)_645 +?del1–3Class 5InSIGHTPuerto Rico2ndndnd
c.(?_-68)_1076 +?del1–6Class 5InSIGHTArgentina1ndndnd
c.212-?_366 +?delp.Ala72Phefs*92Class 5InSIGHTChile1ndndnd
c.226C > Tp.Gln76*2Class 5InSIGHT, UMDMexico18.518.510
c.229_230delAGp.Ser77Cysfs*42Class 5InSIGHTUruguay18.518.510
c.289C > Tp.Gln97*2Class 5InSIGHTArgentina18.838.830
c.367-168C > T 2iNot reportedCurrent studyArgentina26.256.250
c.388_389delCAp.Gln130Valfs*23Class 5InSIGHTBrazil, Argentina36.256.250
c.425C > Gp.Ser142*3Class 5InSIGHTGuatemala16.256.250
c.435 T > Gp.Ile145Met3Class 3InSIGHTArgentina16.256.250
c.458C > Gp.Ser153Cys3Class 337Brazil16.256.250
c.484G > Ap.Gly162Arg3Class 5InSIGHTArgentina16.256.250
c.518 T > Gp.Leu173Arg3Class 3InSIGHTBrazil19.889.880
c.528_529delTGp.Cys176*3Class 5InSIGHTBrazil19.889.880
c.530_531delAAp.Glu177Valfs*33Class 513Uruguay19.889.880
c.557A > Gp.Asn186Ser3Class 3UMDUruguay19.889.880
c.596delTGp.Cys199Leufs*153Class 512Colombia19.889.880
c.638dupT p.Leu213fs3Not reported44Mexico19.889.880
c.645 + 1_645 + 10delins15 3Not reported/Class 5Current studyBrazil19.880.00−100
c.645 + 791_1076 + 4894delp.Ile217Glufs*284–6Class 5InSIGHTBrazil1ndndnd
c.711_727del17 p.Ile237Metfs*134Not reported/Class 5Current studyBrazil17.797.790
c.862C > Tp.Gln288*5Class 5InSIGHTBrazil110.3510.350
c.876_877insC5Class 5Modified from 36Puerto Rico18.598.590
c.897 T > Gp.Tyr299*5Class 531Chile18.598.590
Amplification of exon 55Class 537Brazil1ndndnd
c.905 T > Ap.Leu302*5Class 5InSIGHTPuerto Rico18.598.590
c.914_923delCAGCAGTCAG p.Ala305Glufs*235Not reported/Class 5Current studyArgentina18.598.590
c.942 + 3A > Tp.Val265_Gln314del5iClass 5InSIGHTBrazil28.592.54−70
c.943-1G > T5iClass 5Modified from 36Puerto Rico29.590−100
c.1046C > Gp.Pro349Arg6Class 5InSIGHTArgentina19.819.810
c.1076 + 1_1076 + 2delGT 6iNot reported/Class 5Current studyBrazil19.810.00−100
c.1077-?_1276 +?delp.Leu360Lysfs*167Class 5InSiGHTArgentina; Uruguay; Brazil3ndndnd
c.1077-135_1276 + 119dup7Class 5InSiGHTBrazil18.928.920
c.1143_1144insAp.Arg382Thrfs*77Class 537Brazil15.255.250
c.1147C > Tp.Arg382*7Class 5InSIGHTBrazil15.255.250
c.1165C > Tp.Arg389*7Class 5InSIGHTColombia15.255.250
c.1215C > Ap.Tyr405*7Class 5InSIGHTChile18.928.920
c.1216C > Tp.Arg406*7Class 5InSIGHTUruguay18.928.920
c.1224 T > A p.Tyr408*7Not reported/Class 5InSIGHTArgentina18.928.920
c.1226_1227delAGp.Gln409Argfs*77Class 5InSIGHTBrazil18.928.920
c.1249delGp.Val417Leufs*217Class 5InSIGHTBrazil18.928.920
c.1255C > Tp.Gln419*7Class 5InSIGHTBrazil18.928.920
c.1277-?_1386 +?delp.Lys427Glyfs*48Class 5InSiGHTBrazil1ndndnd
c.1308dupT8Class 5Modified from 36Puerto Rico110.1210.120
c.1444A > Tp.Arg482*9Class 526Brazil211.5911.590
c.1447G > Tp.Glu483*9Class 5InSIGHTBrazil111.5911.590
c.1457_1460delp.Asn486Thrfsx109Class 5InSIGHTPuerto Rico18.858.850
c.1662-2A > G10iClass 4UMD, InSIGHTArgentina18.010.00−100
c.1667delTp. Leu556*11Class 526Brazil18.018.010
c.1667_1668insAp.Thr557Aspfs*511Class 511Brazil18.018.010
c.1705_1706delGAp.Glu569Ilefs*211Class 5InSIGHTBrazil, Puerto Rico28.018.010
c.1738G > Tp.Glu580*11Class 5InSIGHTBrazil17.827.820
c.1759 + 1G > A11iClass 4InSIGHTPuerto Rico17.820.00−100
c.1759 + 57G > T 11iNot reportedCurrent studyArgentina17.827.820
c.1777C > Tp.Gln593*12Class 5InSIGHT, UMDMexico19.059.050
c.1786_1788delAATp.Asn596del12Class 5InSIGHTBrazil19.059.050
c.1861C > Tp.Arg621*12Class 5InSIGHT, UMDArgentina, Brazil29.059.050
c.1864C > Ap.Pro622Thr12Class 314Argentina19.059.050
c.1865C > G p.Pro622Arg12Not reportedInSIGHTArgentina19.059.050
c.1911delCd p.Arg638Glyfs*4712Class 517Argentina14.784.780
c.1967_1970dupACTTp.Phe657Leufs*312Class 526Brazil14.784.780
c.2038C > Tp.Arg680*13Class 5InSIGHTChile18.238.230
c.2046_2047delTGp.Val684AspfsX1413Class 5InSIGHTArgentina18.238.230
c.2078G > A p.Cys693Tyr13Not reportedCurrent studyBrazil18.238.230
