The E3 ubiquitin ligase Rad18 promotes a damage-tolerant and error-prone mode of DNA replication termed trans-lesion synthesis that is pathologically activated in cancer. However, the impact of vertebrate Rad18 on cancer genomes is not known. To determine how Rad18 affects mutagenesis in vivo, we have developed and implemented a novel computational pipeline to analyze genomes of carcinogen (7, 12-Dimethylbenz[a]anthracene, DMBA)-induced skin tumors from Rad18+/+ and Rad18−/− mice. We show that Rad18 mediates specific mutational signatures characterized by high levels of A(T)>T(A) single nucleotide variations (SNVs). In Rad18−/- tumors, an alternative mutation pattern arises, which is characterized by increased numbers of deletions >4 bp. Comparison with annotated human mutational signatures shows that COSMIC signature 22 predominates in Rad18+/+ tumors whereas Rad18−/− tumors are characterized by increased contribution of COSMIC signature 3 (a hallmark of BRCA-mutant tumors). Analysis of The Cancer Genome Atlas shows that RAD18 expression is strongly associated with high SNV burdens, suggesting RAD18 also promotes mutagenesis in human cancers. Taken together, our results show Rad18 promotes mutagenesis in vivo, modulates DNA repair pathway choice in neoplastic cells, and mediates specific mutational signatures that are present in human tumors.
Pathogenic-Th17 (pTh17) cells drive inflammation and immune-pathology, but whether pTh17 cells are a Th17-subset whose generation is under specific molecular control remains unaddressed. We found that Ras p21 protein activator 3 (RASA3) was highly expressed by pTh17 cells relative to non-pTh17 cells and was required specifically for pTh17 generation in vitro and in vivo. Mice conditionally deficient for Rasa3 in T cells showed less pathology during experimental autoimmune encephalomyelitis. Rasa3-deficient T cells acquired a Th2-biased program that dominantly trans-suppressed pTh17 cell generation via interleukin 4 production. The Th2-bias of Rasa3-deficient T cells was due to aberrantly elevated transcription factor IRF4 expression. RASA3 promoted proteasome-mediated IRF4 protein degradation by facilitating interaction of IRF4 with E3-ubiquitin ligase Cbl-b. Therefore, a RASA3-IRF4-Cbl-b pathway specifically directs pTh17 cell generation by balancing reciprocal Th17-Th2 programs. These findings indicate that a distinct molecular program directs pTh17 generation and reveals targets for treating pTh17-related pathology and diseases.
Electronic health records (EHRs) from type 2 diabetes (T2D) patients consist of longitudinally and sparsely measured health markers at clinical encounters. Our goal is to use such data to learn latent patterns that can inform patient's health status related to T2D while accounting for challenges in retrospectively collected EHRs. To handle challenges such as correlated longitudinal measurements, irregular and informative encounter times, and mixed marker types, we propose multivariate generalized linear models to learn latent patient subgroups. In our model, covariate effects were time‐dependent and latent Gaussian processes were introduced to model between‐marker correlations over time. Using inferred latent processes, we integrated the irregularly measured health markers of mixed types into composite scores and applied hierarchical clustering to learn latent subgroup structures among T2D patients. Application to an EHR dataset of T2D patients showed different trends of age, sex, and race effects on hypertension/high blood pressure, total cholesterol, glycated hemoglobin, high‐density lipoprotein, and medications. The associations among these markers varied over time during the study window. Clustering results revealed four subgroups, each with distinct health status. The same patterns were further confirmed using new EHR records of the same cohort. We developed a novel latent model to integrate longitudinal health markers in EHRs and characterize patient latent heterogeneities. Analysis indicated that there were distinct subgroups of T2D patients, suggesting that effective healthcare managements for these patients should be performed separately for each subgroup.
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