Next Article in Journal
Deep Learning Approaches to Osteosarcoma Diagnosis and Classification: A Comparative Methodological Approach
Previous Article in Journal
TIGD1 Function as a Potential Cuproptosis Regulator Following a Novel Cuproptosis-Related Gene Risk Signature in Colorectal Cancer
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Microsatellite Instability: A Review of Molecular Epidemiology and Implications for Immune Checkpoint Inhibitor Therapy

Alexandra Kavun
Egor Veselovsky
Alexandra Lebedeva
Ekaterina Belova
Olesya Kuznetsova
Valentina Yakushina
Tatiana Grigoreva
Vladislav Mileyko
Mikhail Fedyanin
4,7,8 and
Maxim Ivanov
OncoAtlas LLC, 119049 Moscow, Russia
Department of Evolutionary Genetics of Development, Koltzov Institute of Developmental Biology of the Russian Academy of Sciences, 119334 Moscow, Russia
Faculty of Physics, Lomonosov Moscow State University, 119991 Moscow, Russia
N.N. Blokhin Russian Cancer Research Center, 115478 Moscow, Russia
Laboratory of Epigenetics, Research Centre for Medical Genetics, 115522 Moscow, Russia
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, 117997 Moscow, Russia
State Budgetary Institution of Health Care of the City of Moscow “Moscow Multidisciplinary Clinical Center” “Kommunarka” of the Department of Health of the City of Moscow, 142770 Moscow, Russia
Federal State Budgetary Institution “National Medical and Surgical Center named after N.I. Pirogov” of the Ministry of Health of the Russian Federation, 105203 Moscow, Russia
Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
Author to whom correspondence should be addressed.
Cancers 2023, 15(8), 2288;
Submission received: 1 March 2023 / Revised: 10 April 2023 / Accepted: 11 April 2023 / Published: 13 April 2023



Simple Summary

Microsatellite instability (MSI) occurs in a wide variety of tumor types and is one of the most important predictive biomarkers for immune checkpoint inhibitor therapy. The present review aims to summarize the molecular characteristics of MSI tumors as well as the results of major clinical studies evaluating the efficacy of checkpoint inhibitors in the treatment of patients with MSI tumors.


Microsatellite instability (MSI) is one of the most important molecular characteristics of a tumor, which occurs among various tumor types. In this review article, we examine the molecular characteristics of MSI tumors, both sporadic and Lynch-associated. We also overview the risks of developing hereditary forms of cancer and potential mechanisms of tumor development in patients with Lynch syndrome. Additionally, we summarize the results of major clinical studies on the efficacy of immune checkpoint inhibitors for MSI tumors and discuss the predictive role of MSI in the context of chemotherapy and checkpoint inhibitors. Finally, we briefly discuss some of the underlying mechanisms causing therapy resistance in patients treated with immune checkpoint inhibitors.

1. Introduction

Microsatellite instability (MSI) results from impaired DNA mismatch repair (MMR) and causes an accumulation of mutations in microsatellites (MS), also called short tandem repeats (STRs). STRs consist of repeated sequences of 1–6 nucleotides and account for 3% of the genome, both coding and noncoding regions [1,2,3]. The nature of MS determines its outstanding tendency to accumulate errors. It happens due to DNA slippage in the process of DNA replication, which usually leads to a change in MS length [4,5].
The MMR system is highly conserved across species. MMR is responsible for the recognition and correction of mismatched nucleotides and plays a key role in maintaining genomic stability [6,7,8]. Four major proteins encoded by the MLH1 (mutL homologue 1) [9,10], MSH2 (mutS homologue 2) [11], MSH6 (mutS homologue 6), and PMS2 (postmeiotic segregation increased 2) [12] genes play a central role in this process [13]. The MMR system functions through the formation of heterodimers (hMutS and hMutL). hMutS consists of MSH2 and one of the secondary proteins, either MSH6 or MSH3, and recognizes mismatched nucleotides and small indels [7,8]. The hMutL heterodimers, consisting of MLH1 and one of the secondary proteins, PMS2, PMS1, or MLH3, participate in MMR reactions [14,15,16] via its endonuclease activity [17], 5′ nicking [18], modulation, and termination of exonuclease 1′s (Exo1) activity [18,19,20]. Thus, hMutL deficiency leads to Exo1 hyperactivity and increased DNA excision [19,20]. The inactivation of at least one of the following genes: MLH1, MSH2, MSH6, or PMS2, due to germline and/or somatic mutations or epigenetic silencing, results in the MMR system deficiency (dMMR) [21,22].
MSI occurs among various tumor types, and is most common in colorectal, small bowel, endometrial, and gastric cancers [3,23,24,25,26,27,28,29]. Most cases of MSI are sporadic, arising from epigenetic inactivation of MLH1 gene expression. However, the MSI can also be caused by Lynch syndrome, a hereditary condition resulting from germline pathogenic mutations in the MMR genes, coupled with inactivation of the second allele [30,31,32].
MSI is the one of the major biomarkers predictive of the immune checkpoint inhibitor (ICI) benefit across cancer types, both in Lynch syndrome-related and sporadic tumors. ICI therapy aims to overcome tumor immune escape through targeting immune inhibitory molecules (e.g., PD-1, PD-L1, LAG3, and CTLA4) expressed on the surfaces of tumor and immune cells [33,34,35]. Correct assessment of MSI is critical for adequate therapeutic decisions. According to ESMO recommendations [30], several methods are used in clinical practice to assess MSI status. The IHC method indirectly assesses MSI by detecting loss of staining for MLH1, MSH2, PMS2, and MSH6 proteins. An advantage of using IHC to detect MMR proteins is its convenience and ability to identify the target gene for future mutational confirmation [24]. PCR-based approaches directly determine MSI status via amplification of specific microsatellite repeats. ESMO suggests PCR in case of indeterminate IHC results, including disagreement or difficulties in interpreting IHC. The five poly-A mononucleotide repeats panel (BAT-25, BAT-26, NR-21, NR-24, NR-27) is considered the current standard [30], though the Bethesda panel, comprising of two mononucleotide (BAT-25 and BAT-26) and three dinucleotide (D5S346, D2S123, and D17S250) repeats, is also widely utilized in clinical practice [36,37]. In diagnostics, MSI (previously known as MSI-H) denotes alterations in the lengths of several MS (e.g., 2 of 5 loci in a standard PCR test with five poly-A mononucleotide repeats). In contrast, if the number of unstable loci does not exceed one, it is termed as MSS (microsatellite stable). NGS-based MSI detection is considered as one of the most promising, since its advantages include higher accuracy and an expanded spectrum of microsatellites analyzed, which is relevant for non-CRC tumors that can harbor a non-standard set of unstable microsatellites [38]. NGS also allows simultaneous analysis of a comprehensive spectrum of clinically significant biomarkers [14,30].
The first FDA-approved ICI drug was ipilimumab, which was initially approved in 2011 for the treatment of melanoma and is now used in a limited range of cancers. Pembrolizumab is a second FDA-approved ICI, which has the widest range of indications, including tissue-agnostic indications [39]. To date, more than 6 ICI have been approved for site-specific or tumor-agnostic indications. Overall, the objective response rate (ORR) for tumors with MSI varies between 34% and 69% depending on the line of therapy, while the rate of pathologic complete response (pCR) may reach 100% in neoadjuvant settings, which indicates a high efficacy of checkpoint inhibitors in MSI tumors [40,41,42]. At the same time, about a quarter of metastatic colorectal cancers and up to half of some other types of cancer are intrinsically resistant to ICI [43,44]. Several mechanisms of such an intrinsic resistance have been proposed, including the activating mutations in the RAS/RAF signaling pathway [45], mutations in the antigen presentation machinery and interferon pathway genes [46,47], establishment of an immunosuppressive microenvironment [48], as well as the influence of the gut microbiome [49] and immunoediting theory [50].
Here, we describe the prevalence of MSI among various types of cancer, as well as summarize the data on the application of MSI as a biomarker for the efficacy of ICI. Specifically, the clinical studies of patients with colorectal cancer, as well as patients with endometrial and gastric cancer, are reviewed. We also discuss potential mechanisms of resistance to ICI, limiting the response to therapy in tumors with MSI/dMMR.

2. Lynch Syndrome-Associated Cancer Risks

Lynch syndrome is an autosomal-dominant inherited cancer syndrome caused by pathogenic or likely pathogenic germline mutations in genes of the MMR system [9,11,51,52,53,54,55,56]. A large cohort study estimated that a pathogenic variant in one of the MMR genes occurs in 1 out of 279 people in the general population [57]. In Lynch syndrome, MSI is mainly driven by germline mutations in MSH2 (up to 40–45% in colorectal and endometrial cancers). The second place takes the mutations in MLH1 (up to 40% in colorectal and 30% in endometrial cancer) and MSH6 (up to 5–10% in colorectal and 30% in endometrial cancer). PMS2 mutations are the rarest event in Lynch syndrome-associated MSI (up to ∼5–10% in colorectal and mostly absent in endometrial cancer) [58,59,60]. Additionally, up to 3% of Lynch syndrome-associated MSI cases are caused by rare germline 3′ end deletions of the last exons of the epithelial cell adhesion molecule (EPCAM) gene that lead to epigenetic hypermethylation of the MSH2 promoter located downstream of EPCAM [54,61,62].
The presence of pathogenic variants in any of the MMR genes (MLH1, MSH2, MSH6, PMS2, or EPCAM) is associated with an increased risk of developing various cancer types. Among these Lynch-associated cancer types, colorectal, endometrial, ovarian, gastric, small bowel, and pancreatic cancers are most frequently described [36,63,64,65,66,67,68]. Rarer types of cancer that are at slightly increased risk among individuals with Lynch syndrome include renal pelvis and/or ureter, bladder, biliary tract, prostate, breast, central nervous system, and even skin cancer [64,69,70,71,72,73,74].
Carriers of pathogenic variants of the MMR genes are most susceptible to the development of colorectal cancer; historically, Lynch syndrome is also known as hereditary nonpolyposis colorectal cancer syndrome. According to a meta-analysis by Wang et al. [75], which assessed the risk of developing colorectal cancer by age 70, for carriers of pathogenic variants of MLH1, MSH2, and MSH6, the risk was 44%, 54%, and 12%, respectively, for men, and 37%, 39%, and 12%, respectively, for women. For carriers of pathogenic PMS2 variants, this risk is about 8–20% [76,77,78]. There is significant heterogeneity of the reported risks in the literature [63,64,65], as well as in the NCCN guidelines [79]. Overall, the risk of developing colorectal cancer for carriers of pathogenic MMR gene variants is several times greater than the cumulative lifetime risks for the general population, which accounts to 4% [80]. For women affected by Lynch syndrome, the risk of developing endometrial cancer is also elevated [63,66]. According to various studies, for carriers of pathogenic variants MLH1, MSH2, MSH6, and PMS2, the risk of developing uterine cancer is 34–54%, 21–57%, 16–49%, and 13–20%, respectively [63,64,66,76,77,81,82], which is also significantly higher than the population average risk of 1.3% [80].
The risks of developing other common Lynch-associated cancers, such as ovarian, gastric, and small bowel cancers, are generally significantly higher for carriers of pathogenic MLH1 and MSH2 variants compared to those for individuals harboring pathogenic mutations in the MSH6 and PMS2 genes. Thus, according to various estimates, the risk of developing ovarian cancer reaches 4–20% for MLH1 carriers and 8–38% for MSH2 but is only 1–13% for MSH6 and up to 3% for PMS2 [63,64,67,81]. A similar trend is observed for the risks of developing gastric and small bowel cancers. For example, for carriers of MLH1 pathogenic variants, there is a ten-fold increase in the risk of developing gastric and small bowel cancer, although this risk is not as high as for other previously mentioned cancer types, 5–7% and 0.4–11%, respectively [63,64,67,68]. For all other types of cancer, the estimation of risks of developing cancer is either insignificant or inconsistent between studies, resulting in a wide range of values obtained, often not exceeding the risks for the general population.
Gene-specific Lynch syndrome cancer risks based on data from the NCCN guidelines [79] are shown in Figure 1.

3. MSI: Molecular Epidemiology across Cancer Types

The MSI phenotype can be found in many cancer types. In a study analyzing more than 11,000 tissue samples from patients with 39 cancer types, MSI was found in 27 tumor types (overall in 3.8% of all samples) [83]. The tumor types where the MSI phenotype is observed include colon, gastric, endometrial, ovarian, hepatobiliary tract, urinary tract, brain, and skin cancers (Figure 2A). Of those, the highest prevalence of MSI is in colorectal cancer (10.2%, range 6.6–14.5%) [23,24,30,84,85,86,87,88,89,90,91], endometrial cancer (especially endometrioid histotype) (21.9%, range 15.1–29.6%) [25,26,27,84,92,93,94], gastric cancer (8.5%, range 6.4–10.9%) [3,27,28,30,84,95], and small bowel cancer (14.3%, range 5.4–26.3%) [84]. In gastric cancer, the frequency of MSI/dMMR varies significantly within histological subtypes: from 0.9% in the mixed-type and 2.9% in the diffuse-type, to 10.7% of the intestinal-type [28,96]. In other types of cancer, the MSI rate is relatively low [84], specifically 2–10% in ovarian [30,60,97,98] and only 1–2% in pancreatic cancer [30,99,100,101]. The assessments of the MSI rate in urothelial carcinoma are highly contradictory, with the reported values ranging from 1% to as high as 46% [102,103,104]. The MSI phenotype is also reported in Lynch syndrome-unrelated cancer types—in glioblastoma, cervical cancer, small intestine, melanoma, sarcoma, and others, but in these cancer types, MSI is much rarer [30,105,106].
MSI is characteristic of both Lynch syndrome-associated cancer, where it is observed in nearly all cases, and sporadic cancer, where it reaches up to 10–15% of cases [91]. Conversely, Lynch syndrome comprises not more than 19% of MSI cancers, with the highest rate in MSI-positive colorectal cancer, followed by endometrial (5–10%), small bowel (12%), and gastric (4–15%) [96,106,107,108,109,110,111,112]. Respectively, most MSI cases (80% to 95%) arise sporadically [113]. The major cause of MSI is promoter hypermethylation of both MLH1 gene alleles, leading to a loss of MLH1, which is observed in ~90% of sporadic cancer [23,36,58,113,114,115].
When studying the molecular profiles of MSI tumors regardless of whether the tumor is Lynch syndrome-associated or sporadic, a number of oncogenic mutations can be found, including mutations in KRAS, NRAS, BRAF, PIK3CA, APC, TP53, etc. Specifically, KRAS is observed in MSI tumors with a frequency of 30–37% in endometrial, small bowel, and colorectal cancers, and at 15–28% in gastric cancer [29,86,96,116,117,118]. In colorectal cancer, the prevalence of KRAS mutations in MSI cases is lower than in MSS, where it reaches 46% [119]. Notably, MSS tumors harboring KRAS oncogenic mutations are characterized by more aggressive growth [115,120].
BRAF mutations are found with a high frequency (up to 45%) in MSI colorectal cancer, with mostly exclusive prevalence of p.V600E [121,122]. BRAF mutations have strong bias to sporadic cases, and mostly can never be observed in hereditary colorectal cancer [122,123,124,125]. According to Parsons et al.’s meta-analysis [126], BRAF V600E variants occur in only 1.4% of patients with Lynch syndrome. In sporadic colorectal carcinomas displaying the MSI phenotype, MLH1 hypermethylation and BRAF p.V600E mutations frequently co-occur, indicating a possible causal relationship between BRAF mutations and MLH1 loss [127,128,129]. However, the straight relationship between MLH1 hypermethylation and BRAF p.V600E mutation might be called into question by the fact that not all colorectal cancers with BRAF p.V600E mutations display silenced MLH1 with subsequent MSI. Such tumors remain microsatellite-stable, suggesting that other factors can influence the MSI phenotype in BRAF-positive cancer [130]. Indeed, only 20–30% of BRAF p.V600E-mutated metastatic colorectal cancer display MSI [131]. Additionally, the transition to the MSI phenotype via MLH1 hypermethylation is observed in approximately 75% of BRAF-mutated sessile serrated adenomas, with the remaining cases developing into MSS cancers. Among traditional serrated adenomas, BRAF mutations occur in two-thirds of the cases, but MLH1 silencing and the MSI phenotype are rare [132,133]. In other cancer types, the interplay between BRAF p.V600E and MSI/dMMR is not observed [3,27,94,134,135].
TP53 mutations are much less frequently observed in MSI as compared to MSS tumors, and their frequency in colorectal and gastric MSI cancer is 20–30%, as compared to 50–65% among MSS tumors [3,136]. Similarly, in the endometrial, pancreatic, and ovarian cancers, where TP53 mutations are common events, MSI tumors harboring TP53 can rarely be found [94,99,100,137]. This pattern of TP53 distribution among MSI and MSS tumors may indicate that TP53 mutations are unlikely to contribute to the MSI cancer tumorigenesis.
The prevalence of PIK3CA mutations in colorectal and gastric tumors is higher in MSI tumors (30–45%), as compared to MSS (10–25%). However, in endometrial cancer, PIK3CA mutations are equally common among both MSI and MSS tumors, accounting for 45–60% of all cases [94].
Other frequently altered genes in MSI tumors include RNF43, ATM, ARID1A, BRCA2, and PTEN. Mutations in these genes have been shown to have a several-fold increased mutation frequency in MSI colorectal carcinomas compared to MSS [138]. Approximately one in five cases of MSI tumors have important targetable fusions in NTRK1/2/3, ALK, or RET genes [138], but there is no significant relationship between MSI and HER2 amplification [139,140].
In the co-occurrence of MSI and other oncogenic alterations, the role of dMMR and its onset in Lynch syndrome colorectal carcinomas is described with three models [4]. In the first (classical) model, MMR deficiency is a secondary event that occurs after adenoma development, initially driven by somatic oncogenic mutations in APC and KRAS [141,142]. Distinguishing features of adenomas developing in accordance with this model are MMR proficiency and MSS. The classical model is typically observed in patients carrying germline MSH6 or PMS2 mutations [143]. It is known that in case of isolated loss of MSH6, MMR activity can be retained due to overlapping functions with MSH3, which explains the relatively low risk of cancer for MSH6 mutation carriers [144]. Notably, MLH1 and MSH2 mutation carriers rarely develop tumors via the classical model [141]. The prevalence of adenomas developing via this model of carcinogenesis can be roughly estimated at 25% [145,146,147]. In the second and third models, biallelic inactivation of MMR genes leading to dMMR is a driver event, and therefore MSI is observed in all such tumors [141,145]. The second model is mainly observed in MLH1 and MSH2 mutation carriers and is typically characterized by inactivation of tumor suppressors involved in the WNT pathway, predominantly TGFBR2 and RNF43, due to frameshift mutations within microsatellites in the corresponding genes [138,147]. The third model accounts for about 10% of LS-associated colorectal carcinomas and is exclusively observed in patients with MLH1 mutations. Here, dMMR is accomplished with mutations in CTNNB1 and TP53 [141].
The spectrum of potentially actionable alterations typically observed in MSI and MSS tumors based upon data generated by the TCGA Research Network [148] is summarized in Figure 2B.
Another important aspect worth mentioning is the relationship between MSI and tumor mutation burden (TMB). dMMR leads to a hypermutator phenotype and increased TMB, which is believed to make tumors more immunogenic. Considering all solid tumors, the simultaneous presence of MSI and TMB is quite rare and occurs only in about 3–7% of cases [30,149]. However, in tumors associated with Lynch syndrome, the overlap between TMB and MSI becomes more significant. The rate of TMB-H (≥10 mutations/megabase) patients among MSI cases is estimated at around 80–100% in colorectal cancer [84,150,151], 83–93% in endometrial cancer [84,152,153,154], and almost 100% in gastric and small bowel cancer [29,84,155]. In colorectal carcinoma, tumors with simultaneous presence of a high TMB and MSI/dMMR correspond to the CMS1 subtype [156], which is characterized by hypermutation, hypermethylation, enrichment in BRAF V600E mutations, as well as a strong infiltration of the tumor microenvironment with immune cells [88,157,158]. In this subtype, hypermethylation of the promoter regions of the MLH1 gene leads to its silencing, the accumulation of DNA mutations, and the expression of neoantigens that contribute to the high immunogenicity of the tumor [159]. The TMB levels in MSI tumors are likely dependent on certain MMR complex loss and tumor histology/primary site [160,161]. According to a study by Salem et al., evaluating colorectal, endometrial, and other tumors, overall, the loss of mutSα (MSH2/MSH6) leads to a more pronounced TMB than the loss of mutLα (MLH1/PMS2). However, in some types of tumor histology, secondary DNA repair pathways can better mitigate dMMR, resulting in a less pronounced TMB under the same IHC protein loss patterns. These findings support the diversity of gene- and histologically-specific heterogeneity of MSI/dMMR tumors [149]. Patients with MSI displaying a high TMB have a better prognosis and are also good candidates for checkpoint inhibitor therapy [159].
Three predictive biomarkers are currently used to select subgroups of patients eligible for ICI immunotherapy: PD-L1 expression, MSI/MMR status, and TMB.
Initially, it was considered that a common mechanism of tumor immune evasion is the aberrant expression of immune inhibitory molecules, PD-L1, on the surface of cancer cells [162]. However, over time, evidence has emerged that even in the absence of PD-L1 expression, tumors often remain sensitive to ICI [162,163]. Additionally, TMB-H and MSI tumors respond to the immunotherapy regardless of PD-L1 expression [164]. To some extent, it can be explained by the focal expression of PD-L1 [165], which can be missed during needle biopsy, or by the dynamic and inducible nature of PD-L1 expression [166]. This led to the PD-L1 expression-independent indications of ICI for many types of cancers. While anti-PD-L1 therapy acts to overcome local immune resistance, CTLA-4 is expressed in T-cells and acts non-locally, often causing autoimmune reactions and lymphocyte invasion in different unaffected organs [167,168]. For that reason, prescription of anti-CTLA4 therapy does not require determination of the CTLA4 expression status.
dMMR is the cause of the hypermutator phenotype and increased TMB, which likely leads to increased tumor immunogenicity. Indeed, the connection between MMR phenotype, TMB, and tumor immunogenicity is more sophisticated since some methods of TMB calculation may exclude truncating mutations in certain genes [169], while the dMMR phenotype is characterized by an increased frequency of frameshift mutations producing an abundance of highly immunogenic neoantigens [170,171,172]. Thus, dMMR/MSI status should be considered as an independent predictive biomarker of ICI effectiveness, and the presence of a TMB-H in this subgroup may be an additional factor indicating an increased immunogenicity of the tumor.

