Journal of Oncology

Journal of Oncology / 2020 / Article

Review Article | Open Access

Volume 2020 |Article ID 1807929 | https://doi.org/10.1155/2020/1807929

Maria Lorenzi, Mayur Amonkar, Jacky Zhang, Shivani Mehta, Kai-Li Liaw, "Epidemiology of Microsatellite Instability High (MSI-H) and Deficient Mismatch Repair (dMMR) in Solid Tumors: A Structured Literature Review", Journal of Oncology, vol. 2020, Article ID 1807929, 17 pages, 2020. https://doi.org/10.1155/2020/1807929

Epidemiology of Microsatellite Instability High (MSI-H) and Deficient Mismatch Repair (dMMR) in Solid Tumors: A Structured Literature Review

Academic Editor: Giandomenico Roviello
Received09 Oct 2019
Revised23 Jan 2020
Accepted28 Jan 2020
Published09 Mar 2020

Abstract

Background. Given limited data on the epidemiology of MSI-H and dMMR across solid tumors (except colorectal cancer (CRC)), the current study was designed to estimate their prevalence. Materials and Methods. A structured literature review identified English language publications that used immunohistochemistry (IHC) or polymerase chain replication (PCR) techniques. Publications were selected for all tumors except CRC using MEDLINE, EMBASE, and Cochrane databases and key congresses; CRC and pan-tumor genomic publications were selected through a targeted review. Meta-analysis was performed to estimate pooled prevalence of MSI-H/dMMR across all solid tumors and for selected tumor types. Where possible, prevalence within tumor types was estimated by disease stages. Results. Of 1,176 citations retrieved, 103 and 48 publications reported prevalence of MSI-H and dMMR, respectively. Five pan-tumor genomic studies supplemented the evidence base. Tumor types with at least 5 publications included gastric (n = 39), ovarian (n = 23), colorectal (n = 20), endometrial (n = 53), esophageal (n = 6), and renal cancer (n = 8). Overall MSI-H prevalence (with 95% CI) across 25 tumors was based on 90 papers (28,213 patients) and estimated at 14% (10%–19%). MSI-H prevalence among Stage 1/2 cancers was estimated at 15% (8%–23%); Stages 3 and 4 prevalence was estimated at 9% (3%–17%) and 3% (1%–7%), respectively. Overall, dMMR prevalence across 13 tumor types (based on 54 papers and 20,383 patients) was estimated at 16% (11%–22%). Endometrial cancer had the highest pooled MSI-H and dMMR prevalence (26% and 25% all stages, respectively). Conclusions. This is the first comprehensive attempt to report pooled prevalence estimates of MSI-H/dMMR across solid tumors based on published data. Prevalence determined by IHC and PCR was generally comparable, with some variations by cancer type. Late-stage prevalence was lower than that in earlier stages.

1. Introduction

DNA mismatch repair (MMR) is a process that plays a key role in maintaining genomic stability by recognizing and repairing base-base mismatches and insertion/deletion of DNA generated during replication and recombination. Defects in MMR are associated with genome-wide instability and the progressive accumulation of mutations, especially regions of simple repetitive DNA sequences known as microsatellites, resulting in MSI. MSI-high (MSI-H) is a hypermutable phenotype that allows mutations to be accumulated rapidly, resulting in tumor development via the selection of cancer-promoting mutations in pathways that are responsible for maintaining functional DNA repair, apoptosis, and cell growth.

To test for MSI-H and dMMR statuses in solid tumors, polymerase chain reaction (PCR) and immunohistochemistry (IHC) methods have been widely accepted as respective testing platforms for these biomarkers. The PCR method uses a panel of microsatellite markers to detect size shifts in different loci. The IHC method uses a more direct test to determine the presence of MMR proteins. A tumor is typically classified as MSI-H if shifts are detected in at least 2 of 5 loci using the PCR method and dMMR if at least one MMR protein is absent using the IHC method. The use of NCI (BAT-25, BAT-26, D2S123, D5S346, and D17S250) [1] and Promega (BAT-25, BAT-26, NR-21, NR-24, and MONO-27) [2] panels in PCR and the use of MLH1, MSH2, MSH6, and PMS2 proteins in IHC are considered the gold standard approaches [3, 4, 5].

Among patients diagnosed with metastatic cancer and MSI-H or dMMR, prognosis is generally poor [6]. Recently, evidence has mounted on the benefits of immunotherapy, especially with checkpoint inhibitors such as pembrolizumab on MSI-H/dMMR tumors [7, 8, 9]. Historically, most patients with a solid tumor diagnosis were not tested for MSI; a better understanding of MSI-H and dMMR prevalence can help estimate the size of the potential target population. To provide reliable estimates of MSI-H and dMMR prevalence, a comprehensive structured literature review was conducted to gather relevant and recent evidence on the epidemiology of MSI-H and dMMR across multiple tumors. When sufficient data were available, meta-analysis was performed to estimate the prevalence of MSI-H and dMMR tumors overall, across individual tumor types, and by stage of disease.

2. Methods

Study eligibility criteria outlined in Table 1 guided study identification and selection for the literature review.


CriteriaDescription

PopulationPatients with solid tumors

Outcomes(i) Assessment of prevalence of MSI-H (using NCI marker panel: BAT25, BAT26, D2S123, D5S346, and D17S250) or Promega marker panel: BAT25, BAT26, NR21, NR24, and MONO27) and/or dMMR (by immunohistochemistry for all four MMR proteins: MLH1, MSH2, MSH6, and PMS2) overall, by tumor type, by histology subtype, by stage, by treatment, by region, by country, and by gender
(a) Proportion of MSI as defined in study (e.g., MSI-H, MSI-L, and MSI-S)
(b) Proportion of dMMR and pMMR as defined in study
(ii) Survival rates by MSI-H/dMMR status overall, by stage and by tumor type
(a) Overall survival (OS) and progression-free survival (PFS)
(1) Hazard ratios along with 95% confidence interval (CI)
(2) Median (in months) and 95% CI
(iii) Objective response rate (ORR), defined as complete response (CR) or partial response (PR)
(iv) Disease control rate, defined as CR, PR, or stable disease

Study design(i) Prospective and retrospective cohort studies
(ii) Randomized controlled trials
(iii) Case-control studies
(iv) Cross-sectional studies
(v) Controlled and uncontrolled longitudinal studies (cohorts or case series)

LanguageOnly studies published in English will be included

TimeNo time limit

Abbreviations: dMMR, deficient mismatch repair; MLH1, MutL homolog 1; MSH2, MutS protein homolog 2; MSH6, MutS homolog 6; MSI-H, microsatellite instability high; MSI-L, microsatellite instability low; MSI-S/MSS, microsatellite stable; NCI, National Cancer Institute; pMMR, proficient mismatch repair; PMS2, postmeiotic segregation increased 2.
2.1. Literature Review

Relevant studies were identified by searching the following through the Ovid platform: Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica database (Embase), and Cochrane Central Register of Controlled Trials. Predefined search strategies were executed on October 26th, 2017. Study design filters recommended by the Scottish Intercollegiate Guidelines Network (SIGN) were used. Population terms were adapted from published research [9]; no intervention or comparator terms were used.

