14982 results for "cancer studies using rna-seq"

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• A novel TP53-KPNA3 translocation defines a de novo treatment-resistant clone in osteosarcoma

  Osteosarcoma is the most common primary bone cancer. It can be cured by aggressive surgery and chemotherapy, but outcomes for metastatic or chemoresistant disease remain dismal. Cancer sequencing studies have shown that the p53 pathway is dysregulated in nearly every case, often by translocation; however, no studies of osteosarcoma evolution or intratumor heterogeneity have been done to date. We studied a patient with chemoresistant, metastatic disease over the course of three years. We performed exome sequencing on germline DNA and DNA collected from tumor at three separate timepoints. We compared variant calls and variant allele frequencies between different samples. We identified subclonal driver mutations in several different genes in the primary tumor sample and found that one particular subclone dominated subsequent tumor samples at relapse. This clone was marked by a novel TP53-KPNA3 translocation and loss of the opposite-strand wild-type TP53 allele. Future research must focus on functional significance of such clones and strategies to eliminate them.

  Study EGAS00001001805

• Cystic fibrosis multi-omics study

  Cystic fibrosis (CF) is a genetic disorder affecting approximately 1 in 2,500 people in the UK. Here, we generated a number of high-throughput sequence data sets for monocytes and neutrophils from CF patients and matched healthy volunteers (HV); including ChIP-Seq (H3K27Ac), chromatin accessibility (ATAC-Seq), and transcript/gene expression (RNA-Seq) data. Analysis of gene expression and epigenetic profiles demonstrates a robust innate immune gene expression profile that distinguishes CF and HV during periods of disease exacerbation. Upregulation of pathways responsible for the production of proinflammatory cytokines is described.

  Study EGAS00001006421

• scRaCH-seq data targeting BTK and SF3B1

  Data set for scRaCH-seq manuscript. We base call the fast5 using guppy.

  Dataset EGAD50000000235

• FASTQ Files for Human LV H3K27ac ChIP-seq

  This dataset contains 70 human LV H3K27ac ChIP-seq paired-end FASTQ files. The sequencing was performed using Illumina Hiseq 4000.

  Dataset EGAD00001004945

• Single-cell Profiling of an In Vitro Model of Human Interneuron Development Reveals Temporal Dynamics of Cell Type Production and Maturation

  GABAergic interneurons are essential for neural circuit function and their loss or dysfunction is implicated in human neuropsychiatric disease. In vitro methods for interneuron generation hold promise for studying human cellular and functional properties and ultimately therapeutic cell replacement. We used a protocol for generating cortical interneurons from hESCs and analyzed the properties and maturation timecourse of cell types using single-cell RNAseq (data available at GEO under: GSE93802 on March 10 2017). Transcriptomic profiles of the hESC-derived interneurons were compared to several different populations of cells from mid-gestation human neocortex that showed differing levels of PAX6 and SOX2 expression. For this study, 104 samples of 100 human neocortical cells each, have been sorted based on SOX2 and PAX6 expression, mRNA recovered from the fixed cells by FRISCR, and transcriptomic profiles generated by SmartSeq2. The RNA-seq data from the 104 100-cell samples is included in this dbGaP study.

  Study phs001276

• Functional Dynamics of the Elderly Gut Microbiome During Probiotic Consumption

  A mechanistic understanding of the health benefits conferred by consumption of probiotic bacteria has been limited by our knowledge of the resident gut microbiota and its interaction with the host. We used fecal samples from a study of twelve healthy individuals aged 65-80 to characterize the structure and functional dynamics of the gut microbiota associated with consumption of the single-organism probiotic, Lactobacillus rhamnosus GG ATCC 53103 (LGG). Samples were collected prior to probiotic consumption (day 0), on day 28 immediately after consuming 10^10 CFU of LGG twice daily for 28 days and day 56, one month after stopping LGG consumption. Our integrative approach incorporated bacterial 16S rRNA gene sequencing, whole-community expression profiling using RNA-seq, and metagenomic sequencing. We highlight the value of combinatorial 'omics methods and concomitant high-resolution informatics to probe the role that probiotics may play on the structure and function of the resident microbiota.