4. MSI and Chemotherapy

For many years, chemotherapy was the only treatment option for patients with advanced colorectal cancer. It has been well-established that MSI/dMMR status is a good prognostic factor for patients with early-stage (II–III) colorectal cancer [173,174,175,176]. Although, it was subsequently confirmed that while MSI status seems to be a good prognostic factor in low-risk stage III patients (T1-3, N1), it is no longer so in high-risk stage III patients (T4 and/or N2) [177,178]. For patients with stage IV metastatic colorectal cancer, the prognostic impact of MSI status, on the contrary, becomes worse than for those with an MSS tumor [121].
However, as for the role of MSI on chemotherapy response, the predictive role is ambiguous. Several studies have reported data supporting MSI as a predictive biomarker for improved response to irinotecan-based chemotherapy [179,180]. Conversely, an in vitro study found that patients would need an intact MMR system to induce apoptosis of fluorouracil-modified DNA [181]. Consistent with the results of the in vitro study [181], a negative predictive effect of MSI/dMMR status in relation to 5-fluorouracil adjuvant chemotherapy was also reported in a retrospective study [182]. Additional data indicating a negative effect of adjuvant chemotherapy used to treat patients with colorectal cancer has been described in the literature [183]. However, most studies, predominantly retrospective, have found no predictive effect of MSI/dMMR in response to fluorouracil- or oxaliplatin- or irinotecan-based therapy (predominantly FOLFOX or FOLFIRI combinations) [173,174,184,185,186,187,188,189,190]. Innocenti et al. reported results for patients with metastatic colorectal cancer (mCRC), showing no difference between microsatellite instability status in patients treated with bevacizumab as a first-line therapy, but a shorter OS and PFS in MSI mCRC patients treated with cetuximab as compared to MSS mCRC patients. Better outcomes rates were also demonstrated in the MSI subgroup of patients treated with bevacizumab compared to those treated with cetuximab [191].
Thus, data on the predictive role of MSI in relation to chemotherapy efficacy are inconsistent. Fortunately, ICIs have become the standard of care for tumors exhibiting features of MSI, which has reduced the relevance of this issue for chemotherapy.

5. MSI as a Predictive Biomarker for ICI Efficacy

Cancer immunotherapy in the broad sense is the type of cancer treatment aimed to overcome one of the hallmarks of cancer—avoiding immune destruction. One of the mechanisms utilized by cancer cells for this purpose is the expression of immune inhibitory molecules on their surfaces or the recruitment of immune cells expressing these molecules. This class of molecules is called immune checkpoints, and in normal conditions serves to avert autoimmunity. They can be targeted with monoclonal antibodies known as ICIs. The anti-CTLA4 drug ipilimumab became the first ICI approved by the FDA in 2011. The second FDA-approved ICI is an anti-PD-1 drug, pembrolizumab, which has the widest range of indications within ICIs, including tissue-agnostic indication tumors with signs of increased immunogenicity. In current clinical practice, four different immune checkpoints can be targeted by several ICIs: PD-1 by four drugs, PD-L1 by three drugs, LAG3 by relatlimab, and CTLA4 by ipilimumab and tremelimumab (Table 1). CTLA4 inhibitors are almost always used in combination with anti-PD-(L)1 ICIs, while relatlimab is currently used only in combination with nivolumab.
The milestones of ICIs’ approval for MSI/dMMR tumors are presented in Figure 3.

5.1. Site-Agnostic Indications and Clinical Evidence

On 23 May 2017, the anti-PD-1 drug pembrolizumab became the first cancer drug approved by the FDA for tissue/site-agnostic use in patients with unresectable or metastatic MSI or dMMR solid tumors. Approval was based on the results of five different clinical trials: KEYNOTE-016, KEYNOTE-164, KEYNOTE-012, KEYNOTE-028, and KEYNOTE-158. In total, 149 patients with dMMR/MSI were recruited, 89 of them had colorectal cancer (CRC), 14 had endometrial cancer (EC), and 45 had other types of cancers. ORR across tumor types was 39.6%, with a complete response rate of 7.4% and a partial response rate of 32.2% [39]. More recent results from the KEYNOTE-158 study involving 233 patients with MSI/dMMR non-colorectal cancer showed a similar ORR of 34.3%, with median progression-free survival (PFS) of 4.1 months and median overall survival (OS) of 23.5 months [40].
In 2021, another anti-PD-1 drug—dostarlimab—received FDA accelerated approval for tumor-agnostic use in dMMR tumors based on the results of the GARNET trial. According to the drug label, 209 patients took part in the study, 103 of them had EC, 69 had CRC, and 37 had other types of cancers. The ORR was 38.7% in non-endometrial cancer patients [192]. The most recently published interim analysis showed that across 204 patients with non-endometrial cancer and dMMR/MSI or POLE mutations, the ORR reached 43.1%, and the probability of PFS at 6, 9, and 12 months was 51.8%, 48.1%, and 46.4%, respectively [193].
It should be noted that these studies have certain limitations, as they are non-randomized and uncontrolled, and majority of cancer types are represented by few or single patients. However, the high rate of responses observed in patients with exhausted standard therapeutic options allowed for the approval of these indications. Since these studies were performed in heavily pretreated patients, it can be expected that the use of ICI in earlier-line settings will be more effective. This assumption has been confirmed for colorectal cancer, which will be discussed below.

5.2. Site-Specific Indications and Clinical Evidence

5.2.1. Colorectal Cancer

The most abundant data for site-specific use in dMMR/MSI tumors have been collected for CRC.
  • Pembrolizumab
The first observation of a MSI CRC patient having a three-year complete response to pembrolizumab therapy was published in 2013 [194]. More data on pembrolizumab efficacy in MSI CRC were collected in the KEYNOTE-016 trial. There were no objective responses in the cohort of 18 patients with MMR-proficient tumors [195]. Final analysis revealed that 21 of 40 (52%) MSI CRC patients responded to the therapy and 12% of patients achieved a complete response. No statistically significant difference in major endpoints was observed among patients with or without Lynch syndrome-associated tumors: ORR was 46% vs. 59% (p = 0.27), respectively, and hazard ratios for PFS and OS were 1.2 (p = 0.61) and 1.71 (p = 0.24), respectively. All patients were pretreated and had a progressive disease before entering the trial [105].
Results of the phase III randomized KEYNOTE-177 trial evaluating pembrolizumab efficacy in the first-line settings showed an ORR of 45% (n = 69) in patients receiving pembrolizumab and an ORR of 33% (n = 51) in patients receiving chemotherapy. Complete response rates were 13% and 4%, respectively. Median PFS was 16.5 months in pembrolizumab and 8.2 months in chemotherapy groups (HR 0.59). No statistically significant differences in OS were demonstrated, presumably due to the high crossover frequency between chemotherapy and pembrolizumab groups. Subgroup analysis did not reach sufficient statistical power to show the difference between BRAF or RAS mutant and wild-type tumors [196]. However, in an earlier publication of the results of this study, RAS mutant patients were shown to derive no benefit in terms of PFS. There was also a higher incidence of progressive disease in the pembrolizumab group compared to the control group (29% vs. 12%) [197]. Based on the interim results of this trial, pembrolizumab was approved by the FDA for the first-line treatment of patients with MSI CRC in 2020 [198].
A recent study of pembrolizumab in a neoadjuvant setting in 35 patients with localized or locally advanced solid tumors with MSI included 27 CRC patients. Here, 33 patients eligible for radiographic response evaluation had an ORR of 82%. Among 14 CRC patients who underwent surgery, 11 had a pCR (79%). Subgroup analysis did not reveal a difference in treatment efficacy between sporadic and Lynch-associated MSI [199].
Nivolumab and Ipilimumab
Nivolumab with or without ipilimumab is another FDA-approved therapeutic option for dMMR/MSI CRC, with the approval being based on the positive results of the CheckMate-142 uncontrolled trial [200,201]. Long-term survival analysis showed that nivolumab monotherapy results in an ORR of 34% and disease control rate (DCR) of 62% in pretreated patients (n = 74), with a median PFS of 6.6 months and 1-year survival of 72%. Patients (n = 21) who received 2 or less standard chemotherapy regimens achieved an ORR of 52% and DCR of 81% [202], indicating greater efficacy in earlier lines of therapy. Follow-up from CheckMate-142, a study evaluating nivolumab plus low-dose ipilimumab in patients who had more than one previous line of therapy, showed an ORR of 65%. The 24-month PFS and OS rates were 63% and 75%, respectively [203]. The most recent results from CheckMate-142 were obtained on the cohort treated in the first line with nivolumab plus low-dose ipilimumab. The ORR was 69%, with a complete response rate of 13%. The 24-month PFS and OS rates were 74% and 79%, respectively. BRAF and KRAS mutation status did not affect the clinical benefit [41].
The GERCOR NIPICOL study aimed to evaluate the optimal duration of immunotherapy for patients with MSI/dMMR CRC previously treated with fluoropyrimidine, oxaliplatin, and irinotecan, with or without targeted therapies. The patients were administered nivolumab plus ipilimumab for one year. Three-year PFS and OS rates were 70% and 78%, respectively [204].
Nivolumab in combination with ipilimumab was tested in neoadjuvant settings in patients with MMR-deficient and -proficient early-stage colon cancers in the exploratory NICHE study. All 20 patients with dMMR tumors achieved a pathological response, of which 19 had a major pathological response (≤10% residual viable tumor) and 12 had a complete pathological response. Only 4 of 15 patients with MMR-proficient tumors had pathological responses [205]. Final analysis of the NICHE trial showed a 100% pathological response rate. Among 32 dMMR patients, 31 (97%) had a major pathological response and 1 had a partial response. In the pMMR (mismatch repair proficient) cohort, among 30 patients, only 9 (30%) had a pathologic response. No disease recurrence or grade 4 immune-related adverse events were seen in the dMMR cohort [206].
According to results of the NICHE-2 trial, a pathologic response was observed in 99% (106 of 107) of patients, including 95% with a major pathological response, 4% with a partial response, and 67% patients had a complete pathological response. No disease recurrences were observed at the 13-month median follow-up [207]. Results of the NICHE-2 trial presented at the ESMO Congress 2022 showed a difference in pCR between sporadic and Lynch-associated CRC (38 (58%) vs. 25 (78%); p = 0.056) [207].
The efficacy of another anti-PD-1 drug, dostarlimab, in pretreated patients with dMMR solid tumors was tested in the GARNET trial, resulting in an ORR of 36.2% for CRC patients, with 3 complete and 22 partial responses [208,209]. The most impressive results have been obtained with dostarlimab in neoadjuvant settings in patients with dMMR stage II or III rectal cancers. The study design implied the administration of standard chemoradiotherapy and surgery for patients who did not achieve a complete response after neoadjuvant dostarlimab. However, all 12 recruited patients had complete clinical responses, so no surgery was required. During 6 to 25 months of follow-up, no recurrence had been reported [42].
Other currently not FDA-approved ICIs for MSI CRC
The efficacy of avelumab in the second-line setting in patients with MSI CRC was evaluated in the SAMCO-PRODIGE trial, demonstrating an ORR of 28% (n = 61), as compared to an ORR of 30% in the chemotherapy group (n = 61). However, avelumab had better 12- and 18-month PFS rates (19% and 9% in the control group and 31% and 27% in the avelumab group (p = 0.025)) [210]. In the AVETUX trial evaluating the efficacy of avelumab and cetuximab in combination with FOLFOX in previously untreated patients with metastatic CRC, only two patients had MSI. One of them achieved a partial response and another one had stable disease [211,212].
The study of durvalumab in pretreated MSI solid tumors showed an ORR of 23% across all patients (n = 62) and 22% in patients with CRC (n = 36) [213]. Another study, NCT03435107, with a similar design but a different dosage regimen, yielded an ORR of 42% among 33 patients with MSI/dMMR (n = 30) or POLE-mutated tumors (n = 3) [214].
There were no published systematic studies of atezolizumab efficacy in MSI CRC. In the IMblaze 370 study, 6 out of 363 enrolled patients had MSI. Responses were observed in 2 of the 3 patients in the atezolizumab and cobimetinib arm, and in 1 of 3 in the atezolizumab monotherapy group [215]. The MyPathway basket study also showed atezolizumab activity in different types of MSI tumors: among 11 patients with MSI and TMB-H, 6 (54.5%) had a confirmed ORR [216].
Nivolumab in combination with relatlimab is currently being investigated in patients with MSI resistant to prior PD-(L)1 inhibition. Interim analysis of 13 patients showed 1 complete response in a patient with CRC, 1 partial response in a patient with small bowel cancer, and 5 patients achieved stable disease [217].
Tremelimumab in combination with durvalumab and metronomic oral vinorelbine was tested in 30 patients with MSI and/or TMB-H solid tumors. One complete response, nine partial responses, and five stable diseases were observed [218].
Another drug, cemiplimab, has not yet been studied in the context of microsatellite instability.
Therefore, MSI CRC are highly sensitive to immunotherapy with different types of ICIs. Their efficacy tends to increase in earlier lines of therapy. In the neoadjuvant settings, ICIs demonstrate a response rate close to 100%. According to the recent systematic review, clinical trials did not reveal a difference in response between sporadic and Lynch-associated CRC [219]. In two later published studies conducted in neoadjuvant settings and described above, one showed a numerically high, but statistically insignificant, difference in pCR [210], while the other study did not reveal a difference [199]. The absence of a significant difference in responses to ICI between a sporadic and Lynch-associated MSI is consistent with the lack of a response association with the BRAF mutation—a surrogate biomarker of sporadic MSI. Although pembrolizumab is approved for first-line treatment of patients with MSI CRC, interim results of the KEYNOTE-177 study indicate that in KRAS mutant patients, combined anti-PD1/anti-CTLA-4 therapy is preferred over anti-PD1 monotherapy [197]. Additionally, PD-L1 inhibitors avelumab and durvalumab have been shown to result in a numerically lower ORR: 28% and 22%, respectively, as compared to PD-1 inhibitors.

5.2.2. Tumor Types other Than Colorectal

The second most common cancer with high prevalence of the MSI phenotype is endometrial carcinoma (EC). The efficacy of pembrolizumab for the treatment of metastatic MSI EC was established in the KEYNOTE-158 trial. In the pretreated patients (n = 79), the ORR was 48%, median PFS was 13.1 months, and median OS was not reached [220]. Pembrolizumab in combination with lenvatinib showed a numerically lower ORR in the KEYNOTE-775 trial. The study evaluated the efficacy of this combination in patients with pretreated EC with or without dMMR. In the dMMR cohort (n = 65), the ORR was 40%, compared to 12% in the chemotherapy cohort (n = 65) [221]. In the pMMR cohort (n = 346), the ORR was 30% in the experimental group and 15% in the chemotherapy group (n = 351) [221].
The efficacy of dostarlimab in dMMR/MSI or MMR-proficient/MSS EC was evaluated in the GARNET study. The ORR was 45.5% in the dMMR/MSI group (n = 143) and 15.4% in the MMR-proficient (MMRp)/MSS group. PFS probability at the 12th month was 46.4% and 29.4%, respectively. Median OS was not reached in the dMMR/MSI and was 16.9 months in the MMRp/MSS group [222].
Another tumor type with a high occurrence of MSI is gastric cancer. Post hoc analysis of three clinical trials, KEYNOTE-059, KEYNOTE-061, and KEYNOTE-062, showed greater activity of pembrolizumab in MSI advanced gastric or gastroesophageal junction tumors. More than half of the patients had objective responses, while the ORR in chemotherapy groups was significantly lower (17% in KEYNOTE-061 and 37% in KEYNOTE-062) [223]. The GERCOR NEONIPIGA study showed that nivolumab plus ipilimumab in neoadjuvant settings leads to a 58.6% (17 of 29) pathological complete response rate in patients with resectable gastric/gastroesophageal junction (GEJ) adenocarcinoma [224].
The most complete data for other types of cancers were obtained in the KEYNOTE-158 trial (listed in Table 2). The lowest ORR of 18% was observed in pancreatic cancer patients, while other cancers demonstrated an ORR of more than 30%. It should also be noted that despite an ORR of 33% observed in patients with ovarian cancer, 12 of 24 patients had progressive disease, i.e., a high level of primary resistance to immunotherapy [44].
There are some doubts about the efficacy of immunotherapy in adjuvant settings. From the theoretical point of view, immunotherapy may be more effective in the presence of large amounts of tumor cells in the organism [225]. Thus, this approach appears to be more potent either before primary tumor resection or in the presence of metastatic disease. These considerations were confirmed in the mouse models [226] and in melanoma patients [227,228,229]. According to the Clinical Trials Database, a number of clinical trials of adjuvant immunotherapy in MSI cancers were initiated, and the design of two of them was published [230,231]. One of them—POLEM—in stage 3 MSI or POLE mutant CRC patients was recently terminated due to recruitment challenges [232].
In summary, the vast majority of cancer types with features of MSI respond to the immunotherapy. While ICI efficacy in CRC, EC, and gastric cancer is well-established, for other types of cancer, immunotherapy is plausible when other standard options have been exhausted.