c.2131C > Tp.Arg711*13Class 5InSIGHTArgentina, Brazil, Chile410.8610.860
c.2145delp.Asp716Thrfs*413Class 537Brazil110.8610.860
c.2152C > Tp.Gln718*13Class 5InSIGHTBrazil910.8610.860
c.2178_2179insA13Class 5Modified from 51Mexico110.8610.860
c.2185_2192del7insCCCTp.M729_E731delinsP729_X73013Class 520Chile110.8610.860
c.2187G > Tp.Met729Ile13Class 326Brazil110.8610.860
c.2211-?_2458 +?delp.Ser738Cysfs*314Class 5InSIGHTBrazil1ndndnd
c.2525_2526delAGp.Glu842Valfs*315Class 526Brazil29.979.970
c.2785C > Tp.Arg929*16Class 526Brazil, Uruguay26.116.110
EPCAM-MSH2 EPCAM-MSH2 (exon1–4) deletion1–4Class 537Brazil1ndndnd
c.583C > G p.Leu195Val6Not reportedCurrent studyUruguay1ndndnd
c.555 + 402_*1220del 6–9Not reported/Class 5LOVDChile1ndndnd
EPCAM:c.(?_1)_(945_?)_MSH2:c.(?_1)_(1076_?)1–6Class 531Chile1ndndnd
MSH6 c.23_26delACAG p.Tyr8SerfsTer81Not reported/Class 5Current studyBrazil17.387.380
c.44C > Tp.Pro15Leu1Class 3ClinVarUruguay17.387.380
c.124C > Tp.Pro42Leu1Class 337Brazil17.387.380
c.457 + 32del 2iNot reportedCurrent studyArgentina110.7710.770
c.458-?_3172delp.Gly153_Leu1057del3–4Class 532Uruguay1ndndnd
c.663A > Cp.Glu221Asp4Class 3InSIGHTUruguay; Argentina210.8710.870
c.733A > T* p.Ile245Leu4Conflicting interpretations of pathogenicityUMD, InsightUruguay110.8710.870
c.1133_1134delGA p.Arg378Lysfs*34Not reported/Class 5Current studyBrazil110.8710.870
c.1338A > Tp.Glu446Asp4Class 337Brazil110.8710.870
c.1483C > Tp.Arg495*4Class 5InSIGHTBrazil110.8710.870
c.1519dupAp.Arg507Lysfs*94Class 5UMDBrazil210.8710.870
c.1591C > Ap.Pro531Thr4Class 3UMD, ClinVArUruguay110.8710.870
c.1913delInsAGA p.Leu638GlnfsX114Not reported/Class 5Current studyBrazil18.918.910
c.1932G > Cp.Arg644Ser4Class 337Brazil18.918.910
c.2194C > Tp.Arg732*4Class 5InSIGHTBrazil18.918.910
c.2308_2312delinsTp.Gly770Cysfs*44Class 5UMDUruguay18.918.910
c.2332_2335dupCTTT p.Cys779Serfs4Not reported/Class 5Current studyBrazil18.918.910
c.2379_2380delTGp.Ala794Hisfs*94Class 537Brazil1ndndnd
c.2659delC p.Lys888Serfs*184Not reported/Class 5Current studyBrazil18.918.910
c.2983G > Tp.Glu995*4Class 5InSIGHTBrazil18.918.910
c.3023C > T p.Thr1008Ile4Not reportedCurrent studyArgentina18.918.910
c.3119_3120delTTp.Phe1040*4Class 5InSIGHTPuerto Rico18.918.910
c.3487G > Tp.Glu1163*6Class 537Brazil110.5510.550
c.3557-144G > A 6iNot reportedCurrent studyArgentina810.2910.290
c.3557-185C > T 6iNot reportedCurrent studyArgentina110.2910.290
c.3632 T > Cp.Leu1211Pro7Class 5InSIGHTBrazil19.149.140
c.3646 + 91 T > C 6Not reportedCurrent studyArgentina1ndndnd
c.3772C > G p.Gln1258Glu8Not reportedCurrent studyBrazil18.358.350
c.3974_3976delAGAp.K1325del9Class 337Brazil16.256.250
c.4071ins410Class 351Mexico1ndndnd
PMS2 c.23 + 72C > T1iClass 3InSIGHTArgentina58.708.700
c.537 + 187A > G 5iNot reportedCurrent studyArgentina48.048.040
c.697C > Tp.Gln233*6Class 5InSIGHTBrazil16.136.130
c.804-1G > T 8iNot reported/Class 5Current studyColombia13.540.00−100
c.903 + 84 C > T 8iNot reportedCurrent studyArgentina17.647.640
c.903 + 100 T > G 8iNot reportedCurrent studyArgentina17.647.640
c.903 + 144G > T 8iNot reportedCurrent studyArgentina47.647.640
c.1004A > Gp.Asn335Ser10Class 3ClinVarUruguay110.0010.000
c.1144G > Cp.Gly382Arg10Class 337Brazil110.577.69−27
c.1211C > Gp.Pro404Arg11Class 337Brazil17.777.770
c.1239dupp.Asp414Argfs*4411Class 537Brazil17.777.770
c.1437C > Gp.His479Gln11Class 3InSIGHTArgentina17.777.770
c.1831dupAp.Ile611Asnfs*211Class 5InSIGHTArgentina19.069.060
c.2016delGp.Met672Ilefs*1612Class 531Chile18.618.610
c.2036 T > Cp.Ile679Thr12Class 337Brazil1ndndnd
c.2182_2184delinsGp.Thr728Alafs*713Class 5HGMDBrazil2ndndnd
c.2192_2196delTAACT p.Leu731Cysfs*313Class 5InSIGHTBrazil110.7510.750
c.2264 T > Cp.Ile755Thr13Class 337Brazil1ndndnd
c.2276-?_2445 +?delp.Ala759Glyfs*814Class 5InSIGHTChile1ndndnd