Systematic reviews, meta-analyses, and key narrative reviews of interest were identified via hand searching. Targeted hand searches were conducted to identify colorectal cancer (CRC) studies and pan-tumor genomic studies reporting MSI-H/dMMR prevalence. Studies for all solid tumors except CRC were selected through database searches; CRC and pan-tumor genomic studies were selected through a targeted review. One reviewer reviewed all abstracts and proceedings identified through database searches and the targeted review according to the selection criteria. Studies identified as potentially eligible during abstract screening were screened in full-text by the same reviewer. The full-text studies identified at this stage were included for data extraction. The process of study identification and selection are summarized with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagrams [10].

One reviewer extracted data on study characteristics, interventions, patient characteristics, and outcomes from included studies. The second reviewer independently extracted data from a random 10% of the publications, reconciled the data, and determined the error rate and missing data rate of data extraction by the first reviewer. The error rate (number of cells with incorrect data/number of cells with text) was 2.9%, and the missing data rate (number of cells with missing data/number of blank cells) was 1.2% (an error rate greater than 5% would have triggered extraction of a further 10% of publications by the second reviewer). All errors discovered through this process were corrected. Potential publication biases were checked through funnel plots. Data were stored and managed in a Microsoft Excel workbook.

Only studies that used PCR or IHC methods were included in this review. To increase validity of the meta-analysis, only studies that used NCI (BAT-25, BAT-26, D2S123, D5S346, and D17S250) or Promega (BAT-25, BAT-26, NR-21, NR-24, and MONO-27) panels in PCR and MLH1, MSH2, MSH6, and PMS2 proteins in IHC were included in the meta-analysis. The only exceptions were pan-tumor genomic studies, which used large-scale sequencing techniques to test for the presence of only the MLH1 gene. These genomic studies were included in sensitivity analyses to detect their potential effect on the meta-analysis.

Prevalence of MSI-H and/or dMMR was extracted overall, by tumor type, histology, stage, and country.

2.2. Meta-Analysis

Reported proportions were transformed according to the Freeman–Tukey variant of the arcsine square root (double arcsine) transformed proportion [11]. The pooled proportion was calculated by back-transforming the weighted mean of the transformed proportions, using the DerSimonian–Laird random effects model [12].

Meta-analysis was conducted using the metafor package version 1.9-9 in R 3.4.0. Weighting of each tumor type was based on cancer-specific prevalence estimates provided by the GLOBOCAN 2012 database from the World Health Organization [13]. For rare tumor types, when data were unavailable on the GLOBOCAN database, other databases and peer-reviewed publications were referenced [1418]. Each tumor type was assigned a weight based on its general prevalence; in cases where two or more studies were included for a given tumor type, weight was split proportionally between studies based on the sample size.

3. Results

The study selection process for identification of studies reporting MSI-H or dMMR prevalence in the structured literature review is outlined in Figure 1. Overall, 1,176 publications were assessed for eligibility; a total of 156 full-text publications were included based on the structured and targeted literature review.

3.1. Feasibility Assessment of Meta-Analysis

References for included studies can be found in Tables 24. Of the 156 included full-text publications, 103 studies reported prevalence of any MSI status, which included MSI-H, MSI-L (microsatellite instability-low), and MSS (microsatellite stable). Forty-eight studies reported prevalence of dMMR according to the eligibility criteria. Five large pan-tumor genomic studies reported MSI-H status across multiple solid tumors.