6. Mechanisms of Resistance to ICI

As previously shown, a significant proportion of MSI patients do not respond to ICI therapy. About 25% of MSI CRC cases have intrinsic resistance to immunotherapy [43]. Several mechanisms have been proposed to explain this observation.
It has been supposed that copresence of mutations in oncogenes might play a role in therapy resistance to ICI. Numerous prospective clinical trials have tested the effect of BRAF and RAS mutations on the response to ICI therapy in dMMR/MSI CRC patients but all except one described above [197] did not find a significant association [41,196,197,200,201,233,234]. A small retrospective study has linked BRAF mutations to worse 1-year and 2-year PFS rates in 60 dMMR CRC patients (40% vs. 73.3%, 26.7% vs. 73.3%; p < 0.001) [235]. However, according to a recent meta-analysis, BRAF mutations do not influence the response to ICI, while remaining a negative prognostic biomarker [236]. The association between oncogenic mutations with ICI resistance in MSI CRC was not confirmed for B2M, HLA, and JAK1/2, although these genes were found to be frequently mutated in MSI CRC [46,47].
TMB can be considered as an independent biomarker for ICI benefit in MSI tumors. A few retrospective studies showed that TMB correlates with ICI response in MSI gastrointestinal cancers [237,238,239]. Theoretically, MSI tumors should have a large number of mutations, i.e., should be tumor mutational burden-high (TMB-H). In real practice, there is a discordance between these biomarkers as well as discordance between studies. For example, one large study revealed that in 2179 MSI cancer samples, 17.9% were tumor mutational burden-low (TMB-L) (which was defined as <20 mutations/mb) [150]. Another study reported the absence of TMB-L cases (defined as <30 mutations/mb) between 32 CRC samples with MSI, as proven by both IHC and PCR approaches. At the same time, among 56 TMB-L samples, 50 were identified as pMMR/MSS, while 6 samples had discordant MSI status: 5 were determined as dMMR by IHC only, and 1 as MSI by PCR only. IHC retesting resulted in redefining four of five dMMR cases as pMMR [240]. The discordance between these two studies can be explained by different methods of TMB evaluation. In the first study, Foundation One was used, which excludes truncating mutations in tumor suppressor genes [169]. While frameshift mutations are enriched in MSI tumors, this method may underestimate the number of antigen-producing mutations. The second study used a method that takes into account frameshift mutations, explaining the high concordance of its results with the MSI status. This study also revealed a problem of false-positive dMMR recognition, which can contribute to the number of cases resistant to ICI. In addition, it can be assumed that more correct methods for TMB calculation will allow more accurate determination of subgroups of patients resistant to immunotherapy.
Apart from mechanisms involving machinery of the adaptive immune system, MSI tumors may trigger an immune response through accumulation of cytosolic DNA. MLH1 deficiency leads to Exo1 hyperactivity and increased DNA excision. Nuclear DNA release into the cytoplasm activates an innate immune signaling pathway, the cGAS-STING system, which induces expression of type I interferons and other immune molecules. They slow down cell proliferation and promote immune cell infiltration in the affected area. Retrospective analysis showed that patients responding on immunotherapy had higher cGAS/STING expression. Thus, disruption of the cGAS/STING pathway can be considered as one of the mechanisms of resistance to immunotherapy [20,241].
The tumor microenvironment, including tumor-infiltrating lymphocytes (TILs), represents a promising area for finding predictors of the response to immunotherapy. MSI CRC tumors are characterized by significant lymphocyte infiltration [242]. A small study conducted in 30 MSI CRC patients showed an ORR of 70.6% in patients with a high number of TILs, compared to 42.9% in patients with a low number of TILs (odds ratio = 3.20, p = 0.0291) [239]. Lymphocyte subsets’ composition is usually evaluated with the Immunoscore assay based on the quantification of CD3+ and CD8+ cells [243]. It was shown that MSI CRC tumors have significantly higher Immunoscores than MSS: 0.57 (SD 0.97) in the general population (n = 550) vs. 2.4 in MSI tumors (n = 41) (p < 0.0001) [244]. Inflammation is often observed in patients with CRC. A recent study showed that this medical complication is associated with an immunosuppressive microenvironment, a higher neutrophil–lymphocyte ratio, and a worse response to ICI [245].
Gut microbiome composition is associated with ICI response in melanoma patients [246,247]. It was shown that MMR-deficient and -proficient CRC tumors differ in gut microbiome composition [248]. However, the role of microbiota in immunotherapy resistance in MSI-H cancers largely remains underexplored [49]. A retrospective study of 57 MSI-H/dMMR CRC patients showed no association between antibiotic exposure and ICI response, indicating a limited role of gut bacteria [249].
More fundamental mechanisms of ICI resistance may be explained in the context of immunoediting theory. According to this theory, tumor cell subclones harboring immunogenic neoantigens are eliminated by the immune system during tumor progression [250]. This might explain the difference between the prevalence of MSI in early and advanced stages [84] as well as the difference in response between neoadjuvant and palliative therapy described above.
Thus, to date, precise mechanisms of MSI tumors’ resistance to immunotherapy remain unclear and there are no known predictive biomarkers ready for implementation in the clinic. The fact that virtually all tested non-metastatic MSI tumors respond to ICI in neoadjuvant settings suggests that intrinsic resistance may be acquired during tumor evolution to the metastatic state.

7. Conclusions and Future Perspectives

MSI occurs in many types of tumors, both those associated with Lynch syndrome (colorectal cancer, endometrial cancer, cancer of the small intestine, and gastric cancer) and sporadic, but with a lower incidence. MSI is a key diagnostic biomarker for Lynch syndrome and is one of the best predictive biomarkers of immune checkpoint inhibitors’ (ICIs) efficacy. Since the FDA approved the first drug in the class of ICI, the treatment landscape of many cancer types has significantly improved. Recognition of MSI as a tissue/site-agnostic biomarker for pembrolizumab became an important milestone in the development of precision medicine. Among other types, colorectal and endometrial cancers are the most well-studied in terms of the predictive role of MSI in relation to the efficacy of ICI.
However, despite that ICIs typically result in high objective response rates, about a quarter of MSI metastatic cases demonstrate primary resistance, i.e., progress after the start of treatment. The underlying causes for this resistance have been extensively studied. Mutations in certain signaling pathway genes, correlation with TMB, the tumor microenvironment, gut microbiome, and tumor immunoediting have been suggested as possible causes, but to date, precise mechanisms of resistance remain elusive. Thus, further studies are needed, especially to confirm the efficacy of immunotherapy for the MSI rarer, less studied tumors, as well as to reveal the intrinsic difference between individual patients responsive or resistant to treatment.

Author Contributions

Conceptualization, A.L., V.Y. and M.I.; writing—original draft preparation, A.K. and E.V.; writing—review and editing, A.K., E.V., A.L., E.B., O.K., V.Y., T.G., V.M., M.F. and M.I.; supervision, M.I. All authors have read and agreed to the published version of the manuscript.


The research was supported by the Russian Science Foundation (Project No. 22-75-10154;, accessed on 28 February 2023).

Conflicts of Interest

A.K., E.V., A.L., E.B., O.K., V.Y., T.G., V.M., M.F are employees of OncoAtlas LLC. Other co-authors have no conflicts of interest to disclose.