LS: Lynch syndrome; Novel MMR variants are represented in bold; a: reported as Class 2 by UMD but not assessed by the InSIGHT; b: MMR variant downgraded from Class 5 to Class 4; c: MMR variant downgraded from Class 5 to Class 3; d: MMR variant updated in the nomenclature; nd: not determined

Type of MMR variants in Latin America LS families Spectrum of MMR variants in Latin America LS families LS: Lynch syndrome; Novel MMR variants are represented in bold; a: reported as Class 2 by UMD but not assessed by the InSIGHT; b: MMR variant downgraded from Class 5 to Class 4; c: MMR variant downgraded from Class 5 to Class 3; d: MMR variant updated in the nomenclature; nd: not determined By the MaxEntScan algorithm, we found that 12% of the variants in our cohort are expected to have a negative impact on RNA splicing (Table 3). Indeed, for 27 out of the 220 variants, the MaxEntScan algorithm predicts a significant decrease in splice site strength (>15% decrease in MaxEntScan scores relative to corresponding wild-type splice sites). These include 23 intronic variants (7 within acceptor sites and 16 at donor sites) and 4 exonic variants (located either at the penultimate or at the last position of the exon). Among these variants, 24 are already considered pathogenic (either Class 4 or Class 5, with MaxEntScan scores ranging from −23% to −100% of WT), including 15 variants located at the most conserved positions of the consensus splice sites, i.e. IVS ± 1 or IVS ± 2, and a nonsense mutation located at the penultimate position of MLH1 exon 8. The three-remaining potential splicing mutations are either currently considered as Class 3 (MLH1 c.588G + 5G > C, and PMS2 c.1144G > C) or have not yet been reported (MLH1 c.588 + 5G > T). Further studies will be necessary to determine if these three variants cause splicing alterations as predicted by MaxEntScan (decrease in donor splice site strength, MaxEntScan scores ranging from −27% to −55% of WT), and if they are pathogenic or not. Our in-silico assessment of potential variant-induced de novo splice sites (data not shown) indicates that 3 out of the 220 variants analyzed in this study are likely to create new splice sites. More precisely, MLH1 c.117-1G > T is predicted to destroy the acceptor site of MLH1 exon 2 and to concomitantly create a potential new and stronger acceptor site 5 nucleotides downstream, within the exon; MSH2 c.645 + 1_645 + 10delins15 is expected to destroy the donor site of MSH2 exon 3 and to create a new donor site 14 nucleotides downstream the reference site, within intron 8; and PMS2 c.804-1G > T is predicted to destroy the acceptor site of PMS2 exon 8 and to concurrently create a new and stronger acceptor site, 8 nucleotides downstream, within the exon. These in silico predictions support the classification of MLH1 c.117-1G > T, MSH2 c.645 + 1_645 + 10delins15 and PMS2 c.804-1G > T as pathogenic (Table 3). Though the single nucleotide variants (SNV) were spread over the genes, most frequently affected regions included exons 11 of MLH1 (15%), exon 3 and 7 of MSH2 (17 and 15%), exon 4 of MSH6 (65%) and exons 11 and 13 of PMS2 (31% and 23%). We found that the Latin America LS variant spectrum was broad with 80% (175/220) alterations being private i.e., observed in a single family, 15% (33/220) observed in 2–3 families and 6% (12/220) variants observed in ≥4 families. Forty-one variants (19%) had not previously been reported in LS, and thus herein represent novel genetic variants in the MMR genes (including 10 in MLH1, 13 in MSH2, 11 in MSH6, 5 in PMS2 and 2 in EPCAM). The classification of the remaining 179 variants is indicated in Table 3, 37 variants being currently considered as Class 3, 10 as Class 4, 131 as Class 5 and 1 has conflicting interpretations of pathogenicity (Table 3, Fig. 3). The variants have been submitted to the InSiGHT locus-specific database (https://www.insight-group.org).
Fig. 3

Latin America MMR variants spectrum

Latin America MMR variants spectrum In total, 45 MMR variants identified in at least two families were classified as recurrent. Among these, the MLH1 c.1276C > T and the MSH2 c.2152C > T were identified in ≥7 families from different Brazilian cities and the MLH1 c.665del was identified in 4 unrelated Uruguayan families. Recurrent pathogenic variants shared by more than one South American country, include: the MLH1 c.350C > T, c.1852_1854del and the c.2041G > A. More precisely, the MLH1 c.350C > T was identified in 5 unrelated families from Uruguay and Argentina, the MLH1 c.1852_1854del was detected in 6 unrelated families from Argentina, Brazil, El Salvador and Mexico, and the MLH1 c.2041G > A was observed in 7 unrelated families from Chile, Colombia and Brazil. These variants may thus represent frequent MLH1 variants in South American population. Moreover, we found a high incidence of intronic and not previously reported MSH6 and PMS2 variants in Argentina (Table 3).

Founder variants

Here, we identified 16 international founder variants: 8 in MLH1,7 in MSH2 and 1 in MSH6 pathogenic variants in 27 LS families [23, 34, 36, 59–74] (Table 4). International founder pathogenic variants detected in >2 unrelated LS families included e.g. MLH1 c.545 + 3A > G identified as an Italian founder pathogenic variant [75], MSH2 c.388_389del as a Portuguese founder variant identified in Argentina [69]. The MSH2 c.942 + 3A > T was found in 2 unrelated Brazilian families and widely described as a Newfoundland founder variant. It had been identified in different populations and could be considered as a world-wide MSH2 variant [26, 64]. The MLH1 c.1039-8T_1558 + 896Tdup has been suggested to represent a founder MMR variant in Colombia [23]. In line with the Portuguese influence in Brazil, the MLH1 c.1897-?_2271 +?del encompassing exons 17 to 19 have been identified in 4 unrelated Brazilian families [69, 70]. The MLH1 c.2044_2045del have been recently described as a founder variant in Puerto Rico [34, 36] and the MSH2 c.1077-?_1276 +?del as a Spanish founder Alu-mediated rearrangement which have been identified in Argentina, Uruguay and Brazil [67].
Table 4

