The identification of a causal mutation is essential for molecular diagnosis and clinical management of many genetic disorders. However, even if next-generation exome sequencing has greatly improved the detection of nucleotide changes, the biological interpretation of most exonic variants remains challenging. Moreover, particular attention is typically given to protein-coding changes often neglecting the potential impact of exonic variants on RNA splicing. Here, we used the exon 10 of MLH1, a gene implicated in hereditary cancer, as a model system to assess the prevalence of RNA splicing mutations among all single-nucleotide variants identified in a given exon. We performed comprehensive minigene assays and analyzed patient’s RNA when available. Our study revealed a staggering number of splicing mutations in MLH1 exon 10 (77% of the 22 analyzed variants), including mutations directly affecting splice sites and, particularly, mutations altering potential splicing regulatory elements (ESRs). We then used this thoroughly characterized dataset, together with experimental data derived from previous studies on BRCA1, BRCA2, CFTR and NF1, to evaluate the predictive power of 3 in silico approaches recently described as promising tools for pinpointing ESR-mutations. Our results indicate that ΔtESRseq and ΔHZEI-based approaches not only discriminate which variants affect splicing, but also predict the direction and severity of the induced splicing defects. In contrast, the ΔΨ-based approach did not show a compelling predictive power. Our data indicates that exonic splicing mutations are more prevalent than currently appreciated and that they can now be predicted by using bioinformatics methods. These findings have implications for all genetically-caused diseases.

Colorectal cancers with microsatellite instability (MSI) represent 15% of all colorectal cancers, including Lynch syndrome as the most frequent hereditary form of this disease. Notably, MSI colorectal cancers have a higher density of tumor-infiltrating lymphocytes (TIL) than other colorectal cancers. This feature is thought to reflect the accumulation of frameshift mutations in sequences that are repeated within gene coding regions, thereby leading to the synthesis of neoantigens recognized by CD8 þ T cells. However, there has yet to be a clear link established between CD8 þ TIL density and frameshift mutations in colorectal cancer. In this study, we examined this link in 103 MSI colorectal cancers from two independent cohorts where frameshift mutations in 19 genes were analyzed and CD3 þ , CD8 þ , and FOXP3 þ TIL densities were quantitated. We found that CD8 þ TIL density correlated positively with the total number of frameshift mutations. TIL densities increased when frameshift mutations were present within the ASTE1, HNF1A, or TCF7L2 genes, increasing even further when at least one of these frameshift mutations was present in all tumor cells. Through in vitro assays using engineered antigen-presenting cells, we were able to stimulate peripheral cytotoxic T cells obtained from colorectal cancer patients with peptides derived from frameshift mutations found in their tumors. Taken together, our results highlight the importance of a CD8 þ T cell immune response against MSI colorectal cancer-specific neoantigens, establishing a preclinical rationale to target them as a personalized cellular immunotherapy strategy, an especially appealing goal for patients with Lynch syndrome. Cancer Res; 75(17); 3446-55. Ó2015 AACR.

Pathogenicity assessment of DNA variants in disease genes to explain their clinical consequences is an integral component of diagnostic molecular testing. The International Society for Gastrointestinal Hereditary Tumors (InSiGHT) has developed specific criteria for the interpretation of mismatch repair (MMR) gene variants. Here, we performed a systematic investigation of 24 MLH1 and MSH2 variants. The assessments were done by analyzing population frequency, segregation, tumor molecular characteristics, RNA effects, protein expression levels, and in vitro MMR activity. Classifications were confirmed for 15 variants and changed for three, and for the first time determined for six novel variants. Overall, based on our results, we propose the introduction of some refinements to the InSiGHT classification rules. The proposed changes have the advantage of homogenizing the InSIGHT interpretation criteria with those set out by the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium for the BRCA1/BRCA2 genes. We also observed that the addition of only few clinical data was sufficient to obtain a more stable classification for variants considered as "likely pathogenic" or "likely nonpathogenic." This shows the importance of obtaining as many as possible points of evidence for variant interpretation, especially from the clinical setting.