  1. Baretti, M.; Le, D.T. DNA Mismatch Repair in Cancer. Pharmacol. Ther. 2018, 189, 45–62. [Google Scholar] [CrossRef] [PubMed]
  2. Ma, J.; Setton, J.; Lee, N.Y.; Riaz, N.; Powell, S.N. The Therapeutic Significance of Mutational Signatures from DNA Repair Deficiency in Cancer. Nat. Commun. 2018, 9, 3292. [Google Scholar] [CrossRef] [PubMed]
  3. Bass, A.J.; Thorsson, V.; Shmulevich, I.; Reynolds, S.M.; Miller, M.; Bernard, B.; Hinoue, T.; Laird, P.W.; Curtis, C.; Shen, H.; et al. Comprehensive Molecular Characterization of Gastric Adenocarcinoma. Nature 2014, 513, 202–209. [Google Scholar] [CrossRef]
  4. Lepore Signorile, M.; Disciglio, V.; di Carlo, G.; Pisani, A.; Simone, C.; Ingravallo, G. From Genetics to Histomolecular Characterization: An Insight into Colorectal Carcinogenesis in Lynch Syndrome. Int. J. Mol. Sci. 2021, 22, 6767. [Google Scholar] [CrossRef] [PubMed]
  5. Lower, S.S.; McGurk, M.P.; Clark, A.G.; Barbash, D.A. Satellite DNA Evolution: Old Ideas, New Approaches. Curr. Opin. Genet. Dev. 2018, 49, 70–78. [Google Scholar] [CrossRef] [PubMed]
  6. Kolodner, R.D.; Marsischky, G.T. Eukaryotic DNA Mismatch Repair. Curr. Opin. Genet. Dev. 1999, 9, 89–96. [Google Scholar] [CrossRef]
  7. Kunkel, T.A.; Erie, D.A. DNA Mismatch Repair. Annu. Rev. Biochem. 2005, 74, 681–710. [Google Scholar] [CrossRef]
  8. Modrich, P.; Lahue, R. Mismatch Repair in Replication Fidelity, Genetic Recombination, and Cancer Biology. Annu. Rev. Biochem. 1996, 65, 101–133. [Google Scholar] [CrossRef]
  9. Bronner, C.E.; Baker, S.M.; Morrison, P.T.; Warren, G.; Smith, L.G.; Lescoe, M.K.; Kane, M.; Earabino, C.; Lipford, J.; Lindblom, A.; et al. Mutation in the DNA Mismatch Repair Gene Homologue HMLH1 Is Associated with Hereditary Non-Polyposis Colon Cancer. Nature 1994, 368, 258–261. [Google Scholar] [CrossRef]
  10. Papadopoulos, N.; Nicolaides, N.C.; Wei, Y.F.; Ruben, S.M.; Carter, K.C.; Rosen, C.A.; Haseltine, W.A.; Fleischmann, R.D.; Fraser, C.M.; Adams, M.D.; et al. Mutation of a MutL Homolog in Hereditary Colon Cancer. Science 1994, 263, 1625–1629. [Google Scholar] [CrossRef]
  11. Fishel, R.; Lescoe, M.K.; Rao, M.R.S.; Copeland, N.G.; Jenkins, N.A.; Garber, J.; Kane, M.; Kolodner, R. The Human Mutator Gene Homolog MSH2 and Its Association with Hereditary Nonpolyposis Colon Cancer. Cell 1993, 75, 1027–1038. [Google Scholar] [CrossRef] [PubMed]
  12. Nicolaides, N.C.; Papadopoulos, N.; Liu, B.; Weit, Y.F.; Carter, K.C.; Ruben, S.M.; Rosen, C.A.; Haseltine, W.A.; Fleischmann, R.D.; Fraser, C.M.; et al. Mutations of Two PMS Homologues in Hereditary Nonpolyposis Colon Cancer. Nature 1994, 371, 75–80. [Google Scholar] [CrossRef] [PubMed]
  13. Jiricny, J. Postreplicative Mismatch Repair. Cold Spring Harb. Perspect. Biol. 2013, 5, a012633. [Google Scholar] [CrossRef] [PubMed]
  14. Gilson, P.; Merlin, J.L.; Harlé, A. Detection of Microsatellite Instability: State of the Art and Future Applications in Circulating Tumour DNA (CtDNA). Cancers 2021, 13, 1491. [Google Scholar] [CrossRef] [PubMed]
  15. Iyer, R.R.; Pluciennik, A. DNA Mismatch Repair and Its Role in Huntington’s Disease. J. Huntingtons Dis. 2021, 10, 75–94. [Google Scholar] [CrossRef] [PubMed]
  16. Li, Z.; Pearlman, A.H.; Hsieh, P. DNA Mismatch Repair and the DNA Damage Response. DNA Repair 2016, 38, 94–101. [Google Scholar] [CrossRef] [PubMed]
  17. Kadyrov, F.A.; Dzantiev, L.; Constantin, N.; Modrich, P. Endonucleolytic Function of MutLalpha in Human Mismatch Repair. Cell 2006, 126, 297–308. [Google Scholar] [CrossRef]
  18. Ortega, J.; Lee, G.S.; Gu, L.; Yang, W.; Li, G.M. Mispair-Bound Human MutS-MutL Complex Triggers DNA Incisions and Activates Mismatch Repair. Cell Res. 2021, 31, 542–553. [Google Scholar] [CrossRef]
  19. Zhang, Y.; Yuan, F.; Presnell, S.R.; Tian, K.; Gao, Y.; Tomkinson, A.E.; Gu, L.; Li, G.M. Reconstitution of 5′-Directed Human Mismatch Repair in a Purified System. Cell 2005, 122, 693–705. [Google Scholar] [CrossRef]
  20. Guan, J.; Lu, C.; Jin, Q.; Lu, H.; Chen, X.; Tian, L.; Zhang, Y.; Ortega, J.; Zhang, J.; Siteni, S.; et al. MLH1 Deficiency-Triggered DNA Hyperexcision by Exonuclease 1 Activates the CGAS-STING Pathway. Cancer Cell 2021, 39, 109–121.e5. [Google Scholar] [CrossRef]
  21. Olave, M.C.; Graham, R.P. Mismatch Repair Deficiency: The What, How and Why It Is Important. Genes Chromosomes Cancer 2022, 61, 314–321. [Google Scholar] [CrossRef] [PubMed]
  22. Li, G.M. Mechanisms and Functions of DNA Mismatch Repair. Cell Res. 2008, 18, 85–98. [Google Scholar] [CrossRef] [PubMed]
  23. Diao, Z.; Han, Y.; Chen, Y.; Zhang, R.; Li, J. The Clinical Utility of Microsatellite Instability in Colorectal Cancer. Crit. Rev. Oncol. Hematol. 2021, 157, 103171. [Google Scholar] [CrossRef] [PubMed]
  24. Cheah, P.-L.; Looi, L.-M.; Koh, C.-C.; Lau, T.-P.; Chang, S.-W.; Teoh, K.-H.; Mun, K.-S.; Nazarina, A.R. Screening for Microsatellite Instability in Colorectal Carcinoma: Practical Utility of Immunohistochemistry and PCR with Fragment Analysis in a Diagnostic Histopathology Setting. Malays. J. Pathol. 2019, 41, 91–100. [Google Scholar] [PubMed]
  25. Diaz-Padilla, I.; Romero, N.; Amir, E.; Matias-Guiu, X.; Vilar, E.; Muggia, F.; Garcia-Donas, J. Mismatch Repair Status and Clinical Outcome in Endometrial Cancer: A Systematic Review and Meta-Analysis. Crit. Rev. Oncol. Hematol. 2013, 88, 154–167. [Google Scholar] [CrossRef] [PubMed]
  26. Black, D.; Soslow, R.A.; Levine, D.A.; Tornos, C.; Chen, S.C.; Hummer, A.J.; Bogomolniy, F.; Olvera, N.; Barakat, R.R.; Boyd, J. Clinicopathologic Significance of Defective DNA Mismatch Repair in Endometrial Carcinoma. J. Clin. Oncol. 2006, 24, 1745–1753. [Google Scholar] [CrossRef]
  27. Cortes-Ciriano, I.; Lee, S.; Park, W.Y.; Kim, T.M.; Park, P.J. A Molecular Portrait of Microsatellite Instability across Multiple Cancers. Nat. Commun. 2017, 8, 15180. [Google Scholar] [CrossRef]
  28. Polom, K.; Marano, L.; Marrelli, D.; de Luca, R.; Roviello, G.; Savelli, V.; Tan, P.; Roviello, F. Meta-Analysis of Microsatellite Instability in Relation to Clinicopathological Characteristics and Overall Survival in Gastric Cancer. Br. J. Surg. 2018, 105, 159–167. [Google Scholar] [CrossRef]
  29. Schrock, A.B.; Devoe, C.E.; McWilliams, R.; Sun, J.; Aparicio, T.; Stephens, P.J.; Ross, J.S.; Wilson, R.; Miller, V.A.; Ali, S.M.; et al. Genomic Profiling of Small-Bowel Adenocarcinoma. JAMA Oncol. 2017, 3, 1546–1553. [Google Scholar] [CrossRef]
  30. Luchini, C.; Bibeau, F.; Ligtenberg, M.J.L.; Singh, N.; Nottegar, A.; Bosse, T.; Miller, R.; Riaz, N.; Douillard, J.Y.; Andre, F.; et al. ESMO Recommendations on Microsatellite Instability Testing for Immunotherapy in Cancer, and Its Relationship with PD-1/PD-L1 Expression and Tumour Mutational Burden: A Systematic Review-Based Approach. Ann. Oncol. 2019, 30, 1232–1243. [Google Scholar] [CrossRef]
  31. Porkka, N.; Valo, S.; Nieminen, T.T.; Olkinuora, A.; Mäki-Nevala, S.; Eldfors, S.; Peltomäki, P. Sequencing of Lynch Syndrome Tumors Reveals the Importance of Epigenetic Alterations. Oncotarget 2017, 8, 108020–108030. [Google Scholar] [CrossRef] [PubMed]
  32. Lynch, H.T.; Lynch, P.M.; Lanspa, S.J.; Snyder, C.L.; Lynch, J.F.; Boland, C.R. Review of the Lynch Syndrome: History, Molecular Genetics, Screening, Differential Diagnosis, and Medicolegal Ramifications. Clin. Genet. 2009, 76, 1–18. [Google Scholar] [CrossRef] [PubMed]
  33. Pardoll, D.M. The Blockade of Immune Checkpoints in Cancer Immunotherapy. Nat. Rev. Cancer 2012, 12, 252–264. [Google Scholar] [CrossRef] [PubMed]
  34. Sadreddini, S.; Baradaran, B.; Aghebati-Maleki, A.; Sadreddini, S.; Shanehbandi, D.; Fotouhi, A.; Aghebati-Maleki, L. Immune Checkpoint Blockade Opens a New Way to Cancer Immunotherapy. J. Cell Physiol. 2019, 234, 8541–8549. [Google Scholar] [CrossRef] [PubMed]
  35. de Giglio, A.; di Federico, A.; Nuvola, G.; Deiana, C.; Gelsomino, F. The Landscape of Immunotherapy in Advanced NSCLC: Driving beyond PD-1/PD-L1 Inhibitors (CTLA-4, LAG3, IDO, OX40, TIGIT, Vaccines). Curr. Oncol. Rep. 2021, 23, 126. [Google Scholar] [CrossRef]
  36. Umar, A.; Boland, C.R.; Terdiman, J.P.; Syngal, S.; de la Chapelle, A.; Rüschoff, J.; Fishel, R.; Lindor, N.M.; Burgart, L.J.; Hamelin, R.; et al. Revised Bethesda Guidelines for Hereditary Nonpolyposis Colorectal Cancer (Lynch Syndrome) and Microsatellite Instability. J. Natl. Cancer Inst. 2004, 96, 261–268. [Google Scholar] [CrossRef]
  37. Goel, A.; Nagasaka, T.; Hamelin, R.; Boland, C.R. An Optimized Pentaplex PCR for Detecting DNA Mismatch Repair-Deficient Colorectal Cancers. PLoS ONE 2010, 5, 9393. [Google Scholar] [CrossRef]
  38. Ratovomanana, T.; Cohen, R.; Svrcek, M.; Renaud, F.; Cervera, P.; Siret, A.; Letourneur, Q.; Buhard, O.; Bourgoin, P.; Guillerm, E.; et al. Performance of Next-Generation Sequencing for the Detection of Microsatellite Instability in Colorectal Cancer with Deficient DNA Mismatch Repair. Gastroenterology 2021, 161, 814–826.e7. [Google Scholar] [CrossRef]
  39. U.S. Food and Drug Administration Website. KEYTRUDA (Pembrolizumab). Available online: (accessed on 7 February 2023).
  40. Marabelle, A.; Le, D.T.; Ascierto, P.A.; di Giacomo, A.M.; de Jesus-Acosta, A.; Delord, J.P.; Geva, R.; Gottfried, M.; Penel, N.; Hansen, A.R.; et al. Efficacy of Pembrolizumab in Patients with Noncolorectal High Microsatellite Instability/Mismatch Repair-Deficient Cancer: Results from the Phase II KEYNOTE-158 Study. J. Clin. Oncol. 2020, 38, 1–10. [Google Scholar] [CrossRef]
  41. Lenz, H.J.; van Cutsem, E.; Limon, M.L.; Wong, K.Y.M.; Hendlisz, A.; Aglietta, M.; García-Alfonso, P.; Neyns, B.; Luppi, G.; Cardin, D.B.; et al. First-Line Nivolumab Plus Low-Dose Ipilimumab for Microsatellite Instability-High/Mismatch Repair-Deficient Metastatic Colorectal Cancer: The Phase II CheckMate 142 Study. J. Clin. Oncol. 2022, 40, 161–170. [Google Scholar] [CrossRef]
  42. Cercek, A.; Lumish, M.; Sinopoli, J.; Weiss, J.; Shia, J.; Lamendola-Essel, M.; el Dika, I.H.; Segal, N.; Shcherba, M.; Sugarman, R.; et al. PD-1 Blockade in Mismatch Repair-Deficient, Locally Advanced Rectal Cancer. N. Engl. J. Med. 2022, 386, 2363–2376. [Google Scholar] [CrossRef] [PubMed]
  43. Wang, R.; Lian, J.; Wang, X.; Pang, X.; Xu, B.; Tang, S.; Shao, J.; Lu, H. Intrinsic Resistance and Efficacy of Immunotherapy in Microsatellite Instability-High Colorectal Cancer: A Systematic Review and Meta-Analysis. Bosn. J. Basic Med. Sci. 2022, 23, 198–208. [Google Scholar] [CrossRef] [PubMed]
  44. Maio, M.; Ascierto, P.A.; Manzyuk, L.; Motola-Kuba, D.; Penel, N.; Cassier, P.A.; Bariani, G.M.; de Jesus Acosta, A.; Doi, T.; Longo, F.; et al. Pembrolizumab in Microsatellite Instability High or Mismatch Repair Deficient Cancers: Updated Analysis from the Phase II KEYNOTE-158 Study. Ann. Oncol. 2022, 33, 929–938. [Google Scholar] [CrossRef] [PubMed]
  45. Taieb, J.; Svrcek, M.; Cohen, R.; Basile, D.; Tougeron, D.; Phelip, J.M. Deficient Mismatch Repair/Microsatellite Unstable Colorectal Cancer: Diagnosis, Prognosis and Treatment. Eur. J. Cancer 2022, 175, 136–157. [Google Scholar] [CrossRef]
  46. Grasso, C.S.; Giannakis, M.; Wells, D.K.; Hamada, T.; Mu, X.J.; Quist, M.; Nowak, J.A.; Nishihara, R.; Qian, Z.R.; Inamura, K.; et al. Genetic Mechanisms of Immune Evasion in Colorectal Cancer. Cancer Discov. 2018, 8, 730–749. [Google Scholar] [CrossRef]
  47. Zhang, C.; Li, D.; Xiao, B.; Zhou, C.; Jiang, W.; Tang, J.; Li, Y.; Zhang, R.; Han, K.; Hou, Z.; et al. B2M and JAK1/2-Mutated MSI-H Colorectal Carcinomas Can Benefit from Anti-PD-1 Therapy. J. Immunother. 2022, 45, 187–193. [Google Scholar] [CrossRef] [PubMed]
  48. Abushukair, H.; Ababneh, O.; Zaitoun, S.; Saeed, A. Primary and Secondary Immune Checkpoint Inhibitors Resistance in Colorectal Cancer: Key Mechanisms and Ways to Overcome Resistance. Cancer Treat. Res. Commun. 2022, 33, 100643. [Google Scholar] [CrossRef] [PubMed]
  49. Bouferraa, Y.; Chedid, A.; Amhaz, G.; el Lakkiss, A.; Mukherji, D.; Temraz, S.; Shamseddine, A. The Role of Gut Microbiota in Overcoming Resistance to Checkpoint Inhibitors in Cancer Patients: Mechanisms and Challenges. Int. J. Mol. Sci. 2021, 22, 8036. [Google Scholar] [CrossRef]
  50. Ballhausen, A.; Przybilla, M.J.; Jendrusch, M.; Haupt, S.; Pfaffendorf, E.; Seidler, F.; Witt, J.; Hernandez Sanchez, A.; Urban, K.; Draxlbauer, M.; et al. The Shared Frameshift Mutation Landscape of Microsatellite-Unstable Cancers Suggests Immunoediting during Tumor Evolution. Nat. Commun. 2020, 11, 4740. [Google Scholar] [CrossRef]
  51. Bucksch, K.; Zachariae, S.; Aretz, S.; Büttner, R.; Holinski-Feder, E.; Holzapfel, S.; Hüneburg, R.; Kloor, M.; von Knebel Doeberitz, M.; Morak, M.; et al. Cancer Risks in Lynch Syndrome, Lynch-like Syndrome, and Familial Colorectal Cancer Type X: A Prospective Cohort Study. BMC Cancer 2020, 20, 460. [Google Scholar] [CrossRef]
  52. Lynch, H.T.; de la Chapelle, A. Hereditary Colorectal Cancer. N. Engl. J. Med. 2003, 348, 919–932. [Google Scholar] [CrossRef] [PubMed]
  53. Lynch, H.T.; Snyder, C.L.; Shaw, T.G.; Heinen, C.D.; Hitchins, M.P. Milestones of Lynch Syndrome: 1895–2015. Nat. Rev. Cancer 2015, 15, 181–194. [Google Scholar] [CrossRef] [PubMed]
  54. Ligtenberg, M.J.L.; Kuiper, R.P.; Chan, T.L.; Goossens, M.; Hebeda, K.M.; Voorendt, M.; Lee, T.Y.H.; Bodmer, D.; Hoenselaar, E.; Hendriks-Cornelissen, S.J.B.; et al. Heritable Somatic Methylation and Inactivation of MSH2 in Families with Lynch Syndrome Due to Deletion of the 3′ Exons of TACSTD1. Nat. Genet. 2009, 41, 112–117. [Google Scholar] [CrossRef] [PubMed]
  55. Modrich, P. Mismatch Repair, Genetic Stability, and Cancer. Science 1994, 266, 1959–1960. [Google Scholar] [CrossRef] [PubMed]
  56. Leach, F.S.; Nicolaides, N.C.; Papadopoulos, N.; Liu, B.; Jen, J.; Parsons, R.; Peltomäki, P.; Sistonen, P.; Aaltonen, L.A.; Nyström-Lahti, M.; et al. Mutations of a MutS Homolog in Hereditary Nonpolyposis Colorectal Cancer. Cell 1993, 75, 1215–1225. [Google Scholar] [CrossRef]
  57. Win, A.K.; Jenkins, M.A.; Dowty, J.G.; Antoniou, A.C.; Lee, A.; Giles, G.G.; Buchanan, D.D.; Clendenning, M.; Rosty, C.; Ahnen, D.J.; et al. Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer. Cancer Epidemiol. Biomark. Prev. 2017, 26, 404–412. [Google Scholar] [CrossRef]
  58. Poulogiannis, G.; Frayling, I.M.; Arends, M.J. DNA Mismatch Repair Deficiency in Sporadic Colorectal Cancer and Lynch Syndrome. Histopathology 2010, 56, 167–179. [Google Scholar] [CrossRef]
  59. Rossi, L.; le Frere-Belda, M.A.; Laurent-Puig, P.; Buecher, B.; de Pauw, A.; Stoppa-Lyonnet, D.; Canlorbe, G.; Caron, O.; Borghese, B.; Colas, C.; et al. Clinicopathologic Characteristics of Endometrial Cancer in Lynch Syndrome: A French Multicenter Study. Int. J. Gynecol. Cancer. 2017, 27, 953–960. [Google Scholar] [CrossRef]
  60. Evrard, C.; Alexandre, J. Predictive and Prognostic Value of Microsatellite Instability in Gynecologic Cancer (Endometrial and Ovarian). Cancers 2021, 13, 2434. [Google Scholar] [CrossRef]
  61. Tiwari, A.K.; Roy, H.K.; Lynch, H.T. Lynch Syndrome in the 21st Century: Clinical Perspectives. QJM Int. J. Med. 2016, 109, 151–158. [Google Scholar] [CrossRef]
  62. Kempers, M.J.E.; Kuiper, R.P.; Ockeloen, C.W.; Chappuis, P.O.; Hutter, P.; Rahner, N.; Schackert, H.K.; Steinke, V.; Holinski-Feder, E.; Morak, M.; et al. Risk of Colorectal and Endometrial Cancers in EPCAM Deletion-Positive Lynch Syndrome: A Cohort Study. Lancet Oncol. 2011, 12, 49–55. [Google Scholar] [CrossRef] [PubMed]