Founder mutations found in Latin America LS families

GeneFounder mutationTotal number of LS families (references)Origin (comments)
MLH1 c.306 + 5G > A1 in Brazil [61]Spain
MLH1 c.545 + 3A > G2 in Brazil [75]Italy
MLH1 c.1039-8T_1558 + 896Tdup2 in Colombia [23](no haplotype studies were performed)
MLH1 c.1558 + 1G > T1 in Brazil [65]Italy
MLH1 c.1732-?_1896 +?del1 in Brazil [66, 72]Finland
MLH1 c.1897-?_2271 +?del4 in Brazil [70, 68]Portugal (mutation with an estimated age of 283 years)
MLH1 c.2044_2045del2 in Puerto Rico [34, 36]Puerto Rico
MLH1 c.2252_2253delAA1 in Argentina [40]Italy (Northern region)
MSH2 c.(?_-68)_1076 +?del1 in Argentina[63, 71, 73]Italy and North America
MSH2 c.388_389del2 in Argentina and 1 in Brazil [69]Portugal
MSH2 c.942 + 3A > T2 in Brazil [64]Newfoundland (considered a world-wide MSH2 variant)
MSH2 c.1077-?_1276 +?del1 in Argentina, 1 in Uruguay and 1 in Brazil [67]Spain (Alu-mediated rearrangements)
MSH2 c.1165C > T1 in Colombia [62]French Canada
MSH2 c.1277-?_1386 +?del1 in Brazil [60]Italy (Sardinia)
MSH2 c.2185_2192del7insCCCT1 in Chile [20]Amerindian
MSH6 c.2983G > T1 in Brazil [74]Finland

LS Lynch syndrome

Founder mutations found in Latin America LS families LS Lynch syndrome

Update of the MMR variants from the previous South America LS study

Due to changes in InSIGHT classification of variants, 14 variants were altered for the MLH1 gene and 2 for the MSH2 gene, relative to our previous classification in Dominguez-Valentin et al. [32]. For MLH1, 3 previously classified Class 5 variants were downgraded to Class 4, while 4 previously classified Class 5 were moved to Class 3 and 3 previously classified Class 5 were moved to Class 1 (MLH1: c.1558 + 14G > A, c.1852_1853delinsGC, c.1853A > C). Three MLH1 variants were updated in their nomenclature. For MSH2 gene, two variants were updated in their nomenclature (Table 3).

Differences between LS patients according to the path_MMR gene

The clinicopathological characteristics evaluated were similar between path_MLH1, path_MSH2, path_MSH6, path_PMS2 and path_EPCAM carriers, except for the mean age at CRC diagnosis for MLH1 (39.6 years) and MSH2 carriers (41.5 years) (p ≤ 0.05) (Table 5). For path_MLH1 carriers, we observed that the probands had more family history of CRC (56.4%) than LS-associated cancers (20.1%) and 97% fulfilled the AMSII criteria. LS individuals with path_MSH2, path_MSH6 and path_PMS2 were mostly females (63.5%, 90% and 77.8% respectively). Path_MSH2 carriers fulfilled AMSII criteria (100%) while path_MSH6 and path_PMS2 carriers had more family history of CRC (30% and 75%, respectively) than LS-associated cancers (10% and 25%, respectively). Path_EPCAM carriers had a lower number for each clinical characteristic (Table 5). Deviating distributions of the parameters discussed above for path_MSH6 and especially path_PMS2 carriers may have escaped significance due to limited number of carriers included.
Table 5

Clinicopathologic characterization of LS patients acording to the affected MMR gene

Clinical characteristicsPath_MMR carriers p value
Path_MLH1 Path_MSH2 Path_MSH6 Path_PMS2 Path_EPCAM
Age at CRC diagnosis (mean)*37.5–41.7 (39.6)*38.6–41.7 (41.5)*31.2–43.9 (37.5)38–58 (48)38–65 (51.5)
Gender (n(%))
 Female39 (54.2)40 (63.5)9 (90)7 (77.8)1 (33.3)
 Male33 (45.8)23 (36.5)1 (10)2 (22.2)2 (66.7)0.261
Family history of CRC (n(%))
 Yes53 (56.4)35 (48.6)3 (30)3 (75)2 (66.7)
 No41 (43.6)37 (51.4)7 (70)1 (25)1 (33.3)0.449
Family history LS associated cancers (n(%))
 Yes27 (20.1)18 (25)1 (10)1 (25)2 (66.7)
 No107 (79.9)54 (75)9 (90)3 (75)1 (33.3)0.135
AMSII/Bethesda criteria (n(%))
 AMSII criteria131(97)72(100)8 (100)2 (66.7)2 (66.7)
 Bethesda4 (3)0001 (33.3)na
 Other criteria0001 (33.3)

*P ≤ 0.05; LS: Lynch syndrome; CRC: colorectal cancer; na: not applied; Path_MMR: Pathogenic (disease-causing) variant of an MMR gene; path_MLH1: pathogenic variant of the MLH1 gene; path_MSH2: pathogenic variant of the MSH2 gene; path_MSH6: pathogenic variant of the MSH6 gene; path_PMS2: pathogenic variant of the PMS2 gene; path_EPCAM: pathogenic variant of the EPCAM gene

The analysis was performed based on available information from Hospital de las Fuerzas Armadas, Uruguay (except for the gender); Clinicas Las Condes, Chile; Hospital Italiano, Argentina; Hospital Espanol de Rosario, Argentina; Hospital de Clinicas, Brazil (except for family history of LS associated cancers) and Clinica del Country, Colombia

Clinicopathologic characterization of LS patients acording to the affected MMR gene *P ≤ 0.05; LS: Lynch syndrome; CRC: colorectal cancer; na: not applied; Path_MMR: Pathogenic (disease-causing) variant of an MMR gene; path_MLH1: pathogenic variant of the MLH1 gene; path_MSH2: pathogenic variant of the MSH2 gene; path_MSH6: pathogenic variant of the MSH6 gene; path_PMS2: pathogenic variant of the PMS2 gene; path_EPCAM: pathogenic variant of the EPCAM gene The analysis was performed based on available information from Hospital de las Fuerzas Armadas, Uruguay (except for the gender); Clinicas Las Condes, Chile; Hospital Italiano, Argentina; Hospital Espanol de Rosario, Argentina; Hospital de Clinicas, Brazil (except for family history of LS associated cancers) and Clinica del Country, Colombia

Tumor testing results

Tumors specimens from 83 individuals from Peru, 6 from Argentina, 61 from Bolivia, and 60 from Mexico were analyzed either by IHC and MSI-testing, MSI-testing only, or IHC only, respectively, (Table 6). Of these, 69 (32.8%) were found to have MMR-deficient tumors as determined by IHC or MSI analysis (Table 6). The range of the mean age at diagnosis was 27–43 years for CRC and 37–52 years for endometrial cancer in the different registries. The prevalence of deficient MMR protein expression (MLH1, MSH2, MSH6, PMS2) among Peruvian, Argentinean and Mexican patients was 48%, 50% and 38%, respectively, with most cases having absence of MLH1 protein (data available upon request). Regardless of their MMR proficiency status (proficient vs. deficient), patients had similar ages at CRC diagnosis and gender (Table 7). As shown in Table 7, family history of CRC was increased in MMR-deficient individuals compared to MMR proficient (P ≤ 0.05). Interestingly, AMSII criteria were more frequently fulfilled among MMR deficient (42.4%) than MMR-proficient (10.9%) individuals and this difference was statistically significant (P ≤ 0.05) (Table 7).
Table 6

