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Random Telegraph Noise (RTN) is one of the major reliability concerns in nanoscale complementary metal-oxide semiconductor (CMOS) technologies. In this paper, we discuss the characterization of RTN in 40 nm CMOS technology using Ring Oscillators (ROSCs). We used different types of ROSCs to study the temporal and spectral characteristics of the RTN. We conducted measurements on one of the arrays with 128 identical ROSC cells. These results enabled statistical characterization of the RTN amplitude strength and its frequency characteristics in different supply voltage variations from 0.5 V to 0.7 V. At power supply of 0.65 V, dominant and observable RTN amplitude above 0.37% Δ f / f mean is found in 60% of cells in the array. Further, the capture and emission time constant τ e / / c can be extracted from the measurements, the values observed ranging from 0.2  μ s to 10 ms., (© The Author(s) 2023.)

Primary clear cell renal cell carcinoma (ccRCC) has been previously characterized, but the genomic landscape of metastatic ccRCC is largely unexplored. Here, we performed whole exome sequencing (WES) in 68 samples from 44 patients with ccRCC, including 52 samples from a metastatic site. SETD2, PBRM1, APC and VHL were the most frequently mutated genes in the metastatic ccRCC cohort. RBM10 and FBXW7 were also among the 10 most frequently mutated genes in metastatic tissues. Recurrent somatic copy number variations (CNV) were observed at the previously identified regions 3p25, 9p21 and 14q25, but also at 6p21 (CDKN1A) and 13q14 (RB1). No statistically significant differences were found between samples from therapy-naïve and pretreated patients. Clonal evolution analyses with multiple samples from 13 patients suggested that early appearance of CNVs at 3p25, 9p21 and 14q25 may be associated with rapid clinical progression. Overall, the genomic landscapes of primary and metastatic ccRCC seem to share frequent CNVs at 3p25, 9p21 and 14q25. Future work will clarify the implication of RBM10 and FBXW7 mutations and 6p21 and 13q14 CNVs in metastatic ccRCC., (© 2022 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Background: DNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions., Results: Using GTEx samples, we generate a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12 to 23 donors. We identify differentially methylated regions between brain regions among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pairwise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identify unique CpG differentially methylated regions, many associated with ion transport. We also identify 81,130 regions of variably CpG methylated regions, i.e., variable methylation among individuals in the same brain region, which are enriched in regulatory regions and in CpG differentially methylated regions. Many variably methylated regions are unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. Variably methylated regions identified in the amygdala, anterior cingulate cortex, and hippocampus are enriched for heritability of schizophrenia., Conclusions: These data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder.

Context.—: An increasing number of molecular laboratories are implementing next-generation sequencing platforms to identify clinically actionable and relevant genomic alterations for precision oncology., Objective.—: To describe the validation studies as per New York State-Department of Health (NYS-DOH) guidelines for the Oncomine Comprehensive Panel v2, which was originally tailored to the National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) trial., Design.—: Accuracy, precision, and reproducibility were investigated by using 130 DNA and 18 RNA samples from cytology cell blocks; formalin-fixed, paraffin-embedded tissues; and frozen samples. Analytic sensitivity and specificity were tested by using ATCC and HapMap cell lines., Results.—: High accuracy and precision/reproducibility were observed for single nucleotide variants and insertion/deletions. We also share our experience in the detection of gene fusions and copy number alterations from an amplicon-based sequencing platform. After sequencing analysis, variant annotation and report generation were performed by using the institutional knowledgebase., Conclusions.—: This study serves as an example for validating a comprehensive targeted next-generation sequencing assay with both DNASeq and RNASeq components for NYS-DOH., (© 2020 College of American Pathologists.)

The lack of in vitro prostate cancer models that recapitulate the diversity of human prostate cancer has hampered progress in understanding disease pathogenesis and therapy response. Using a 3D organoid system, we report success in long-term culture of prostate cancer from biopsy specimens and circulating tumor cells. The first seven fully characterized organoid lines recapitulate the molecular diversity of prostate cancer subtypes, including TMPRSS2-ERG fusion, SPOP mutation, SPINK1 overexpression, and CHD1 loss. Whole-exome sequencing shows a low mutational burden, consistent with genomics studies, but with mutations in FOXA1 and PIK3R1, as well as in DNA repair and chromatin modifier pathways that have been reported in advanced disease. Loss of p53 and RB tumor suppressor pathway function are the most common feature shared across the organoid lines. The methodology described here should enable the generation of a large repertoire of patient-derived prostate cancer lines amenable to genetic and pharmacologic studies., (Copyright © 2014 Elsevier Inc. All rights reserved.)