Lynch syndrome (LS) is the most common hereditary colorectal cancer (CRC) syndrome, caused by heterozygous mutations in the mismatch repair (MMR) genes. Biallelic mutations in these genes lead however, to constitutive mismatch repair deficiency (CMMRD). In this study, we follow the diagnostic journey of a 12-year old patient with CRC, with a clinical phenotype overlapping CMMRD. We perform molecular and functional assays to discard a CMMRD diagnosis then identify by exome sequencing and validation in a cohort of 134 LS patients, a candidate variant in the MLH1 UTR region in homozygosis. We propose that this variant, together with other candidates, could be responsible for age-of-onset modulation. Our data support the idea that low-risk modifier alleles may influence early development of cancer in LS leading to a LS-to-CMMRD phenotypic continuum. Therefore, it is essential that larger efforts are directed to the identification and study of these genetic modifiers, in order to provide optimal cancer prevention strategies to these patients.

Establishing the pathogenic nature of variants in ATM, a gene associated with breast cancer and other hereditary cancers, is crucial for providing patients with adequate care. Unfortunately, achieving good variant classifications is still an unsolved problem. Here, this challenge is addressed, extending the range of in silico tools with a series of graphical tools devised for the analysis of computational evidence by healthcare professionals. We propose a family of fast and easy-to-use graphical representations in which the impact of a variant is considered relative to other pathogenic and benign variants. To illustrate their value, the representations are applied to three problems in variant interpretation. In the assessment of computational pathogenicity predictions, it is shown that the graphics provide an intuitive view of prediction reliability, complementing and extending conventional numerical reliability indexes. When applied to VUS populations, the representations shed light on the nature of these variants and can be used to prioritize VUS for further studies. In a third application, the graphics are utilized to compare the two versions of the ATM-adapted ACMG/AMP guidelines obtaining valuable information on their relative virtues and weaknesses. Finally, a server (ATMision) has been created where users can utilize these representations in their variant interpretation problems, to check the ATM-adapted guidelines' criteria for computational evidence on their variant(s), access different sources of information, etc.

Colorectal cancer (CRC) is increasingly diagnosed in individuals under 50 years of age, yet the underlying genetic predisposition remains largely unexplained, particularly in mismatch repair (MMR)-proficient cases. This study aimed to identify novel hereditary CRC susceptibility genes by integrating germline and tumour whole-exome sequencing (WES) with transcriptomic profiling across a cohort of early-onset CRC (EOCRC) patients. Tumours were categorised using Consensus Molecular Subtypes (CMS) classification and analysed for mutational signature and burden. We used a novel ‘All vs One’ multi-omic integration approach to identify loss-of-function rare germline variants with concordant gene expression alterations in tumour tissue. Five candidate genes ( ADCY4 , NOXO1, CDHR2 , ARHGAP10 , EEF2K ) were prioritised based on this approach and potential biological relevance in CRC. These findings highlight the molecular heterogeneity of EOCRC and demonstrate the utility of multi-omic approaches in refining germline variant interpretation. Integrating tumour transcriptomics enhances gene discovery efforts and supports a more comprehensive understanding of CRC heritability in younger individuals.