AuthorYearTitleJournalTumor type

Abraham2002Microsatellite instability in intraductal papillary neoplasms of the biliary tractNaturePancreatic
Adduri2014P53 nuclear stabilization is associated with FHIT loss and younger age of onset in squamous cell carcinoma of oral tongueBMC Clinical PathologyOral cavity
Akbari2017Correlation between germline mutations in MMR genes and microsatellite instability in ovarian cancer specimensFamilial CancerOvarian
Alldinger2007Microsatellite instability in Ewing tumor is not associated with loss of mismatch repair protein expressionJournal of Cancer Research and Clinical OncologyEwing sarcoma
Altavilla2010Microsatellite instability and hMLH1 and hMSH2 expression in renal tumorsOncology ReportsRenal
Amaki-Takao2016Colorectal cancer with BRAF D594G mutation is not associated with microsatellite instability or poor prognosisOncology (Switzerland)Colorectal
An2005Prognostic significance of CpG island methylator phenotype and microsatellite instability in gastric carcinomaClinical Cancer ResearchGastric
An2012Microsatellite instability in sporadic gastric cancer: its prognostic role and guidance for 5-fu based chemotherapy after r0 resectionInternational Journal of CancerGastric
Aparicio2013Small bowel adenocarcinoma phenotyping, a clinicobiological prognostic studyBritish Journal of CancerSmall bowel
Aysal2012Ovarian endometrioid adenocarcinoma: incidence and clinical significance of the morphologic and immunohistochemical markers of mismatch repair protein defects and tumor microsatellite instabilityThe American Journal of Surgical PathologyOvarian
Bacani2005Tumor microsatellite instability in early onset gastric cancerJournal of Molecular DiagnosticsGastric
Bae2015Usefulness of immunohistochemistry for microsatellite instability screening in gastric cancerGut and LiverGastric
Basil2000Clinical significance of microsatellite instability in endometrial carcinomaCancerEndometrial
Bataille2003Alterations in p53 predict response to preoperative high dose chemotherapy in patients with gastric cancerJournal of Clinical Pathology-Molecular PathologyGastric
Billingsley2015Polymerase e (pole) mutations in endometrial cancer: clinical outcomes and implications for Lynch syndrome testingCancerEndometrial
Black2006Clinicopathologic significance of defective DNA mismatch repair in endometrial carcinomaJournal of Clinical OncologyEndometrial
Buller2001p53 mutations and microsatellite instability in ovarian cancer: Yin and YangAmerican Journal of Obstetrics & GynecologyOvarian
Buttin2006Increased risk for abnormalities on perioperative colon screening in patients with microsatellite instability-positive endometrial carcinomaInternational Journal of Gynecological CancerEndometrial
Cai2004Microsatellite instability and alteration of the expression of hMLH1 and hMSH2 in ovarian clear cell carcinomaHuman PathologyOvarian
Catasus2004Molecular genetic alterations in endometrioid carcinomas of the ovary: similar frequency of beta-catenin abnormalities but lower rate of microsatellite instability and PTEN alterations than in uterine endometrioid carcinomasHuman PathologyOvarian
Cesinaro2007Mismatch repair proteins expression and microsatellite instability in skin lesions with sebaceous differentiation: a study in different clinical subgroups with and without extracutaneous cancerThe American Journal of DermatopathologySebaceous
Chiaravalli2001Immunohistochemical pattern of hMSH2/hMLH1 in familial and sporadic colorectal, gastric, endometrial and ovarian carcinomas with instability in microsatellite sequencesVirchows ArchivGastric, endometrial, ovarian, and colorectal
Choe2005High frequency of microsatellite instability in intestinal-type gastric cancer in Korean patientsThe Korean Journal of Internal MedicineGastric
Choi2015Correlation between microsatellite instability-high phenotype and occult lymph node metastasis in gastric carcinomaAPMISGastric
Chong2013The genomic landscape of oesophagogastric junctional adenocarcinomaJournal of PathologyOesophagogastric junctional
Choy2004Microsatellite instability and MLH1 promoter methylation in human retinoblastomaInvestigative Ophthalmology and Visual scienceRetinoblastoma
Cook2013Endometrial cancer and a family history of cancerGynecologic OncologyEndometrial and other unspecified tumors
Cullinane2004Microsatellite instability is a rare finding in tumors of patients with both primary renal and rectal neoplasmsCancer Genetics & CytogeneticsRectal and renal
Dewdney2012Uterine serous carcinoma: increased familial risk for Lynch-associated malignanciesCancer Prevention ResearchEndometrial
Evans2004Microsatellite instability in esophageal adenocarcinomaCancer LettersEsophageal
Fu2012Cpg island methylator phenotype-positive tumors in the absence of mlh1 methylation constitute a distinct subset of duodenal adenocarcinomas and are associated with poor prognosisClinical Cancer ResearchSmall bowel
Garcia2006Mismatch repair protein expression and microsatellite instability: a comparison of clear cell sarcoma of soft parts and metastatic melanomaModern PathologyClear Cell Sarcoma and Melanoma
Gargano2007Aberrant methylation within RUNX3 CpG island associated with the nuclear and mitochondrial microsatellite instability in sporadic gastric cancers. Results of a GOIM (gruppo oncologico dell’italia meridionale) prospective studyAnnals of OncologyGastric
Geiseler2003Mismatch repair gene expression defects contribute to microsatellite instability in ovarian carcinomaCancerOvarian
Glavac2003Low microsatellite instability and high loss of heterozygosity rates indicate dominant role of the suppressor pathway in squamous cell carcinoma of head and neck and loss of heterozygosity of 11q14.3 correlates with tumor gradeCancer Genetics & CytogeneticsHead and neck
Goodfellow2003Prevalence of defective DNA mismatch repair and MSH6 mutation in an unselected series of endometrial cancersProceedings of the National Academy of Sciences of the United States of AmericaEndometrial
Gras2001Microsatellite instability, MLH-1 promoter hypermethylation, and frameshift mutations at coding mononucleotide repeat microsatellites in ovarian tumorsCancerOvarian
Grogg2003Lymphocyte-rich gastric cancer: associations with Epstein-Barr virus, microsatellite instability, histology, and survivalModern PathologyGastric
Gu2009Analysis of microsatellite instability, protein expression and methylation status of hmlh1 and hmsh2 genes in gastric carcinomasHepato-GastroenterologyGastric
Hampel2005Screening for the Lynch syndrome (hereditary nonpolyposis colorectal cancer)The New England Journal of MedicineColorectal
Hasuo2007Assessment of microsatellite instability status for the prediction of metachronous recurrence after initial endoscopic submucosal dissection for early gastric cancerBritish Journal of CancerGastric
Hermsen2009Genome-wide analysis of genetic changes in intestinal-type sinonasal adenocarcinomaHead & neckNasopharynx
Honecker2009Microsatellite instability, mismatch repair deficiency, and BRAF mutation in treatment-resistant germ cell tumorsJournal of Clinical OncologyTestis
Hong2012The differential impact of microsatellite instability as a marker of prognosis and tumour response between colon cancer and rectal cancerEuropean Journal of CancerColorectal
Huang2010Comparative features of colorectal and gastric cancers with microsatellite instability in Chinese patientsJournal of Zhejiang University ScienceGastric and colorectal
Jahng2012Endoscopic and clinicopathologic characteristics of early gastric cancer with high microsatellite instabilityWorld Journal of GastroenterologyGastric
Jensen2008Microsatellite instability and mismatch repair protein defects in ovarian epithelial neoplasms in patients 50 years of age and youngerAmerican Journal of surgical PathologyOvarian
Jung2016aPrognostic impact of microsatellite instability in colorectal cancer presenting with mucinous, signet-ring, and poorly differentiated cellsAnnals of ColoproctologyColorectal
Jung2016bObservational study: familial relevance and oncological significance of revised bethesda guidelines in colorectal patients that have undergone curative resectionMedicine (United States)Colorectal
Kanopiene2014Impact of microsatellite instability on survival of endometrial cancer patientsMedicinaEndometrial
Karpińska-Kaczmarczyk2016Expression of mismatch repair proteins in early and advanced gastric cancer in PolandMedical Science MonitorGastric
