12214 results for "cancer rna-seq"

in 17.05 milliseconds.

• RNA sequencing of PTCL-NOS

  Study EGAS00001005015

• Notch Signaling and Efficacy PD-1/PD-L1 Blockade in Relapsed Small Cell Lung Cancer

  Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine (NE) cancer that accounts for approximately 15% of all lung cancer, with an annual incidence of more than 34,000 in the United States alone. SCLC is characterized by loss of function of p53 and RB and high tumor mutational burden, which suggests that these tumors could be immunogenic and respond to immune checkpoint blockade (ICB). However, the benefit from ICB in an unselected SCLC population is modest. In this study, we evaluated the genomic features associated with clinical outcomes in relapsed SCLC to gain insight into the underlying mechanisms of ICB response. Exome, RNA and TCR sequencing data from a prospective clinical trial of relapsed SCLC treated with durvalumab and olaparib and RNA-sequencing data for second cohort of relapsed SCLC cohort treated with nivolumab are included.   

  Study phs002176

• Childhood Cancer Data Initiative (CCDI): OncoKids - NGS Panel for Pediatric Malignancies

  This study aimed to systematically collect clinical, registry and genomic data on pediatric cancer patients, and to contribute to the CCDI Pediatric Data Ecosystem. Clinical, treatment and outcome data on 1,039 pediatric cancer patients whose molecular profile was characterized on OncoKids gene panel at Children's Hospital Los Angeles was abstracted and harmonized for submission to the NCI’s Cancer Data Service. The OncoKids panel was designed to detect DNA mutations and amplification in almost 200 oncogenes and tumor suppressor genes, a limited number of pharmacogenomic targets and 1,700 disease-associated gene fusions at the RNA level. The panel encompasses the vast majority of FDA’s relevant pediatric molecular target list, as well as additional genes associated with ultra-rare pediatric tumors. The final data elements included DNA/RNA sequence data, OncoKids test results, clinical data on demographics, diagnosis, comorbidity and adverse events and treatment data.

  Study phs002518

• Ongoing_mutagenesis_RNAseq

  One of the key questions to be explored is whether the biological processes generating specific mutational signatures continue to operate in the human cancer cell lines or simply reflect past mutagenic activity which is no longer operative. To address this question, we have extracted mutational signatures from 1,000 cancer cell lines of diverse cancer types. Several cell lines with mutational signatures of interest were selected, subcloned over a defined period of time and their genomes sequenced. The increased load of the mutations representative of a specific mutational signature within the genome of a subclone when compared to its parental clone was informative of the on-going mutational processes. To further study the recent observation that some of the clones belonging to a same cell line acquired differencet numbers of mutations over a set period of time, their RNA will be subjected to RNA-sequencing to study their differences.

  Study EGAS00001002364

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models: validation cohort

  While cell-free DNA (cfDNA) in liquid biopsies is widely being used and investigated, free circulating RNA (extracellular RNA, exRNA) has the potential to improve therapy response monitoring and cancer detection due to its dynamic nature. A fundamental open question hampering the initiation of large-scale liquid biopsy collections for tumour exRNA analysis is that it remains unclear in which blood subcompartment tumour-derived exRNAs primarily reside. We set out to develop a host-xenograft deconvolution framework, exRNAxeno, with cDNA mapping strategies to either a combined human-mouse reference genome or both species genomes in parallel, that can be applied to exRNA sequencing data from liquid biopsies of human xenograft mouse models, enabling to distinguish (human) tumoural RNA from (murine) host RNA, and as such to specifically analyse tumour-derived exRNA. Subsequently, the preferred exRNAxeno combination pipeline was applied to total exRNA sequencing data from blood platelets and three plasma fractions from a breast cancer patient-derived and neuroblastoma cell line-derived xenograft mouse model. We show that tumoural exRNA concentrations are not determined by plasma platelet levels, while host exRNA concentrations increase with platelet content. Furthermore, a large variability in exRNA levels and gene content across individual mice is observed. In general, the tumoural gene detectability in plasma is correlated with the RNA expression levels in the tumour tissue or cancer cell line. Our results unravel new aspects of tumour-derived exRNA biology in xenograft mouse models.

  Study EGAS00001006582

• FASTQ files of the small RNA-Seq dataset from the POPS cohort

  Placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater(ThermoFisher). For each biopsy,total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. Total RNA-libraries were prepared from 300-500ng of total placental RNA with the “TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat”(Illumina). Small RNA-libraries were prepared from 150ng of total placental RNA with the “NEBNext Multiplex Small RNA Library Prep Kit for Illumina”(New England Biolabs)and concentrated using the “QIAquick PCR purification kit”(Qiagen). Paired libraries were combined and size selected using the Pippin Prep and 3% Agarose Gel Cassette with marker F (Sage Science),pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and HiSeq4000 instrument.