  63. Bonadona, V.; Bonaïti, B.; Olschwang, S.; Grandjouan, S.; Huiart, L.; Longy, M.; Guimbaud, R.; Buecher, B.; Bignon, Y.J.; Caron, O.; et al. Cancer Risks Associated with Germline Mutations in MLH1, MSH2, and MSH6 Genes in Lynch Syndrome. JAMA 2011, 305, 2304–2310. [Google Scholar] [CrossRef] [PubMed]
  64. Møller, P.; Seppälä, T.T.; Bernstein, I.; Holinski-Feder, E.; Sala, P.; Evans, D.G.; Lindblom, A.; Macrae, F.; Blanco, I.; Sijmons, R.H.; et al. Cancer Risk and Survival in Path_MMR Carriers by Gene and Gender up to 75 Years of Age: A Report from the Prospective Lynch Syndrome Database. Gut 2018, 67, 1306–1316. [Google Scholar] [CrossRef]
  65. Ryan, N.A.J.; Morris, J.; Green, K.; Lalloo, F.; Woodward, E.R.; Hill, J.; Crosbie, E.J.; Gareth Evans, D. Association of Mismatch Repair Mutation with Age at Cancer Onset in Lynch Syndrome: Implications for Stratified Surveillance Strategies. JAMA Oncol. 2017, 3, E1–E5. [Google Scholar] [CrossRef] [PubMed]
  66. Møller, P.; Seppälä, T.; Bernstein, I.; Holinski-Feder, E.; Sala, P.; Evans, D.G.; Lindblom, A.; Macrae, F.; Blanco, I.; Sijmons, R.; et al. Cancer Incidence and Survival in Lynch Syndrome Patients Receiving Colonoscopic and Gynaecological Surveillance: First Report from the Prospective Lynch Syndrome Database. Gut 2017, 66, 464–472. [Google Scholar] [CrossRef] [PubMed]
  67. Engel, C.; Loeffler, M.; Steinke, V.; Rahner, N.; Holinski-Feder, E.; Dietmaier, W.; Schackert, H.K.; Goergens, H.; von Knebel Doeberitz, M.; Goecke, T.O.; et al. Risks of Less Common Cancers in Proven Mutation Carriers with Lynch Syndrome. J. Clin. Oncol. 2012, 30, 4409–4415. [Google Scholar] [CrossRef]
  68. Capelle, L.G.; van Grieken, N.C.T.; Lingsma, H.F.; Steyerberg, E.W.; Klokman, W.J.; Bruno, M.J.; Vasen, H.F.A.; Kuipers, E.J. Risk and Epidemiological Time Trends of Gastric Cancer in Lynch Syndrome Carriers in the Netherlands. Gastroenterology 2010, 138, 487–492. [Google Scholar] [CrossRef]
  69. Dominguez-Valentin, M.; Joost, P.; Therkildsen, C.; Jonsson, M.; Rambech, E.; Nilbert, M. Frequent Mismatch-Repair Defects Link Prostate Cancer to Lynch Syndrome. BMC Urol. 2016, 16, 15. [Google Scholar] [CrossRef]
  70. Joost, P.; Therkildsen, C.; Dominguez-Valentin, M.; Jönsson, M.; Nilbert, M. Urinary Tract Cancer in Lynch Syndrome; Increased Risk in Carriers of MSH2 Mutations. Urology 2015, 86, 1212–1217. [Google Scholar] [CrossRef]
  71. Watson, P.; Vasen, H.F.A.; Mecklin, J.P.; Bernstein, I.; Aarnio, M.; Järvinen, H.J.; Myrhoj, T.; Sunde, L.; Wijnen, J.T.; Lynch, H.T. The Risk of Extra-Colonic, Extra-Endometrial Cancer in the Lynch Syndrome. Int. J. Cancer 2008, 123, 444–449. [Google Scholar] [CrossRef]
  72. Adan, F.; Crijns, M.B.; Zandstra, W.S.E.; Bekkenk, M.W.; Bleeker, F.E.; Dekker, E.; van Leerdam, M.E. Cumulative Risk of Skin Tumours in Patients with Lynch Syndrome. Br. J. Dermatol. 2018, 179, 522–523. [Google Scholar] [CrossRef] [PubMed]
  73. South, C.D.; Hampel, H.; Comeras, I.; Westman, J.A.; Frankel, W.L.; de La Chapelle, A. The Frequency of Muir-Torre Syndrome among Lynch Syndrome Families. J. Natl. Cancer Inst. 2008, 100, 277–281. [Google Scholar] [CrossRef] [PubMed]
  74. Wu, Y.; Berends, M.J.W.; Mensink, R.G.J.; Kempinga, C.; Sijmons, R.H.; van der Zee, A.G.J.; Hollema, H.; Kleibeuker, J.H.; Buys, C.H.C.M.; Hofstra, R.M.W. Association of Hereditary Nonpolyposis Colorectal Cancer-Related Tumors Displaying Low Microsatellite Instability with MSH6 Germline Mutations. Am. J. Hum. Genet. 1999, 65, 1291–1298. [Google Scholar] [CrossRef] [PubMed]
  75. Wang, C.; Wang, Y.; Hughes, K.S.; Parmigiani, G.; Braun, D. Penetrance of Colorectal Cancer Among Mismatch Repair Gene Mutation Carriers: A Meta-Analysis. JNCI Cancer Spectr. 2020, 4, pkaa027. [Google Scholar] [CrossRef]
  76. Senter, L.; Clendenning, M.; Sotamaa, K.; Hampel, H.; Green, J.; Potter, J.D.; Lindblom, A.; Lagerstedt, K.; Thibodeau, S.N.; Lindor, N.M.; et al. The Clinical Phenotype of Lynch Syndrome Due to Germ-Line PMS2 Mutations. Gastroenterology 2008, 135, 419–428.e1. [Google Scholar] [CrossRef]
  77. Broeke, S.W.T.; Klift, H.M.V.; Tops, C.M.J.; Aretz, S.; Bernstein, I.; Buchanan, D.D.; dela Chapelle, A.; Capella, G.; Clendenning, M.; Engel, C.; et al. Cancer Risks for PMS2-Associated Lynch Syndrome. J. Clin. Oncol. 2018, 36, 2961–2968. [Google Scholar] [CrossRef]
  78. Suerink, M.; Rodríguez-Girondo, M.; van der Klift, H.M.; Colas, C.; Brugieres, L.; Lavoine, N.; Jongmans, M.; Munar, G.C.; Evans, D.G.; Farrell, M.P.; et al. An Alternative Approach to Establishing Unbiased Colorectal Cancer Risk Estimation in Lynch Syndrome. Genet. Med. 2019, 21, 2706–2712. [Google Scholar] [CrossRef]
  79. NCCN Guidelines Version 2.2022 Genetic/Familial High-Risk Assessment: Colorectal. Available online: (accessed on 19 January 2023).
  80. Siegel, R.L.; Miller, K.D.; Fuchs, H.E.; Jemal, A. Cancer Statistics, 2022. CA Cancer J. Clin 2022, 72, 7–33. [Google Scholar] [CrossRef]
  81. Dominguez-Valentin, M.; Sampson, J.R.; Seppälä, T.T.; ten Broeke, S.W.; Plazzer, J.P.; Nakken, S.; Engel, C.; Aretz, S.; Jenkins, M.A.; Sunde, L.; et al. Cancer Risks by Gene, Age, and Gender in 6350 Carriers of Pathogenic Mismatch Repair Variants: Findings from the Prospective Lynch Syndrome Database. Genet. Med. 2020, 22, 15–25. [Google Scholar] [CrossRef]
  82. Baglietto, L.; Lindor, N.M.; Dowty, J.G.; White, D.M.; Wagner, A.; Gomez Garcia, E.B.; Vriends, A.H.J.T.; Cartwright, N.R.; Barnetson, R.A.; Farrington, S.M.; et al. Risks of Lynch Syndrome Cancers for MSH6 Mutation Carriers. J. Natl. Cancer Inst. 2010, 102, 193–201. [Google Scholar] [CrossRef]
  83. Bonneville, R.; Krook, M.A.; Kautto, E.A.; Miya, J.; Wing, M.R.; Chen, H.-Z.; Reeser, J.W.; Yu, L.; Roychowdhury, S. Landscape of Microsatellite Instability Across 39 Cancer Types. JCO Precis. Oncol. 2017, 1, 1–15. [Google Scholar] [CrossRef] [PubMed]
  84. Kang, Y.J.; O’Haire, S.; Franchini, F.; Ijzerman, M.; Zalcberg, J.; Macrae, F.; Canfell, K.; Steinberg, J. A Scoping Review and Meta-Analysis on the Prevalence of Pan-Tumour Biomarkers (DMMR, MSI, High TMB) in Different Solid Tumours. Sci. Rep. 2022, 12, 20495. [Google Scholar] [CrossRef] [PubMed]
  85. Carr, P.R.; Alwers, E.; Bienert, S.; Weberpals, J.; Kloor, M.; Brenner, H.; Hoffmeister, M. Lifestyle Factors and Risk of Sporadic Colorectal Cancer by Microsatellite Instability Status: A Systematic Review and Meta-Analyses. Ann. Oncol. 2018, 29, 825–834. [Google Scholar] [CrossRef] [PubMed]
  86. Ashktorab, H.; Ahuja, S.; Kannan, L.; Llor, X.; Nathan, E.; Xicola, R.M.; Laiyemo, A.O.; Carethers, J.M.; Brim, H.; Nouraie, M. A Meta-Analysis of MSI Frequency and Race in Colorectal Cancer. Oncotarget 2016, 7, 34546–34557. [Google Scholar] [CrossRef]
  87. Gkekas, I.; Novotny, J.; Pecen, L.; Strigård, K.; Palmqvist, R.; Gunnarsson, U. Microsatellite Instability as a Prognostic Factor in Stage II Colon Cancer Patients, a Meta-Analysis of Published Literature. Anticancer Res. 2017, 37, 6563–6574. [Google Scholar] [CrossRef]
  88. Guinney, J.; Dienstmann, R.; Wang, X.; de Reyniès, A.; Schlicker, A.; Soneson, C.; Marisa, L.; Roepman, P.; Nyamundanda, G.; Angelino, P.; et al. The Consensus Molecular Subtypes of Colorectal Cancer. Nat. Med. 2015, 21, 1350–1356. [Google Scholar] [CrossRef]
  89. Petrelli, F.; Ghidini, M.; Cabiddu, M.; Pezzica, E.; Corti, D.; Turati, L.; Costanzo, A.; Varricchio, A.; Ghidini, A.; Barni, S.; et al. Microsatellite Instability and Survival in Stage II Colorectal Cancer: A Systematic Review and Meta-Analysis. Anticancer Res. 2019, 39, 6431–6441. [Google Scholar] [CrossRef]
  90. Aaltonen, L.A.; Peltomäki, P.; Leach, F.S.; Sistonen, P.; Pylkkänen, L.; Mecklin, J.P.; Järvinen, H.; Powell, S.M.; Jen, J.; Hamilton, S.R.; et al. Clues to the Pathogenesis of Familial Colorectal Cancer. Science 1993, 260, 812–816. [Google Scholar] [CrossRef]
  91. Mohamed, A.; Jiang, R.; Philip, P.A.; Diab, M.; Behera, M.; Wu, C.; Alese, O.; Shaib, W.L.; Gaines, T.M.; Balch, G.G.; et al. High-Risk Features Are Prognostic in DMMR/MSI-H Stage II Colon Cancer. Front. Oncol. 2021, 11, 755113. [Google Scholar] [CrossRef]
  92. Hecht, J.L.; Mutter, G.L. Molecular and Pathologic Aspects of Endometrial Carcinogenesis. J. Clin. Oncol. 2006, 24, 4783–4791. [Google Scholar] [CrossRef]
  93. Zighelboim, I.; Goodfellow, P.J.; Gao, F.; Gibb, R.K.; Powell, M.A.; Rader, J.S.; Mutch, D.G. Microsatellite Instability and Epigenetic Inactivation of MLH1 and Outcome of Patients with Endometrial Carcinomas of the Endometrioid Type. J. Clin. Oncol. 2007, 25, 2042–2048. [Google Scholar] [CrossRef] [PubMed]
  94. Getz, G.; Gabriel, S.B.; Cibulskis, K.; Lander, E.; Sivachenko, A.; Sougnez, C.; Lawrence, M.; Kandoth, C.; Dooling, D.; Fulton, R.; et al. Integrated Genomic Characterization of Endometrial Carcinoma. Nature 2013, 497, 67–73. [Google Scholar] [CrossRef]
  95. Kwon, M.; An, M.; Klempner, S.J.; Lee, H.; Kim, K.M.; Sa, J.K.; Cho, H.J.; Hong, J.Y.; Lee, T.; Min, Y.W.; et al. Determinants of Response and Intrinsic Resistance to PD-1 Blockade in Microsatellite Instability-High Gastric Cancer. Cancer Discov. 2021, 11, 2168–2185. [Google Scholar] [CrossRef] [PubMed]
  96. Puliga, E.; Corso, S.; Pietrantonio, F.; Giordano, S. Microsatellite Instability in Gastric Cancer: Between Lights and Shadows. Cancer Treat. Rev. 2021, 95, 102175. [Google Scholar] [CrossRef] [PubMed]
  97. Murphy, M.A.; Wentzensen, N. 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. Int. J. Cancer 2011, 129, 1914–1922. [Google Scholar] [CrossRef]
  98. Pal, T.; Permuth-Wey, J.; Kumar, A.; Sellers, T.A. Systematic Review and Meta-Analysis of Ovarian Cancers: Estimation of Microsatellite-High Frequency and Characterization of Mismatch Repair Deficient Tumor Histology. Clin. Cancer Res. 2008, 14, 6847–6854. [Google Scholar] [CrossRef]
  99. Raphael, B.J.; Hruban, R.H.; Aguirre, A.J.; Moffitt, R.A.; Yeh, J.J.; Stewart, C.; Robertson, A.G.; Cherniack, A.D.; Gupta, M.; Getz, G.; et al. Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma. Cancer Cell 2017, 32, 185–203.e13. [Google Scholar] [CrossRef]
  100. Luchini, C.; Brosens, L.A.A.; Wood, L.D.; Chatterjee, D.; Shin, J.I.; Sciammarella, C.; Fiadone, G.; Malleo, G.; Salvia, R.; Kryklyva, V.; et al. Comprehensive Characterisation of Pancreatic Ductal Adenocarcinoma with Microsatellite Instability: Histology, Molecular Pathology and Clinical Implications. Gut 2021, 70, 148–156. [Google Scholar] [CrossRef]
  101. Luchini, C.; Scarpa, A. Microsatellite Instability in Pancreatic and Ampullary Carcinomas: Histology, Molecular Pathology, and Clinical Implications. Hum. Pathol. 2022, 132, 176–182. [Google Scholar] [CrossRef]
  102. Kullmann, F.; Strissel, P.L.; Strick, R.; Stoehr, R.; Eckstein, M.; Bertz, S.; Wullich, B.; Sikic, D.; Wach, S.; Taubert, H.; et al. Frequency of Microsatellite Instability (MSI) in Upper Tract Urothelial Carcinoma: Comparison of the Bethesda Panel and the Idylla MSI Assay in a Consecutively Collected, Multi-Institutional Cohort. J. Clin. Pathol. 2023, 76, 126–132. [Google Scholar] [CrossRef]
  103. Sobrino-Reig, E.; Meizoso, T.; García, J.; Varillas-Delgado, D.; Martin, Y.B. Morphological Predictors for Microsatellite Instability in Urothelial Carcinoma. Diagn. Pathol. 2021, 16, 106. [Google Scholar] [CrossRef] [PubMed]
  104. Schneider, B.; Glass, Ä.; Jagdmann, S.; Hühns, M.; Claus, J.; Zettl, H.; Dräger, D.L.; Maruschke, M.; Hakenberg, O.W.; Erbersdobler, A.; et al. Loss of Mismatch-Repair Protein Expression and Microsatellite Instability in Upper Tract Urothelial Carcinoma and Clinicopathologic Implications. Clin. Genitourin. Cancer 2020, 18, e563–e572. [Google Scholar] [CrossRef] [PubMed]
  105. Le, D.T.; Durham, J.N.; Smith, K.N.; Wang, H.; Bartlett, B.R.; Aulakh, L.K.; Lu, S.; Kemberling, H.; Wilt, C.; Luber, B.S.; et al. Mismatch Repair Deficiency Predicts Response of Solid Tumors to PD-1 Blockade. Science 2017, 357, 409–413. [Google Scholar] [CrossRef] [PubMed]
  106. Latham, A.; Srinivasan, P.; Kemel, Y.; Shia, J.; Bandlamudi, C.; Mandelker, D.; Middha, S.; Hechtman, J.; Zehir, A.; Dubard-Gault, M.; et al. Microsatellite Instability Is Associated with the Presence of Lynch Syndrome Pan-Cancer. J. Clin. Oncol. 2019, 37, 286. [Google Scholar] [CrossRef] [PubMed]
  107. Hampel, H.; Frankel, W.; Panescu, J.; Lockman, J.; Sotamaa, K.; Fix, D.; Comeras, I.; la Jeunesse, J.; Nakagawa, H.; Westman, J.A.; et al. Screening for Lynch Syndrome (Hereditary Nonpolyposis Colorectal Cancer) among Endometrial Cancer Patients. Cancer Res. 2006, 66, 7810–7817. [Google Scholar] [CrossRef]
  108. Stelloo, E.; Jansen, A.M.L.; Osse, E.M.; Nout, R.A.; Creutzberg, C.L.; Ruano, D.; Church, D.N.; Morreau, H.; Smit, V.T.H.B.M.; van Wezel, T.; et al. Practical Guidance for Mismatch Repair-Deficiency Testing in Endometrial Cancer. Ann. Oncol. 2017, 28, 96–102. [Google Scholar] [CrossRef]
  109. Goodfellow, P.J.; Billingsley, C.C.; Lankes, H.A.; Ali, S.; Cohn, D.E.; Broaddus, R.J.; Ramirez, N.; Pritchard, C.C.; Hampel, H.; Chassen, A.S.; et al. Combined Microsatellite Instability, MLH1 Methylation Analysis, and Immunohistochemistry for Lynch Syndrome Screening in Endometrial Cancers from GOG210: An NRG Oncology and Gynecologic Oncology Group Study. J. Clin. Oncol. 2015, 33, 4301–4308. [Google Scholar] [CrossRef]
  110. Simpkins, S.B.; Bocker, T.; Swisher, E.M.; Mutch, D.G.; Gersell, D.J.; Kovatich, A.J.; Palazzo, J.P.; Fishel, R.; Goodfellow, P.J. MLH1 Promoter Methylation and Gene Silencing Is the Primary Cause of Microsatellite Instability in Sporadic Endometrial Cancers. Hum. Mol. Genet. 1999, 8, 661–666. [Google Scholar] [CrossRef]
  111. Deshpande, M.; Romanski, P.A.; Rosenwaks, Z.; Gerhardt, J. Gynecological Cancers Caused by Deficient Mismatch Repair and Microsatellite Instability. Cancers 2020, 12, 3319. [Google Scholar] [CrossRef]
  112. Leite, M.; Corso, G.; Sousa, S.; Milanezi, F.; Afonso, L.P.; Henrique, R.; Soares, J.M.; Castedo, S.; Carneiro, F.; Roviello, F.; et al. MSI Phenotype and MMR Alterations in Familial and Sporadic Gastric Cancer. Int. J. Cancer 2011, 128, 1606–1613. [Google Scholar] [CrossRef]
  113. Gay, L.J.; Arends, M.J.; Mitrou, P.N.; Bowman, R.; Ibrahim, A.E.; Happerfield, L.; Luben, R.; McTaggart, A.; Ball, R.Y.; Rodwell, S.A. MLH1 Promoter Methylation, Diet, and Lifestyle Factors in Mismatch Repair Deficient Colorectal Cancer Patients from EPIC-Norfolk. Nutr. Cancer 2011, 63, 1000–1010. [Google Scholar] [CrossRef]
  114. Meyer, L.A.; Broaddus, R.R.; Lu, K.H. Endometrial Cancer and Lynch Syndrome: Clinical and Pathologic Considerations. Cancer Control 2009, 16, 14–22. [Google Scholar] [CrossRef]
  115. Ibrahim, A.E.K.; Arends, M.J. Molecular Typing of Colorectal Cancer: Applications in Diagnosis and Treatment. Diagn. Histopathol. 2012, 18, 70–80. [Google Scholar] [CrossRef]
  116. Jin, J.; Shi, Y.; Zhang, S.; Yang, S. PIK3CA Mutation and Clinicopathological Features of Colorectal Cancer: A Systematic Review and Meta-Analysis. Acta Oncol. 2020, 59, 66–74. [Google Scholar] [CrossRef] [PubMed]
  117. Brennetot, C.; Duval, A.; Hamelin, R.; Pinto, M.; Oliveira, C.; Seruca, R.; Schwartz, S. Frequent Ki-Ras Mutations in Gastric Tumors of the MSI Phenotype. Gastroenterology 2003, 125, 1282–1283. [Google Scholar] [CrossRef]
  118. Polom, K.; Das, K.; Marrelli, D.; Roviello, G.; Pascale, V.; Voglino, C.; Rho, H.; Tan, P.; Roviello, F. KRAS Mutation in Gastric Cancer and Prognostication Associated with Microsatellite Instability Status. Pathol. Oncol. Res. 2019, 25, 333–340. [Google Scholar] [CrossRef] [PubMed]