  Study phs000896

• Transcriptome alterations underlying metabolic dysfunction and liver disease in myotonic dystrophy type 1

  Myotonic dystrophy type 1 (DM1) is a multisystem disorder affecting various organs, including the skeletal muscles, eyes, heart, central nervous system, and endocrine system. Liver dysfunction and lipid metabolism abnormalities are frequently observed in DM1 but are not fully understood. To explore the molecular basis of these abnormalities, transcriptome analysis was performed on postmortem liver samples from DM1 patients DM1 patients (n = 11) and disease control patients (n = 9) using bulkRNA sequencing (RNA-seq) on the MGI DNBSEQ-G400RS. Differential gene expression and alternative splicing analyses revealed significant transcriptomic changes associated with lipid metabolism, liver fibrosis, and glucose homeostasis. Interestingly, transcriptome changes in DM1 livers also revealed partial resolution of sexual dimorphism in gene expression, along with unique sex-specific pathway alterations. A correlation between serum GGT levels and splicing abnormalities in DM1 patients was identified, suggesting a link between transcriptomic changes and clinical outcomes. This dataset provides valuable insights into the molecular mechanisms underlying DM1-related liver dysfunction and metabolic abnormalities.

  Study JGAS000814

• A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

  Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. The determination of TM-interconnectivity in individual tumors has been challenging and the impact on patient survival unresolved. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells has been established using a dye uptake methodology, confirmed with recording of cellular calcium epochs and validated with clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, network connectivity correlated with the mesenchymal subtype and dismal patient survival. CHI3L1 has been identified and validated as a robust molecular marker of connectivity with functional relevance. The connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients’ prognosis, and serves as a robust prognostic biomarker.

  Study EGAS00001007611

• Strand-seq of hematopoietic stem and progenitor cells along human aging

  Somatic mosaicism (SM), referring to the presence of somatic mutations in sub-populations of cells within healthy individuals, is associated with an increased risk of a variety of diseases, including cancer. Blood is at particularly high risk of SM, given its rapid turnover and functionally- heterogeneous cell-type composition. While the roles of point mutations and large-scale rearrangements in blood SM have been scrutinised in recent years, the functional impact of mosaic structural variants (mSVs) remains poorly understood. Using haplotype-resolved single-cell multi-omics based on Strand-seq technology, we explored the mSV landscape of human hematopoietic stem and progenitor cells (HSPCs).

  Dataset EGAD00001009402

• Cystic Fibrosis Varsity Project Multi-omics data

  This Dataset contains RNA-Seq, H3K27Ac ChIP-Seq, and ATAC-Seq data for 13 cystic fibrosis (CF) patients and 8 healthy volunteers (HV).

  Dataset EGAD00001009062

• Analysis of T-cell receptor clonotypes in tumor micro-environment identifies shared cancer type-specific signatures

  Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias towards the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T-cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus- driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T-cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (ie viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer, but in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific motifs that were unique to each cancer type, suggesting they may be enriched for specificity to common antigens found in the tumor microenvironment. The identification of shared TCRs in infiltrating tumor T-cells not only adds to our understanding of the tumor adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

  Study EGAS00001005480

• RIP-seq of SF3B4 binding RNA fragments

  There are 2 paired samples. The project aims to characterize SF3B4 binding RNA fragments within liver organoids to understand its role in splicing regulation

  Study EGAS50000001129

• The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

  RNA-seq data for ALL patients as described in "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001006335

• Germline Genomic Analyses of Breast Cancer in Latinas

  In this case-control study of breast cancer among Hispanic/Latina (H/L) women, the goals were to identify breast cancer susceptibility genes and genetic variants for risk of developing breast cancer in H/L women. There were two phases with whole exome sequencing (WES) done in a discovery phase and targeted sequencing of candidate genes in the replication phase. The candidate genes selected for replication came from the first phase and from genes known to affect breast cancer risk in prior studies. Cases and controls were drawn from several studies. Breast cancer cases for discovery phase included women from the City of Hope (COH) Clinical Cancer Genomics Community Research Network (CCGCRN), UCSF Cancer Genetics Clinic and USC Cancer Genetics clinic. Controls for discovery phase included women who did not have breast and were recruited through City of Hope community fairs. A separate group of controls included women from the California Teachers Study. Additional controls for discovery were obtained from WES already generated by the Multi-ethnic cohort (MEC) study. The discovery/WES results of known breast cancer genes were published (PMID 31206626). In the replication phase, we included cases and controls from the Cancer de Mama (CAMA) study which is a case-control study of breast cancer in Mexico, MEC for those not included in the discovery dataset, the San Francisco Bay Area Cancer study (phs000912), the Northern California Breast Cancer Registry, and the California Pacific Medical Center Research Institute Women's Cohort (phs000395). Cases from the PATHWAYS study who were recruited from Northern California Kaiser Permanente were also included. Results from the combined discovery and replication analyses are reported in PMID 36747679.

  Study phs003144

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265