Copy number alterations in urothelial carcinomas: their clinicopathological significance and correlation with DNA methylation alterations

The aim of this study was to clarify the genetic backgrounds underlying the clinicopathological characteristics of urothelial carcinomas (UCs). Array comparative genomic hybridization analysis using a 244K oligonucleotide array was performed on 49 samples of UC tissue. Losses of 2q33.3–q37.3, 4p15.2–q13.1 and 5q13.3–q35.3 and gains of 7p11.2–q11.23 and 20q13.12–q13.2 were correlated with higher histological grade, and gain of 7p21.2–p21.12 was correlated with deeper invasion. Losses of 6q14.1–q27 and 17p13.3–q11.1 and gains of 19q13.12–q13.2 and 20q13.12–q13.33 were correlated with lymph vessel involvement. Loss of 16p12.2–p12.1 and gain of 3q26.32–q29 were correlated with vascular involvement. Losses of 5q14.1–q23.1, 6q14.1–q27, 8p22–p21.3, 11q13.5–q14.1 and 15q11.2–q22.2 and gains of 7p11.2–q11.22 and 19q13.12–q13.2 were correlated with the development of aggressive non-papillary UCs. Losses of 1p32.2–p31.3, 10q11.23–q21.1 and 15q21.3 were correlated with tumor recurrence. Unsupervised hierarchical clustering analysis based on copy number alterations clustered UCs into three subclasses: copy number alterations associated with genome-wide DNA hypomethylation, regional DNA hypermethylation on C-type CpG islands and genome-wide DNA hypo- and hypermethylation were accumulated in clusters A, B1 and B2, respectively. Tumor-related genes that may encode therapeutic targets and/or indicators useful for the diagnosis and prognostication of UCs should be explored in the above regions. Both genetic and epigenetic events appear to accumulate during urothelial carcinogenesis, reflecting the clinicopathological diversity of UCs

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Caching Strategies for Run-time Probabilistic Model Checking

Abstract-For software systems that need to adapt to their environment at run-time, run-time verification is useful to guarantee the correctness of their behaviors. Probabilistic model checking using discrete time Markov chain (DTMC) model has been applied to implement run-time verification. A current existing approach provides an efficient run-time verification mechanism by pre-generating expressions for model checking at design time. In case that a system model is changed, the system is required to re-generate the expressions. In order to expand the applicability of the approach, we propose three strategies, caching, prediction, and reduction, for reducing computational time for re-generated expressions at run-time. We conduct preliminary experiments and demonstrate that our approach could expand the applicability of run-time verification by reducing the computational cost at runtime

Towards Automatic Requirements Elicitation from Feedback Comments: Extracting Requirements Topics Using LDA

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