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Abstract Objective The phenotypic and genotypic spectrum of adult patients with epilepsy and intellectual disability (ID) is less clear than in children. We investigated an adult patient cohort to further elucidate this and inform the genetic testing approach. Methods Fifty‐two adult patients (30 male, 22 female) with epilepsy, at least mild ID and no known genetic or acquired cause were included and phenotyped. Variants identified through exome sequencing were evaluated using ACMG criteria. Identified variants were compared with commercially available gene panels. Cluster analysis of two features, age at seizure onset and age at ascertainment of cognitive deficits, was performed. Results Median age was 27 years (range 20‐57 years) with median seizure onset at 3 years and median ascertainment of cognitive deficits at 1 year. Likely pathogenic/pathogenic variants were identified in 16/52 patients (31%) including 14 (27%) single nucleotide variants and 2 (4%) copy number variants. Simulated yield of commercial gene panels varied between 13% in small (≤144 genes) and 27% in large panels (≥1478 genes). Cluster analysis (optimal number 3 clusters) identified a cluster with early seizure onset and early developmental delay (developmental and epileptic encephalopathy, n = 26), a cluster with early developmental delay but late seizure onset (ID with epilepsy, n = 16) and a third cluster with late ascertainment of cognitive deficits and variable seizure onset (n = 7). The smaller gene panels particularly missed the genes identified in the cluster with early ascertainment of cognitive deficits and later onset of epilepsy (0/4) as opposed to the cluster with developmental and epileptic encephalopathy (7/10). Significance Our data indicates that adult patients with epilepsy and ID represent a heterogeneous cohort that includes grown‐up patients with DEE but also patients with primary ID and later onset of epilepsy. To maximize diagnostic yield in this cohort either large gene panels or exome sequencing should be used.

Single‐cell transcriptomics have revolutionized our understanding of the cell composition of tumors and allowed us to identify new subtypes of cells. Despite rapid technological advancements, single‐cell analysis remains resource‐intense hampering the scalability that is required to profile a sufficient number of samples for clinical associations. Therefore, more scalable approaches are needed to understand the contribution of individual cell types to the development and treatment response of solid tumors such as esophageal adenocarcinoma where comprehensive genomic studies have only led to a small number of targeted therapies. Due to the limited treatment options and late diagnosis, esophageal adenocarcinoma has a poor prognosis. Understanding the interaction between and dysfunction of individual cell populations provides an opportunity for the development of new interventions. In an attempt to address the technological and clinical needs, we developed a protocol for the separation of esophageal carcinoma tissue into leukocytes (CD45+), epithelial cells (EpCAM+), and fibroblasts (two out of PDGFRα, CD90, anti‐fibroblast) by fluorescence‐activated cell sorting and subsequent RNA sequencing. We confirm successful separation of the three cell populations by mapping their transcriptomic profiles to reference cell lineage expression data. Gene‐level analysis further supports the isolation of individual cell populations with high expression of CD3, CD4, CD8, CD19, and CD20 for leukocytes, CDH1 and MUC1 for epithelial cells, and FAP, SMA, COL1A1, and COL3A1 for fibroblasts. As a proof of concept, we profiled tumor samples of nine patients and explored expression differences in the three cell populations between tumor and normal tissue. Interestingly, we found that angiogenesis‐related genes were upregulated in fibroblasts isolated from tumors compared with normal tissue. Overall, we suggest our protocol as a complementary and more scalable approach compared with single‐cell RNA sequencing to investigate associations between clinical parameters and transcriptomic alterations of specific cell populations in esophageal adenocarcinoma.

Abstract The prevalence of germ line mutations in non‐BRCA1/2 genes associated with hereditary breast cancer (BC) is low, and the role of some of these genes in BC predisposition and pathogenesis is conflicting. In this study, 5589 consecutive BC index patients negative for pathogenic BRCA1/2 mutations and 2189 female controls were screened for germ line mutations in eight cancer predisposition genes (ATM, CDH1, CHEK2, NBN, PALB2, RAD51C, RAD51D, and TP53). All patients met the inclusion criteria of the German Consortium for Hereditary Breast and Ovarian Cancer for germ line testing. The highest mutation prevalence was observed in the CHEK2 gene (2.5%), followed by ATM (1.5%) and PALB2 (1.2%). The mutation prevalence in each of the remaining genes was 0.3% or lower. Using Exome Aggregation Consortium control data, we confirm significant associations of heterozygous germ line mutations with BC for ATM (OR: 3.63, 95%CI: 2.67–4.94), CDH1 (OR: 17.04, 95%CI: 3.54–82), CHEK2 (OR: 2.93, 95%CI: 2.29–3.75), PALB2 (OR: 9.53, 95%CI: 6.25–14.51), and TP53 (OR: 7.30, 95%CI: 1.22–43.68). NBN germ line mutations were not significantly associated with BC risk (OR:1.39, 95%CI: 0.73–2.64). Due to their low mutation prevalence, the RAD51C and RAD51D genes require further investigation. Compared with control datasets, predicted damaging rare missense variants were significantly more prevalent in CHEK2 and TP53 in BC index patients. Compared with the overall sample, only TP53 mutation carriers show a significantly younger age at first BC diagnosis. We demonstrate a significant association of deleterious variants in the CHEK2, PALB2, and TP53 genes with bilateral BC. Both, ATM and CHEK2, were negatively associated with triple‐negative breast cancer (TNBC) and estrogen receptor (ER)‐negative tumor phenotypes. A particularly high CHEK2 mutation prevalence (5.2%) was observed in patients with human epidermal growth factor receptor 2 (HER2)‐positive tumors.