  119. Lin, E.I.; Tseng, L.H.; Gocke, C.D.; Reil, S.; Le, D.T.; Azad, N.S.; Eshleman, J.R. Mutational Profiling of Colorectal Cancers with Microsatellite Instability. Oncotarget 2015, 6, 42334–42344. [Google Scholar] [CrossRef]
  120. Andreyev, H.J.N.; Norman, A.R.; Cunningham, D.; Oates, J.; Dix, B.R.; Iacopetta, B.J.; Young, J.; Walsh, T.; Ward, R.; Hawkins, N.; et al. Kirsten Ras Mutations in Patients with Colorectal Cancer: The “RASCAL II” Study. Br. J. Cancer 2001, 85, 692–696. [Google Scholar] [CrossRef]
  121. Venderbosch, S.; Nagtegaal, I.D.; Maughan, T.S.; Smith, C.G.; Cheadle, J.P.; Fisher, D.; Kaplan, R.; Quirke, P.; Seymour, M.T.; Richman, S.D.; 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. Clin. Cancer Res. 2014, 20, 5322–5330. [Google Scholar] [CrossRef]
  122. Salem, M.; Kopetz, S.; El-Refai, S.; Tabernero, J.; Sinicrope, F.; Tie, J.; George, T.; van Cutsem, E.; Mauer, E.; Lonardi, S.; et al. LBA SO-34 Impact of BRAF-V600E Mutation on Immunologic Characteristics of the Tumor Microenvironment (TME) and Associated Genomic Alterations in Patients with Microsatellite Instability-High (MSI-H) or Mismatch-Repair–Deficient (DMMR) Colorectal Cancer (CRC). Ann. Oncol. 2022, 33, S378. [Google Scholar] [CrossRef]
  123. McGivern, A.; Wynter, C.V.A.; Whitehall, V.L.J.; Kambara, T.; Spring, K.J.; Walsh, M.D.; Barker, M.A.; Arnold, S.; Simms, L.A.; Leggett, B.A.; et al. Promoter Hypermethylation Frequency and BRAF Mutations Distinguish Hereditary Non-Polyposis Colon Cancer from Sporadic MSI-H Colon Cancer. Fam. Cancer 2004, 3, 101–107. [Google Scholar] [CrossRef] [PubMed]
  124. Bessa, X.; Ballesté, B.; Andreu, M.; Castells, A.; Bellosillo, B.; Balaguer, F.; Castellví-bel, S.; Paya, A.; Jover, R.; Alenda, C.; et al. A Prospective, Multicenter, Population-Based Study of BRAF Mutational Analysis for Lynch Syndrome Screening. Clin. Gastroenterol. Hepatol. 2008, 6, 206–214. [Google Scholar] [CrossRef]
  125. Porkka, N.; Lahtinen, L.; Ahtiainen, M.; Böhm, J.P.; Kuopio, T.; Eldfors, S.; Mecklin, J.P.; Seppälä, T.T.; Peltomäki, P. Epidemiological, Clinical and Molecular Characterization of Lynch-like Syndrome: A Population-Based Study. Int. J. Cancer 2019, 145, 87–98. [Google Scholar] [CrossRef] [PubMed]
  126. Parsons, M.T.; Buchanan, D.D.; Thompson, B.; Young, J.P.; Spurdle, A.B. Correlation of Tumour BRAF Mutations and MLH1 Methylation with Germline Mismatch Repair (MMR) Gene Mutation Status: A Literature Review Assessing Utility of Tumour Features for MMR Variant Classification. J. Med. Genet. 2012, 49, 151–157. [Google Scholar] [CrossRef] [PubMed]
  127. Kambara, T.; Simms, L.A.; Whitehall, V.L.J.; Spring, K.J.; Wynter, C.V.A.; Walsh, M.D.; Barker, M.A.; Arnold, S.; McGivern, A.; Matsubara, N.; et al. BRAF Mutation Is Associated with DNA Methylation in Serrated Polyps and Cancers of the Colorectum. Gut 2004, 53, 1137–1144. [Google Scholar] [CrossRef] [PubMed]
  128. Weisenberger, D.J.; Siegmund, K.D.; Campan, M.; Young, J.; Long, T.I.; Faasse, M.A.; Kang, G.H.; Widschwendter, M.; Weener, D.; Buchanan, D.; et al. CpG Island Methylator Phenotype Underlies Sporadic Microsatellite Instability and Is Tightly Associated with BRAF Mutation in Colorectal Cancer. Nat. Genet. 2006, 38, 787–793. [Google Scholar] [CrossRef] [PubMed]
  129. Alvi, M.A.; Loughrey, M.B.; Dunne, P.; McQuaid, S.; Turkington, R.; Fuchs, M.A.; McGready, C.; Bingham, V.; Pang, B.; Moore, W.; et al. Molecular Profiling of Signet Ring Cell Colorectal Cancer Provides a Strong Rationale for Genomic Targeted and Immune Checkpoint Inhibitor Therapies. Br. J. Cancer 2017, 117, 203–209. [Google Scholar] [CrossRef]
  130. Fennell, L.J.; Jamieson, S.; McKeone, D.; Corish, T.; Rohdmann, M.; Furner, T.; Bettington, M.; Liu, C.; Kawamata, F.; Bond, C.; et al. MLH1-93 G/a Polymorphism Is Associated with MLH1 Promoter Methylation and Protein Loss in Dysplastic Sessile Serrated Adenomas with BRAFV600E Mutation. BMC Cancer 2018, 18, 35. [Google Scholar] [CrossRef]
  131. Tabernero, J.; Ros, J.; Élez, E. The Evolving Treatment Landscape in BRAF-V600E-Mutated Metastatic Colorectal Cancer. Am. Soc. Clin. Oncol. Educ. Book 2022, 42, 254–263. [Google Scholar] [CrossRef]
  132. Bettington, M.; Walker, N.; Rosty, C.; Brown, I.; Clouston, A.; McKeone, D.; Pearson, S.A.; Leggett, B.; Whitehall, V. Clinicopathological and Molecular Features of Sessile Serrated Adenomas with Dysplasia or Carcinoma. Gut 2017, 66, 97–106. [Google Scholar] [CrossRef]
  133. Bettington, M.L.; Walker, N.I.; Rosty, C.; Brown, I.S.; Clouston, A.D.; McKeone, D.M.; Pearson, S.A.; Klein, K.; Leggett, B.A.; Whitehall, V.L.J. A Clinicopathological and Molecular Analysis of 200 Traditional Serrated Adenomas. Mod. Pathol. 2015, 28, 414–427. [Google Scholar] [CrossRef] [PubMed]
  134. Bell, D.; Berchuck, A.; Birrer, M.; Chien, J.; Cramer, D.W.; Dao, F.; Dhir, R.; Disaia, P.; Gabra, H.; Glenn, P.; et al. Integrated Genomic Analyses of Ovarian Carcinoma. Nature 2011, 474, 609–615. [Google Scholar] [CrossRef]
  135. Weinstein, J.N.; Akbani, R.; Broom, B.M.; Wang, W.; Verhaak, R.G.W.; McConkey, D.; Lerner, S.; Morgan, M.; Creighton, C.J.; Smith, C.; et al. Comprehensive Molecular Characterization of Urothelial Bladder Carcinoma. Nature 2014, 507, 315–322. [Google Scholar] [CrossRef]
  136. Muzny, D.M.; Bainbridge, M.N.; Chang, K.; Dinh, H.H.; Drummond, J.A.; Fowler, G.; Kovar, C.L.; Lewis, L.R.; Morgan, M.B.; Newsham, I.F.; et al. Comprehensive Molecular Characterization of Human Colon and Rectal Cancer. Nature 2012, 487, 330–337. [Google Scholar] [CrossRef]
  137. Wang, Y.K.; Bashashati, A.; Anglesio, M.S.; Cochrane, D.R.; Grewal, D.S.; Ha, G.; McPherson, A.; Horlings, H.M.; Senz, J.; Prentice, L.M.; et al. Genomic Consequences of Aberrant DNA Repair Mechanisms Stratify Ovarian Cancer Histotypes. Nat. Genet. 2017, 49, 856–864. [Google Scholar] [CrossRef]
  138. Wang, J.; Li, R.; He, Y.; Yi, Y.; Wu, H.; Liang, Z. Next-Generation Sequencing Reveals Heterogeneous Genetic Alterations in Key Signaling Pathways of Mismatch Repair Deficient Colorectal Carcinomas. Mod. Pathol. 2020, 33, 2591–2601. [Google Scholar] [CrossRef] [PubMed]
  139. Qiu, M.Z.; He, C.Y.; Yang, X.H.; Yang, L.Q.; Lin, J.Z.; Zhou, D.L.; Long, Y.K.; Guan, W.L.; Jin, Y.; Li, Y.H.; et al. Relationship of HER2 Alteration and Microsatellite Instability Status in Colorectal Adenocarcinoma. Oncologist 2021, 26, e1161–e1170. [Google Scholar] [CrossRef]
  140. Saygin, I.; Cakir, E. The Status of HER2 in Colorectal Carcinoma and the Relation of HER2 with Prognostic Parameters and MSI. Indian J. Pathol. Microbiol. 2022, 65, 336–342. [Google Scholar] [CrossRef]
  141. Engel, C.; Ahadova, A.; Seppälä, T.T.; Aretz, S.; Bigirwamungu-Bargeman, M.; Bläker, H.; Bucksch, K.; Büttner, R.; de Vos tot Nederveen Cappel, W.T.; Endris, V.; et al. Associations of Pathogenic Variants in MLH1, MSH2, and MSH6 With Risk of Colorectal Adenomas and Tumors and With Somatic Mutations in Patients with Lynch Syndrome. Gastroenterology 2020, 158, 1326–1333. [Google Scholar] [CrossRef]
  142. Mäki-Nevala, S.; Valo, S.; Ristimäki, A.; Sarhadi, V.; Knuutila, S.; Nyström, M.; Renkonen-Sinisalo, L.; Lepistö, A.; Mecklin, J.P.; Peltomäki, P. DNA Methylation Changes and Somatic Mutations as Tumorigenic Events in Lynch Syndrome-Associated Adenomas Retaining Mismatch Repair Protein Expression. EBioMedicine 2019, 39, 280–291. [Google Scholar] [CrossRef]
  143. Yurgelun, M.B.; Goel, A.; Hornick, J.L.; Sen, A.; Turgeon, D.K.; Ruffin IV, M.T.; Marcon, N.E.; Baron, J.A.; Bresalier, R.S.; Syngal, S.; et al. Microsatellite Instability and DNA Mismatch Repair Protein Deficiency in Lynch Syndrome Colorectal Polyps. Cancer Prev. Res. 2012, 5, 574–582. [Google Scholar] [CrossRef] [PubMed]
  144. Chang, D.K.; Ricciardiello, L.; Goel, A.; Chang, C.L.; Boland, C.R. Steady-State Regulation of the Human DNA Mismatch Repair System. J. Biol. Chem. 2000, 275, 18424–18431. [Google Scholar] [CrossRef] [PubMed]
  145. Ahadova, A.; Gallon, R.; Gebert, J.; Ballhausen, A.; Endris, V.; Kirchner, M.; Stenzinger, A.; Burn, J.; von Knebel Doeberitz, M.; Bläker, H.; et al. Three Molecular Pathways Model Colorectal Carcinogenesis in Lynch Syndrome. Int. J. Cancer 2018, 143, 139–150. [Google Scholar] [CrossRef] [PubMed]
  146. Stormorken, A.T.; Clark, N.; Grindedal, E.; Mæhle, L.; Møller, P. Prevention of Colorectal Cancer by Colonoscopic Surveillance in Families with Hereditary Colorectal Cancer. Scand. J. Gastroenterol. 2007, 42, 611–617. [Google Scholar] [CrossRef]
  147. Møller, P. The Prospective Lynch Syndrome Database Reports Enable Evidence-Based Personal Precision Health Care. Hered. Cancer Clin. Pract. 2020, 18, 6. [Google Scholar] [CrossRef]
  148. The Cancer Genome Atlas Program—NCI. Available online: (accessed on 10 January 2023).
  149. Salem, M.E.; Bodor, J.N.; Puccini, A.; Xiu, J.; Goldberg, R.M.; Grothey, A.; Korn, W.M.; Shields, A.F.; Worrilow, W.M.; Kim, E.S.; et al. Relationship between MLH1, PMS2, MSH2 and MSH6 Gene-Specific Alterations and Tumor Mutational Burden in 1057 Microsatellite Instability-High Solid Tumors. Int. J. Cancer 2020, 147, 2948–2956. [Google Scholar] [CrossRef]
  150. Goodman, A.M.; Sokol, E.S.; Frampton, G.M.; Lippman, S.M.; Kurzrock, R. Microsatellite-Stable Tumors with High Mutational Burden Benefit from Immunotherapy. Cancer Immunol. Res. 2019, 7, 1570–1573. [Google Scholar] [CrossRef]
  151. Fabrizio, D.A.; George, T.J.; Dunne, R.F.; Frampton, G.; Sun, J.; Gowen, K.; Kennedy, M.; Greenbowe, J.; Schrock, A.B.; Hezel, A.F.; et al. Beyond Microsatellite Testing: Assessment of Tumor Mutational Burden Identifies Subsets of Colorectal Cancer Who May Respond to Immune Checkpoint Inhibition. J. Gastrointest. Oncol. 2018, 9, 610–617. [Google Scholar] [CrossRef]
  152. Lee, S.; Lara, O.; Karpel, H.; Pothuri, B. The Association of Tumor Mutational Burden, Microsatellite Stability, and Mismatch Repair Deficiency in an Endometrial Cancer Patient Cohort (194). Gynecol. Oncol. 2022, 166, S111. [Google Scholar] [CrossRef]
  153. Oaknin, A.; Gilbert, L.; Tinker, A.V.; Brown, J.; Mathews, C.; Press, J.; Sabatier, R.; O’Malley, D.M.; Samouelian, V.; Boni, V.; et al. Safety and Antitumor Activity of Dostarlimab in Patients with Advanced or Recurrent DNA Mismatch Repair Deficient/Microsatellite Instability-High (DMMR/MSI-H) or Proficient/Stable (MMRp/MSS) Endometrial Cancer: Interim Results from GARNET-a Phase I, Single-Arm Study. J. Immunother. Cancer 2022, 10, e003777. [Google Scholar] [CrossRef]
  154. Jones, N.L.; Xiu, J.; Rocconi, R.P.; Herzog, T.J.; Winer, I.S. Immune Checkpoint Expression, Microsatellite Instability, and Mutational Burden: Identifying Immune Biomarker Phenotypes in Uterine Cancer. Gynecol. Oncol. 2020, 156, 393–399. [Google Scholar] [CrossRef] [PubMed]
  155. Cho, J.; Ahn, S.; Son, D.S.; Kim, N.K.D.; Lee, K.W.; Kim, S.; Lee, J.; Park, S.H.; Park, J.O.; Kang, W.K.; et al. Bridging Genomics and Phenomics of Gastric Carcinoma. Int. J. Cancer 2019, 145, 2407–2417. [Google Scholar] [CrossRef] [PubMed]
  156. Müller, M.F.; Ibrahim, A.E.K.; Arends, M.J. Molecular Pathological Classification of Colorectal Cancer. Virchows Arch. 2016, 469, 125–134. [Google Scholar] [CrossRef] [PubMed]
  157. Dienstmann, R.; Vermeulen, L.; Guinney, J.; Kopetz, S.; Tejpar, S.; Tabernero, J. Consensus Molecular Subtypes and the Evolution of Precision Medicine in Colorectal Cancer. Nat. Rev. Cancer 2017, 17, 79–92. [Google Scholar] [CrossRef] [PubMed]
  158. Włodarczyk, M.; Włodarczyk, J.; Siwiński, P.; Sobolewska-Włodarczyk, A.; Fichna, J. Genetic Molecular Subtypes in Optimizing Personalized Therapy for Metastatic Colorectal Cancer. Curr. Drug Targets 2018, 19, 1731–1737. [Google Scholar] [CrossRef] [PubMed]
  159. Nguyen, L.H.; Goel, A.; Chung, D.C. Pathways of Colorectal Carcinogenesis. Gastroenterology 2020, 158, 291–302. [Google Scholar] [CrossRef]
  160. Salem, M.E.; Xiu, J.; Lenz, H.-J.; Atkins, M.B.; Philip, P.A.; Hwang, J.J.; Gatalica, Z.; Xiao, N.; Gibney, G.T.; El-Deiry, W.S.; et al. Characterization of Tumor Mutation Load (TML) in Solid Tumors. J. Clin. Oncol. 2017, 35, 11517. [Google Scholar] [CrossRef]
  161. Salem, M.E.; Puccini, A.; Grothey, A.; Raghavan, D.; Goldberg, R.M.; Xiu, J.; Michael Korn, W.; Weinberg, B.A.; Hwang, J.J.; Shields, A.F.; et al. Landscape of Tumor Mutation Load, Mismatch Repair Deficiency, and PD-L1 Expression in a Large Patient Cohort of Gastrointestinal Cancers. Mol. Cancer Res. 2018, 16, 805–812. [Google Scholar] [CrossRef]
  162. Kumar, S. A Perfect Biomarker for Immune Checkpoint Inhibition—An Elusive Goal? Cancer Res. Stat. Treat. 2021, 4, 594–595. [Google Scholar]
  163. Grossman, J.E.; Vasudevan, D.; Joyce, C.E.; Hildago, M. Is PD-L1 a Consistent Biomarker for Anti-PD-1 Therapy? The Model of Balstilimab in a Virally-Driven Tumor. Oncogene 2021, 40, 1393–1395. [Google Scholar] [CrossRef]
  164. Marabelle, A.; Fakih, M.; Lopez, J.; Shah, M.; Shapira-Frommer, R.; Nakagawa, K.; Chung, H.C.; Kindler, H.L.; Lopez-Martin, J.A.; Miller, W.H.; et al. Association of Tumour Mutational Burden with Outcomes in Patients with Advanced Solid Tumours Treated with Pembrolizumab: Prospective Biomarker Analysis of the Multicohort, Open-Label, Phase 2 KEYNOTE-158 Study. Lancet Oncol. 2020, 21, 1353–1365. [Google Scholar] [CrossRef] [PubMed]
  165. Dong, H.; Strome, S.E.; Salomao, D.R.; Tamura, H.; Hirano, F.; Flies, D.B.; Roche, P.C.; Lu, J.; Zhu, G.; Tamada, K.; et al. Tumor-Associated B7-H1 Promotes T-Cell Apoptosis: A Potential Mechanism of Immune Evasion. Nat. Med. 2002, 8, 793–800. [Google Scholar] [CrossRef] [PubMed]
  166. Kim, T.K.; Vandsemb, E.N.; Herbst, R.S.; Chen, L. Adaptive Immune Resistance at the Tumour Site: Mechanisms and Therapeutic Opportunities. Nat. Rev. Drug Discov. 2022, 21, 529–540. [Google Scholar] [CrossRef] [PubMed]
  167. Weber, J.S.; Kähler, K.C.; Hauschild, A. Management of Immune-Related Adverse Events and Kinetics of Response with Ipilimumab. J. Clin. Oncol. 2012, 30, 2691–2697. [Google Scholar] [CrossRef] [PubMed]
  168. Tivol, E.A.; Borriello, F.; Schweitzer, A.N.; Lynch, W.P.; Bluestone, J.A.; Sharpe, A.H. Loss of CTLA-4 Leads to Massive Lymphoproliferation and Fatal Multiorgan Tissue Destruction, Revealing a Critical Negative Regulatory Role of CTLA-4. Immunity 1995, 3, 541–547. [Google Scholar] [CrossRef] [PubMed]
  169. Chalmers, Z.R.; Connelly, C.F.; Fabrizio, D.; Gay, L.; Ali, S.M.; Ennis, R.; Schrock, A.; Campbell, B.; Shlien, A.; Chmielecki, J.; et al. Analysis of 100,000 Human Cancer Genomes Reveals the Landscape of Tumor Mutational Burden. Genome Med. 2017, 9, 34. [Google Scholar] [CrossRef]
  170. Mandal, R.; Samstein, R.M.; Lee, K.W.; Havel, J.J.; Wang, H.; Krishna, C.; Sabio, E.Y.; Makarov, V.; Kuo, F.; Blecua, P.; et al. Genetic Diversity of Tumors with Mismatch Repair Deficiency Influences Anti-PD-1 Immunotherapy Response. Science 2019, 364, 485–491. [Google Scholar] [CrossRef]
  171. Turajlic, S.; Litchfield, K.; Xu, H.; Rosenthal, R.; McGranahan, N.; Reading, J.L.; Wong, Y.N.S.; Rowan, A.; Kanu, N.; al Bakir, M.; et al. Insertion-and-Deletion-Derived Tumour-Specific Neoantigens and the Immunogenic Phenotype: A Pan-Cancer Analysis. Lancet Oncol. 2017, 18, 1009–1021. [Google Scholar] [CrossRef]