Kawaguchi2009Analysis of candidate target genes for mononucleotide repeat mutation in microsatellite instability-high (MSI-H) endometrial cancerInternational Journal of OncologyEndometrial
Kawanaka2016Effects of Helicobacter pylori eradication on the development of metachronous gastric cancer after endoscopic treatment: analysis of molecular alterations by a randomised controlled trialBritish Journal of CancerGastric
Kim1999Accumulated frameshift mutations at coding nucleotide repeats during the progression of gastric carcinoma with microsatellite instabilityLaboratory InvestigationGastric
Kim2013aMicrosatellite instability status in gastric cancer: a reappraisal of its clinical significance and relationship with mucin phenotypesKorean Journal of PathologyGastric
Kim2013bDifferential clinicopathologic features in microsatellite-unstable gastric cancers with and without MLH1 methylationHuman PathologyGastric
Kim2016aClinicopathologic features of gastric cancer with synchronous and metachronous colorectal cancer in Korea: are microsatellite instability and p53 overexpression useful markers for predicting colorectal cancer in gastric cancer patients?Gastric CancerGastric and colorectal
Kim2016bMicrosatellite instability of gastric and colorectal cancers as a predictor of synchronous gastric or colorectal neoplasmsGut and LiverGastric and colorectal
Koopman2009Deficient mismatch repair system in patients with sporadic advanced colorectal cancerBritish Journal of CancerColorectal
Kubo2005Frequent microsatellite instability in primary esophageal carcinoma associated with extraesophageal primary carcinomaInternational Journal of CancerEsophageal
Kumagai2015Mucinous phenotype and cd10 expression of primary adenocarcinoma of the small intestineWorld Journal of GastroenterologySmall bowel
Leenen2012Prospective evaluation of molecular screening for Lynch syndrome in patients with endometrial cancer ≤70 yearsGynecologic OncologyEndometrial
Leite2011MSI phenotype and MMR alterations in familial and sporadic gastric cancerInternational Journal of CancerGastric
Liu2004Microsatellite instability and expression of hMLH1 and hMSH2 proteins in ovarian endometrioid cancerModern PathologyOvarian
Lu2007Prospective determination of prevalence of Lynch syndrome in young women with endometrial cancerJournal of Clinical OncologyEndometrial
Martinez2005Low-level microsatellite instability phenotype in sporadic glioblastoma multiformeJournal of Cancer Research and Clinical OncologyBrain
Mathiak2017Clinicopathologic characteristics of microsatellite instable gastric carcinomas revisited: urgent need for standardizationApplied Immunohistochemistry and Molecular MorphologyGastric
Matsumoto2007Microsatellite instability and clinicopathological features in esophageal squamous cell cancerOncology ReportsEsophageal
McCleary2016Prognostic utility of molecular factors by age at diagnosis of colorectal cancerClinical Cancer ResearchColorectal
McConechy2015Detection of DNA mismatch repair (mmr) deficiencies by immunohistochemistry can effectively diagnose the microsatellite instability (msi) phenotype in endometrial carcinomasGynecologic OncologyEndometrial
McCourt2007Body mass index: relationship to clinical, pathologic and features of microsatellite instability in endometrial cancerGynecologic OncologyEndometrial
Moy2015Microsatellite instability in gallbladder carcinomaVirchows ArchivGallbladder
Nagahashi2008Genetic changes of p53, Kras, and microsatellite instability in gallbladder carcinoma in high-incidence areas of Japan and HungaryWorld Journal of GastroenterologyGallbladder
Okuda2005The profile of hMLH1 methylation and microsatellite instability in colorectal and non-small cell lung cancerInternational Journal of Molecular MedicineColorectal, NSCLC
Rajan2014DNA mismatch repair defects and microsatellite instability status in periocular sebaceous carcinomaAmerican Journal of OphthalmologySebaceous
Roa2005Microsatellite instability in preneoplastic and neoplastic lesions of the gallbladderJournal of GastroenterologyGallbladder
Rodriguez-Hernandez2013Integrated analysis of mismatch repair system in malignant astrocytomasPLoS One (electronic resource)Brain
Rubio2016Analysis of Lynch syndrome mismatch repair genes in women with endometrial cancerOncologyEndometrial
Rubio-Del-Campo2008Implications of mismatch repair genes hmlh1 and hmsh2 in patients with sporadic renal cell carcinomaBJU internationalRenal
Ruemmele2009Histopathologic features and microsatellite instability of cancers of the papilla of vater and their precursor lesionsThe American Journal of Survival PathologyPancreatic
Saetta2004Mononucleotide markers of microsatellite instability in carcinomas of the urinary bladderEuropean Journal of Surgical OncologyBladder
Schneider2000Microsatellite instability, prognosis and metastasis in gastric cancers from a low-risk populationInternational Journal of CancerGastric
Seo2009Clinicopathologic characteristics and outcomes of gastric cancers with the MSI-H phenotypeJournal of Surgical OncologyGastric
Seo2015Clinicopathologic and molecular features associated with patient age in gastric cancerWorld Journal of GastroenterologyGastric
Shibata2006RAB32 hypermethylation and microsatellite instability in gastric and endometrial adenocarcinomasInternational Journal of CancerGastric and endometrial
Shilpa2014Microsatellite instability, promoter methylation and protein expression of the DNA mismatch repair genes in epithelial ovarian cancerGenomicsOvarian
Shirai2006Interleukin-8 gene polymorphism associated with susceptibility to non-cardia gastric carcinoma with microsatellite instabilityJournal of Gastroenterology and Hepatology (Australia)Gastric
Singer2004Different types of microsatellite instability in ovarian carcinomaInternational Journal of CancerOvarian
Skenderi2017Warthin-like papillary renal cell carcinoma: Clinicopathologic, morphologic, immunohistochemical and molecular genetic analysis of 11 casesAnnals of Diagnostic PathologyRenal
Soliman2005Women with synchronous primary cancers of the endometrium and ovary: do they have Lynch syndrome?Journal of Clinical Oncology: Official Journal of the American Society of Clinical OncologyEndometrial and ovarian
Sood2001Application of the National Cancer Institute international criteria for determination of microsatellite instability in ovarian cancerCancer ResearchOvarian
Stello2016Improved risk assessment by integrating molecular and clinicopathological factors in early-stage endometrial cancer-combined analysis of the PORTEC cohortsClinical Cancer ResearchEndometrial
Stoehr2012Mismatch repair proteins hMLH1 and hMSH2 are differently expressed in the three main subtypes of sporadic renal cell carcinomaPathobiologyRenal
Suemori2015Intratumoral cd8+ lymphocyte infiltration as a prognostic factor and its relationship with cyclooxygenase 2 expression and microsatellite instability in endometrial cancerInternational Journal of Gynecological CancerEndometrial
Sugai2017Genetic differences stratified by PCR-based microsatellite analysis in gastric intramucosal neoplasiaGastric CancerGastric
Tanaka2006Effect of eradication of Helicobacter pylori on genetic instabilities in gastric intestinal metaplasiaAlimentary Pharmacology and Therapeutics Symposium SeriesGastric
Tay2003A combined comparative genomic hybridization and expression microarray analysis of gastric cancer reveals novel molecular subtypesCancer ResearchGastric
Vladimirova2008Low level of microsatellite instability in paediatric malignant astrocytomasNeuropathology and Applied NeurobiologyBrain
Wen2012DNA mismatch repair deficiency in breast carcinoma a pilot study of triple-negative and non-triple-negative tumorsThe American Journal of Survival PathologyBreast
Wong2003The role of microsatellite instability in cervical intraepithelial neoplasia and squamous cell carcinoma of the cervixGynecologic OncologyCervical
Yan2016Prediction of biological behavior and prognosis of colorectal cancer patients by tumor msi/mmr in the Chinese populationOncoTargets and TherapyColorectal
Yoon2008Clinical significance of microsatellite instability in sporadic epithelial ovarian tumorsYonsei Medical JournalOvarian
Zighelboim2007Microsatellite instability and epigenetic inactivation of MLH1 and outcome of patients with endometrial carcinomas of the endometrioid typeJournal of Clinical OncologyEndometrial


