Molecular Profile of MSH6-Associated Colorectal Carcinomas Shows Distinct Features From Other Lynch Syndrome–Associated Colorectal Carcinomas

This is the authors' abstract. We don't add key points for this paper.

See editorial on page 20. See editorial on page 20. Lynch syndrome (LS) is the most common hereditary colorectal cancer (CRC) syndrome and is caused by pathogenic constitutional variants in 1 of the mismatch repair (MMR) genes, including MLH1, MSH2 (EPCAM), MSH6, and PMS2. Although generally referred to as 1 entity, LS exhibits a highly heterogeneous phenotype, exemplified by major differences in cancer penetrance between MMR gene variant carriers.1Helderman N.C. et al.Crit Rev Oncol Hematol. 2021; 163103338Crossref PubMed Scopus (10) Google Scholar These differences imply that the quality of colonoscopy, optimal surveillance intervals, treatment, preventive strategies, and other aspects of care likely differ between LS subgroups. Nevertheless, in most countries all (newly) diagnosed LS patients are subject to identical screening and treatment regimes. The study of LS CRC molecular profiles will improve our understanding of phenotypic heterogeneity and may in turn stimulate the development of gene-specific guidelines. Because previous molecular studies focused predominantly on MLH1-, MSH2-, and PMS2-associated CRCs, our study aimed to define the molecular profile of MSH6-associated CRCs relative to other LS CRCs. The study included 106 confirmed LS CRCs, of which 44 (25 MSH6-, 5 MLH1-, 5 MSH2-, and 9 PMS2-associated CRCs) were analyzed by whole exome sequencing (WES) and 62 (24 MLH1-, 18 MSH2-, and 20 PMS2-associated CRCs) by a cancer hotspot panel (CHP) described previously.2Ten Broeke S.W. et al.Gastroenterology. 2018; 155: 844-851Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar For a full description of the materials and methods used, refer to the Supplementary Methods. A description of the total cohort, consisting of both WES and CHP cohorts, is presented in Supplementary Table 1. A full description of all available histologic and molecular characteristics (including constitutional MMR and somatic variants) for each analyzed LS CRC is presented in Supplementary Table 2. Although the overall variant spectra of MSH6-, MLH1-, MSH2-, and PMS2-associated CRCs look similar, notable differences exist. These include the higher (P < .01) overall number of deficient MMR (dMMR) signature-associated single nucleotide variants (SNVs) and the lower (P = .01) overall number of dMMR signature-associated insertion/deletion variants (INDELs) in MSH6-associated CRCs vs PMS2-associated CRCs (Figure 1A–C, Supplementary Table 1). One possible explanation for these findings is the specific protein function during MMR: although the PMS2–MLH1 complex (hMutLɑ) is essential for the repair of SNVs and INDELs, the MSH2–MSH6 (hMutSα) complex is mainly involved in the repair of SNVs and is believed to be redundant for INDEL repair, which mainly depends on MSH2–MSH3 (hMutSβ).1Helderman N.C. et al.Crit Rev Oncol Hematol. 2021; 163103338Crossref PubMed Scopus (10) Google Scholar Consequently, the absence of MSH6 activity likely results in the accumulation of SNVs, rather than the profound microsatellite instability (MSI; associated with INDELs) that follows MLH1, MSH2, or PMS2 dysfunction. This is further reflected by 2 microsatellite stable MSH6-associated CRCs with loss of MSH6 expression in our cohort and would imply that immunohistochemical MMR staining may be more sensitive than MSI testing in MSH6-associated CRCs.3Hendriks Y.M. et al.Gastroenterology. 2004; 127: 17-25Abstract Full Text Full Text PDF PubMed Scopus (351) Google Scholar The fact that MSH6 dysfunction predominantly leads to the accumulation of SNVs, whereas PMS2 (and MLH1, MSH2) dysfunction promotes MSI is intriguing in light of the previously observed lower CRC penetrance of PMS2 (5.9%–13%) vs MSH6 variants (20%).4Moller P. et al.Gut. 2017; 66: 464-472Crossref PubMed Scopus (362) Google Scholar, 5Suerink M. et al.Genet Med. 2019; 21: 2706-2712Abstract Full Text Full Text PDF PubMed Scopus (8) Google Scholar, 6Ten Broeke S.W. et al.J Clin Oncol. 