  172. Sena, L.A.; Fountain, J.; Isaacsson Velho, P.; Lim, S.J.; Wang, H.; Nizialek, E.; Rathi, N.; Nussenzveig, R.; Maughan, B.L.; Velez, M.G.; et al. Tumor Frameshift Mutation Proportion Predicts Response to Immunotherapy in Mismatch Repair-Deficient Prostate Cancer. Oncologist 2021, 26, e270–e278. [Google Scholar] [CrossRef]
  173. Schiappacasse Cocio, G.V.; Schiappacasse, E.D. Is Adjuvant Chemotherapy Efficient in Colon Cancer with High Microsatellite Instability? A Look Towards the Future. Cancer Res. 2019, 79, 441–444. [Google Scholar] [CrossRef]
  174. des Guetz, G.; des Guetz, G.; Lecaille, C.; Mariani, P.; Bennamoun, M.; Uzzan, B.; Nicolas, P.; Boisseau, A.; Sastre, X.; Cucherousset, J.; et al. Prognostic Impact of Microsatellite Instability in Colorectal Cancer Patients Treated with Adjuvant FOLFOX. Anticancer Res. 2010, 30, 4297–4302. [Google Scholar] [PubMed]
  175. Vasen, H.F.A.; Blanco, I.; Aktan-Collan, K.; Gopie, J.P.; Alonso, A.; Aretz, S.; Bernstein, I.; Bertario, L.; Burn, J.; Capella, G.; et al. Revised Guidelines for the Clinical Management of Lynch Syndrome (HNPCC): Recommendations by a Group of European Experts. Gut 2013, 62, 812–823. [Google Scholar] [CrossRef]
  176. Popat, S.; Hubner, R.; Houlston, R.S. Systematic Review of Microsatellite Instability and Colorectal Cancer Prognosis. J. Clin. Oncol. 2005, 23, 609–618. [Google Scholar] [CrossRef] [PubMed]
  177. Cohen, R.; Taieb, J.; Fiskum, J.; Yothers, G.; Goldberg, R.; Yoshino, T.; Alberts, S.; Allegra, C.; de Gramont, A.; Seitz, J.F.; et al. Microsatellite Instability in Patients with Stage III Colon Cancer Receiving Fluoropyrimidine with or without Oxaliplatin: An ACCENT Pooled Analysis of 12 Adjuvant Trials. J. Clin. Oncol. 2021, 39, 642–651. [Google Scholar] [CrossRef] [PubMed]
  178. Sinicrope, F.A.; Chakrabarti, S.; Laurent-Puig, P.; Huebner, L.; Smyrk, T.C.; Tabernero, J.; Mini, E.; Goldberg, R.M.; Zaanan, A.; Folprecht, G.; et al. Prognostic Variables in Low and High Risk Stage III Colon Cancers Treated in Two Adjuvant Chemotherapy Trials. Eur. J. Cancer 2021, 144, 101–112. [Google Scholar] [CrossRef] [PubMed]
  179. Bertagnolli, M.M.; Niedzwiecki, D.; Compton, C.C.; Hahn, H.P.; Hall, M.; Damas, B.; Jewell, S.D.; Mayer, R.J.; Goldberg, R.M.; Saltz, L.B.; et al. Microsatellite Instability Predicts Improved Response to Adjuvant Therapy with Irinotecan, Fluorouracil, and Leucovorin in Stage III Colon Cancer: Cancer and Leukemia Group B Protocol 89803. J. Clin. Oncol 2009, 27, 1814–1821. [Google Scholar] [CrossRef] [PubMed]
  180. Fallik, D.; Borrini, F.; Boige, V.; Viguier, J.; Jacob, S.; Miquel, C.; Sabourin, J.-C.; Ducreux, M.; Praz, F. Microsatellite Instability Is a Predictive Factor of the Tumor Response to Irinotecan in Patients with Advanced Colorectal Cancer. Cancer Res. 2003, 63, 5738–5744. [Google Scholar] [PubMed]
  181. Tajima, A.; Hess, M.T.; Cabrera, B.L.; Kolodner, R.D.; Carethers, J.M. The Mismatch Repair Complex HMutSα Recognizes 5-Fluorouracil-Modified DNA: Implications for Chemosensitivity and Resistance. Gastroenterology 2004, 127, 1678–1684. [Google Scholar] [CrossRef]
  182. Jover, R.; Zapater, P.; Castells, A.; Llor, X.; Andreu, M.; Cubiella, J.; Piñol, V.; Xicola, R.M.; Bujanda, L.; Reñé, J.M.; et al. Mismatch Repair Status in the Prediction of Benefit from Adjuvant Fluorouracil Chemotherapy in Colorectal Cancer. Gut 2006, 55, 848–855. [Google Scholar] [CrossRef]
  183. Hutchins, G.; Southward, K.; Handley, K.; Magill, L.; Beaumont, C.; Stahlschmidt, J.; Richman, S.; Chambers, P.; Seymour, M.; Kerr, D.; et al. Value of Mismatch Repair, KRAS, and BRAF Mutations in Predicting Recurrence and Benefits from Chemotherapy in Colorectal Cancer. J. Clin. Oncol. 2011, 29, 1261–1270. [Google Scholar] [CrossRef]
  184. Klingbiel, D.; Saridaki, Z.; Roth, A.D.; Bosman, F.T.; Delorenzi, M.; Tejpar, S. Prognosis of Stage II and III Colon Cancer Treated with Adjuvant 5-Fluorouracil or FOLFIRI in Relation to Microsatellite Status: Results of the PETACC-3 Trial. Ann. Oncol. 2015, 26, 126–132. [Google Scholar] [CrossRef] [PubMed]
  185. Ribic, C.M.; Sargent, D.J.; Moore, M.J.; Thibodeau, S.N.; French, A.J.; Goldberg, R.M.; Hamilton, S.R.; Laurent-Puig, P.; Gryfe, R.; Shepherd, L.E.; et al. Tumor Microsatellite-Instability Status as a Predictor of Benefit from Fluorouracil-Based Adjuvant Chemotherapy for Colon Cancer. N. Engl. J. Med. 2003, 349, 247–257. [Google Scholar] [CrossRef] [PubMed]
  186. Gavin, P.G.; Colangelo, L.H.; Fumagalli, D.; Tanaka, N.; Remillard, M.Y.; Yothers, G.; Kim, C.; Taniyama, Y.; Kim, S.I.; Choi, H.J.; et al. Mutation Profiling and Microsatellite Instability in Stage II and III Colon Cancer: An Assessment of Their Prognostic and Oxaliplatin Predictive Value. Clin. Cancer Res. 2012, 18, 6531–6541. [Google Scholar] [CrossRef] [PubMed]
  187. Kim, J.E.; Hong, Y.S.; Kim, H.J.; Kim, K.P.; Kim, S.Y.; Lim, S.B.; Park, I.J.; Kim, C.W.; Yoon, Y.S.; Yu, C.S.; et al. Microsatellite Instability Was Not Associated with Survival in Stage III Colon Cancer Treated with Adjuvant Chemotherapy of Oxaliplatin and Infusional 5-Fluorouracil and Leucovorin (FOLFOX). Ann. Surg. Oncol. 2017, 24, 1289–1294. [Google Scholar] [CrossRef]
  188. Jover, R.; Zapater, P.; Castells, A.; Llor, X.; Andreu, M.; Cubiella, J.; Balaguer, F.; Sempere, L.; Xicola, R.M.; Bujanda, L.; et al. The Efficacy of Adjuvant Chemotherapy with 5-Fluorouracil in Colorectal Cancer Depends on the Mismatch Repair Status. Eur. J. Cancer 2009, 45, 365–373. [Google Scholar] [CrossRef]
  189. Kim, G.P.; Colangelo, L.H.; Wieand, H.S.; Paik, S.; Kirsch, I.R.; Wolmark, N.; Allegra, C.J. Prognostic and Predictive Roles of High-Degree Microsatellite Instability in Colon Cancer: A National Cancer Institute-National Surgical Adjuvant Breast and Bowel Project Collaborative Study. J. Clin. Oncol. 2007, 25, 767–772. [Google Scholar] [CrossRef]
  190. Sargent, D.J.; Marsoni, S.; Monges, G.; Thibodeau, S.N.; Labianca, R.; Hamilton, S.R.; French, A.J.; Kabat, B.; Foster, N.R.; Torri, V.; et al. Defective Mismatch Repair as a Predictive Marker for Lack of Efficacy of Fluorouracil-Based Adjuvant Therapy in Colon Cancer. J. Clin. Oncol. 2010, 28, 3219–3226. [Google Scholar] [CrossRef]
  191. Innocenti, F.; Ou, F.S.; Qu, X.; Zemla, T.J.; Niedzwiecki, D.; Tam, R.; Mahajan, S.; Goldberg, R.M.; Bertagnolli, M.M.; Blanke, C.D.; et al. Mutational Analysis of Patients with Colorectal Cancer in CALGB/SWOG 80405 Identifies New Roles of Microsatellite Instability and Tumor Mutational Burden for Patient Outcome. J. Clin. Oncol. 2019, 37, 1217–1227. [Google Scholar] [CrossRef]
  192. U.S. Food and Drug Administration Website. JEMPERLI (Dostarlimab-Gxly). Available online: (accessed on 7 February 2023).
  193. Andre, T.; Berton, D.; Curigliano, G.; Jimenez-Rodriguez, B.; Ellard, S.; Gravina, A.; Miller, R.; Tinker, A.; Jewell, A.; Pikiel, J.; et al. Efficacy and Safety of Dostarlimab in Patients (Pts) with Mismatch Repair Deficient (DMMR) Solid Tumors: Analysis of 2 Cohorts in the GARNET Study. J. Clin. Oncol. 2022, 40, 2587. [Google Scholar] [CrossRef]
  194. Lipson, E.J.; Sharfman, W.H.; Drake, C.G.; Wollner, I.; Taube, J.M.; Anders, R.A.; Xu, H.; Yao, S.; Pons, A.; Chen, L.; et al. Durable Cancer Regression Off-Treatment and Effective Reinduction Therapy with an Anti-PD-1 Antibody. Clin. Cancer Res. 2013, 19, 462–468. [Google Scholar] [CrossRef]
  195. Le, D.T.; Uram, J.N.; Wang, H.; Bartlett, B.R.; Kemberling, H.; Eyring, A.D.; Skora, A.D.; Luber, B.S.; Azad, N.S.; Laheru, D.; et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N. Engl. J. Med. 2015, 372, 2509–2520. [Google Scholar] [CrossRef] [PubMed]
  196. Diaz, L.A.; Shiu, K.K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab versus Chemotherapy for Microsatellite Instability-High or Mismatch Repair-Deficient Metastatic Colorectal Cancer (KEYNOTE-177): Final Analysis of a Randomised, Open-Label, Phase 3 Study. Lancet Oncol. 2022, 23, 659–670. [Google Scholar] [CrossRef] [PubMed]
  197. André, T.; Shiu, K.-K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab in Microsatellite-Instability-High Advanced Colorectal Cancer. N. Engl. J. Med. 2020, 383, 2207–2218. [Google Scholar] [CrossRef] [PubMed]
  198. Casak, S.J.; Marcus, L.; Fashoyin-Aje, L.; Mushti, S.L.; Cheng, J.; Shen, Y.L.; Pierce, W.F.; Her, L.; Goldberg, K.B.; Theoret, M.R.; et al. FDA Approval Summary: Pembrolizumab for the First-Line Treatment of Patients with MSI-H/DMMR Advanced Unresectable or Metastatic Colorectal Carcinoma. Clin. Cancer Res. 2021, 27, 4680–4684. [Google Scholar] [CrossRef] [PubMed]
  199. Ludford, K.; Ho, W.J.; Thomas, J.V.; Raghav, K.P.S.; Murphy, M.B.; Fleming, N.D.; Lee, M.S.; Smaglo, B.G.; You, Y.N.; Tillman, M.M.; et al. Neoadjuvant Pembrolizumab in Localized Microsatellite Instability High/Deficient Mismatch Repair Solid Tumors. J. Clin. Oncol. 2023, JCO2201351. [Google Scholar] [CrossRef] [PubMed]
  200. Overman, M.J.; Lonardi, S.; Wong, K.Y.M.; Lenz, H.J.; Gelsomino, F.; Aglietta, M.; Morse, M.A.; van Cutsem, E.; McDermott, R.; Hill, A.; et al. Durable Clinical Benefit with Nivolumab Plus Ipilimumab in DNA Mismatch Repair-Deficient/Microsatellite Instability-High Metastatic Colorectal Cancer. J. Clin. Oncol. 2018, 36, 773–779. [Google Scholar] [CrossRef]
  201. Overman, M.J.; McDermott, R.; Leach, J.L.; Lonardi, S.; Lenz, H.J.; Morse, M.A.; Desai, J.; Hill, A.; Axelson, M.; Moss, R.A.; et al. Nivolumab in Patients with Metastatic DNA Mismatch Repair-Deficient or Microsatellite Instability-High Colorectal Cancer (CheckMate 142): An Open-Label, Multicentre, Phase 2 Study. Lancet Oncol. 2017, 18, 1182–1191. [Google Scholar] [CrossRef]
  202. Overman, M.J.; Bergamo, F.; McDermott, R.S.; Aglietta, M.; Chen, F.; Gelsomino, F.; Wong, M.; Morse, M.; van Cutsem, E.; Hendlisz, A.; et al. Nivolumab in Patients with DNA Mismatch Repair-Deficient/Microsatellite Instability-High (DMMR/MSI-H) Metastatic Colorectal Cancer (MCRC): Long-Term Survival According to Prior Line of Treatment from CheckMate-142. J. Clin. Oncol. 2018, 36, 554. [Google Scholar] [CrossRef]
  203. André, T.; Lonardi, S.; Wong, K.Y.M.; Lenz, H.J.; Gelsomino, F.; Aglietta, M.; Morse, M.A.; van Cutsem, E.; McDermott, R.; Hill, A.; et al. Nivolumab plus Low-Dose Ipilimumab in Previously Treated Patients with Microsatellite Instability-High/Mismatch Repair-Deficient Metastatic Colorectal Cancer: 4-Year Follow-up from CheckMate 142. Ann. Oncol. 2022, 33, 1052–1060. [Google Scholar] [CrossRef]
  204. Cohen, R.; Meurisse, A.; Pudlarz, T.; Bennouna, J.; Tournigand, C.; la Fouchardiere, C.D.; Tougeron, D.; Borg, C.; Mazard, T.; Chibaudel, B.; et al. One-Year Duration of Nivolumab plus Ipilimumab in Patients (Pts) with Microsatellite Instability-High/Mismatch Repair-Deficient (MSI/DMMR) Metastatic Colorectal Cancer (MCRC): Long-Term Follow-up of the GERCOR NIPICOL Phase II Study. J. Clin. Oncol. 2022, 40, 13. [Google Scholar] [CrossRef]
  205. Chalabi, M.; Fanchi, L.F.; Dijkstra, K.K.; van den Berg, J.G.; Aalbers, A.G.; Sikorska, K.; Lopez-Yurda, M.; Grootscholten, C.; Beets, G.L.; Snaebjornsson, P.; et al. Neoadjuvant Immunotherapy Leads to Pathological Responses in MMR-Proficient and MMR-Deficient Early-Stage Colon Cancers. Nat. Med. 2020, 26, 566. [Google Scholar] [CrossRef] [PubMed]
  206. Verschoor, Y.L.; van den Berg, J.; Beets, G.; Sikorska, K.; Aalbers, A.; van Lent, A.; Grootscholten, C.; Huibregtse, I.; Marsman, H.; Oosterling, S.; et al. Neoadjuvant Nivolumab, Ipilimumab, and Celecoxib in MMR-Proficient and MMR-Deficient Colon Cancers: Final Clinical Analysis of the NICHE Study. J. Clin. Oncol. 2022, 40, 3511. [Google Scholar] [CrossRef]
  207. Chalabi, M.; Verschoor, Y.L.; van den Berg, J.; Sikorska, K.; Beets, G.; Lent, A.V.; Grootscholten, M.C.; Aalbers, A.; Buller, N.; Marsman, H.; et al. LBA7 Neoadjuvant Immune Checkpoint Inhibition in Locally Advanced MMR-Deficient Colon Cancer: The NICHE-2 Study. Ann. Oncol. 2022, 33, S1389. [Google Scholar] [CrossRef]
  208. Andre, T.; Berton, D.; Curigliano, G.; Ellard, S.; Pérez, J.M.T.; Arkenau, H.-T.; Abdeddaim, C.; Moreno, V.; Guo, W.; Im, E.; et al. Safety and Efficacy of Anti–PD-1 Antibody Dostarlimab in Patients (Pts) with Mismatch Repair-Deficient (DMMR) Solid Cancers: Results from GARNET Study. J. Clin. Oncol. 2021, 39, 9. [Google Scholar] [CrossRef]
  209. Andre, T.; de Braud, F.G.; Jimenez-Rodriguez, B.; Berton, D.; Curigliano, G.; Arkenau, T.; Torres, A.A.; Paez, D.; Ellard, S.; Abdeddaim, C.; et al. Antitumor Activity and Safety of Dostarlimab Monotherapy in Patients with Mismatch Repair Deficient Non-Endometrial Solid Tumors: A Post-Hoc Subgroup Analysis of Patients with Colorectal Cancer. J. Clin. Oncol. 2022, 40, 201. [Google Scholar] [CrossRef]
  210. Taieb, J.; Bouche, O.; André, T.; Barbier, E.; Laurent-Puig, P.; Bez, J.; Toullec, C.; Borg, C.; Randrian, V.; Evesque, L.; et al. Avelumab versus Standard Second-Line Treatment Chemotherapy in Metastatic Colorectal Cancer (MCRC) Patients with Microsatellite Instability (MSI): The SAMCO-PRODIGE 54 Randomised Phase II Trial. Ann. Oncol. 2022, 22, S808–S869. [Google Scholar] [CrossRef]
  211. Tintelnot, J.; Ristow, I.; Sauer, M.; Simnica, D.; Schultheiß, C.; Scholz, R.; Goekkurt, E.; von Wenserski, L.; Willscher, E.; Paschold, L.; et al. Translational Analysis and Final Efficacy of the AVETUX Trial—Avelumab, Cetuximab and FOLFOX in Metastatic Colorectal Cancer. Front. Oncol. 2022, 12, 993611. [Google Scholar] [CrossRef]
  212. Stein, A.; Binder, M.; Goekkurt, E.; Lorenzen, S.; Riera-Knorrenschild, J.; Depenbusch, R.; Ettrich, T.J.; Doerfel, S.; Al-Batran, S.-E.; Karthaus, M.; et al. Avelumab and Cetuximab in Combination with FOLFOX in Patients with Previously Untreated Metastatic Colorectal Cancer (MCRC): Final Results of the Phase II AVETUX Trial (AIO-KRK-0216). J. Clin. Oncol. 2020, 38, 96. [Google Scholar] [CrossRef]
  213. Segal, N.H.; Wainberg, Z.A.; Overman, M.J.; Ascierto, P.A.; Arkenau, H.-T.; Butler, M.O.; Eder, J.P.; Keilholz, U.; Kim, D.-W.; Cunningham, D.; et al. Safety and Clinical Activity of Durvalumab Monotherapy in Patients with Microsatellite Instability–High (MSI-H) Tumors. J. Clin. Oncol. 2019, 37, 670. [Google Scholar] [CrossRef]
  214. Oh, C.R.; Kim, J.E.; Hong, Y.S.; Kim, S.Y.; Ahn, J.B.; Baek, J.Y.; Lee, M.A.; Kang, M.J.; Cho, S.H.; Beom, S.H.; et al. Phase II Study of Durvalumab Monotherapy in Patients with Previously Treated Microsatellite Instability-High/Mismatch Repair-Deficient or POLE-Mutated Metastatic or Unresectable Colorectal Cancer. Int. J. Cancer 2022, 150, 2038–2045. [Google Scholar] [CrossRef]
  215. McGregor, M.; Price, T.J. IMblaze 370: Lessons Learned and Future Strategies in Colorectal Cancer Treatment. Ann. Transl. Med. 2019, 7, 602. [Google Scholar] [CrossRef] [PubMed]
  216. Friedman, C.F.; Hainsworth, J.D.; Kurzrock, R.; Spigel, D.R.; Burris, H.A.; Sweeney, C.J.; Meric-Bernstam, F.; Wang, Y.; Levy, J.; Grindheim, J.; et al. Atezolizumab Treatment of Tumors with High Tumor Mutational Burden from MyPathway, a Multicenter, Open-Label, Phase IIa Multiple Basket Study. Cancer Discov. 2022, 12, 654–669. [Google Scholar] [CrossRef] [PubMed]
  217. Bever, K.; Wang, H.; Durham, J.; Apostol, C.; Azad, N.; Browner, I.; Gaillard, S.; Laheru, D.; Lee, V.; Sharfman, W.; et al. 711 Interim Results of a Phase 2 Study of Nivolumab and Relatlimab in Advanced Mismatch Repair Deficient (DMMR) Cancers Resistant to Prior PD-(L)1 Inhibition. J. Immunother. Cancer 2022, 10, A743. [Google Scholar] [CrossRef]