AuthorYearTitleJournalTumor type

Backes2009Prospective evaluation of DNA mismatch repair protein expression in primary endometrial cancerGynecologic OncologyEndometrial
Bennett2016Mismatch repair protein expression in clear cell carcinoma of the ovary: incidence and morphologic associations in 109 casesThe American Journal of Surgical PathologyOvarian
Bhosale2017Can reduced field-of-view diffusion sequence help assess microsatellite instability in FIGO stage 1 endometrial cancer?Journal of Magnetic Resonance ImagingEndometrial
Brady2017Sebaceous carcinoma treated with Mohs micrographic surgeryDermatologic SurgerySebaceous
Bregar2017Characterization of immune regulatory molecules b7-h4 and pd-l1 in low and high grade endometrial tumorsGynecologic OncologyEndometrial
Bruegl2014Evaluation of clinical criteria for the identification of Lynch syndrome among unselected patients with endometrial cancerCancer Prevention ResearchEndometrial
Bruegl2017Clinical challenges associated with universal screening for Lynch syndrome-associated endometrial cancerCancer Prevention ResearchEndometrial
Buchanan2014Tumor mismatch repair immunohistochemistry and DNA mlh1 methylation testing of patients with endometrial cancer diagnosed at age younger than 60 years optimizes triage for population-level germline mismatch repair gene mutation testingJournal of Clinical OncologyEndometrial
Carleton2016A detailed immunohistochemical analysis of a large series of cervical and vaginal gastric-type adenocarcinomasThe American Journal of Surgical pathologyCervical and vaginal
Chen2017Immunohistochemical profiling of endometrial serous carcinomaInternational Journal of Gynecological PathologyEndometrial
Clay2014Risk of secondary malignancy (including breast) in patients with mismatch-repair protein deficiencyThe American Journal of Surgical pathologyEndometrial
Connor2017Association of distinct mutational signatures with correlates of increased immune activity in pancreatic ductal adenocarcinomaJAMA OncologyPancreatic
Djordjevic2013Relationship between PTEN, DNA mismatch repair, and tumor histotype in endometrial carcinoma: retained positive expression of PTEN preferentially identifies sporadic non-endometrioid carcinomasModern PathologyEndometrial
Everett2014Screening for germline mismatch repair mutations following diagnosis of sebaceous neoplasmJAMA DermatologySebaceous
Gaskin2011The significance of DNA mismatch repair genes in the diagnosis and management of periocular sebaceous cell carcinoma and Muir-Torre syndromeBritish Journal of OphthalmologySebaceous
Goldberg2017Microcystic, elongated, and fragmented pattern invasion in ovarian endometrioid carcinoma: immunohistochemical profile and prognostic implicationsInternational Journal of Gynecological PathologyOvarian
Grzankowski2012Clinical and pathologic features of young endometrial cancer patients with loss of mismatch repair expressionGynecologic OncologyEndometrial
Joehlin-Price2014Mismatch repair protein expression in 1049 endometrial carcinomas, associations with body mass index, and other clinicopathologic variablesGynecologic OncologyEndometrial
Kato2015DNA mismatch repair-related protein loss as a prognostic factor in endometrial cancersJournal of Gynecologic OncologyEndometrial
Kawazoe2017Clinicopathological features of programmed death ligand 1 expression with tumor-infiltrating lymphocyte, mismatch repair, and Epstein-Barr virus status in a large cohort of gastric cancer patientsGastric CancerGastric
Kobel2017Frequent mismatch repair protein deficiency in mixed endometrioid and clear cell carcinoma of the endometriumInternational Journal of Gynecological PathologyEndometrial
Liau2014Hypermethylation of the cdkn2a gene promoter is a frequent epigenetic change in periocular sebaceous carcinoma and is associated with younger patient ageHuman PathologySebaceous
Liu2014DNA mismatch repair abnormalities in acinar cell carcinoma of the pancreas frequency and clinical significancePancreasPancreatic
Milione2016The clinicopathologic heterogeneity of grade 3 gastroenteropancreatic neuroendocrine neoplasms: morphological differentiation and proliferation identify different prognostic categoriesNeuroendocrinologyGastroenteropancreatic
Moreira2012Identification of Lynch syndrome among patients with colorectal cancerJAMAColorectal
Okoye2016Defective DNA mismatch repair influences expression of endometrial carcinoma biomarkersInternational Journal of Gynecological PathologyEndometrial
Park2016Epstein-Barr virus positivity, not mismatch repair-deficiency, is a favorable risk factor for lymph node metastasis in submucosa-invasive early gastric cancerGastric CancerGastric
Pecorino2017Genetic screening in young women diagnosed with endometrial cancerJournal of Gynecologic OncologyEndometrial
Peterson2012Molecular characterization of endometrial cancer: a correlative study assessing microsatellite instability, mlh1 hypermethylation, DNA mismatch repair protein expression, and pten, pik3ca, kras, and braf mutation analysisInternational Journal of Gynecological PathologyEndometrial
Ramos2017Lymphoepithelioma-like gastric carcinoma: Clinicopathological characteristics and infection statusJournal of surgical ResearchGastric
Ring2013Women 50 years or younger with endometrial cancer the argument for universal mismatch repair screening and potential for targeted therapeuticsInternational Journal of Gynecological CancerEndometrial
Roberts2013Screening for Muir-Torre syndrome using mismatch repair protein immunohistochemistry of sebaceous neoplasmsJournal of Genetic CounselingSebaceous
Rosa-Rosa2016Molecular genetic heterogeneity in undifferentiated endometrial carcinomasModern PathologyEndometrial
Ruiz2014Lack of association between deficient mismatch repair expression and outcome in endometrial carcinomas of the endometrioid typeGynecologic OncologyEndometrial
Sahnane2015Microsatellite unstable gastrointestinal neuroendocrine carcinomas: a new clinicopathologic entityEndocrine-Related CancerGastroenteropancreatic
Shih2011Clinicopathologic significance of DNA mismatch repair protein defects and endometrial cancer in women 40 years of age and youngerGynecologic OncologyEndometrial
Steinestel2014Invasion pattern and histologic features of tumor aggressiveness correlate with MMR protein expression, but are independent of activating kras and braf mutations in CRCVirchows ArchivColorectal
Talhouk2016Molecular classification of endometrial carcinoma on diagnostic specimens is highly concordant with final hysterectomy: earlier prognostic information to guide treatmentGynecologic OncologyEndometrial
Talhouk2015A clinically applicable molecular-based classification for endometrial cancersBritish Journal of CancerEndometrial
Talhouk2017Confirmation of ProMisE: a simple, genomics-based clinical classifier for endometrial cancerCancerEndometrial
Therkildsen2015Glioblastomas, astrocytomas and oligodendrogliomas linked to Lynch syndromeEuropean Journal of NeurologyBrain
Thoury2014Evidence for different expression profiles for c-Met, EGFR, PTEN and the mTOR pathway in low and high grade endometrial carcinomas in a cohort of consecutive women. Occurrence of pik3ca and k-ras mutations and microsatellite instabilityHistology and HistopathologyEndometrial
Vierkoetter2014Lynch syndrome in patients with clear cell and endometrioid cancers of the ovaryGynecologic OncologyOvarian
Vierkoetter2016Loss of mismatch repair protein expression in unselected endometrial adenocarcinoma precursor lesionsInternational Journal of Gynecological CancerEndometrial
Watkins2016Universal screening for mismatch-repair deficiency in endometrial cancers to identify patients with Lynch syndrome and Lynch-like syndromeInternational Journal of Gynecological PathologyEndometrial
Wiegand2014Arid1a/baf250a as a prognostic marker for gastric carcinoma: a study of 2 cohortsHuman PathologyGastric
Woo2014The immunohistochemistry signature of mismatch repair (MMR) proteins in a multiethnic Asian cohort with endometrial carcinomaInternational Journal of Gynecological PathologyEndometrial
Zakhour2017Abnormal mismatch repair and other clinicopathologic predictors of poor response to progestin treatment in young women with endometrial complex atypical hyperplasia and well-differentiated endometrial adenocarcinoma: a consecutive case seriesBJOG: An International Journal of Obstetrics and GynecologyEndometrial


AuthorYearTitleJournalTumor type

Bonneville2017Landscape of microsatellite instability across 39 cancer typesJCO Precision OncologyMany (genomic)
Chalmers2017Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burdenGenome MedicineMany (genomic)
Cortes-Ciriano2017A molecular portrait of microsatellite instability across multiple cancersNature CommunicationsMany (genomic)
Hause2016Classification and characterization of microsatellite instability across 18 cancer typesNature MedicineMany (genomic)
Le2017Mismatch-repair deficiency predicts response of solid tumors to PD-1 blockadeScienceMany (genomic)

3.2. Study Characteristics

The most common tumor types (excluding CRC) identified were endometrial (53 studies), gastric (39 studies), ovarian (23 studies), renal (9 studies), and esophageal (6 studies). Twenty CRC studies were identified from the targeted review. Overall, 54 studies were conducted in the United States, 18 in Korea, 12 in Japan, 12 in multiple countries, and 60 in other countries. Most studies provided an MSI-H cut-off between 30 and 40%, inclusive, translating into a change in loci size of greater than or equal to 2 of 5 loci tested; however, there were two prominent outliers at 9% (Glavac 2003) and 66% (Wen 2012). Fifty-four studies used all four MMR proteins to detect MMR status, 3 studies used three proteins, 6 studies used two proteins, and 3 studies did not specify number of proteins used. Included studies reported different study designs: case control, cross-sectional, prospective cohort, and retrospective cohort.