  Dataset EGAD00001004860

• Effects of 2DG, Galactose, or Oligomycin on the epigenome remodeling induce by T cells activation.

  T cell activation is known to require a metabolic shift towards glycolysis, triggered by TCR-engagement . To substantiate the role of glycolysis in transcriptional reprogramming during antigen-driven T cell activation, we utilized a well-established ex-vivo model to recapitulate the process of antigen stimulation without the requirement for additional antigen-presenting cells . We initially explored and validated the conditions for both metabolic and epigenetic reprogramming. Antigen-mediated CD4+ T cells activation initiates context-specific gene-expression programs that drive effector functions and cell fates through changes in the epigenetic landscape . To evaluate global changes in histone modifications, we isolated CD4+ T cells from peripheral blood (PB) of healthy control (HC) human donors and either maintained them in resting conditions or stimulated with anti-CD3/CD28 for 24h. Rapid changes in the CD4+ epigenome and transcriptome were observed within 24h as measured by RNA-sequencing (RNA-seq) and H3K27ac chromatin immunoprecipitation followed by DNA-sequencing (ChIP-seq).To explore the requirement for metabolic reprogramming in regulating transcriptional responses after initial TCR engagement, CD4+ T cells from PB of healthy donors were isolated and activated in either the presence or absence of oligomycin (inhibitor of ATP synthase blocking the production of ATP by OXPHOS), 2-deoxyglucose (2DG; competitively inhibiting production of glucose-6-phosphate from glucose), or replacement of glucose with galactose. Galactose is metabolized through glycolysis, utilizing the Leloir pathway which is energy neutral, forcing cells to use all the pyruvate production to sustain the TCA cycle for OXPHOS and ATP synthesis at the expense of lactate production. Employing ChIP-seq and RNA-seq, inhibition of OXPHOS-mediated ATP production by oligomycin had only a limited effect on H3K27-acetylation or activation-induced transcription during the first 24h of activation. In contrast, inhibition of glycolysis by 2DG treatment compromised both H3K27-acetylation and transcriptional changes. However, under conditions of galactose-metabolism where lactate production is abrogated, activated CD4+ T cells were still able to globally remodel H3K27 acetylation and reprogram the transcriptome.

  Study EGAS00001007115

• Multiregion Whole Exome and Smart-Seq3 single cell RNA sequencing of Breast Tumors

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Study EGAS00001006851

• Comprehensive molecular phenotyping of ARID1A-deficient gastric cancer reveals pervasive epigenomic reprogramming and therapeutic opportunities

  This dataset includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset.

  Dataset EGAD50000000660

• SGCC GASCAD-II dataset

  The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

  Dataset EGAD00001015433

• SCLC MeDIP-seq

  Methylation profile of 33 patients with small cell lung cancer (SCLC) for both, tumour and normal lung samples using MeDIP-seq.

  Dataset EGAD50000000724

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• Common Deleterious Germline Variants Shape the Urothelial Cancer Genome

  Our study used whole-exome, whole-genome, and RNA sequencing to analyze samples from primary tumors, locally recurrent or metastatic urothelial tumors collected over time, and matched normal urothelium. We described the molecular landscape of mutational signatures and structural variants in chemotherapy-resistant urothelial cancer.

  Study phs001087

• Expression profiles of DLL1 positive and negative subpopulations in metastatic colorectal cancer organoids under cetuximab treatment

  Bulk RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids subjected to cetuximab treatment and FACS-sorted according to DLL1 positivity. This study is part of a larger set of studies focused on investigating cetuximab induced populations in mCRC organoids

  Study EGAS50000001780

• CRUK Accelerator: Non-small cell lung cancer whole exome and RNA sequencing

  Whole exome and RNASeq raw sequencing data for a cohort 24 patients with non-small cell lung cancer, 15 adenocarcinoma (8 female, 7 male) and 9 squamous cell carcinoma(5 female, 4 male). Median age at diagnosis was 69. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001007934

• Human lymphoma plasma cfRNA - raw data

  This study contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma patients, 13 primary mediastinal large B-cell lymphoma patients and 22 cancer-free controls.