  218. Hervieu, A.; Guigay, J.; Borcoman, E.; Lavaud, P.; Coquan, E.; Frenel, J.-S.; de La Motte Rouge, T.; Augereau, P.; Cropet, C.; Legrand, F.; et al. 478P Metronomic Oral Vinorelbine (MOV) Combined with Tremelimumab (T) + Durvalumab (D): Results of the Tumor Mutational Burden-High (TMB-h) and/or Microsatellite Instability-High (MSI-h) Cohort of the MOVIE Study. Ann. Oncol. 2022, 33, S758–S759. [Google Scholar] [CrossRef]
  219. Therkildsen, C.; Jensen, L.H.; Rasmussen, M.; Bernstein, I. An Update on Immune Checkpoint Therapy for the Treatment of Lynch Syndrome. Clin. Exp. Gastroenterol. 2021, 14, 181–197. [Google Scholar] [CrossRef]
  220. O’Malley, D.M.; Bariani, G.M.; Cassier, P.A.; Marabelle, A.; Hansen, A.R.; de Jesus Acosta, A.; Miller, W.H.; Safra, T.; Italiano, A.; Mileshkin, L.; et al. Pembrolizumab in Patients with Microsatellite Instability–High Advanced Endometrial Cancer: Results from the KEYNOTE-158 Study. J. Clin. Oncol. 2022, 40, 752–761. [Google Scholar] [CrossRef]
  221. Makker, V.; Colombo, N.; Casado Herráez, A.; Santin, A.D.; Colomba, E.; Miller, D.S.; Fujiwara, K.; Pignata, S.; Baron-Hay, S.; Ray-Coquard, I.; et al. Lenvatinib plus Pembrolizumab for Advanced Endometrial Cancer. New Engl. J. Med. 2022, 386, 437–448. [Google Scholar] [CrossRef]
  222. Oaknin, A.; Pothuri, B.; Gilbert, L.; Sabatier, R.; Ghamande, S.A.; Gravina, A.; Calvo, E.; Banerjee, S.N.; Miller, R.; Pikiel, J.; et al. Dostarlimab in Advanced/Recurrent (AR) Mismatch Repair Deficient/Microsatellite Instability–High or Proficient/Stable (DMMR/MSI-H or MMRp/MSS) Endometrial Cancer (EC): The GARNET Study. J. Clin. Oncol. 2022, 40, 5509. [Google Scholar] [CrossRef]
  223. Chao, J.; Fuchs, C.S.; Shitara, K.; Tabernero, J.; Muro, K.; van Cutsem, E.; Bang, Y.J.; de Vita, F.; Landers, G.; Yen, C.J.; et al. Assessment of Pembrolizumab Therapy for the Treatment of Microsatellite Instability-High Gastric or Gastroesophageal Junction Cancer Among Patients in the KEYNOTE-059, KEYNOTE-061, and KEYNOTE-062 Clinical Trials. JAMA Oncol. 2021, 7, 895–902. [Google Scholar] [CrossRef]
  224. André, T.; Tougeron, D.; Piessen, G.; de La Fouchardière, C.; Louvet, C.; Adenis, A.; Jary, M.; Tournigand, C.; Aparicio, T.; Desrame, J.; et al. Neoadjuvant Nivolumab Plus Ipilimumab and Adjuvant Nivolumab in Localized Deficient Mismatch Repair/Microsatellite Instability-High Gastric or Esophagogastric Junction Adenocarcinoma: The GERCOR NEONIPIGA Phase II Study. J. Clin. Oncol. 2023, 41, 255–265. [Google Scholar] [CrossRef]
  225. Versluis, J.M.; Long, G.V.; Blank, C.U. Learning from Clinical Trials of Neoadjuvant Checkpoint Blockade. Nat. Med. 2020, 26, 475–484. [Google Scholar] [CrossRef] [PubMed]
  226. Liu, J.; Blake, S.J.; Yong, M.C.R.; Harjunpää, H.; Ngiow, S.F.; Takeda, K.; Young, A.; O’Donnell, J.S.; Allen, S.; Smyth, M.J.; et al. Improved Efficacy of Neoadjuvant Compared to Adjuvant Immunotherapy to Eradicate Metastatic Disease. Cancer Discov. 2016, 6, 1382–1399. [Google Scholar] [CrossRef] [PubMed]
  227. Blank, C.U.; Rozeman, E.A.; Fanchi, L.F.; Sikorska, K.; van de Wiel, B.; Kvistborg, P.; Krijgsman, O.; van den Braber, M.; Philips, D.; Broeks, A.; et al. Neoadjuvant versus Adjuvant Ipilimumab plus Nivolumab in Macroscopic Stage III Melanoma. Nat. Med. 2018, 24, 1655–1661. [Google Scholar] [CrossRef] [PubMed]
  228. Versluis, J.M.; Reijers, I.L.M.; Rozeman, E.A.; Sikorska, K.; van Houdt, W.J.; van Thienen, J.V.; Adriaansz, S.A.; Mallo, H.; van Tinteren, H.; van de Wiel, B.A.; et al. 4-Year Relapse-Free Survival (RFS), Overall Survival (OS) and Long-Term Toxicity of (Neo)Adjuvant Ipilimumab (IPI) + Nivolumab (NIVO) in Macroscopic Stage III Melanoma: OpACIN Trial. Ann. Oncol. 2020, 31, S742–S743. [Google Scholar] [CrossRef]
  229. Patel, S.P.; Othus, M.; Chen, Y.; Wright, G.P.; Yost, K.J.; Hyngstrom, J.R.; Hu-Lieskovan, S.; Lao, C.D.; Fecher, L.A.; Truong, T.-G.; et al. Neoadjuvant-Adjuvant or Adjuvant-Only Pembrolizumab in Advanced Melanoma. N. Engl. J. Med. 2023, 388, 813–823. [Google Scholar] [CrossRef]
  230. Lau, D.; Kalaitzaki, E.; Church, D.N.; Pandha, H.; Tomlinson, I.; Annels, N.; Gerlinger, M.; Sclafani, F.; Smith, G.; Begum, R.; et al. Rationale and Design of the POLEM Trial: Avelumab plus Fluoropyrimidine-Based Chemotherapy as Adjuvant Treatment for Stage III Mismatch Repair Deficient or POLE Exonuclease Domain Mutant Colon Cancer: A Phase III Randomised Study. ESMO Open 2020, 5, e000638. [Google Scholar] [CrossRef]
  231. Sinicrope, F.A.; Ou, F.-S.; Zemla, T.; Nixon, A.B.; Mody, K.; Levasseur, A.; Dueck, A.C.; Dhanarajan, A.R.; Lieu, C.H.; Cohen, D.J.; et al. Randomized Trial of Standard Chemotherapy Alone or Combined with Atezolizumab as Adjuvant Therapy for Patients with Stage III Colon Cancer and Deficient Mismatch Repair (ATOMIC, Alliance A021502). J. Clin. Oncol. 2019, 37, e15169. [Google Scholar] [CrossRef]
  232. ClinicalTrials.Gov. Avelumab Plus 5-FU Based Chemotherapy as Adjuvant Treatment for Stage 3 MSI-High or POLE Mutant Colon Cancer—Full Text View. Available online: (accessed on 3 April 2023).
  233. Le, D.T.; Kim, T.W.; van Cutsem, E.; Geva, R.; Jäger, D.; Hara, H.; Burge, M.; O’Neil, B.; Kavan, P.; Yoshino, T.; et al. Phase II Open-Label Study of Pembrolizumab in Treatment-Refractory, Microsatellite Instability-High/Mismatch Repair-Deficient Metastatic Colorectal Cancer: KEYNOTE-164. J. Clin. Oncol. 2020, 38, 11–19. [Google Scholar] [CrossRef]
  234. Cohen, R.; Bennouna, J.; Meurisse, A.; Tournigand, C.; de La Fouchardière, C.; Tougeron, D.; Borg, C.; Mazard, T.; Chibaudel, B.; Garcia-Larnicol, M.L.; et al. RECIST and IRECIST Criteria for the Evaluation of Nivolumab plus Ipilimumab in Patients with Microsatellite Instability-High/Mismatch Repair-Deficient Metastatic Colorectal Cancer: The GERCOR NIPICOL Phase II Study. J. Immunother. Cancer 2020, 8, e001499. [Google Scholar] [CrossRef]
  235. Sahin, I.H.; Goyal, S.; Pumpalova, Y.; Sonbol, M.B.; Das, S.; Haraldsdottir, S.; Ahn, D.; Ciombor, K.K.; Chen, Z.; Draper, A.; et al. Mismatch Repair (MMR) Gene Alteration and BRAF V600E Mutation Are Potential Predictive Biomarkers of Immune Checkpoint Inhibitors in MMR-Deficient Colorectal Cancer. Oncologist 2021, 26, 668. [Google Scholar] [CrossRef]
  236. Park, R.; da Silva, L.L.; Lee, S.; Saeed, A. Impact of BRAF Mutations on Prognosis and Immunotherapy Response in Microsatellite Instability/Mismatch Repair Deficient Metastatic Colorectal Cancer: A Systematic Review and Meta-Analysis. J. Clin. Oncol. 2021, 39, 3557. [Google Scholar] [CrossRef]
  237. Schrock, A.B.; Ouyang, C.; Sandhu, J.; Sokol, E.; Jin, D.; Ross, J.S.; Miller, V.A.; Lim, D.; Amanam, I.; Chao, J.; et al. Tumor Mutational Burden Is Predictive of Response to Immune Checkpoint Inhibitors in MSI-High Metastatic Colorectal Cancer. Ann. Oncol. 2019, 30, 1096–1103. [Google Scholar] [CrossRef] [PubMed]
  238. Chida, K.; Kawazoe, A.; Kawazu, M.; Suzuki, T.; Nakamura, Y.; Nakatsura, T.; Kuwata, T.; Ueno, T.; Kuboki, Y.; Kotani, D.; et al. A Low Tumor Mutational Burden and PTEN Mutations Are Predictors of a Negative Response to PD-1 Blockade in MSI-H/DMMR Gastrointestinal Tumors. Clin. Cancer Res. 2021, 27, 3714–3724. [Google Scholar] [CrossRef]
  239. Loupakis, F.; Depetris, I.; Biason, P.; Intini, R.; Prete, A.A.; Leone, F.; Lombardi, P.; Filippi, R.; Spallanzani, A.; Cascinu, S.; et al. Prediction of Benefit from Checkpoint Inhibitors in Mismatch Repair Deficient Metastatic Colorectal Cancer: Role of Tumor Infiltrating Lymphocytes. Oncologist 2020, 25, 481–487. [Google Scholar] [CrossRef] [PubMed]
  240. Xiao, J.; Li, W.; Huang, Y.; Huang, M.; Li, S.; Zhai, X.; Zhao, J.; Gao, C.; Xie, W.; Qin, H.; et al. A Next-Generation Sequencing-Based Strategy Combining Microsatellite Instability and Tumor Mutation Burden for Comprehensive Molecular Diagnosis of Advanced Colorectal Cancer. BMC Cancer 2021, 21, 282. [Google Scholar] [CrossRef]
  241. Lu, C.; Guan, J.; Lu, S.; Jin, Q.; Rousseau, B.; Lu, T.; Stephens, D.; Zhang, H.; Zhu, J.; Yang, M.; et al. DNA Sensing in Mismatch Repair-Deficient Tumor Cells Is Essential for Anti-Tumor Immunity. Cancer Cell 2021, 39, 96–108. [Google Scholar] [CrossRef] [PubMed]
  242. Smyrk, T.C.; Watson, P.; Kaul, K.; Lynch, H.T. Tumor-Infiltrating Lymphocytes Are a Marker for Microsatellite Instability in Colorectal Carcinoma. Cancer 2001, 91, 2417–2422. [Google Scholar] [CrossRef]
  243. Bruni, D.; Angell, H.K.; Galon, J. The Immune Contexture and Immunoscore in Cancer Prognosis and Therapeutic Efficacy. Nat. Rev. Cancer 2020, 20, 662–680. [Google Scholar] [CrossRef]
  244. Noepel-Duennebacke, S.; Juette, H.; Schulmann, K.; Graeven, U.; Porschen, R.; Stoehlmacher, J.; Hegewisch-Becker, S.; Raulf, A.; Arnold, D.; Reinacher-Schick, A.; et al. Microsatellite Instability (MSI-H) Is Associated with a High Immunoscore but Not with PD-L1 Expression or Increased Survival in Patients (Pts.) with Metastatic Colorectal Cancer (MCRC) Treated with Oxaliplatin (Ox) and Fluoropyrimidine (FP) with and without Bevacizumab (Bev): A Pooled Analysis of the AIO KRK 0207 and RO91 Trials. J. Cancer Res. Clin. Oncol. 2021, 147, 3063–3072. [Google Scholar] [CrossRef]
  245. Sui, Q.; Zhang, X.; Chen, C.; Tang, J.; Yu, J.; Li, W.; Han, K.; Jiang, W.; Liao, L.; Kong, L.; et al. Inflammation Promotes Resistance to Immune Checkpoint Inhibitors in High Microsatellite Instability Colorectal Cancer. Nat. Commun. 2022, 13, 7316. [Google Scholar] [CrossRef]
  246. Vétizou, M.; Pitt, J.M.; Daillère, R.; Lepage, P.; Waldschmitt, N.; Flament, C.; Rusakiewicz, S.; Routy, B.; Roberti, M.P.; Duong, C.P.M.; et al. Anticancer Immunotherapy by CTLA-4 Blockade Relies on the Gut Microbiota. Science 2015, 350, 1079–1084. [Google Scholar] [CrossRef] [PubMed]
  247. Gopalakrishnan, V.; Spencer, C.N.; Nezi, L.; Reuben, A.; Andrews, M.C.; Karpinets, T.V.; Prieto, P.A.; Vicente, D.; Hoffman, K.; Wei, S.C.; et al. Gut Microbiome Modulates Response to Anti-PD-1 Immunotherapy in Melanoma Patients. Science 2018, 359, 97–103. [Google Scholar] [CrossRef] [PubMed]
  248. Jin, M.; Wu, J.; Shi, L.; Zhou, B.; Shang, F.; Chang, X.; Dong, X.; Deng, S.; Liu, L.; Cai, K.; et al. Gut Microbiota Distinct between Colorectal Cancers with Deficient and Proficient Mismatch Repair: A Study of 230 CRC Patients. Front. Microbiol. 2022, 13, 993285. [Google Scholar] [CrossRef] [PubMed]
  249. Serpas Higbie, V.; Rogers, J.; Hwang, H.; Qiao, W.; Xiao, L.; Dasari, A.; Mola-Rudd, K.; Morris, V.K.; Wolff, R.A.; Raghav, K.; et al. Antibiotic Exposure Does Not Impact Immune Checkpoint Blockade Response in MSI-H/DMMR Metastatic Colorectal Cancer: A Single-Center Experience. Oncologist 2022, 27, 952–957. [Google Scholar] [CrossRef] [PubMed]
  250. Desai, R.; Coxon, A.T.; Dunn, G.P. Therapeutic Applications of the Cancer Immunoediting Hypothesis. Semin. Cancer Biol. 2022, 78, 63–77. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Lynch syndrome-associated cancer risks by age 80, according to the NCCN guidelines. GP = general population.
Figure 1. Lynch syndrome-associated cancer risks by age 80, according to the NCCN guidelines. GP = general population.
Cancers 15 02288 g001
Figure 2. The landscape of MSI and genomic characteristics of MSI tumors across cancer types, according to TCGA. (A) Prevalence of MSI (%) across tumor types. (B) Prevalence of genomic alterations typically found in MSI and MSS tumors in colorectal adenocarcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma.
Figure 2. The landscape of MSI and genomic characteristics of MSI tumors across cancer types, according to TCGA. (A) Prevalence of MSI (%) across tumor types. (B) Prevalence of genomic alterations typically found in MSI and MSS tumors in colorectal adenocarcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma.
Cancers 15 02288 g002
Figure 3. FDA approval timeline of immune checkpoint inhibitors for MSI/dMMR tumors.
Figure 3. FDA approval timeline of immune checkpoint inhibitors for MSI/dMMR tumors.
Cancers 15 02288 g003
Table 1. dMMR/MSI-related indications for immune checkpoint inhibitors.
Table 1. dMMR/MSI-related indications for immune checkpoint inhibitors.
CheckpointDrugIndications for MSI and/or dMMR Tumors
CTLA4Ipilimumab (in combination with nivolumab)MSI/dMMR colorectal cancer
TremelimumabIndications do not include MSI/dMMR tumors
PD1NivolumabMSI/dMMR colorectal cancer
PembrolizumabAll types of MSI/dMMR tumors (site-agnostic)
MSI/dMMR colorectal cancer
MSI/dMMR endometrial cancer
CemiplimabIndications do not include MSI/dMMR tumors
DostarlimabAll types of dMMR tumors (site agnostic)
dMMR endometrial cancer
PD-L1AtezolizumabIndications do not include MSI/dMMR tumors
AvelumabIndications do not include MSI/dMMR tumors
DurvalumabIndications do not include MSI/dMMR tumors
LAG3RelatlimabIndications do not include MSI/dMMR tumors
Table 2. Response rates of MSI/dMMR tumors to ICI therapy in selected clinical trials.
Table 2. Response rates of MSI/dMMR tumors to ICI therapy in selected clinical trials.
StudyTotal Number of
DrugORR or pCR (for Neoadjuvant Settings)Lynch Syndrome AccountedBRAF/RAS Status
Status Evaluated by IHC
Tissue/Site-Agnostic Treatment in Pretreated Metastatic Patients
149 patients:
89 CRC
14 EC
45 other
KEYNOTE-158 [40]233 non-CRCPembrolizumab34%NoNoYes
GARNET [193] (including POLE mutant)209 non-ECDostarlimab43%NoNoYes
Colorectal cancer
Late lines
KEYNOTE-016 [105]40Pembrolizumab52%YesNoYes
CheckMate-142 [200]119Nivolumab plus Ipilimumab55%YesYesYes
NCT01693562 [213]36Durvalumab22%No informationNo informationNo information
NCT03435107 [214]33Durvalumab42%NoYesNo
SAMCO-PRODIGE [210]61Avelumab28%NoYesYes
First line
KEYNOTE-177 [196]153Pembrolizumab45%NoYesNo
CheckMate-142 [41]45Nivolumab plus Ipilimumab69%NoYesYes
Neoadjuvant settings
NICHE [205]20Nivolumab plus Ipilimumab60%YesYesYes
NICHE-2 [207]107Nivolumab plus Ipilimumab67%No informationNo informationNo information
NCT04165772 [42]12Nivolumab plus Ipilimumab100%YesYesYes
Endometrial cancer
KEYNOTE-158 [220]79Pembrolizumab48%NoNoYes
GARNET [153,222]143Dostarlimab46%NoNoYes
Gastric cancer
KEYNOTE-062 [223]
KEYNOTE-158 [44]42Pembrolizumab31%NoNoYes
Small intestine cancer
KEYNOTE-158 [44]25Pembrolizumab48%NoNoYes
Ovarian cancer
KEYNOTE-158 [44]24Pembrolizumab33%NoNoYes
Cholangiocarcinoma/biliary tract cancer
KEYNOTE-158 [44]22Pembrolizumab41%NoNoYes
Pancreatic cancer
KEYNOTE-158 [44]22Pembrolizumab18%NoNoYes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kavun, A.; Veselovsky, E.; Lebedeva, A.; Belova, E.; Kuznetsova, O.; Yakushina, V.; Grigoreva, T.; Mileyko, V.; Fedyanin, M.; Ivanov, M. Microsatellite Instability: A Review of Molecular Epidemiology and Implications for Immune Checkpoint Inhibitor Therapy. Cancers 2023, 15, 2288.

AMA Style

Kavun A, Veselovsky E, Lebedeva A, Belova E, Kuznetsova O, Yakushina V, Grigoreva T, Mileyko V, Fedyanin M, Ivanov M. Microsatellite Instability: A Review of Molecular Epidemiology and Implications for Immune Checkpoint Inhibitor Therapy. Cancers. 2023; 15(8):2288.

Chicago/Turabian Style

Kavun, Alexandra, Egor Veselovsky, Alexandra Lebedeva, Ekaterina Belova, Olesya Kuznetsova, Valentina Yakushina, Tatiana Grigoreva, Vladislav Mileyko, Mikhail Fedyanin, and Maxim Ivanov. 2023. "Microsatellite Instability: A Review of Molecular Epidemiology and Implications for Immune Checkpoint Inhibitor Therapy" Cancers 15, no. 8: 2288.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop