14983 results for "cancer studies using rna-seq"

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• Single-cell transcriptomics of hepatoblastoma

  10X Genomics single-cell transcriptomics of hepatoblastoma tissues using Chromium Next GEM Single-Cell 3’ Reagent Kits v3.1. Single-cell transcriptomics data (bam files) of PT9, post-chemotherapy tumor sample, and PT13, treatment naive tumor sample. Single-cell solutions were obtained from viably frozen tissue samples using enzymatic digestion.

  Dataset EGAD50000000794

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese B cell DNA bank; We sequenced those genomic DNAs using PacBio and 10X Genomics sequencing technologies, and analyzed genomic structural variations.

  Study JGAS000173

• Genomic Structural Variants in Japanese Malignant mesothelioma patients

  We extracted genomic DNAs from established mesothelioma cell lines from Japanese malignant mesothelioma patients. We sequenced those genomic DNAs using 10X Genomics sequencing technologies, and analyzed genomic structural variations.

  Study JGAS000176

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese B cell DNA bank; We sequenced those genomic DNAs using PacBio Sequel and Sequel II and analyzed genomic structural variations.

  Study JGAS000286

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set6)

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one B-other ALL patients (ALLK-138). Sequencing library was made using Novogene NGS DNA Library Prep Set. Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002161

• WES data generated in multifocal ileal NETs study

  This dataset includes whole-exome sequencing data for multifocal ileal tumor samples from two patients. Exonic sequences were enriched using the Agilent V2 capture probe set and sequenced by 76-bp paired-end reads using the Illumina Genome Analyzer IIx system with a mean coverage of 80x for each base

  Dataset EGAD00001006408

• Illumina whole genome sequencing data for two patients with congenital disease

  BAM files with sequencing reads derived from Illumina whole genome sequencing of two DNA samples from lymphoblastoid cell lines from two patients with congenital disease. Whole genome sequencing was performed using Illumina HiSeq X Ten and samples were prepared using TruSeq library prep.

  Dataset EGAD00001003510

• WES data of primary tumors and metastasis corresponding to three patients

  Fastq files of WES data. Primary tumor and/or metastasic samples of three chRCC patients. DNA libraries were produced using the SureSelect XT HumanAllExon V5 kit (Agilent Technologies), and sequencing was performed in a HiSeq instrument (Illumina) using a 100-bp paired-end mode.

  Dataset EGAD00001010173

• Chromatin_Profiling_in_Twins

  50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, subjected to Chromatin Immunoprecipitation using an antibody for H3K4me1. H3K4me1 peaks mark distal regulatory elements.

  Study EGAS00001000098

• Covid19 WGS Raw Read files

  The Samples were collected from Saint James's Hospital, Dublin and after informed consent Extracted Genomic DNA samples were prepared and sequenced using the Automated Illumina TruSeq PCR-free methodology.

  Study EGAS00001007106

• BRCA Mutation Status Shapes the Microenvironment of Pancreatic Adenocarcinoma

  This study was established in order to address how the stromal landscape is influenced by BRCA-mutated and BRCA Wild-type (WT) pancreatic ductal adenocarcinoma (PDAC). A primary cohort of 12 PDAC patients (7 BRCA-WT and 5 germline BRCA-mut) was analyzed by laser-capture microdissection, RNA-sequencing and multiplexed immunofluorescence.

  Study phs002994

• T-cell receptor repertoire profiling (PBMC)

  This study assessed the TCR repertoire in peripheral blood from patients before, during and after neoadjuvant chemoimmunotherapy. TCR beta chain sequences in RNA from peripheral blood were amplified with the OncomineTM long read assay, templated and sequenced. TCR metrics such as clonality, evenness and diversity were assessed in relation with response metrics.

  Study EGAS50000001137

• T-cell receptor repertoire profiling (FFPE tissue)

  This study assessed the TCR repertoire in tumor tissue from NSCLC patients before, during and after neoadjuvant chemoimmunotherapy. TCR beta chain sequences in RNA from FFPE tissue were amplified with the OncomineTM short read assay, templated and sequenced. TCR metrics such as clonality, evenness and diversity were assessed in relation with response metrics.

  Study EGAS50000001138

• Transcriptomic analysis of hiPSC-derived vascular cells from CADASIL and isogenic control patient lines

  Bulk-RNA sequencing from hiPSC-derived cells (hiPSC; Endothelial Cells; Neural Crests Cells; Vascular Smooth Muscle Cells) from CADASIL patient lines (n=3) and respective isogenic-controls (n=3). CADASIL is a hereditary brain small vessel disease caused by pathogenic variants in the NOTCH3 gene, which lead to deposits of NOTCH3 protein in the walls of small arteries. This causes pathological vessel wall changes including degeneration of vascular smooth muscle cells. To investigate the impact of pathogenic NOTCH3 variants in hiPSC and differentiated cells we performed a bulk-RNA sequencing.

  Dataset EGAD50000002181

• Epithelioid sarcoma dataset

  This deposit consists of DNA and RNA sequencing data from 32 EPS patients. 28 samples had tumor DNA sequencing data. 2 had matched normal sequencing data. 27 samples had tumor RNA sequencing data.

  Dataset EGAD00001008515

• RNA sequencing of CD8 T cells from melanoma patients prior to and during checkpoint immunotherapy and untreated healthy controls

  We are interested in inter-individual variation in transcriptional response to immune checkpoint blockade. We have analysed poly A purified RNA expression from CD8 T cells (297 transcriptomes in total) isolated from metastatic melanoma patients (n=106) prior to and during treatment with either single agent (Pembrolizumab) or combination (Ipilimumab/ Nivolumab) immune checkpoint blockade. We compare expression at different stages of treatment and additionally contrast this with that from healthy controls (n=68).

  Dataset EGAD00001005973

• Analysis_of_resistance_to_PLX4032

  We have collected material from a patient who had BrafV600E mutant melanoma that wastreated with PLX4032. We have germline DNA from the patient and DNA and RNA fromdistinct lesions before and after treatment with PLX4032. We would like to exome sequencethese samples to gain a snap shot of the mechanisms of resistance that are operative.

  Study EGAS00001000415

• Oncogenic gene fusions in primary colon cancers

  This study represents RNA-sequencing data from 278 primary colon cancers obtained from fresh-frozen tumor sections. The project goal was to identify novel oncogenic gene fusions in these data. In addition, we studied the detected gene fusions at the molecular level and defined their effects on downstream pathways.

  Study EGAS00001002197

• Hypothalamic transcriptome in Prader-Willi syndrome

  Transcriptional analysis of brain tissue from people with molecularly defined causes of obesity may highlight novel disease mechanisms and therapeutic targets. Prader-Willi syndrome (PWS) is a genetic obesity syndrome characterised by severe hyperphagia. We performed RNA sequencing of the hypothalamus from 4 individuals with PWS and 4 age-matched controls.

  Study EGAS00001002901

• The_Transcriptome_of_PLX4032_resistance

  We have collected material from a patient who had BrafV600E mutant melanoma that wastreated with PLX4032. We have germline DNA from the patient and DNA and RNA fromdistinct lesions before and after treatment with PLX4032. We have transcriptome sequenced these samples to obtain a snap shot of the mechanisms of resistance that are operative.

  Study EGAS00001000413

• Whole-genome and transcriptome sequencing of tumor-stage mycosis fungoides

  Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma (CTCL), a group of malignancies derived from skin-homing malignant T cells. We subjected tumor biopsies from MF patients to whole-genome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001002860

• The genomic landscape of primary cutaneous anaplastic large cell lymphoma (pcALCL)

  Primary cutaneous anaplastic large cell lymphoma (pcALCL) is the second most common variant of cutaneous T-cell lymphoma. We subjected tumor biopsies from patients with pcALCL to whole-genome sequencing, whole-exome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001004429

• Natural Killer Cell Plasticity During IL-15-driven Homeostatic Proliferation

  Here we performed single-cell RNA sequencing to address repertoire stability and subset plasticity during IL-15 driven homeostatic proliferation. Sorted NK cell subsets representing discrete stages of NK cell differentiation are compared with the corresponding subsets after proliferation and further sorted into two subsets depending on the rate of proliferation.

  Study EGAS00001003946

• Transcriptomic signatures of CD4+ T cells from visceral leishmaniasis (VL) patients

  Bulk RNA-sequencing was performed on CD4+ T cells isolated from the blood of visceral leishmaniasis patients (n = 12) and endemic controls (EC; n = 12). CD4+ T cells were obtained by magnetic-activated cell sorting (MACS). Alterations in the transcripts of T helper (Th) cells during infection were identified.

  Study EGAS00001004152

• Facioscapulohumeral dystrophy transcriptome signatures correlate with different stages of disease and are marked by different MRI biomarkers

  This project includes RNA-sequencing data from human FSHD and control skeletal muscle biopsies. This project includes data from 28 FSHD patients (total 37 samples, including vastus lateralis and tibialis anterior muscles) and 12 control individuals (total 24 samples, including vastus lateralis and tibialis anterior muscles).

  Study EGAS00001005782

• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). 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. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; 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 updates on the study.

