15075 results for "cancer studies using rna-seq"

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• Bulk RNA sequencing of hematological toxicity following CAR-T cells injection

  Bone marrow aspirations obtained from patients treated with CAR-T cells were analyzed using bulk RNA sequencing (CD3+, CAR T+, CD34+ sorted populations).

  Study EGAS50000000777

• Bulk RNA from sorted CD8+ T cells after 48h co-culture with human Mito-DsRed MSCs.

  For human samples, total cellular RNA was isolated from post-sorted Mito+ and Mito CD8+ cells using the RNeasy Mini Kit (Qiagen). Stranded RNA libraries were created using SMARTSeq Stranded.

  Dataset EGAD00001011082

• R compatible Seurat's objetc .rds files with count data and metadata from single cell RNA seq analysis to characterize the prostate cancer tumoral microenviroment of 31 fusion biopses.

  Pre-processed Seurat objects with cellular and functional annotation information from the scRNAseq study on PC fusion biopsy samples. The data consists of rds files composed of normalised counts matrices, normalised and scaled counts, functional enrichment counts at the cellular level and metadata with patient grouping and cellular annotation variables. There are 3 .rds files, one with the total cells (SCP_data_analysis), with the selection of cells annotated as cancerous (selected_cancer_analysis) and cancer-associated fibroblasts (selected_caf_analysis).

  Dataset EGAD50000001298

• DAC_RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Data access committee for RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Dac EGAC50000000352

• 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

• Genomics_of_acral_lentiginous_melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003740

• South Asia Rheumatic Heart Disease Genetics Network

  Rheumatic heart disease (RHD) is a major cause of cardiovascular death and disability amongst young adults. Building on a sample collection established for and genotyped in several earlier successful candidate gene studies, this case-control study investigated host genetic susceptibility to RHD using a genome-wide approach. The current dataset comprises over 850 individuals recruited in Uttar Pradesh, India, including cases of RHD based on echocardiographic diagnosis and controls recruited on the basis of normal echocardiograms. For this analysis all available samples were genotyped using the Illumina HumanCore-24 BeadChip platform. Efforts are now underway to establish new sample collections in other areas of India as well as Pakistan and later other neighbouring countries.

  Study EGAS00001003565

• Bulk RNA-seq paired fastq files from i3Ns harbouring a SNCA A53T mutation, with or without RSL3 treatment

  FASTQ files from bulk RNA sequencing of a iPSC-derived rapid neuronal model (i3Ns) harbouring the SNCA A53T mutation in a WTC11 background as a model of synucleinopathy, with or without treatment of 300nM RSL3 for 6 hours. Libraries were prepared using the Watchmaker rRNA and globin depletion kit and sequenced on a NovaSeq X with an average depth of ~27 million paired-end reads with a fragment length of 100 base pairs, per sample. 19 samples are included in this dataset, each with two paired fastq files (R1 and R2). The dataset includes control neurons (WT: dcas9 parental line and C4 CRISPR control) and A53T clones (B7, H8 and L8) across two neuronal inductions (ind1 vs ind2), with or without treatment of RSL3 (UT vs. RSL3).

  Dataset EGAD50000002209

• Covid19 Transcriptomic Data analysis in Irish Population

  The Samples were collected from Saint James's Hospital, Dublin and after informed consent. RNA-Sequencing library preparation was performed using the Illumina TruSeq Stranded Total RNA Library Prep Globin kit (20020612) with an input amount of 100 – 1000 ng. Library preparation was automated and processed using a Hamilton NGS Star. Library quality was assessed using the Roche KAPA Library Quantification Kit (7960298001) and GX Caliper HS Assay (CLS760672, 760517), run on Roche Lightcycler 480 II and Perkin Elmer LabChip GX Touch analyser respectively. Libraries were pooled and sequenced (75bp PE) on an Illumina NovaSeq 6000 instrument using NovaSeq 6000 S2 Reagent Kit v1.5 (20028314) targeting 50M paired reads. Raw data (BCL format) were demultiplexed and converted to FASTQ format using BCL2FastQ (Illumina). Adapters were trimmed using Skewer (PMID: 24925680) and QC assessed using FASTQC. STAR (PMID: 23104886) was used to align reads to the reference genome (GRCh38/hg38) as well as to the transcriptome (GENCODE v. 25). Quality of the RNA alignment was assessed using Picard QC. Gene and isoform quantification was performed using RSEM (PMID: 21816040). The study shares expression data (gene.results) and chimeric.junction.out.

  Study EGAS00001007116

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  This study was designed to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk. We performed single cell RNA-sequencing (scRNA-seq) of BE, EAC and paired normal esophagus and gastric fundus tissue samples. After analyzing individual cell types, we integrated the scRNA-seq data and data of a genome-wide association study (GWAS) on BE/EAC to determine cell type-specific genetic risk. Raw data from the RNA-sequencing is provided here.

  Study EGAS50000000530

• Development and Validation of Patient-Derived Xenografts from Fibrolamellar Carcinoma Human Tissue

  We developed and validated Patient-Derived Xenografts (PDX) of Fibrolamellar Carcinoma human tissue from surgical resections. Human tissues from primary liver tumor, recurrent liver, and liver metastases were implanted into NOD-SCID-Gamma (NSG) mice (Jackson laboratories) and monitored for tumor growth. Some of the original tissues were frozen for further analysis including RNA sequencing. Tumors that grew were then harvested and passaged into additional mice. Some tumor tissues from the PDX samples were frozen for RNA-Seq analysis. The PDX was validated by histologic, transcriptomic and proteomic analysis. The RNA-Seq analysis was performed on original tissue samples including primary liver tumor, recurrent liver, liver metastases, normal liver, and the derived PDX.

