15016 results for "cancer studies using rna-seq"

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• Single_cell_measurements_to_characterise_B_cell_repopulation_in_SLE_after_rituximab_therapy__a_pilot_study

  Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterised by autoantibodies against DNA and nuclear proteins. Kidney involvement (lupus nephritis) is one of the most serious manifestations and is the leading determinant of long-term prognosis. Therapies targeting B cells (e.g. rituximab) are used in the treatment of severe lupus, including lupus nephritis. Rituximab is a monoclonal antibody that targets the CD20 surface protein on the surface of B cells. Following rituximab treatment, there is near complete depletion of B cells in peripheral blood. Peripheral blood B cells slowly return over a period of months. The speed of repopulation varies but typically B cells have returned to baseline levels between 9 and 12 months post rituximab therapy. Return of B cells may be associated with increased disease activity, but this is not always the case. For example, some patients remain in clinical remission for several years following one cycle of rituximab, despite B cell repopulation, whilst others relapse as soon as the B cell number reaches the normal range. The reasons for the different response remain unclear. The B cell subpopulations that return following B cell depleting therapy have been previously studied using flow cytometry but have never been characterised using single cell -omic technologies and thus no data on their molecular signatures are available. Previous studies have shown that naïve B cells were the predominant repopulating B-cells, indicating de novo production of B cells. Obtaining an integrated understanding of the molecular programs of these cells at the single cell level will enhance our ability to predict disease outcome, to identify patients with poorer B-cell drug responses, understand disease heterogeneity and design more effective B-cell targeted therapies approach.

  Study EGAS00001006798

• Acquired RAD51C promoter methylation loss causes PARP inhibitor resistance in high grade serous ovarian carcinoma

  Analysis of RAD51C promoter methylation using targeted bisulfite sequencing (amplicon sequencing) in ovarian cancer pre-clinical models and patient samples.

  Dataset EGAD00001007799

• Count Me In (CMI): The Metastatic Prostate Cancer (MPC) Project (CMI-MPCproject)

  Count Me In - The Metastatic Prostate Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Prostate Cancer Research The Metastatic Prostate Cancer Project (MPCproject; http://mpcproject.org/) is a research study that empowers men with metastatic and advanced prostate cancer to partner directly with researchers by sharing their samples and clinical information, with the ultimate goal of accelerating scientific discoveries that have clinical impact. The MPCproject enables any man with metastatic or advanced prostate cancer in the US and Canada to participate in cutting-edge genomic and molecular research, regardless of where they live. Metastatic or advanced prostate cancer patients visit the project website and complete an online questionnaire of basic information about themselves and their cancer. Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA, and transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided with updates on the study.

  Study phs001939

• Comprehensive gene analysis of colorectal cancer cases

  Colorectal cancer is the third most common morbidity and the fourth leading cause of cancer death in the world.To characterize the mutation profiles of colorectal cancer with liver metastasis,we performed both whole-exosome sequencing and RNA sequencing for 12 cases of colorectal cancer with liver metastasis (group A) and 16 cases of colorectal cancer without liver metastasis (group B). As a result of driver mutation search by Mutsig pipeline, PTEN was identified as a significant mutant gene in group A alone.ADAMTS10,NELL1 and RXFP3 were identified as candidate genes for metastasis by MuTect,SID and VarScan pipeline.Furthermore, in all samples, the copy number of chromosomes 1p,4,7,8,13,15, 17p,18,20 and 22q were significantly abnormal. Chromosomes 1p,4,15,18,17p,22q were deleted and chromosomes 7, 8,13 and 20 were amplified by CNV.Pathway analysed revealed Wnt/Ca2+ and PCP pathway was involved in metastasis of cl cancer.9 kinds of fusion genes were identified in deFuse pipeline. Among them, ADAP1 fusion genes were identified in 2 samples, and ADAP1 fusion genes were further identified in 3 samples by our in-house algorithm. It is suggested that new fusion genes present in such multiple samples may be involved in the development of colorectal cancer.

  Study JGAS000128

• Characterization of X Chromosome Inactivation Using Integrated Analysis of Whole-Exome and mRNA Sequencing

  This study of DNA and RNA sequencing of 5 parent-offspring trios is a single center study. The goal of this study is to characterize X chromosome inactivation (XCI) ratio in females using phased genomic variations obtained through whole genome or exome sequencing in trios, followed by allele-specific expression analysis of the phased, heterozygous alleles in the mRNA of the female offspring, and to apply this method to clinical diagnosis. The distribution of allele ratios across X obtained from mRNA sequencing allows for the estimation of X inactivation status of inherited X chromosomes, and the parameters of each parental allele distributions in the offspring's mRNA data can be used as determinants for XCI ratio. This approach was used to evaluate the contribution of skewed XCI ratio to phenotypic heterogeneity in an undiagnosed, mild neurological condition.

  Study phs000816

• Single-cell RNA sequencing data of peripheral blood mononuclear cells obtained from 30 ATL patients, 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Single-cell RNA sequencing (scRNA-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 30 ATL patients (34 samples including 4 sequential ones), 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Dataset EGAD00001007015

• Upper respiratory microbiome of COVID-19 patients

  Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 microbiome studies by analyzing the upper respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We found that time in the intensive care unit and the type of oxygen support explained the most variation within the upper respiratory tract microbiome, dwarfing (non-significant) effects from viral load, disease severity, and immune status. Specifically, mechanical ventilation was linked to altered community structure, lower species- and higher strain-level diversity, and significant shifts in oral taxa previously associated with COVID-19.

