Microsatellite instability (MSI) refers to the hypermutability of short repetitive sequences in the genome caused by impaired DNA mismatch repair. Although MSI has been studied for decades, large amounts of sequencing data now available allows us to examine the molecular fingerprints of MSI in greater detail. Here, we analyse ∼8,000 exomes and ∼1,000 whole genomes of cancer patients across 23 cancer types. Our analysis reveals that the frequency of MSI events is highly variable within and across tumour types. We also identify genes in DNA repair and oncogenic pathways recurrently subject to MSI and uncover non-coding loci that frequently display MSI. Finally, we propose a highly accurate exome-based predictive model for the MSI phenotype. These results advance our understanding of the genomic drivers and consequences of MSI, and our comprehensive catalogue of tumour-type-specific MSI loci will enable panel-based MSI testing to identify patients who are likely to benefit from immunotherapy.

Genomic and precision medicine research has afforded notable advances in human cancer treatment, yet applicability to other species remains uncertain. Through whole-exome and transcriptome analyses of 191 spontaneous canine mammary tumors (CMTs) that exhibit the archetypal features of human breast cancers, we found a striking resemblance of genomic characteristics including frequent PIK3CA mutations (43.1%), aberrations of the PI3K-Akt pathway (61.7%), and key genes involved in cancer initiation and progression. We also identified three gene expression-based CMT subtypes, one of which segregated with basallike human breast cancer subtypes with activated epithelial-to-mesenchymal transition, low claudin expression, and unfavorable disease prognosis. A relative lack of ERBB2 amplification and Her2-enrichment subtype in CMT denoted species-specific molecular mechanisms. Taken together, our results elucidate cross-species oncogenic signatures for a better understanding of universal and context-dependent mechanisms in breast cancer development and provide a basis for precision diagnostics and therapeutics for domestic dogs.

In many next-generation sequencing (NGS) studies, multiple samples or data types are profiled for each individual. An important quality control (QC) step in these studies is to ensure that datasets from the same subject are properly paired. Given the heterogeneity of data types, file types and sequencing depths in a multi-dimensional study, a robust program that provides a standardized metric for genotype comparisons would be useful. Here, we describe NGSCheckMate, a user-friendly software package for verifying sample identities from FASTQ, BAM or VCF files. This tool uses a model-based method to compare allele read fractions at known single-nucleotide polymorphisms, considering depth-dependent behavior of similarity metrics for identical and unrelated samples. Our evaluation shows that NGSCheckMate is effective for a variety of data types, including exome sequencing, whole-genome sequencing, RNA-seq, ChIP-seq, targeted sequencing and single-cell whole-genome sequencing, with a minimal requirement for sequencing depth (>0.5X). An alignment-free module can be run directly on FASTQ files for a quick initial check. We recommend using this software as a QC step in NGS studies. Availability: https://github.com/parklab/NGSCheckMate

Ocular marginal zone lymphoma is a common type of low-grade B-cell lymphoma. To investigate the genomic changes that occur in ocular marginal zone lymphoma, we analyzed 10 cases of ocular marginal zone lymphoma using whole-genome and RNA sequencing and an additional 38 cases using targeted sequencing. Major genetic alterations affecting genes involved in nuclear factor (NF)-κB pathway activation (60%), chromatin modification and transcriptional regulation (44%), and B-cell differentiation (23%) were identified. In whole-genome sequencing, the 6q23.3 region containing TNFAIP3 was deleted in 5 samples (50%). In addition, 5 structural variation breakpoints in the first intron of IL20RA located in the 6q23.3 region was found in 3 samples (30%). In targeted sequencing, a disruptive mutation of TNFAIP3 was the most common alteration (54%), followed by mutations of TBL1XR1 (18%), cAMP response element binding proteins (CREBBP) (17%) and KMT2D (6%). All TBL1XR1 mutations were located within the WD40 domain, and TBL1XR1 mutants transfected into 293T cells increased TBL1XR1 binding with nuclear receptor corepressor (NCoR), leading to increased degradation of NCoR and the activation of NF-κB and JUN target genes. This study confirms genes involving in the activation of the NF-kB signaling pathway is the major driver in the oncogenesis of ocular MZL.

No abstract

BackgroundSide effects are unwanted responses to drug treatment and are important resources for human phenotype information. The recent development of a database on side effects, the side effect resource (SIDER), is a first step in documenting the relationship between drugs and their side effects. It is, however, insufficient to simply find the association of drugs with biological processes; that relationship is crucial because drugs that influence biological processes can have an impact on phenotype. Therefore, knowing which processes respond to drugs that influence the phenotype will enable more effective and systematic study of the effect of drugs on phenotype. To the best of our knowledge, the relationship between biological processes and side effects of drugs has not yet been systematically researched.MethodsWe propose 3 steps for systematically searching relationships between drugs and biological processes: enrichment scores (ES) calculations, t-score calculation, and threshold-based filtering. Subsequently, the side effect-related biological processes are found by merging the drug-biological process network and the drug-side effect network. Evaluation is conducted in 2 ways: first, by discerning the number of biological processes discovered by our method that co-occur with Gene Ontology (GO) terms in relation to effects extracted from PubMed records using a text-mining technique and second, determining whether there is improvement in performance by limiting response processes by drugs sharing the same side effect to frequent ones alone.ResultsThe multi-level network (the process-drug-side effect network) was built by merging the drug-biological process network and the drug-side effect network. We generated a network of 74 drugs-168 side effects-2209 biological process relation resources. The preliminary results showed that the process-drug-side effect network was able to find meaningful relationships between biological processes and side effects in an efficient manner.ConclusionsWe propose a novel process-drug-side effect network for discovering the relationship between biological processes and side effects. By exploring the relationship between drugs and phenotypes through a multi-level network, the mechanisms underlying the effect of specific drugs on the human body may be understood.

Studies of naturally occurring cancers in dogs, which share many genetic and environmental factors with humans, provide valuable information as a comparative model for studying the mechanisms of human cancer pathogenesis. While individual and small-scale studies of canine cancers are underway, more generalized multi-omics studies have not been attempted due to the lack of large-scale and well-controlled genomic data. Here, we produced reliable whole-exome and whole-transcriptome sequencing data of 197 canine mammary cancers and their matched controls, annotated with rich clinical and biological features. Our dataset provides useful reference points for comparative analysis with human cancers and for developing novel diagnostic and therapeutic technologies for cancers in pet dogs.

Graphene-based non-volatile memory devices composed of a single-layer graphene channel and an Al2O3/HfOx/Al2O3 charge-storage layer exhibit memory functionality. The impact of the gate material’s work-function (Φ) on the memory characteristics is investigated using different types of metals [Ti (ΦTi = 4.3 eV) and Ni (ΦNi = 5.2 eV)]. The ambipolar carrier conduction of graphene results in an enlargement of memory window (ΔVM), which is ∼4.5 V for the Ti-gate device and ∼9.1 V for the Ni-gate device. The increase in ΔVM is attributed to the change in the flat-band condition and the suppression of electron back-injection within the gate stack.