  Study phs002435

• Long-Read Sequencing to Identify Inherited Mutations Predisposing to Breast Cancer

  We aimed to detect deeply intronic mutations within genes linked to breast/ovarian cancer that are potentially under-reported in clinical testing due to technical limitations. Current DNA and RNA tests typically exclude these regions, which harbor many variants within complex repetitive sequences that short-read sequencing cannot align. By employing targeted long read sequencing together with recent in silico prediction tools, we assessed the implications of rare deep intronic variants in severely affected patients with breast, ovarian, and/or metastatic prostate cancer, who had previously tested negative using standard genomic or cDNA methods. Through this approach, we identified participants who carried deep intronic mutations in tumor suppressor genes, resulting in abnormal transcripts causing premature truncations and loss of gene function. This study underscores the potential of long read DNA and cDNA sequencing in enhancing mutation discovery efforts.

  Study phs003638

• Genome-Wide Association Studies in Upper Gastrointestinal Cancers (Asian)

  This project aims to conduct genome-wide association studies (GWAS) in two anatomically different upper gastrointestinal (UGI) cancer sites in two populations with distinctly different disease rates and genetic profiles. One population has very high rates for both esophageal squamous cell carcinomas (ESCCs) and gastric cancers (GCs) and is comprised of Asians (the "Asian UGI GWAS"), while the other population has low rates of ESCC and GC and includes non-Asians from the Americas, Europe, and Australia (the "Non-Asian UGI GWAS"). Study participants for the Asian UGI GWAS reported here (Illumina 660W Quad chip) were drawn from 2 studies, the Shanxi Upper Gastrointestinal Cancer Genetics Project (Shanxi) and the Linxian Nutrition Intervention Trial (NIT), a prospective cohort, and included a total of 1898 ESCCs, 1625 GCs, and 2100 controls. For the 2nd phase (8 TaqMan SNPs), additional subjects from Shanxi and NIT as well as subjects from the Shanghai Men's Health Study (SMHS), the Shanghai Women's Health Study (SWHS), and the Singapore Chinese Health Study (SCHS) were also included (217 ESCCs, 615 GCs, 1202 controls). Altogether 2115 ESCCs, 2240 GCs, and 3302 controls were genotyped in this study.

  Study phs000361

• Whole-exome sequencing of human pancreatic cancers and characterization of genomic instability caused by MLH1 haploinsufficiency and complete deficiency

  Whole-exome sequencing (Exome-Seq) has been successfully applied in several recent studies. We here performed Exome-Seq of 15 pancreatic tumor-normal pairs. We captured 162,073 exons of 16,954 genes and sequenced the targeted regions to a mean coverage of 56 folds. This study identified a total of 1,517 somatic mutations and validated 934 of them by transcriptome sequencing. We detected recurrent mutations in 56 genes. Among them, 41 have not been described. The mutation rates varied widely among tumors. The diversity of mutation rates was significantly correlated with the distinct MLH1 copy-number status. Exome-Seq revealed intensive genomic instability in a tumor with MLH1 homozygous deletion, indicated by a dramatically elevated mutation rate of somatic substitutions, small insertions/deletions (indels), as well as indels presented at microsatellites. Notably, we detected MLH1 allelic loss in 4 tumors. MLH1 expression was decreased by nearly half in these cases. While they were negative in the conventional microsatellite instability assay, they showed a 10.5-fold increase in the mutation rate of somatic indels, e.g. truncating indels in TP53 and TGFBR2, indicating MLH1 haploinsufficiency in correction of DNA indel errors. We further analyzed the exomes of 15 renal cell carcinomas (RCCs) and confirmed MLH1 haploinsufficiency. We observed a significant increase in the mutation rate of somatic indels in affected cases and identified recurrent truncating indels in several cancer genes such as VHL, PBRM1 and JARID1C. Together, our data suggest that MLH1 hemizygous deletion, through increasing the mutation rate of somatic indels, could drive the development and progression of sporadic cancers.

  Study EGAS00001000149

• Melanoma and Cancer-Associated Fibroblast Short-Term Cultures Derived from Patient Metastases

  The purpose of this study was to obtain tissue specimens derived from patients with melanoma to generate research tools to advance our understanding of the genetics, pathogenesis, and therapeutics of melanoma. Briefly, tissue was obtained from metastatic lesions and used to generate clonal primary cell lines from melanoma cells and fibroblasts from the tumor microenvironment. RNA was extracted from low passage cell lines using Trizol reagent. cDNA libraries were prepared using the TruSeq mRNA sample preparation kit, v2 (Illumina) and sequenced on the HiSeq 2000 platform (Illumina). The submitted files are bam files that contain both unaligned and aligned reads (human genome, build hg19).

  Study phs001115

• Medulloblastoma Illumina RNA-Seq

  Illumina RNA-sequencing of Medulloblastoma primary and relapse tumor.

  Dataset EGAD00001009425

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• Cam_121: RNA Seq data

  Dac EGAC00001001737

• Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  HCHWA-D is an early onset hereditary form of Cerebral Amyloid Angiopathy (CAA) caused by a point mutation resulting in an amino acid change (NP_000475.1:p.Glu693Gln) in the Amyloid Precursor Protein (APP). Post-mortem brain tissue (9 patients and 9 age-related controls; frontal and occipital cortex) was used for next generation sequencing of RNA (RNA-Seq with ribosomal RNA depletion).

  Study EGAS00001002730

• Single-cell RNA-Seq of human lymphoma reveals malignant B cell diversity and patterns of T cell immune checkpoint co-expression

  Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

  Study phs001378