15059 results for "cancer studies using rna-seq"

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• Bone Microarchitecture

  Osteoporosis affects more than 28 million people in the United States and the lifetime risk for osteoporosis-related morbidity is higher than a woman's combined risk for breast cancer, endometrial cancer and ovarian cancer. Health care expenditures for osteoporotic patients in this country are currently nearly 13 billion dollars per annum and are predicted to increase markedly in the next decades due the aging of the population; therefore, it is important to understand the factors that contribute to bone strength and fracture risk. With the advent of skeletal imaging modalities such as high resolution peripheral quantitative computed tomography (HR-pQCT), it is now possible to study the genetics of more highly refined peripheral skeletal microarchitecture phenotypes. Because these refined phenotypes have not been measured in many cohort studies, this project was a collaborative effort to include almost all the existing data on HR-pQCT of the radius and tibia, and genetics from around the world. Cohorts involved in the discovery included: 1) Framingham Osteoporosis Study, 2) Mayo Clinic cohort; 3) Geneva Retirees cohort; 4) OFELY cohort from Lyon France; 5) STRAMBO cohort from Lyon France; 6) Swedish Male cohorts. Replication cohorts undergoing de novo genotyping include: 1) QUALYOR cohort from Lyon France; 2) CaMOS cohort from Canada. Other than the Framingham cohort and the Swedish male cohorts, all discovery cohorts underwent genome wide genotyping with the Affymetrix Axiom Biobank array that had common variants along with exome content based on the early findings from the Exome Sequencing Project. All genotype data from the discovery cohorts were then imputed using the Haplotype Reference Consortium reference panel. Variants for replication genotyping using the Kasp technology were selected based on novelty compared with previously identified loci using DXA phenotypes, minor allele frequency, underlying LD structure within a locus, and likelihood of a variant being functional as assessed using various algorithms for coding and non-coding variants.    

  Study phs002102

• RNA Seq OMELib

  The transcriptional landscape of haematopoietic cells will be characterized by RNA Seq following amplification of RNA/cDNA and preparation of libraries by PTA(primary template-directed amplification). Samples have been sourced from the Cambridge Biobank.

  Dataset EGAD00001015252

• Single-cell RNA-seq of PBMC from 2 patients iGRAN-Low and 2 patients iGRAN-High

  Single-cell RNA-seq of PBMC from 2 patients iGRAN-Low and 2 patients iGRAN-High [Publication title] CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia

  Study EGAS50000000556

• Longitudinal RNA-seq (whole blood) in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Study EGAS00001001763

• RNA-seq data: Histone mutations in human Pre-Leukemic HSC and AML

  RNA-seq data from TEX cells transduced with HIST1H3H WT, HIST1H3H K27M, HIST1H3F WT, HIST1H3F K27I and Luc2 control in triplicate. In addition, RNA-Seq was performed on untransduced TEX cells. Libraries [rRNA-depleted stranded (HMR)] were sequenced on an Illumina Hiseq 4000 platform to generate 100 bp paired-end reads.

  Dataset EGAD00001004437

• Optimized large-scale longitudinal biorepository of gastroesophageal adenocarcinoma patient-derived organoids

  To enable translation studies we created patient derived models to assess biomarkers, target validation, and patient response. To evaluate that the PDOs retain the genomic characteristics of the primary tumours we performed (WES) sequencing of 11 matched primary tumours and their matched organoid samples (total n=22). Libraries were sequenced using Illumina NovaSeq technology. Reads were aligned with BWA alignment to hg38. Files were processed following GATK best practices (version GATK 4.2.3.0). Variants were called using Mutect2. The dataset contains the alignmnent files (.bam) and the called mutations (.vcf).

  Study EGAS50000001614

• Single-cell RNA-seq cases

  Single-cell RNA-seq cases (Tumor and adjacent tissue)

  Dataset EGAD00001008835

• scRNA-seq of monochorionic dizygotic twin chimera PBMC

  Single cell RNA-seq of PBMC of monochorionic dizygotic twin chimeras. 10x chromium v3.1 was used to generate barcoded scRNA library.