  Study EGAS00001007127

• Dataset of 5 RNAseq from 3 non-muscle-invasive bladder cancer patients

  RNAseq (FASTQ files) of 5 tumor from 3 non-muscle-invasive bladder cancer patients. For patient UC2, RNA from 3 different synchronous tumors was extracted. Relating to the other datasets from the project : no RNA was available from patient UC4. NB : patients aliases are the following : ROXY : UC1, OMAD : UC2, MAKI : UC3, HAPE : UC4

  Dataset EGAD50000002009

• RNA-seq on patient-derived, stage II, CRC cell lines

  The gut microbiome is a key player in the immunomodulatory and pro-tumorigenic microenvironment in colorectal cancer (CRC). It is well established that Fusobacterium’s virulence factors are responsible for its pro-tumorigenic properties, however the role of its metabolic cross-talk with the tumor remains unexplored. Here we use in vitro, in vivo, and in silico methods to describe a novel microbe-host interaction keystone: formate. Omics data reveals molecular signatures, linking a metabolically driven CRC phenotype with Fusobacteria. We observed a metabolic shift towards increased F. nucleatum formate secretion in gut-on-chip model co-cultures with patient-derived CRC cells, along with an accelerated cancer glutamine metabolism. We show that high formate levels trigger AhR signaling, increase cancer stemness and cellular invasion. Finally, we observed an expansion of Th17 cells accompanying F. nucleatum-induced tumorigenesis. Moving beyond observational studies, we applied new experimental approaches for gaining ecosystem-level mechanistic understanding of F. nucleatum’s role in cancer pathogenesis.

  Study EGAS00001005948

• 20210729_EGA_BrainMet Saunus et al J Path (2015)

  Exome sequencing on HiSeq platform of 36 brain metastases with matched normal samples, 32 having matched RNA seq. Published Saunus et al J Path, (2015); https://doi.org/10.1002/path.4583

  Dataset EGAD00001007973

• Dataset for Stromal-induced epithelial-mesenchymal transition induces drug resistance in acute lymphoblastic leukemia

  RNA-seq was performed to compare gene expression profiles between 11 patient adherent ALL samples and nonadherent ALL samples.

  Dataset EGAD00001009056

• Profiling human first-trimester neurodevelopment using scATAC-seq and multiomics

  116 single cell ATAC runs and 23 single cell multiome (ATAC+RNA) runs on various brain regions during human first-trimester development.

  Dataset EGAD00001011300

• Atezolizumab monotherapy following dCRT indicated a promising cCR rate in patients with unresectable locally advanced esophageal squamous cell carcinoma (EPOC1802)

  The objective is to analyze tumor and normal cell exome sequencing of esophageal cancer patients participating in the Tenergy trial before treatment and RNA sequencing specimens of tumor biopsy specimens at three points before treatment, after radiation chemotherapy, and after atezolizumab administration, in order to search for biomarkers to predict treatment response. Exome sequencing of pretreatment tumor tissue (27 specimens) and normal tissue (27 specimens) from esophageal cancer patients participating in the Tenergy trial, and RNA sequencing of tumor biopsy specimens at three time points before treatment (28 specimens), after radiation chemotherapy (25 specimens) and after atezolizumab administration (25 specimens).

  Study JGAS000708

• scRNA-seq and snRNA-seq of trophoblast stem cells (TSCs) differentiation into extravillous trophoblast organoids (EVTs)

  This dataset is part of a study that aims to compare in vivo human trophoblast differentiation into EVTs to different in vitro trophoblast organoids using single-cell and single-nuclei RNA sequencing. This specific dataset includes scRNA-seq and snRNA-seq data from trophoblast stem cells (TSCs). Trophoblast stem cell (TSC) lines BTS5 and BTS11 derived by Okae and colleagues were grown as described previously (Okae et al. 2018) together with EVT differentiation media. This study shows that the main regulatory programs mediating EVT invasion in vivo are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. Data for primary trophoblast organoids is available under E-MTAB-12650.

  Dataset EGAD00001010017

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• PCA Atlas Chromium scRNA-seq and demultiplexing support (FASTQs, BAMs, capture-level VCFs and mapping tables)

  This dataset contains Chromium single-cell RNA-seq data and demultiplexing support for the PCA Atlas study EGAS00001008332. Included data objects: - 16 Chromium scRNA-seq FASTQ runs (EGAR accessions) for captures PCa1–PCa16. - 16 aligned BAM analyses (one Cell Ranger possorted_genome_bam.bam per capture). - 16 capture-level genotype VCF analyses derived from the Axiom UK Biobank array, used as demultiplexing panels. - demux_map.csv (EGAZ00001945520): donor–capture–sample mapping for genotype-based demultiplexing. - chromium.csv (EGAZ00001945537): run-level mapping linking captures, EGA samples, runs (EGAR), experiments (EGAX) and BAM analyses. Together these objects provide a complete view of the Chromium scRNA-seq data and the genotype-based demultiplexing support needed to reproduce donor assignment and downstream analyses.See also https://zenodo.org/records/17372603

  Dataset EGAD00001015795