  Study EGAS00001004951

• Polygenic Risk Score for the Prediction of Breast Cancer Is Related to Lesser Terminal Duct Lobular Unit Involution of the Breast

  The Susan G. Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center is an annotated biobank, which has recruited healthy women who provided demographic, lifestyle, and cancer-related information via self-administered questionnaire, blood samples and normal breast tissues. H&E slides of the normal breast tissues were scanned for image analysis and a pathologist measured the number of terminal duct lobular units (TDLUs) ("TDLU count"). The acini count per TDLU was quantified using the TDLU analyzer software. In this analysis, we computed the recently developed polygenic risk score (PRS) based on 313 common variants for the prediction of breast cancer and related this PRS to TDLU count and acini count per TDLU. We did this for the overall PRS, the ER-positive PRS and the ER-negative PRS.

  Study phs002062

• MYC Inhibition By Omomyc Causes DNA Damage And Overcomes PARPi Resistance In Breast Cancer.

  This study investigates the role of MYC dysregulation in DNA damage response (DDR) and PARP inhibitor (PARPi) resistance in breast cancer. Using Omomyc, a direct MYC inhibitor, we demonstrate that MYC inhibition shuts down DDR genes in triple-negative breast cancer (TNBC), causing DNA repair defects and inducing DNA damage that synergizes with PARPi treatment. Through patient-derived models and clinical samples from metastatic HR-altered breast cancer patients treated with PARPi, we identify MYC transcriptional activity as a predictive biomarker of PARPi resistance. Digital spatial profiling (DSP) analysis of pre-treatment tumor biopsies reveals that patients with progressive disease have significantly elevated MYC signatures compared to responders. These findings support the therapeutic strategy of combining MYC inhibition with PARPi in PARPi-resistant breast cancers where high MYC activity predicts poor response to therapy.

  Study EGAS50000001347

• Custom long non-coding RNA capture enhances detection sensitivity in different human sample types.

  Long non-coding RNAs (lncRNAs) are a heterogeneous group of transcripts that lack protein coding potential and display regulatory functions in various cellular processes. As a result of their cell- and cancer-specific expression patterns, lncRNAs have emerged as potential diagnostic and therapeutic targets. The accurate characterization of lncRNAs in bulk transcriptome data remains challenging due to their low abundance compared to protein coding genes. To tackle this issue, we describe a unique short-read custom lncRNA capture sequencing approach that relies on a comprehensive set of 565,878 capture probes for 49,372 human lncRNA genes. This custom lncRNA capture approach was evaluated on various sample types ranging from artificial high-quality RNA mixtures to more challenging formalin-fixed paraffin-embedded tissue and biofluid material. The custom enrichment approach allows the detection of a more diverse repertoire of lncRNAs, with better reproducibility and higher coverage compared to classic total RNA-sequencing.

  Study EGAS00001005418

• Reconstructed VDJ sequences from Smart-seq2 data

  The dataset contains reconstructed VDJ sequences (fasta files) and accompanying metadata for each cell (csv file) from scRNA-seq data generated with the Smart-seq2 protocol. The VDJ sequences were reconstructed with the computational tool BraCeR using raw fastq files as input. The dataset contains sequences from 355 IgA+ peripheral blood B-lineage cells of two untreated celiac disease patients. The sequences comprise both IgA+ transglutaminase 2-specific and other IgA+ B cells.

  Dataset EGAD50000000341

• Human brain development single cell sequencing additional samples

  69 tissue samples from various parts of the developing human embryo brain were dissociated and single cells were collected and processed without bias for mRNA-seq using 10X chromium 3' protocol. Libraries were sequenced on Illumina NovaSeq and reads aligned against the human GRCh38 genome. This is an addition to EGAD00001006049 Human development single cell sequencing, consisting of samples added after the original submission to EGA, but included in final paper.

  Dataset EGAD50000001295

• COVID-19 Challenge Project Single Cell Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection.

  Dataset EGAD00001012227

• FFPE

  The mutational status of 112 recurrently mutated genes in B-cell lymphoma was examined by targeted next-generation sequencing (NGS). Libraries were performed with 150 ng of genomic DNA (gDNA) obtained from formalin-fixed paraffin-embedded (FFPE) biopsy using molecular-barcoded library adapters (ThruPLEX Tag-seq kit; Takara) coupled with a custom hybridization capture based method (SureSelect XT Target Enrichment System Capture strategy, Agilent Technologies Inc.) and sequenced in a MiSeq instrument (Illumina, 2x150bp).

  Dataset EGAD00001006565

• Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk paediatric cancer

  Zero Childhood Cancer is a precision medicine program to benefit children with poor-outcome, rare, relapsed or refractory cancer. Utilising tumour and germline whole genome sequencing (WGS) and RNA sequencing (RNAseq) across 252 tumours from high-risk paediatric cancer patients, we identified 968 reportable molecular aberrations (39.9% in WGS and RNAseq, 35.1% WGS-only, 25.0% RNAseq-only). 93.7% of patients had at least one germline or somatic aberration, 71.4% had therapeutic targets and 5.2% had a change in diagnosis. WGS identified pathogenic cancer-predisposing variants in 16.2% of patients. In 76 CNS tumours, methylome analysis confirmed diagnosis in 71.1% and contributed to a change of diagnosis in two cases (2.6%). To date 43 patients have received a recommended therapy, 38 of whom could be evaluated. A small but encouraging proportion of 31% showed some evidence of clinical benefit. Comprehensive molecular profiling resolved the molecular basis of virtually all high-risk cancers, which in some cases has significant clinical impact.

  Study EGAS00001004572