Summary of hereditary cancer registries data from tumor MMR analysis from suspected Latin America LS families

Latin American InstitutionsNumber of familiesNumber of individualsAge at CRC diagnosis (mean ± SD)Age at endometrial cancer diagnosis (mean ± SD)Clinical criteriaMMR deficient (%)MMR non-deficient (%)
AMSIIRevised Bethesda
Instituto Nacional de Enfermedades Neoplásicas (Lima, Peru)a 828341(13.1)52(9.01)226040(48.2)43(51.8)
Centro de EnfermedadesNeoplasicas Oncovida (La Paz, Boliva)b 466127.7(12.7)na4603(4.9)58(95.1)
Instituto Nacional de Cancerología de México (Mexico City, Mexico)c 236033(14.6)37.5(12.02)111223(38.3)37(61.7)
Hospital Privado Universitario de Cordoba (Cordoba, Argentina)c 6643.3(8.7)NA063(50.0)3(50.0)
Total157210797869(32.8)141(67.2)

a: MMR deficiency analyzed based on IHC and/or MSI; b: MMR deficiency based on BAT-25 MSI marker; c: MMR deficiency based on IHC; NA: not applied; MMR: mismatch-repair; CRC: colorectal cancer; SD: standard deviation; IHC: immunohistochemistry; MSI: microsatellite instability; MSI-H: MSI-high; MSS: microsatellite stable

Table 7

Comparison of MMR- deficient versus MMR- proficient individuals from suspected Latin America LS families

Clinical characteristicsMMR status p value
DeficientProficient
Age at CRC diagnosis (mean + − SD)42.4736.3
Gender (n(%))
 Male27 (39.1)36 (34.6)
 Female42 (60.9)68 (65.4)0.545637
Family history of CRC (n(%))
 Yes66 (98.5)40 (87)
 No1 (1.5)6 (13) 0.012333
Family history Lynch syndrome associated cancers (n(%))
 Yes14 (20.9)6 (13)
 No53 (79.1)40 (87)0.282626
AMSII/Bethesda criteria (n(%))
 AMSII28 (42.4)5 (10.9)
 Bethesda38 (57.6)41 (89.1) 0.000314

*P ≤ 0.05; CRC colorectal cancer, MMR mismatch repair

Summary of hereditary cancer registries data from tumor MMR analysis from suspected Latin America LS families a: MMR deficiency analyzed based on IHC and/or MSI; b: MMR deficiency based on BAT-25 MSI marker; c: MMR deficiency based on IHC; NA: not applied; MMR: mismatch-repair; CRC: colorectal cancer; SD: standard deviation; IHC: immunohistochemistry; MSI: microsatellite instability; MSI-H: MSI-high; MSS: microsatellite stable Comparison of MMR- deficient versus MMR- proficient individuals from suspected Latin America LS families *P ≤ 0.05; CRC colorectal cancer, MMR mismatch repair Compilation of IHC and MSI data from reports on Latin America LS cases (published results and/or database entries) revealed that 21% had MMR deficiency based on IHC and/or MSI analysis (2.5%–60%). No information was available for the mean age at CRC and endometrial cancer diagnosis (Table 8). This data highlights the importance of genetic testing for LS in these populations.
Table 8

Summary of published data from tumor MMR analysis from suspected Latin America LS families

Latin America published dataNumber of familiesNumber of individualsClinical criteriaMMR deficient (%)MMR non-deficient (%)Loss IHCMSI
AMSIIRevised BethesdaOther criteriaMLH1 (%)PMS2 (%)MSH2 (%)MSH6 (%)PMS1 or MSH3* (%)MSI-H (%)MSS (%)
Medellin, Colombia [16]41414271014 (34.1)27 (65.9)nanananana14 (34.1)27 (65.9)
Rosario Santa Fe, Argentina [14]131nana1 (33.3)2 (66.7)nanananana1 (33.3)2 (66.7)
Sao Paulo, Brazil [15]106106nanana14 (13.2)92 (86.8)nanananana14 (13.2)91 (85.9)
Buenos Aires, Argentina [18]41401602518 (45)22 (55)12 (30)na7 (17.5)nana13 (32.5)17 (42.5)
Minas Gerais, Brazil [22]66668154315 (22.7)51 (77.3)nanananana15 (22.7)51 (77.3)
San Juan, Puerto Rico [21]164164nanana7 (4.3)157 (95.7)1 (0.06)na6 (3.7)nana1 (0.6)na
Lima, Peru [24]9090nanana35 (38.9)55 (61.1)23 (25.6)18 (20)4 (4.4)2 (2.2)na26 (28.9)64 (71.1)
Rio Grande do Sul, Brazil [25]21219722100042 (21.3)155 (78.7)nanananana42 (21.4)155 (78.7)
Mexico City, Mexico [27]1060512 (33.3)4 (66.7)2 (33.3)na0nananana
Minas Gerais, Brazil [28]777710171016 (20.8)61 (79.2)nanananana16 (20.8)61 (79.2)
Santiago, Chile [31]35351916na21 (60)14 (40)21 (60)06 (17.1)4 (11.4)na28 (80)7 (20)
Lambayeque, Peru [35]5350na1 (33.3)2 (66.7)1 (33.3)1 (33.3)00na1 (33.3)0
Sao Paulo, Brazil [37]118118952573 (2.5)115 (97.5)3 (2.5)3 (2.5)5 (4.2)5 (4.2)na12 (10.2)na
Santo Andre, SP, Brazil [43]48482na1713 (27.1)35 (72.9)2 (4.2)3 (6.3)02 (4.2)9 (19)nana
Lima, Peru [45]2828002811 (39.3)17 (60.7)nanananana11 (39.3)17 (60.7)
Total1042102296232191213 (20.8)809 (79.2)65 (46.4)25 (17.9)28 (20)13 (9.3)9 (6.4)168 (36.9)287 (63.1)