3.3. Patient Characteristics

Across studies, the mean/median age ranged from 20.7 to 74 years. Percentage of patients by ethnicity ranged as follows: Caucasian (0–94.8%), African American (0–17.2%), Asian (0–100%), and other ethnic groups (0–13.8%). In studies where disease stage was reported, percentage of patients with stage 1 disease ranged from 0 to 80.7%, stage 2 disease ranged from 4.2 to 38.6%, stage 3 disease ranged from 8 to 73.5%, and stage 4 disease ranged from 0 to 97.7%.

3.4. MSI-H and dMMR Prevalence

The number of studies with available MSI-H and dMMR data is presented in Table 5. Of the 156 included studies, MSI-H prevalence as determined by NCI or Promega markers was reported in 90 studies, and MSS prevalence was reported in 79 studies. Sixty-six studies reported dMMR prevalence; 54 of those used all 4 MMR proteins in the IHC assay. Pooled MSI-H and dMMR prevalence estimates were reported in 140 studies.


SubsetAny (with and without results)Reported MSI-H dataReported dMMR (any IHC)Reported dMMR (4 MMR proteins)Reported MSSReported MSI-H/dMMR

Total number of studies included15694665479140
Studies in gastric cancer3932642335
Studies in endometrial cancer532728261649
Studies in ovarian cancer2317851320
Studies in colorectal cancer201484617
Studies in esophageal cancer660036
Studies in renal cancer973138
Studies in other cancers361816132131

Abbreviations: MSI-H, microsatellite instability-high; dMMR, deficient mismatch repair; MSS, microsatellite stable.

MSI-H prevalence was available in 25 studies conducted in the United States, 17 studies conducted in Korea, and 8 studies conducted in Japan. dMMR prevalence data were available in 27 conducted in the United States and 2 studies conducted in Japan. MSI-H prevalence was reported by stages 1 (18 studies), 2 (18 studies), 3 (17 studies), 4 (16 studies), 1 or 2 (24 studies), and 3 or 4 (23 studies).

Beyond the 6 main tumor types feasible for tumor-specific meta-analyses, 19 other tumor types were included in the meta-analysis of overall MSI-H prevalence. Overall, MSI-H prevalence differed considerably across tumor types. A low prevalence of 2% (95% CI, 0%–8%) was observed in Ewing sarcoma [19], while a much higher prevalence of 35% (95% CI, 15%–57%) was reported in sebaceous tumors [20]. Small bowel [21] and cervical tumors [22] had prevalence of 12% each, which were very close to the all-tumor estimate.

3.5. Meta-Analysis Results: Random Effects

Overall meta-analysis results is presented in Figure 2. Prevalence estimates, 95% confidence intervals, and number of studies included in each analysis are shown. Meta-analysis results obtained from the random effects model in all tumor types are presented as forest plots in the Supplementary information (Appendix Figures 1–Figure 26). Funnel plots obtained from each meta-analysis are also presented in the Supplementary information (Appendix Figure 27–Figure 44).

The weighted prevalence of MSI-H without genomic studies was estimated to be 14% (95% CI, 10%–19%) across all tumor types and stages. The prevalence was 10% (95% CI, 7%–14%) when four of the five large pan-tumor genomic studies were included (one genomic study was excluded as it did not report the total number of patients or the number of patients with MSI-H). Overall weighted dMMR prevalence was estimated to be 16% (95% CI, 11%–22%) across all tumor types and stages. This estimate remained unchanged (16% (95% CI, 12%–21%)) in the sensitivity analysis, in which two studies (Everett 2014 and Roberts 2013) that possibly screened patients based on their Lynch syndrome status were excluded. Overall, MSS prevalence was found to be 79% (95% CI, 72%–85%) across tumor types and stages. Estimated pooled MSI-H and dMMR prevalence without genomic studies was 15% (95% CI, 11%–18%) and dropped to 11% (95% CI, 8%–15%) when genomic studies were included.

Country-specific MSI-H prevalence was estimated only in the United States, Korea, and Japan, for which at least 2 publications were included. The weighted prevalence of MSI-H for the United States, Korea, and Japan was estimated at 20% (95% CI, 16%–24%), 9% (95% CI, 6%–12%), and 16% (95% CI, 9%–26%), respectively, across all cancers and stages. dMMR all-stage prevalence for the United States was estimated at 14% (95% CI, 6%–23%) and for Japan was estimated at 20% (95% CI, 0%–63%). Stages 1-2 MSI-H prevalence was 15% (8–23%), while stage 3 and stage 4 prevalence was estimated at 9% (3%–17%) and 3% (1%–7%), respectively.

Tumor-specific meta-analysis was feasible for 3 key gastrointestinal tumors (gastric, colorectal, and esophageal), 2 gynecological tumors (endometrial and ovarian), and 1 genitourinary tumor (renal) with results presented in Figures 35. Among the gastrointestinal tumors, gastric cancer MSI-H pooled prevalence (with 95% CI) from 32 studies (16,308 patients) was estimated at 11% (9–12%) and dMMR pooled prevalence from 4 studies (854 patients) was estimated at 8% (2–17%); Based on stages across gastrointestinal tumors, the prevalence was 13% (10%–16%; 10 studies; 3,194 patients) for stages 1-2, and the prevalence was 10% (7–13%; 10 studies; 1,319 patients) in stages 3-4 cancer. The highest MSI-H pooled prevalence was observed for the intestinal histological subtype with 13% (10–17%) based on 14 studies (2,652 patients). In CRC, MSI-H pooled prevalence from 14 studies (8,156 patients) was estimated at 13% (10–16%) and dMMR pooled prevalence from 4 studies (11,434 patients) was estimated at 10% (5–15%). For stages 1-2 CRC, the prevalence was 20% (10%–32%; 4 studies; 888 patients), and for stages 3-4, the prevalence was 9% (3–16%; 4 studies; 873 patients). Based on histology, the highest MSI-H pooled prevalence was observed for the poorly differentiated CRC subtype with 32% (25–40%) based on 6 studies (1,204 patients). Among esophageal cancers, MSI-H pooled prevalence from 3 studies (147 patients) was estimated at 4% (0–11%). For stages 3-4 esophageal cancers, the prevalence was 18% (4%–39%; 2 studies; 62 patients). Based on histology, the highest MSI-H pooled prevalence was observed for well-differentiated and poorly differentiated esophageal subtypes with 16% (3–35%) and 16% (0%–45%), respectively. dMMR analysis was not feasible for esophageal tumors. For the gynecological tumors, endometrial cancer MSI-H pooled prevalence from 27 studies (6,813 patents) was estimated at 26% (23–29%) and dMMR pooled prevalence from 26 studies (5,248 patients) was estimated at 25% (22–28%). In ovarian cancers, MSI-H pooled prevalence from 17 studies (4,150 patients) was estimated at 11% (6–18%) and dMMR pooled prevalence from 5 studies (356 patients) was estimated at 8% (6–11%). Based on histology, the highest MSI-H pooled prevalence was observed for endometrioid subtype for each tumor with 30% (25–35%) based on 6 studies (1,204 patients) for endometrial cancers and 17% (25–35%) based on 3 studies (211 patients) for ovarian cancers. Among renal tumors, MSI-H all-stage prevalence was estimated to be 1% (95% CI, 0%–2%) based on 7 studies (2,231 patients); dMMR analysis was not feasible for renal tumors.