  Study EGAS50000000097

• SF11612 scRNA-Seq Recurrent oligodendroglioma

  Single Cell RNA seq from Recurrent oligodendroglioma sample. Gender Male Age 67. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005411

• RNAseq following LDC67 or JQ1 treatment

  For RNA-Seq total RNA was isolated following LDC67 or JQ1 treatment. 3’RNAseq libraries were prepared with QUANT SEQ FWD 3´mRNA-Seq Kit (Lexogen, Austria), sequenced on an Illumina HiSeq 4000

  Dataset EGAD00001003464

• SF9259S snRNA-Seq Primary GBM

  Single Nuceli Primary GBM 73 Male. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005428

• Diffuse Intrinsic Pontine Glioma

  This study contains DNA and RNA sequencing data for 5 DIPG patients. All patients have tumor DNA data, 4 have matched normal DNA data and 3 have tumor RNA seq data

  Study EGAS00001006353

• RNA-Seq data for paper titled 'Genomic Landscape of Pediatric Myelodysplastic Syndromes'

  When available (25 primary MDS, 12 MDS/MPN, and 6 AML-MRC cases), high quality RNA (stranded-total) was submitted for RNA-seq. RNA was extracted from bulk myeloid cells which was used as the tumor population. Files uploaded are mapped BAM files.

  Dataset EGAD00001003782

• Resilience and Susceptibility Patterns in the Viral Immune Response Using RNA-Seq (ReSP VIRUS Study)

  This is a cross sectional study to investigate the relationship between nasal mucosa gene expression and clinical outcomes in infants with critical Respiratory Syncytial Virus (RSV) infection. We collected nasal mucosa samples from infants admitted to the pediatric intensive care unit with polymerase chain reaction confirmed RSV bronchiolitis. Samples were obtained by mucosal scrape biopsy of the inferior turbinate using a sterile plastic curette and bulk RNA-sequencing of mRNA was performed. Clinical data was extracted from the electronic health record including: demographics, medical history, duration of symptoms, time from admission to sample collection, hospital and intensive care unit length of stay, and type and duration of respiratory support.

  Study phs003053

• Transcriptomics for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002236

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011192

• Asan Medical Center Data Access Committee

  This DAC is responsible for reviewing and approving data access requests to protect the sensitive information of patients. The dataset includes RNA-seq data from CRLM patients treated with FOLFOX, bevacizumab, and atezolizumab, and supports research in gene expression analysis and therapeutic response. Data access requests require an approved ethical research plan, limited to projects related to cancer biology and therapy development.

  Dac EGAC50000000439

• A phase II trial of the aurora kinase A inhibitor alisertib for patients with castration resistant and neuroendocrine prostate cancer: efficacy and biomarker evaluation

  Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may develop de novo or as a mechanism of treatment resistance. N-myc is capable of driving NEPC progression. Alisertib inhibits the interaction between N-myc and its stabilizing factor Aurora-A, inhibiting N-myc signaling, and suppressing tumor growth. In this single arm, multi-institutional open label phase 2 clinical trial of alisertib, sixty men were treated with alisertib 50mg twice daily for 7 days every 21-days. Eligibility included metastatic prostate cancer and at least one: small cell neuroendocrine morphology; ≥50% neuroendocrine marker expression; new liver metastases without PSA progression; elevated serum neuroendocrine markers. The primary endpoint was six-month radiographic progression free survival. Pre-treatment biopsies were evaluated by whole exome and RNA-seq.

  Study phs001666

• RNA-seq derived from metastatic Castration-Resistant Prostate Cancer

  Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy. 118 total samples including 14 paired samples (baseline and later progression). Various organ sites including soft tissue & bone were present. Published in DOI: 10.1200/JCO.2017.77.6880 Journal of Clinical Oncology 36, no. 24 (August 20, 2018) 2492-2503.

  Dataset EGAD00001008991

• Whole genome sequencing data of pediatric B-other subtype acute lymphoblastic leukemia

  For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases is acquired from ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) based on the RNA-seq profiles.

  Study EGAS50000001497