15075 results for "cancer studies using rna-seq"

in 17.58 milliseconds.

• Differentially methylated CpGs in response to growth hormone administration in children with idiopathic short stature

  Background: Recombinant human growth hormone (rhGH) has shown a great growth-promoting potential in children with idiopathic short stature (ISS). However, the response to rhGH differs across individuals, largely due to genetic and epigenetic heterogeneity. Since epigenetic marks on the methylome can be dynamically influenced by GH, we performed a comprehensive pharmaco-epigenomics analysis of DNA methylation changes associated with long-term rhGH administration in children with ISS. Results: We measured DNA methylation profiles before and after GH treatment (with a duration of ~18 months in average) on 47 healthy children using customized methylC-seq capture sequencing. Their changes were compared and associated with changes in plasma IGF1 by adjusting sex, age, treatment duration, and estimated blood proportions. We observed a considerable inter-individual heterogeneity of DNA methylation changes responding to GH treatment. We identified 267 response-associated differentially methylated cytosines (DMC) that were enriched in promoter regions, CpG islands and blood cell-type specific regulatory elements. Furthermore, the genes associated with these DMCs were enriched in the biology process of "cell development", "neuron differentiation" and "developmental growth", and in the TGF-beta signaling pathway, PPAR Alpha pathway, endoderm differentiation pathway, adipocytokine signaling pathway as well as PI3K-Akt signaling pathway, and cAMP signaling pathway. Conclusion: Our study provides a first insight in DNA methylation changes associated with rhGH administration, which may help understand mechanisms of epigenetic regulation on GH-responsive genes.

  Study EGAS00001006115

• Aspirin and Inflammation: Mutations, Genes, Pathways and Prevention in Barrett's Esophagus

  Background: Use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to protect against tetraploidy, aneuploidy, and chromosomal alterations in the metaplastic condition Barrett's esophagus (BE) and to lower the incidence and mortality of esophageal adenocarcinoma (EA). The esophagus is exposed to both intrinsic and extrinsic mutagens resulting from gastric reflux, chronic inflammation and exposure to environmental carcinogens such as those found in cigarettes. Here we test the hypothesis that NSAID use inhibits accumulation of point mutations/indels during somatic genomic evolution in BE. Methods: Whole exome sequences were generated from 82 purified epithelial biopsies and paired blood samples from a cross-sectional study of 41 NSAID users and 41 nonusers matched by sex, age, smoking, and continuous time using or not using NSAIDs. Results: NSAID use reduced overall frequency of point mutations across the spectrum of mutation types, lowered the frequency of mutations even when adjusted for both TP53 mutation and smoking status, and decreased the prevalence of clones with high variant allele frequency. Never smokers who consistently used NSAIDs had fewer point mutations in signature 17, which is commonly found in EA. NSAID users had on average a 50% reduction in functional gene mutations in nine cancer-associated pathways and also had less diversity in pathway mutational burden compared to nonusers. Conclusions: These results indicate NSAID use functions to limit overall mutations on which selection can act and supports a model in which specific mutant cell populations survive or expand better in the absence of NSAIDs. Galipeau PC, et al. Genome Med. 2018 Feb 27;10(1):17. PMID: 29486792.

  Study phs001654

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• Mayo Clinic and Illumina Collaborative Early Stage Ovarian Cancer (ESOC) Study

  Twenty five patients with early stage carcinoma (Stage I and II) of the ovary were consented for this study. As part of a collaborative agreement with Illumina Inc, Tumor-DNA and patient matched normal DNA from blood underwent whole genome sequencing and microarray genotyping and RNA underwent RNASeq. Tissue also underwent IHC staining for TP53 mutations. The aim of the study was to profile the genomic landscape of these early tumors to discover biomarkers for early detection or subgrouping into different genomic or outcome subgroups. Analyses performed include somatic mutation analysis, RNASeq mutation analysis, LOH analysis, structural variant detection. The current release of this study focusses on 17 patients with serous carcinoma and stage 1 or 2 and with high grade (3 or 4).

  Study phs000897

• DAC for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Data access comittee for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Dac EGAC50000000650

• RNA sequencing of mCRPC patient biopsies

  RNA sequencing of mCRPC patient biopsies obtained for the profiling of the prevalence of immune transcripts. Manuscript can be found at PMID: 35491356

  Dataset EGAD50000001811

• SIA Subtyping RNA Sequencing

  Associated with Molecular classification of small intestinal adenocarcinomas. RNA sequencing generated 849 .fastq files from 137 primary and recurrent small intestine adenocarcinoma samples from 135 patients.

  Dataset EGAD50000001762

• Single cell RNA sequencing of samples from core and periphery of human glioblastoma

  Samples taken from various regions of three human glioblastomas were subject to single cell RNA sequencing.

  Dataset EGAD50000002080

• Multiome sequencing of primary colon tissue and derived organoids

  Multiome (ATAC + RNA) sequencing of primary colon tissue and organoids derived from the same donors.

  Study EGAS00001008110

• Long non-coding RNA capture

  Capture lncRNA and totalRNA sequencing of various sample types (including plasma, FFPE and high quality RNA).

  Dataset EGAD00001007819