  Study phs001931

• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

  Study phs001680

• Blood Somatic Mutations in TCGA Donors Suffering from Solid Tumors

  Blood somatic mutations identified across 8,530 solid tumor patients in TCGA cohort. We reasoned that low-coverage whole-genome sequencing of blood samples routinely carried out in cancer genomics projects may be repurposed to detect clonal hematopoiesis (CH). Thus, inspired by a previous approach to identify early mutations in the development of the hematopoietic system, we implemented a pipeline to systematically carry out this "reverse" somatic mutation calling on the paired blood/tumor samples. Blood somatic mutations were called using a 'reverse' approach, in which the tumor sample taken from each patient was used as control of their germline genome. Blood somatic mutations are thus detected as variants in the blood (with respect to the human reference genome) that are absent in the tumor sample. The variant calling was carried out in our in house cluster on downloaded blood/tumor BAM files. The matched blood and tumoral BAM files -- masked and deduplicated using GATK -- of 8,530 whole-exome patients were obtained as described above. The variant calling was carried out using Strelka2 (employing default parameters) with the blood sample as the tumoral input and the tumor sample as control (reverse calling). All variants with two or more supporting reads matching the caller PASS filter and with VAF<0.5 were kept. Mutations in lowly mappable regions as defined by the DUST algorithm (k=30) and UMAP68 (36-kmers) were excluded. Contiguous variants were merged into double-base substitutions. Variants with greater frequency across the cohorts than the DNMT3A R882H or JAK2 V617F hotspot in a cohort-specific Panel of Normals and in gnomAD v2.1 were removed. This was equivalent to discarding variants present in these datasets with an allele frequency greater than 0.008 in PoN TCGA and 0.0003 in gnomAD v2.1. Additionally, common SNPs as defined by the dbSNP 151 Common UCSC track and dbSNP were excluded. Mutations within segmental duplications, simple repeats and masked regions as defined in UCSC tracks were also removed. Finally, samples with the mutation count above the 97.5 percentile of the mutation burden across the cohort were deemed unreliable and excluded for further analyses. We call the set of variants obtained after the application of these filters the full set. A more conservative subset of somatic mutations was generated from the full set of blood somatic mutations. To this end, we applied MosaicForecast, a software designed to phase mutations to polymorphisms with the aim of identifying somatic mutations in a small number of cells and also predict mosaicism for the unphased ones with a random forest classifier. As a result, we obtained a subset of mosaic-phased mutations, and a subset of mutations likely to be somatic (mosaic set).In order to obtain access to this study, please first obtain access to TCGA study (phs000178).

  Study phs002867

• The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

  Purpose In high-grade osteosarcoma, prognostic factors at diagnosis are insufficient for stratifying patients into relevant subgroups. Recently, a transcriptomic study developed the G1/G2 gene expression signature, in which the G2 signature was associated with unfavorable survival. An orthogonal study identified MYC amplification as an unfavorable prognostic factor using targeted next-generation sequencing. The purpose of this study was to validate the independent prognostic value and to investigate the combined prognostic value of the G1/G2 signature with, MYC amplification and/or MYC expression for survival prediction. Material and methods This study included pediatric and adolescent patients with high-grade osteosarcoma. RNA sequencing was performed in 48 patients. Whole-exome sequencing was performed in 40 patients. Gene expression signature scores, MYC amplification (defined as > 7 copies) and MYC expression levels were calculated. Multivariable Cox proportional hazards analysis was performed for event-free survival (EFS) (primary endpoint) and overall survival (OS) (secondary endpoint). Results In the full cohort, the 3-year event-free survival rate was 37%. In multivariable Cox regression analysis with metastatic disease stage (n=21, 44%) as covariate, the G2 signature and MYC expression were independently associated with worse outcomes in terms of EFS (Hazard ratio (HR) 3.32, 95% confidence interval (CI) 1.34-8.21 and HR 3.38, 95%-CI 1.71-6.66, respectively) and OS (HR 4.07, 95%-CI 1.19-13.9 and HR 2.88, 95%-CI 1.22-6.76, respectively). MYC amplification was not associated with EFS or OS in univariable analysis (HR 1.88, 95% -CI 0.74-4.77 and HR 0.79, 95%-CI 0.21-3.05, respectively). Conclusion The G2 gene expression signature and MYC expression were independently associated with unfavorable outcomes in a pediatric cohort of patients with high-grade osteosarcoma. The combined prognostic value warrants further prospective validation and could potentially serve as a stratification marker for future osteosarcoma treatment protocols.

  Study EGAS00001008073

• RNA Editing Transcriptome

  Transcriptome sequencing data of tumor and 10 matched normal samples of the EGAS00001000495 project

  Dataset EGAD00001000627