BackgroundThe extent to which metastatic tumors further evolve by accumulating additional mutations is unclear and has yet to be addressed extensively using next-generation sequencing of high-grade serous ovarian cancer.MethodsEleven spatially separated tumor samples from the primary tumor and associated metastatic sites and two normal samples were obtained from a Stage IIIC ovarian cancer patient during cytoreductive surgery prior to chemotherapy. Whole exome sequencing and copy number analysis were performed. Omental exomes were sequenced with a high depth of coverage to thoroughly explore the variants in metastatic lesions. Somatic mutations were further validated by ultra-deep targeted sequencing to sort out false positives and false negatives. Based on the somatic mutations and copy number variation profiles, a phylogenetic tree was generated to explore the evolutionary relationship among tumor samples.ResultsOnly 6% of the somatic mutations were present in every sample of a given case with TP53 as the only known mutant gene consistently present in all samples. Two non-spatial clusters of primary tumors (cluster P1 and P2), and a cluster of metastatic regions (cluster M) were identified. The patterns of mutations indicate that cluster P1 and P2 diverged in the early phase of tumorigenesis, and that metastatic cluster M originated from the common ancestral clone of cluster P1 with few somatic mutations and copy number variations.ConclusionsAlthough a high level of intratumor heterogeneity was evident in high-grade serous ovarian cancer, our results suggest that transcoelomic metastasis arises with little accumulation of somatic mutations and copy number alterations in this patient.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1077-4) contains supplementary material, which is available to authorized users.
The chemical structure of a polyphenol compound and its inhibitory activity against ZIKV NS2B-NS3 can be explored to develop highly selective inhibitors against ZIKV NS2B-NS3.
Infection with Clostridium difficile is a growing concern because of the increasing prevalence and spread of nosocomial infections. Emergence of the hypervirulent 027/NAP1/BI strain is also notable. Existing diagnostic methods have low sensitivity or are time-consuming. Therefore, establishing a rapid and accurate microbiological diagnostic assay is needed. We evaluated the Xpert C. difficile assay (Xpert CD assay; Cepheid, USA) to detect toxigenic C. difficile. This assay is a real-time multiplex PCR assay that can be used to detect toxigenic C. difficile strains and differentiate the C. difficile presumptive 027/NAP1/BI strain. A total of 253 loose stool specimens were collected and toxigenic cultures, VIDAS C. difficile A & B assays (VIDAS CDAB assay; bioMérieux, France), and the Xpert CD assay were performed. In comparison to toxigenic cultures, the sensitivity, specificity, and positive and negative predictive values were 100%, 94.6%, 83.1%, and 100%, respectively, for the Xpert CD assay and 40.8%, 98.0%, 100%, and 88.9%, respectively, for VIDAS CDAB assay. Because of the low prevalence of the PCR ribotype 027 in Korea, the evaluation of the usefulness of the Xpert CD assay for screening for the 027 strain was limited. The Xpert CD assay provides great sensitivity in diagnosing toxigenic C. difficile infection. In addition, this method has excellent usability because it is simple and fast.
CRISPR-based screening methods using single-cell RNA sequencing (scRNA-seq) technology enable comprehensive profiling of gene perturbations from knockout mutations. However, evaluating substitution mutations using scRNA-seq is currently limited. We combined CRISPR RNA-guided deaminase and scRNA-seq technology to develop a platform for introducing mutations in multiple genes and assessing the mutation-associated signatures. Using this platform, we generated a library consisting of 420 sgRNAs, performed sgRNA tracking analysis, and assessed the effect size of the response to vemurafenib in the human melanoma cell line, which has been well-studied via knockout-based drop-out screens. However, a substitution mutation library screen has not been applied and transcriptional information for mechanisms of action was not assessed. Our platform permits discrimination of several candidate mutations that function differently from other mutations by integrating sgRNA candidates and gene expression readout. We anticipate that our platform will enable highthroughput analyses of the mechanisms related to a variety of biological events.
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