2018; 36: 2961-2968Crossref PubMed Scopus (130) Google Scholar This suggests that SNVs rather than INDELs drive the development of MSH6-associated CRCs, thereby potentially mitigating the importance of MSI as a driving force of tumor development. Moreover, it suggests the hypothesis that MSH6-associated CRCs are less sensitive to immunotherapies and frameshift peptide neoantigen-based vaccines compared with other LS subgroups, because MSI is among the important biomarkers for immunotherapy response. Future studies should explore the (coding) microsatellite mutation and immune profile of MSH6-associated CRCs to test this hypothesis as well as stratify immunotherapy responses based on the underlying MMR gene defect. Another striking finding involved the lower abundance of CTNNB1 variants in MSH6-associated CRCs (8%, 2/25) vs MLH1-associated CRCs (47%, 14/29; P = .04) (Supplementary Table 1). CTNNB1 variants are believed to be responsible for an invasive growth pattern,7Ahadova A, et al. Fam Cancer 2016;15:579–586.Google Scholar for instance through submucosal growth or direct tumor progression from MMR deficient crypt foci (MMR-DCF carcinoma pathway) (Figure 1D).1Helderman N.C. et al.Crit Rev Oncol Hematol. 2021; 163103338Crossref PubMed Scopus (10) Google Scholar,8Ahadova A. et al.Int J Cancer. 2018; 143: 139-150Crossref PubMed Scopus (113) Google Scholar,9Engel C. et al.Gastroenterology. 2020; 158: 1326-1333Abstract Full Text Full Text PDF PubMed Scopus (50) Google Scholar This invasive growth pattern may hypothetically lead to the development of postcolonoscopy CRCs, which are diagnosed after a colonoscopy in which no cancer was found. The relatively low abundance of CTNNB1 variants in MSH6-associated CRCs might therefore explain the relatively low (15%) prevalence of postcolonoscopy CRCs observed among MSH6 variant carriers10Moller P. et al.Gut. 2017; 67: 1306-1316Crossref PubMed Scopus (366) Google Scholar and illustrates that surveillance intervals may be extended for MSH6 variant carriers. The latter has already been proposed for PMS2 variant carriers2Ten Broeke S.W. et al.Gastroenterology. 2018; 155: 844-851Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar and may have resulted from the fact that current guidelines were formulated based on cohorts that primarily consisted of MLH1 and MSH2 variant carriers, for whom the prevalence of postcolonoscopy CRCs is remarkably higher (45%).10Moller P. et al.Gut. 2017; 67: 1306-1316Crossref PubMed Scopus (366) Google Scholar LS CRCs may alternatively originate from MMR-proficient adenomas (adenoma–carcinoma pathway) or from MMR-DCF through an intervening adenoma stage (MMR-DCF adenoma–carcinoma pathway).8Ahadova A. et al.Int J Cancer. 2018; 143: 139-150Crossref PubMed Scopus (113) Google Scholar These pathways have been linked to APC variants, which were observed in 32% of all MSH6-associated CRCs. Our gene-based signature analysis also cast light on the distinct pathways of LS carcinogenesis, including potential time windows for mutational events in each gene (Figure 1E). For instance, most APC, KRAS, and TP53 variants in MSH6-associated CRCs were dMMR signature-associated. This suggests that these variants occurred after the second hit in the wild-type MSH6 allele, which was therefore probably an early event. The latter would fit with the MMR-DCF adenoma–carcinoma pathway, implying that most MSH6-associated CRCs developing through adenomas follow the MMR-DCF adenoma–carcinoma pathway rather than the adenoma–carcinoma pathway. A limitation of this study was the number of available WES data of MLH1-, MSH2-, and PMS2-associated CRCs, which impeded firm comparisons with MSH6-associated CRCs. Although this was in part corrected by inclusion of the CHP data, the minimal coverage of the CHP data as compared with the WES data influences the quality of our mutational analysis. In conclusion, the clinical heterogeneity observed in LS patients may be partly explained by the molecular profile of individual LS CRCs. The molecular profile of MSH6-associated CRCs is characterized by an abundance of dMMR signature-associated SNVs yet contains fewer dMMR signature-associated INDELs compared with PMS2-associated CRCs and fewer CTNNB1 variants compared with MLH1-associated CRCs. Once confirmed, these findings will find application in the management of LS patients targeted to gene-specific subgroups, with the ultimate goal to fine-tune current “mismatches” in care. Members of the MSH6 Tumor Group are as follows: Diantha