4. Discussion

This structured literature review and meta-analysis investigated MSI-H and dMMR prevalence across tumor types and compared prevalence estimates by tumor type, tumor stage, and country subgroups. Analysis results estimated the prevalence of MSI-H across all tumor types as 14% (95% CI, 10%–19%). dMMR prevalence was comparable at 16% (95% CI, 11%–22%).

Pooled dMMR prevalence estimates by tumor type were similar to those for MSI-H. It has been suggested that, for Lynch syndrome testing, PCR testing may be less sensitive than IHC due to the fact that mutations in MSH6 may present as MSI-L [23]. The results of this review, however, suggest that MSI-H and dMMR IHC testing results are generally comparable.

The United States had higher MSI-H prevalence than Korea and Japan, but this result is possibly biased due to the lack of weighting for country-specific tumor prevalence.

Subgroup analysis indicated that early stage diseases (stage 1 and 2) tended to have a higher MSI-H prevalence than later stages (stages 3 and 4). Numerous studies have established the value of MSI status as a prognostic factor [2426]. Results of a meta-analysis including 7642 patients indicated that MSI (MSI-H + MSI-L) tumors corresponded with significantly improved prognosis compared to MSS CRCs (overall survival HR 0.65 (95% CI, 0.59–0.71) [27]. This may partially explain the lower MSI-H prevalence in the later stages of cancers.

Some tumor types had noticeably higher MSI-H prevalence than others. Endometrial tumors had MSI-H prevalence of 26% (95% CI, 23%–29%), whereas renal tumors only had MSI-H prevalence of 1% (95% CI, 0%–2%). This observation corroborates findings from recent genomic studies, which revealed that the frequency of MSI-H events is highly variable across tumor types [13, 28]. One study noted that MSI-H prevalence was highest in Lynch syndrome-associated tumor types (endometrial, colon, gastric, and rectal) [13] which is well-aligned with findings from the current study.

The identified evidence base included 156 articles reporting on the prevalence of MSI-H and/or dMMR published between 1999 and 2017. This review includes the most cancer types of a published review to date. Of the other two known published meta-analyses that have quantified the prevalence of MSI-H for selective tumors, the first (including publications to 2007) reported an MSI-H prevalence of 12% (95% CI, 8%–17%) in ovarian tumors [29], the second (including publications to 2009) reported an MSI-H prevalence of 10% (95% CI, 6%–14%) in ovarian tumors [30], and the third (including studies published up to 2014) reported an MSI-H prevalence of 17% (95% CI, 15%–19%) in colorectal tumors [31]. The finding from the current meta-analysis suggests MSI-H prevalence of 11% (95% CI, 6%–18%) in ovarian cancer patients and 13% (95% CI, 10%–16%) in colorectal cancer patients, which are well-aligned with findings from previous meta-analyses.

This large-scale meta-analysis of the prevalence of MSI-H and dMMR used rigorous methodology in selection of testing methods, subgroup analyses, and incorporation of pan-tumor genomic studies in sensitivity analyses. First, this meta-analysis of MSI-H and dMMR prevalence included the most number of studies (156) to date. Second, weighting techniques were used to adjust for overall tumor prevalence in order to prevent oversampling of commonly reported tumor types. Third, only studies that utilized the “gold standard” MSI-H and dMMR testing methods were included in the meta-analysis, so the results from these studies were more comparable. Fourth, the subgroup analyses, which were stratified by factors such as tumor type, country, and disease stage, indicated which factors had potential association with prevalence. Fifth, the inclusion of pan-tumor genomic studies in the sensitivity analyses offered an alternative scenario and suggested that the testing method used in large-scale genomic studies (sequencing) is significantly different from the widely accepted methods (PCR and IHC) used in other included studies.

This meta-analysis has some limitations. First, the literature review for CRC was a targeted hand search; some potentially relevant publications may not have been identified. Studies were reviewed by a single researcher, but a quality check was performed to validate the dataset. An additional limitation was the heterogeneity of included study designs included, which included case control, cross-sectional, prospective cohort, and retrospective cohort studies. However, because of scarcity of the numbers in most cancer types, studies with different designs were included to maximize the data sources. Symmetry was observed on most funnel plots, which suggest a lack of publication bias. To address heterogeneity in study designs included in the meta-analysis, data were analyzed using fixed- and random-effects models; however, this exploration did not provide evidence of any specific source of heterogeneity. Finally, given the lack of MSI/MMR publications on a few major cancer types, the “overall” prevalence estimate does not include all solid tumors.

Recent evidence [32, 33] supporting the role of MSI-H and dMMR, and associated immunogenicity as a mechanism for increased efficacy of PD-1/PD-L1 blockade in metastatic tumors with MSI-H or dMMR [8], demonstrates to the importance of increasing understanding [34] of prevalence across tumor type, stage, histology, and ethnicity.

Conflicts of Interest

M. Amonkar and K.-L. Liaw are employees of and own shares in Merck & Co, Inc. The other authors declare no conflicts of interests.

Acknowledgments

This work was financially supported by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA.

Supplementary Materials

Meta-analysis results obtained from random effects model in all tumor types are presented as forest plots in the Supplementary information (Appendix Figures 1–Figure 26). Funnel plots obtained from each meta-analysis are also presented in the Supplementary information (Appendix Figure 27–Figure 44). (Supplementary Materials)