MMR mismatch repair, MSI microsatellite instabily, MSI-H MSI-high, MSS microsatellite stable; na not applied, SD standard deviation, IHC immunohistochemistry

Summary of published data from tumor MMR analysis from suspected Latin America LS families MMR mismatch repair, MSI microsatellite instabily, MSI-H MSI-high, MSS microsatellite stable; na not applied, SD standard deviation, IHC immunohistochemistry Since there are no premonitory signs of susceptibility to LS, family history has been the primary method for identifying patients at risk in Brazil, Mexico, Peru and Paraguay. Four published reports showed that 11.5% (107/931) were selected as likely LS on the basis of a positive family history (Table 9).
Table 9

Summary of family history analysis from published data from suspected Latin America LS families

Latin American DatabasesNumber of familiesNumber of individualsClinical criteriaInterpreted as Sporadic casesSuspected LS (%)Non-suspected LS (%)Median age at CRC diagnosis
AMSIIRevised BethesdaOther criteria
Mexico City, Mexico [49]21021020561542 (0.95)208 (99.05)na
Asuncion, Paraguay [50]32432490na3159 (2.8)315 (97.2)55
Sao Paulo, Brazil [19]3113114412139845 (31.5)266 (85.5)na
Lima, Peru [33]8686203180651 (59.3)35 (40.7)na
Total 9319313572349573107 (11.5)824 (88.6)

na not applied, MMR mismatch-repair genes, CRC colorectal cancer, LS Lynch syndrome

Summary of family history analysis from published data from suspected Latin America LS families na not applied, MMR mismatch-repair genes, CRC colorectal cancer, LS Lynch syndrome

Discussion

Progress has been achieved throughout the past years regarding a better molecular and clinical characterization of LS in Latin America, which is important for the surveillance and management of high-risk patients and their families [2]. Here, we present the first thorough LS investigation in Latin America by taking into account 15 different countries. We found that germline genetic testing for LS is already available in six of these countries (Argentina, Brazil, Chile, Colombia, Uruguay and Puerto Rico). Moreover, in three countries (Bolivia, Peru and Mexico), where genetic testing is not yet implemented, tumor analyses are already performed for identifying patients most likely to carry a path_MMR variant. According to our data, the contribution from the different MMR genes is apparently slightly higher for MLH1 and MSH2 and lower for MSH6 and PMS2 when comparing to the InSIGHT database and international reports. It is possible that this pattern reflects the recent inclusion of MSH6, PMS2 and EPCAM in LS genetic testing in Latin America molecular diagnostic laboratories but could also reflect population structure [32, 48, 76, 77]. Interestingly, the clinicopathological features of path_MMR carriers described in Latin America families are in accordance with other studies, e.g. the AMSII criteria were fulfilled by 64% of the path_MMR carriers [37, 77]. This study revealed that the Latin America spectrum of MMR variants is broad with a total of 220 different variants, of which 80% are currently considered as private, whereas 20% are deemed as recurrent. Our data support evidence on a significant contribution from large deletions/duplications in EPCAM and frameshift variants in MLH1 and MSH2. Of the 220 MMR variants, 178 were already listed in the InSiGHT database or previous studies [78, 79], whereas 41 have not been previously reported in LS [80]. In addition, we observed that MSH2 variants most frequently caused disease in Argentinean LS families. Further studies are needed to elucidate the ancestral origin of MMR variants in this population, which may increase the knowledge on the inheritance of LS among affected Latin America individuals [10, 14, 17, 40]. Differences in the spectrum of path_MMR variants between populations could be due to differences in the sample size, clinical criteria, selection bias, as well as, genetic ancestry of the individual populations. For instance, Caribbean Hispanics have higher percentage of African ancestry compared to Argentineans and Uruguay nationals [36]. Puerto Ricans are an admixed population of three ancestral populations, including European, Africans and Taínos [36]. The South American population is ethnically mixed from American Indian, European, and other ancestries, but the proportions may vary between countries. For instance, European ancestry predominates in Uruguay and Argentina, whereas Brazil includes a more heterogeneous population, which is the result of interethnic crosses between the European colonizers (mainly Portuguese), African slaves, and the autochthonous Amerindians [15]. The Peruvian population is a multi-ethnic population with Amerindian (45%), Mestizo (37%), white Spanish influence (15%), as well as other minority ethnic groups, such as African-American, Japanese, and Chinese (3%) [24]. In Chile, Colombia and Bolivia, Spanish colonist and American Indian ancestry influence the populations [20, 32]. It is well established that awareness of founder variants in a specific geographic area or population can be very helpful in designing cost-effective molecular diagnostic approaches [70, 81, 82]. Founder mutations provide molecular diagnostic centers the benefit of unambiguous results and thereby, do not demand high skilled professional training. The other aim of the study was to investigate if the previously MMR variants identified in South American LS families [32] are in accordance with the 5-tier classification system [55]. We were able to refine the classification of 16 MLH1 and MSH2 variants. When the tumor MMR data from original and published studies were combined, up to 33% of suspected LS individuals had MMR deficiency. The frequency of MMR deficiency was lower than that reported in studies focusing in American, Spanish and Australian LS families (56%–72%) but is in line to the reported prevalence of MSI in sporadic CRC among Hispanic patients [34, 83–86]. These differences could also be a reflect of the differences in the tumor testing methodologies across the countries, e.g. MSI analysis is not widely available in the majority of routine pathology service laboratories, the number of MSI mononucleotide markers varies between laboratories as well as the limitation in the number of MMR proteins analyzed by IHC. Moreover, even if MMR deficiency is a good predictor of carrying a germline path_MMR variant, MMR deficiency can also result from somatic inactivation, most commonly due to methylation of the MLH1 promoter [86]. IHC and MSI testing will, however, combined identify most LS patients with high sensitivity and specificity. In Latin America, low budgets make the issue of integrating genetics into clinical practice a challenge, a situation in which the use of family history becomes important for patient care, as it is a low-cost strategy and a risk assessment tool [19]. In this scenario, published family history data from Paraguay, Peru, Brazil and Mexico suggest its use as a triage tool together with IHC and MSI to identify and stratify genetic risk in these populations [19]. However, awareness of hereditary cancer among clinicians involved in diagnosis and treatment of CRC is currently low, and families actually meeting the clinical criteria may not be identified [77]. In addition, the average life expectancy in Latin America and the Caribbean is 75 years and inequalities persist among and within the countries (www.paho.org). These countries are mainly represented by a young population where family history could be less informative and insensitive for assessing genetic screening for LS. Limitation on genetic testing has an impact in the evaluation of the patients at risk of hereditary cancer and their relatives, and ultimately increases the burden of cancer for this minority population [35]. As mentioned, in Latin America, genetic testing is not routinely available at the public health system, with exception of few studies conducted in research institutes or private institutions. For instance, until recently the coverage of oncogenetic services in Brazil, was restricted to less than 5% of the population. However, a significant advance took place in 2012, when the coverage of genetic testing by private health care plans became mandatory in Brazil, currently covering around 20–30% of the population [19, 87]. This work provides a snapshot view of the current LS-associated diagnostics practice/output in Latin America. The limitations of this study include the selection of patients recruited from selected reference centers and/or from a nation-wide public reference hospital for cancer patients that cannot renders a representative sample. Furthermore, the diagnostic methodologies may vary between the countries regarding the coverage of the coding region of the genes tested and the clinical criteria for referral to genetic counseling and testing, thus causing an even larger knowledge gap. Finally, several countries are not represented; for instance, we could not find any reports from Venezuela, Honduras, Nicaragua or Ecuador. It will be important to pursue additional studies on LS in Latin America countries to both increase the knowledge of MMR variants in different populations and to bring additional awareness of this condition to medical professionals and public health leaders in Latin America.

Conclusions

The Latin America LS MMR variants spectrum included new MMR variants, genetic frequent regions and potential founder effect. The present study provides support to set or improve LS genetic testing in these countries. Improving the accessibility, including tertiary care, is vital in low-income and middle-income countries that face an increasing burden of CRC. An early diagnosis and intensive screening may predict the disease and/or improve the disease prognosis. Low cost approaches to reach these ends are discussed.
  83 in total

1.  A unique MSH2 exon 8 deletion accounts for a major portion of all mismatch repair gene mutations in Lynch syndrome families of Sardinian origin.

Authors:  Iolanda Borelli; Marco A Barberis; Francesca Spina; Guido C Casalis Cavalchini; Caterina Vivanet; Luisa Balestrino; Monica Micheletti; Anna Allavena; Paola Sala; Carlo Carcassi; Barbara Pasini
Journal:  Eur J Hum Genet       Date:  2012-07-11       Impact factor: 4.246

2.  Characterization of germline mutations of MLH1 and MSH2 in unrelated south American suspected Lynch syndrome individuals.

Authors:  Mev Dominguez Valentin; Felipe Carneiro da Silva; Erika Maria Monteiro dos Santos; Bianca Garcia Lisboa; Ligia Petrolini de Oliveira; Fabio de Oliveira Ferreira; Israel Gomy; Wilson Toshihiko Nakagawa; Samuel Aguiar Junior; Mariana Redal; Carlos Vaccaro; Adriana Della Valle; Carlos Sarroca; Dirce Maria Carraro; Benedito Mauro Rossi
Journal:  Fam Cancer       Date:  2011-12       Impact factor: 2.375

Review 3.  Mismatch repair genes founder mutations and cancer susceptibility in Lynch syndrome.

Authors:  G Ponti; E Castellsagué; C Ruini; A Percesepe; A Tomasi
Journal:  Clin Genet       Date:  2014-12-09       Impact factor: 4.438

4.  Frequency of hereditary non-polyposis colorectal cancer among Uruguayan patients with colorectal cancer.

Authors:  C Sarroca; A Della Valle; R Fresco; E Renkonen; P Peltömaki; Ht Lynch
Journal:  Clin Genet       Date:  2005-07       Impact factor: 4.438

5.  Microsatellite instability among individuals of Hispanic origin with colorectal cancer.

Authors:  Samir Gupta; Raheela Ashfaq; Payal Kapur; Bianca B Afonso; Thuy-Phuong T Nguyen; Faryal Ansari; C Richard Boland; Ajay Goel; Don C Rockey
Journal:  Cancer       Date:  2010-11-01       Impact factor: 6.860

6.  Risk of cancer in cases of suspected lynch syndrome without germline mutation.

Authors:  María Rodríguez-Soler; Lucía Pérez-Carbonell; Carla Guarinos; Pedro Zapater; Adela Castillejo; Victor M Barberá; Miriam Juárez; Xavier Bessa; Rosa M Xicola; Juan Clofent; Luis Bujanda; Francesc Balaguer; Josep-Maria Reñé; Luisa de-Castro; José C Marín-Gabriel; Angel Lanas; Joaquín Cubiella; David Nicolás-Pérez; Alejandro Brea-Fernández; Sergi Castellví-Bel; Cristina Alenda; Clara Ruiz-Ponte; Angel Carracedo; Antoni Castells; Montserrat Andreu; Xavier Llor; José L Soto; Artemio Payá; Rodrigo Jover
Journal:  Gastroenterology       Date:  2013-01-24       Impact factor: 22.682

7.  Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals.

Authors:  Gene Yeo; Christopher B Burge
Journal:  J Comput Biol       Date:  2004       Impact factor: 1.479

8.  [Immunohistochemical expression and microsatellite instability in Lynch syndrome].

Authors:  Carlos A Vaccaro; Jorge E Carrozzo; Esteban Mocetti; Mariana Berho; Paula Valdemoros; Eduardo Mullen; Myriam Oviedo; Maria A Redal
Journal:  Medicina (B Aires)       Date:  2007       Impact factor: 0.653

Review 9.  The promise of biomarkers in colorectal cancer detection.

Authors:  Asad Umar; Sudhir Srivastava
Journal:  Dis Markers       Date:  2004       Impact factor: 3.434

10.  Lynch syndrome mutation spectrum in New South Wales, Australia, including 55 novel mutations.

Authors:  Wenche Sjursen; Mary McPhillips; Rodney J Scott; Bente A Talseth-Palmer
Journal:  Mol Genet Genomic Med       Date:  2016-01-11       Impact factor: 2.183

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  15 in total

1.  Low Referral Rate for Genetic Testing in Racially and Ethnically Diverse Patients Despite Universal Colorectal Cancer Screening.

Authors:  Charles Muller; Sang Mee Lee; William Barge; Shazia M Siddique; Shivali Berera; Gina Wideroff; Rashmi Tondon; Jeremy Chang; Meaghan Peterson; Jessica Stoll; Bryson W Katona; Daniel A Sussman; Joshua Melson; Sonia S Kupfer
Journal:  Clin Gastroenterol Hepatol       Date:  2018-08-18       Impact factor: 11.382

Review 2.  Genetic predisposition to colorectal cancer: syndromes, genes, classification of genetic variants and implications for precision medicine.

Authors:  Laura Valle; Eduardo Vilar; Sean V Tavtigian; Elena M Stoffel
Journal:  J Pathol       Date:  2019-02-20       Impact factor: 7.996

3.  When guidelines face reality - Lynch syndrome screening in the setting of public health system in a developing country.

Authors:  Vanessa Nascimento Kozak; Enilze Maria de Souza Fonseca Ribeiro; Milena Massumi Kozonoe; Sergio Ossamu Ioshii; Jose Claudio Casali da Rocha
Journal:  J Community Genet       Date:  2021-10-08

Review 4.  Recent progress in Lynch syndrome and other familial colorectal cancer syndromes.

Authors:  Patrick M Boland; Matthew B Yurgelun; C Richard Boland
Journal:  CA Cancer J Clin       Date:  2018-02-27       Impact factor: 508.702

5.  Challenges to Bringing Personalized Medicine to a Low-Resource Setting in Peru.

Authors:  Nelly Solis; Elizabeth Zavaleta; Patrik Wernhoff; Constantino Dominguez-Barrera; Mev Dominguez-Valentin
Journal:  Int J Environ Res Public Health       Date:  2021-02-04       Impact factor: 3.390

6.  Evidence of response to pembrolizumab in a patient with Lynch syndrome-related metastatic colon cancer.

Authors:  Pamela Salman; Sergio Panay; René Fernández; Mauricio Mahave; Cristian Soza-Ried
Journal:  Onco Targets Ther       Date:  2018-10-23       Impact factor: 4.147

7.  Mutation Spectrum of Cancer-Associated Genes in Patients With Early Onset of Colorectal Cancer.

Authors:  Gulnur Zhunussova; Georgiy Afonin; Saltanat Abdikerim; Abai Jumanov; Anastassiya Perfilyeva; Dilyara Kaidarova; Leyla Djansugurova
Journal:  Front Oncol       Date:  2019-08-02       Impact factor: 6.244

Review 8.  Genetics and genomics in Peru: Clinical and research perspective.

Authors:  Heinner Guio; Julio A Poterico; Kelly S Levano; Mario Cornejo-Olivas; Pilar Mazzetti; Gioconda Manassero-Morales; Manuel F Ugarte-Gil; Eduardo Acevedo-Vásquez; Milagros Dueñas-Roque; Alejandro Piscoya; Ricardo Fujita; Cesar Sanchez; Sandro Casavilca-Zambrano; Luis Jaramillo-Valverde; Yasser Sullcahuaman-Allende; Juan M Iglesias-Pedraz; Hugo Abarca-Barriga
Journal:  Mol Genet Genomic Med       Date:  2018-11       Impact factor: 2.183

9.  Spectrum and Frequency of Tumors, Cancer Risk and Survival in Chilean Families with Lynch Syndrome: Experience of the Implementation of a Registry.

Authors:  Karin Álvarez; Paulina Orellana; Marjorie De la Fuente; Tamara Canales; Eliana Pinto; Claudio Heine; Benjamín Solar; Claudia Hurtado; Pål Møller; Udo Kronberg; Alejandro José Zarate; Mev Dominguez-Valentin; Francisco López-Köstner
Journal:  J Clin Med       Date:  2020-06-15       Impact factor: 4.241

Review 10.  From colorectal cancer pattern to the characterization of individuals at risk: Picture for genetic research in Latin America.

Authors:  Carlos Alberto Vaccaro; Francisco López-Kostner; Della Valle Adriana; Edenir Inez Palmero; Benedito Mauro Rossi; Marina Antelo; Angela Solano; Dirce Maria Carraro; Nora Manoukian Forones; Mabel Bohorquez; Leonardo S Lino-Silva; Jose Buleje; Florencia Spirandelli; Kiyoko Abe-Sandes; Ivana Nascimento; Yasser Sullcahuaman; Carlos Sarroca; Maria Laura Gonzalez; Alberto Ignacio Herrando; Karin Alvarez; Florencia Neffa; Henrique Camposreis Galvão; Patricia Esperon; Mariano Golubicki; Daniel Cisterna; Florencia C Cardoso; Giovana Tardin Torrezan; Samuel Aguiar Junior; Célia Aparecida Marques Pimenta; Maria Nirvana da Cruz Formiga; Erika Santos; Caroline U Sá; Edite P Oliveira; Ricardo Fujita; Enrique Spirandelli; Geiner Jimenez; Rodrigo Santa Cruz Guindalini; Renata Gondim Meira Velame de Azevedo; Larissa Souza Mario Bueno; Sonia Tereza Dos Santos Nogueira; Mariela Torres Loarte; Jorge Padron; Maria Del Carmen Castro-Mujica; Julio Sanchez Del Monte; Carmelo Caballero; Carlos Mario Muñeton Peña; Joseph Pinto; Claudia Barletta-Carrillo; Gutiérrez Angulo Melva; Tamara Piñero; Paola Montenegro Beltran; Patricia Ashton-Prolla; Yenni Rodriguez; Richard Quispe; Norma Teresa Rossi; Claudia Martin; Sergio Chialina; Pablo German Kalfayan; Juan Carlos Bazo-Alvarez; Alcides Recalde Cañete; Constantino Dominguez-Barrera; Lina Nuñez; Sabrina Daniela Da Silva; Yesilda Balavarca; Patrik Wernhoff; John-Paul Plazzer; Pål Møller; Eivind Hovig; Mev Dominguez-Valentin
Journal:  Int J Cancer       Date:  2018-12-05       Impact factor: 7.396

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