Terlouw,1,2 Sanne W. Bajwa-ten Broeke,3 Mar Rodríguez-Girondo,4 Demi van Egmond,2 Alexandra M. J. Langers,5 Monique E. van Leerdam,5,6 Emily Rayner,7 Christi J. van Asperen,1 Liselotte P. van Hest,8 Hans J. P. Gille,8 Floor A. M. Duijkers,9 Anja Wagner,10 Ellis L. Eikenboom,10,11 Tom G. W. Letteboer,12 Mirjam M. de Jong,3 Fonnet E. Bleeker,13 Encarna B. Gomez Garcìa,14 Manon Suerink,1 Carli M. Tops,1 Niels de Wind7; from the 1Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands; 2Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands; 3Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; 4Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands; 5Department of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, The Netherlands; 6Department of Gastrointestinal Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands; 7Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands; 8Department of Clinical Genetics, Amsterdam University Medical Center, location Vrije Universiteit Amsterdam and location University of Amsterdam, Amsterdam, The Netherlands; 9Department of Human Genetics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands; 10Department of Clinical Genetics, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands; 11Department of Gastroenterology and Hepatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands; 12Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands; 13Department of Clinical Genetics, Netherlands Cancer Institute, Amsterdam, The Netherlands; 14Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands. The authors sincerely thank all patients and their families for their participation in this study. We gratefully acknowledge the editing assistance of MedicalEditing.nl and the support from the participating pathology centers. Noah Cornelis Helderman, BSc, PhD candidate (Formal analysis: Lead; Investigation: Lead; Methodology: Equal; Visualization: Lead; Writing – original draft: Lead; Writing – review & editing: Lead). Anne-Sophie van der Werf-'t Lam, MD, PhD candidate (Formal analysis: Supporting; Methodology: Supporting; Writing – original draft: Supporting; Writing – review & editing: Equal). Diantha Terlouw, MSc, PhD candidate (Formal analysis: Supporting; Investigation: Supporting; Writing – review & editing: Equal). Sanne W. Bajwa-ten Broeke, MD, PhD (Formal analysis: Supporting; Investigation: Supporting; Writing – review & editing: Equal). Mar Rodríguez-Girondo, PhD (Methodology: Supporting; Writing – review & editing: Equal). Demi van Egmond (Formal analysis: Supporting; Investigation: Supporting; Writing – review & editing: Supporting). Alexandra M. J. Langers, MD, PhD (Writing – review & editing: Equal). Monique E. van Leerdam, MD, PhD (Writing – review & editing: Equal). Emily Rayner, PhD (Writing – review & editing: Equal). Christi J. van Asperen, MD, PhD (Writing – review & editing: Equal). Liselotte P. van hest, MD (Writing – review & editing: Supporting). Hans J. P. Gille, PhD (Writing – review & editing: Supporting). Floor A. M. Duijkers, MD, PhD (Writing – review & editing: Supporting). Anja Wagner, MD, PhD (Writing – review & editing: Supporting). Ellis L. Eikenboom, PhD candidate (Writing – review & editing: Supporting). Tom G. W. Letteboer, PhD (Writing – review & editing: Supporting). Mirjam M. de Jong, MD, PhD (Writing – review & editing: Supporting). Fonnet E. Bleeker, MD, PhD (Writing – review & editing: Supporting). Encarna B. Gomez Garcìa, MD, PhD (Writing – review & editing: Supporting). Manon Suerink, MD, PhD (Writing – review & editing: Equal). Carli M. Tops, PhD (Writing – review & editing: Equal). Niels de Wind, PhD (Writing – review & editing: Equal). Hans Morreau, MD, PhD (Conceptualization: Equal; Formal analysis: Equal; Investigation: Equal; Methodology: Equal; Writing – review & editing: Equal). Arnoud Boot, PhD (Formal analysis: Equal; Investigation: Equal; Methodology: Equal; Writing – review & editing: Equal). Tom van Wezel, PhD (Conceptualization: Equal; Formal analysis: Equal; Investigation: Equal; Methodology: Equal; Writing – review & editing: Equal). Maartje Nielsen, MD, PhD (Conceptualization: Lead; Formal analysis: Equal; Funding acquisition: Lead; Investigation: Equal; Methodology: Equal; Project administration: Lead; Supervision: Lead; Writing – original draft: Supporting; Writing – review & editing: Equal). Download .pdf (.67 MB) Help with pdf files Supplementary Data This study was approved by the Medical Ethical Committee of Leiden, The Hague, Delft (protocol P17.098). Patient samples were handled according to the medical ethical guidelines described in the Code of Conduct for responsible use of human tissue in the context of health research (Federation of Dutch Medical Scientific Societies). Samples were coded, and all patients provided informed consent for the use of tissue and clinical data. The study included 106 confirmed LS CRCs, of which 44 (25 MSH6-, 5 MLH1-, 5 MSH2-, and 9 PMS2-associated CRCs) were analyzed by WES. Resultant tissue blocks were made available by various pathology departments in the Netherlands. For the remaining 62 LS CRCs, we retrieved CHP data from an earlier study by our research group.1Ten Broeke S.W. et al.Gastroenterology. 2018; 155: 844-851Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar This group comprised 24 MLH1-, 18 MSH2-, and 20 PMS2-associated CRCs. For a detailed description of the CHP analysis see Ten Broeke et al.1Ten Broeke S.W. et al.Gastroenterology. 2018; 155: 844-851Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar For each LS CRC of the WES cohort, DNA was isolated from formalin-fixed paraffin-embedded tissue blocks of both tumor and normal tissue, using tissue cores, microdissection, or whole sections and the NucleoSpin DNA FFPE XS kit (Macherey-Nagel, Düren, DE). The Qubit Meter dsDNA High Sensitivity kit (ThermoFisher Scientific, Waltham, MA) was used to assess whether sufficient DNA was isolated for downstream analyses. WES was performed using the NovaSeq 6000 Sequencing System (Illumina Inc, San Diego, CA). Sequencing reads were trimmed using Trimomatic v.0.362Bolger A.M. et al.Bioinformatics. 2014; 30: 2114-2120Crossref PubMed Scopus (34534) Google Scholar and aligned to GRCh38 using BWA-MEM.3Li H. et al.Bioinformatics. 2009; 25: 1754-1760Crossref PubMed Scopus (30551) Google Scholar Polymerase chain reaction duplicate removal and merging were conducted in Sambamba (v0.5.8),4Tarasov A. et al.Bioinformatics. 2015; 31: 2032-2034Crossref PubMed Scopus (1000) Google Scholar and variant calling (ie, SNVs and INDELs) was performed using Strelka (v2.014).5Saunders C.T. et al.Bioinformatics. 2012; 28: 1811-1817Crossref PubMed Scopus (1092) Google Scholar Artifacts caused by formalin fixation were removed by reverse variant calling (ie, swapping tumor and normal) and filter optimization: Variants were filtered for variant allele frequencies of ≥10%, ≥20 times coverage in both the tumor and normal sample and at least 4 reads supporting the variant. SNVs in dbSNPv132, 1000 genomes (The 1000 Genomes Project Consortium 2015), segmental duplications, microsatellites, homopolymers, and the GL and KI sequences were excluded. Variant annotation and the removal of (likely) benign variants were performed using ANNOVAR.6Wang K. et al.Nucleic Acids Res. 2010; 38: e164Crossref PubMed Scopus (9047) Google Scholar First, we developed a pipeline within ANNOVAR and data parser (source code available on request) that selected nonsynonymous or splice variants, which were not located in segmental duplications and not observed in the Exome Aggregation Consortium7Genomes Project Consortium, et-alNature. 2010; 467: 1061-1073Crossref PubMed Scopus (6148) Google Scholar and/or Exome Sequencing Project8https://esp.gs.washington.edu/drupal/node/1Google Scholar with an allele frequency higher than 1%. Databases used for this pipeline were downloaded from ANNOVAR directly or were retrieved from the University of California, San Diego Genome Browser Annotation Database.9Karolchik D. et al.Nucleic Acids Res. 2014; 42: D764-D770Crossref PubMed Scopus (526) Google Scholar Next, variants were selected if located in any of 205 well-known onco- and tumor suppressor genes. This list of genes was created primarily by extracting the overlapping genes from the TruSight Oncology 500 Assay (Illumina), the Oncomine Tumor Mutation Load Assay (ThermoFisher Scientific), MSK-IMPACT,10Cheng D.T. et al.J Mol Diagn. 2015; 17: 251-264Abstract Full Text Full Text PDF PubMed Scopus (1365) Google Scholar and the Cancer Gene Census11Sondka Z. et al.Nat Rev Cancer. 