Contribution of mRNA Splicing to Mismatch Repair Gene Sequence Variant Interpretation

Abstract

Functional assays that assess mRNA splicing can be used in interpretation of the clinical significance of sequence variants, including the Lynch syndrome-associated mismatch repair (MMR) genes. The purpose of this study was to investigate the contribution of splicing assay data to the classification of MMR gene sequence variants. We assayed mRNA splicing for 24 sequence variants in MLH1, MSH2, and MSH6, including 12 missense variants that were also assessed using a cell-free in vitro MMR activity (CIMRA) assay. Multifactorial likelihood analysis was conducted for each variant, combining CIMRA outputs and clinical data where available. We collated these results with existing public data to provide a dataset of splicing assay results for a total of 671 MMR gene sequence variants (328 missense/in-frame indel), and published and unpublished repair activity measurements for 154 of these variants. There were 241 variants for which a splicing aberration was detected: 92 complete impact, 33 incomplete impact, and 116 where it was not possible to determine complete versus incomplete splicing impact. Splicing results mostly aided in the interpretation of intronic (72%) and silent (92%) variants and were the least useful for missense substitutions/in-frame indels (10%). MMR protein functional activity assays were more useful in the analysis of these exonic variants but by design they were not able to detect clinically important splicing aberrations identified by parallel mRNA assays. The development of high throughput assays that can quantitatively assess impact on mRNA transcript expression and protein function in parallel will streamline classification of MMR gene sequence variants.

Keywords: Lynch syndrome; mRNA splicing; mismatch repair genes; splicing aberrations; variant interpretation and classification; variant type.

FIGURE 1

Cell-free in vitro mismatch repair activity (CIMRA) assay results for 12 missense substitutions. The MLH1 p.G67R, MSH2 p.A636P, and MSH6 p.G1139S variants are included in every experiment as repair-deficient (pathogenic) controls. Bars represent mean ± SEM of 3–4 experiments. Asterisks indicate substitutions where the CIMRA assay results converted to a functional LR contributed to the final classification of the variant. The color code (red, blue, yellow) refers to the classification of the variants as determined in this study.

FIGURE 2

Summary of contribution of splicing assay data to variant classification. The figure legend describes the categorization of the splicing and MMR activity assay data. Splice site refers to variants in the conserved IVS ± 1/2 dinucleotides of the acceptor or donor splice site, while intronic includes all other intronic variants. Predicted loss of function variants other than splice site variants were excluded from this summary because they are classified as pathogenic regardless of splicing assay results (frameshift: n = 25; nonsense: n = 24). There were also two initiation codon variants and two stoploss variants not included in this summary. Com, complete impact, variant allele causes complete splicing aberration; D, deficient function (MLH1/MSH2: <23% wild-type repair, MSH6/PMS2: <18% wild-type activity); Inc, incomplete impact, variant allele results in expression of both reference (full-length) and alternatively spliced transcript(s); M, moderate function (MLH1/MSH2: 23% to <70% wild-type repair, MSH6/PMS2: 18 to <100% wild-type activity); Norm, no splicing aberration detected; P, proficient function (MLH1/MSH2: ≥70% wild-type repair, MSH6/PMS2: ≥100% wild-type activity); Unk, extent of impact unknown, splicing aberration detected, but unable to determine if variant impact was complete/incomplete.

FIGURE 3

Decision tree for the recommended course of action when assessing the functional impact of MMR gene variants, updated from the decision tree published in Thompson et al. (2014). * As per likelihood ratio or odds for pathogenicity cut-offs reported by Tavtigian et al. (2018) and Brnich et al. (2019).