References

  1. K. D. Berg, C. L. Glaser, R. E. Thompson, S. R. Hamilton, C. A. Griffin, and J. R. Eshleman, “Detection of microsatellite instability by fluorescence multiplex polymerase chain reaction,” The Journal of Molecular Diagnostics, vol. 2, no. 1, pp. 20–28, 2000. View at: Publisher Site | Google Scholar
  2. P. Ward, L. Dubeau, C. Felix J, G. Kim, and J. Bacher, “Comparison between performance of primers for long versus short microsatellite biomarkers in the detection of microsatellite instability due to aberrant MSH6 expression in endometrioid carcinomas,” in Proceedings of the Association for Molecular Pathology, Bethesda, MD, USA, November 2014. View at: Google Scholar
  3. C. R. Boland, S. N. Thibodeau, S. R. Hamilton et al., “A National Cancer Institute workshop on microsatellite instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer,” Cancer Research, vol. 58, no. 22, pp. 5248–5257, 1998. View at: Google Scholar
  4. A. Umar, C. R. Boland, J. P. Terdiman et al., “Revised Bethesda guidelines for hereditary nonpolyposis colorectal cancer (lynch syndrome) and microsatellite instability,” JNCI Journal of the National Cancer Institute, vol. 96, no. 4, pp. 261–268, 2004. View at: Publisher Site | Google Scholar
  5. W. K. Funkhouser Jr., I. M. Lubin, F. A. Monzon et al., “Relevance, pathogenesis, and testing algorithm for mismatch repair-defective colorectal carcinomas,” The Journal of Molecular Diagnostics, vol. 14, no. 2, pp. 91–103, 2012. View at: Publisher Site | Google Scholar
  6. S. Venderbosch, I. D. Nagtegaal, T. S. Maughan et al., “Mismatch repair status and BRAF mutation status in metastatic colorectal cancer patients: a pooled analysis of the CAIRO, CAIRO2, COIN, and FOCUS studies,” Clinical Cancer Research, vol. 20, no. 20, pp. 5322–5330, 2014. View at: Publisher Site | Google Scholar
  7. P. P. Singh, P. K. Sharma, G. Krishnan, and A. C. Lockhart, “Immune checkpoints and immunotherapy for colorectal cancer,” Gastroenterology Report, vol. 3, p. gov053, 2015. View at: Publisher Site | Google Scholar
  8. D. T. Le, J. N. Uram, H. Wang et al., “PD-1 blockade in tumors with mismatch-repair deficiency,” New England Journal of Medicine, vol. 372, no. 26, pp. 2509–2520, 2015. View at: Publisher Site | Google Scholar
  9. J. C. Dudley, M.-T. Lin, D. T. Le, and J. R. Eshleman, “Microsatellite instability as a biomarker for PD-1 blockade,” Clinical Cancer Research, vol. 22, no. 4, pp. 813–820, 2016. View at: Publisher Site | Google Scholar
  10. D. Moher, A. Liberati, J. Tetzlaff, D. G. Altman, and P. Group, “Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement,” Journal of Clinical Epidemiology, vol. 62, no. 10, pp. 1006–1012, 2009. View at: Publisher Site | Google Scholar
  11. J. J. Miller, “The inverse of the freeman-Tukey double arcsine transformation,” The American Statistician, vol. 32, no. 4, p. 138, 1978. View at: Publisher Site | Google Scholar
  12. R. DerSimonian and N. Laird, “Meta-analysis in clinical trials,” Controlled Clinical Trials, vol. 7, no. 3, pp. 177–188, 1986. View at: Publisher Site | Google Scholar
  13. R. Bonneville, M. A. Krook, E. A. Kautto et al., “Landscape of microsatellite instability across 39 cancer types,” JCO Precision Oncology, no. 1, pp. 1–15, 2017. View at: Publisher Site | Google Scholar
  14. I. Danielsson and L. Lister, “A pilot study of the teratogenicity of vagus nerve stimulation in a rabbit model,” Brain Stimulation, vol. 2, no. 1, pp. 41–49, 2009. View at: Publisher Site | Google Scholar
  15. NCI, SEER, https://seer.cancer.gov/statfacts/html/oralcav.html.
  16. G. W. Jung, A. I. Metelitsa, D. C. Dover, and T. G. Salopek, “Trends in incidence of nonmelanoma skin cancers in Alberta, Canada, 1988-2007,” The British Journal of Dermatology, vol. 163, no. 163, pp. 146–154, 2010. View at: Publisher Site | Google Scholar
  17. S. Y. Pan and H. Morrison, “Epidemiology of cancer of the small intestine,” World Journal of Gastrointestinal Oncology, vol. 3, no. 3, pp. 33–42, 2011. View at: Publisher Site | Google Scholar
  18. AAO, http://eyewiki.aao.org/Retinoblastoma.
  19. I. Alldinger, K. L. Schaefer, D. Goedde et al., “Microsatellite instability in Ewing tumor is not associated with loss of mismatch repair protein expression,” Journal of Cancer Research and Clinical Oncology, vol. 133, no. 10, pp. 749–759, 2007. View at: Publisher Site | Google Scholar
  20. A. M. Cesinaro, A. Ubiali, P. Sighinolfi, G. P. Trentini, F. Gentili, and F. Facchetti, “Mismatch repair proteins expression and microsatellite instability in skin lesions with sebaceous differentiation: a study in different clinical subgroups with and without extracutaneous cancer,” The American Journal of Dermatopathology, vol. 29, no. 4, pp. 351–358, 2007. View at: Publisher Site | Google Scholar
  21. R. Kumagai, K. Kohashi, S. Takahashi et al., “Mucinous phenotype and CD10 expression of primary adenocarcinoma of the small intestine,” World Journal of Gastroenterology, vol. 21, no. 9, pp. 2700–2710, 2015. View at: Publisher Site | Google Scholar
  22. Y.-F. Wong, T.-H. Cheung, K.-Y. Poon et al., “The role of microsatellite instability in cervical intraepithelial neoplasia and squamous cell carcinoma of the cervix,” Gynecologic Oncology, vol. 89, no. 3, pp. 434–439, 2003. View at: Publisher Site | Google Scholar
  23. Y. Wu, M. J. W. Berends, R. G. J. Mensink et al., “Association of hereditary nonpolyposis colorectal cancer-related tumors displaying low microsatellite instability with MSH6 germline mutations,” The American Journal of Human Genetics, vol. 65, no. 5, pp. 1291–1298, 1999. View at: Publisher Site | Google Scholar
  24. A. Copija, D. Waniczek, A. Witkos, K. Walkiewicz, and E. Nowakowska-Zajdel, “Clinical significance and prognostic relevance of microsatellite instability in sporadic colorectal cancer patients,” International Journal of Molecular Sciences, vol. 18, no. 1, 2017. View at: Publisher Site | Google Scholar
  25. K. C. Halling, A. J. French, S. K. McDonnell et al., “Microsatellite instability and 8p allelic imbalance in stage B2 and C colorectal cancers,” JNCI Journal of the National Cancer Institute, vol. 91, no. 15, pp. 1295–1303, 1999. View at: Publisher Site | Google Scholar
  26. S. A. Khan, M. Morris, K. Idrees et al., “Colorectal cancer in the very young: a comparative study of tumor markers, pathology and survival in early onset and adult onset patients,” Journal of Pediatric Surgery, vol. 51, no. 11, pp. 1812–1817, 2016. View at: Publisher Site | Google Scholar
  27. S. Popat, R. Hubner, and R. S. Houlston, “Systematic review of microsatellite instability and colorectal cancer prognosis,” Journal of Clinical Oncology, vol. 23, no. 3, pp. 609–618, 2005. View at: Publisher Site | Google Scholar
  28. I. Cortes-Ciriano, S. Lee, W. Y. Park, T. M. Kim, and P. J. Park, “A molecular portrait of microsatellite instability across multiple cancers,” Nature Communications, vol. 8, p. 15180, 2017. View at: Publisher Site | Google Scholar
  29. T. Pal, J. Permuth-Wey, A. Kumar, and T. A. Sellers, “Systematic review and meta-analysis of ovarian cancers: estimation of microsatellite-high frequency and characterization of mismatch repair deficient tumor histology,” Clinical Cancer Research, vol. 14, no. 21, pp. 6847–6854, 2008. View at: Publisher Site | Google Scholar
  30. M. A. Murphy and N. Wentzensen, “Frequency of mismatch repair deficiency in ovarian cancer: a systematic review this article is a US Government work and, as such, is in the public domain of the United States of America,” International Journal of Cancer, vol. 129, no. 8, pp. 1914–1922, 2011. View at: Publisher Site | Google Scholar
  31. H. Ashktorab, S. Ahuja, L. Kannan et al., “A meta-analysis of MSI frequency and race in colorectal cancer,” Oncotarget, vol. 7, no. 23, pp. 34546–34557, 2016. View at: Publisher Site | Google Scholar
  32. KEYTRUDA® (pembrolizumab, Highlights of Prescribing Information, Merck Sharp & Dohme Corp, Kenilworth, NJ, USA, 2018.
  33. OPDIVO® (nivolumab), Highlights of Prescribing Information, Bristol-Myers Squibb Corp, New York, NY, USA, 2018.
  34. National Comprehensive Cancer Network, Clinical Practice Guidelines in Oncology, National Comprehensive Cancer Network, Fort Washington, PA, USA, 2019.

Copyright © 2020 Maria Lorenzi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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