2018; 18: 696-705Crossref PubMed Scopus (752) Google Scholar (list available upon request). The selected variants were visualized and validated using Integrative Genomics Viewer.12Robinson J.T. et al.Nat Biotechnol. 2011; 29: 24-26Crossref PubMed Scopus (8762) Google Scholar Variants with a variant allele frequency < 20%, <3 unique reads on both the plus and minus strands, and/or a read difference > 1:7 between both strands were not considered. Finally, variants were classified according to the American College of Medical Genetics and Genomics recommendations for variant interpretation using Franklin.13https://franklin.genoox.com/clinical-db/homeGoogle Scholar,14Richards C.S. et al.Genet Med. 2008; 10: 294-300Abstract Full Text Full Text PDF PubMed Scopus (680) Google Scholar Variants reported in this study classify as variants of unknown significance, likely pathogenic or pathogenic, and in addition have a combined annotation-dependent depletion score higher than 20, indicating they are considered to be in the top 1% of possibly pathogenic variants.15Rentzsch P. et al.Nucleic Acids Res. 2019; 47: D886-D894Crossref PubMed Scopus (1829) Google Scholar LOH of the MMR genes was manually curated with the use of Integrative Genomics Viewer.12Robinson J.T. et al.Nat Biotechnol. 2011; 29: 24-26Crossref PubMed Scopus (8762) Google Scholar LOH was considered when the variant allele frequency of the germline MMR variant differed ≥20% between tumor and normal tissue or when at least 4 of 10 randomly assessed single-nucleotide polymorphisms, located both upstream and downstream of the MMR variant, showed a variant allele frequency difference of ≥20% between tumor and normal tissue. Mutational signatures were extracted from the WES data to score the overall contribution of dMMR to the total number of variants in each LS CRC of the WES cohort, using SigProfiler and the SigProfiler reference mutational signatures.16Alexandrov L.B. et al.Nature. 2020; 578: 94-101Crossref PubMed Scopus (1568) Google Scholar The SNV mutational signatures SBS6, SBS15, SBS20, SBS21, SBS26, and SBS44 and the INDEL mutational signatures ID1, ID2, and ID7 were considered dMMR signature-associated. SBS1, SBS5, and SBS40 were considered to be L.B. et al.Nature. 2020; 578: 94-101Crossref PubMed Scopus (1568) Google Scholar, L.B. et al.Nature. PubMed Scopus Google Scholar, 2020; of Genomes PubMed Scopus Google Scholar, et al.Nucleic Acids Res. 2019; 47: PubMed Scopus Google Scholar, M. et Cancer Res. 2021; PubMed Scopus Google Scholar For each gene with at least 5 variants in the combined WES and CHP cohorts, we the of dMMR signature-associated variants to the of mutational SNVs were considered dMMR signature-associated when they involved at or with L.B. et al.Nature. 2020; 578: 94-101Crossref PubMed Scopus (1568) Google Scholar, L.B. et al.Nature. PubMed Scopus Google Scholar, 2020; of Genomes PubMed Scopus Google Scholar, et al.Nucleic Acids Res. 2019; 47: PubMed Scopus Google Scholar, M. et Cancer Res. 2021; PubMed Scopus Google Scholar INDELs were considered dMMR signature-associated if they involved single-nucleotide INDELs sequences with ID1, ID2, and L.B. et al.Nature. 2020; 578: 94-101Crossref PubMed Scopus (1568) Google Scholar, L.B. et al.Nature. PubMed Scopus Google Scholar, 2020; of Genomes PubMed Scopus Google Scholar, et al.Nucleic Acids Res. 2019; 47: PubMed Scopus Google Scholar, M. et Cancer Res. 2021; PubMed Scopus Google Scholar were performed using for and for are presented as and were compared using the test or test are presented as and were compared using test or test were compared between MSH6-associated CRCs vs MLH1-, MSH2-, or PMS2-associated CRCs, and P were for the number of comparisons and using & for In the combined WES and CHP data variants observed in the WES cohort were if the was in the The latter not for the gene-based signature analysis. P in this are and considered when P < Cancer for cancer (CRC) was of to be and the of events involved in the and progression of CRC are well in and data have to an to molecular of CRC in including instability and PDF Lynch A Cancer or by syndrome is the most common of hereditary cancer 1 in This to cancer is caused by or germline pathogenic in the DNA mismatch repair (MMR) genes MLH1, MSH2, MSH6, and PMS2. In constitutional of MLH1 or MSH2 to an is also the specific patients with Lynch syndrome identical clinical management in most PDF