14983 results for "cancer studies using rna-seq"

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• Whole-transcriptome characterization of cell-free RNA (cfRNA) in cancer and non-cancer patients

  Whole-transcriptome characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Dataset includes collapsed BAM files for plasma cfRNA from each patient, as well as collapsed BAM files for RNA from matched tumor tissue (when available).

  Dataset EGAD00001006484

• EM-seq data from plasma cfDNA samples of ALS patients, control and C9-carriers

  This dataset contains targeted EM-seq data from 61 plasma cfDNA samples spanning 20 sporadic ALS, 10 C9orf72-ALS, 10 asymptomatic C9orf72 expansion carriers, and 21 non-disease controls. Libraries were prepared with the NEBNext Enzymatic Methyl-seq (EM-seq) kit, captured using the Twist Human Methylome Panel (3.98 M CpGs; 123 Mb), and sequenced on Illumina NovaSeq 6000 (150 bp paired-end; ~45× on-target depth) with unmethylated lambda DNA spike-in and a 20% PhiX balance library. The dataset includes per-sample gzipped FASTQ files (R1/R2) and minimal metadata.

  Dataset EGAD50000001808

• Multivalent State Transitions Shape the Intratumoral Composition of Small Cell Lung Carcinoma

  Small cell lung carcinoma (SCLC) is an aggressive, tobacco-associated tumor characterized by rapid growth, early metastases, and initial response followed by almost invariable resistance to chemotherapy. Studies to date have not resolved the extent that diverse transcriptional programs drive SCLC and contribute to its lethality. We combined patient-derived xenograft (PDX) (n = 64) resources with multi-omic profiling, single-cell fluorescence tracking of ex vivo tumor cells, and mathematical and statistical models to study the topology of the SCLC transcriptional state space and its plasticity.

  Study phs003102

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program - Neuroblastoma

  The goal of NCI's Pediatric In Vivo Testing Consortium (PIVOT) is to advance the development of effective treatments for pediatric cancers through preclinical in vivo testing of novel therapeutic agents. To design impactful experiments that can be rapidly translated to the clinic, PIVOT investigators require comprehensive genomic characterization of the patient-derived xenograft (PDX) models used across the consortium. This robust experimental design enhances collaboration with industry partners by providing proof-of-concept data for drugs in development. As part of this effort, neuroblastoma PDX models are being molecularly characterized to identify promising therapeutic candidates. The molecular profiling includes whole exome sequencing (WES), RNA-seq, MethylEPIC array, CytoSNP array, and DNA fingerprinting for quality control. Additionally, demographic and clinical data (e.g., diagnosis, disease site, disease status) are shared. These characterized PDX models, matched with patient tumors, guide model selection for preclinical drug testing.

  Study phs003163

• Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA-sequencing the pros and cons

  RNA sequencing data of a collection of 6 pediatric ependymoma cases

  Dataset EGAD00001009301

• Single-cell proteogenomics of MDS upon AZA

  To study the evolution of the clonal molecular and cellular architecture of MDS upon the treatment with AZA, we performed scDNA-seq of an amplicon panel of 53 genes recurrently mutated in myeloid malignancies, as well as typically lost or gain DNA regions, and scProt-seq of 42 cell-surface proteins to provide a simultaneous landscape of the genetic setting and immunophenotype using the Tapestri platform (MissionBio). We sequenced thousands of cells from 14 MDS patients, where paired bone marrow samples were obtained at the timepoint of diagnosis and after AZA treatment.

  Study EGAS00001007427

• Ancestry and somatic profile predict acral melanoma origin and prognosis – WXS

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015755

• Prostate cancer m6A epitranscriptome

  Using meRIP-sequencing, we profiled N-6 methyladenosine (m6A) in a cohort of 148 primary prostate cancer samples as part of the Canadian Prostate Cancer Genome Network project (CPC-GENE). Paired-end sequencing of 150 bp reads were mapped to GRCh38.p13 using annotations from gencode.v34.chr_patch_hapl_scaff.annotation.gtf. Peaks were called using MeTPeak, joint peaks were identified and IP reads were quantitated, normalized and adjusted using Input reads to obtain estimates of m6A abundance.

  Dataset EGAD00001009869

• Whole genome sequencing data using Adaptive sampling from 33 patients with hereditary cancer syndrome

  We performed whole genome sequencing using adaptive sampling with GridION on 33 patients with clinically suspected hereditary cancer syndromes to evaluate an efficient computational workflow.

  Study JGAS000654

• RNA sequencing of a glioblastoma PDX cohort

  Patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In this project, we molecularly characterized a comprehensive panel of glioma PDX models with well conserved molecular and pathological features over multiple passages. PDX samples were subjected to next generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in glioblastoma. In summary, we reported a newly established and molecularly characterized panel of glioma PDX models with high relevance for translational preclinical research.

  Study EGAS00001007119

• Spatial transcriptomic data of breast cancer

  Fastq files from spatial transcriptomic of breast cancer coming from 8 Breast cancer sections. Sample preparation: frozen BC samples were chosen based on tissue structure and RNA quality (RIN > 8). The “Visium Spatial Tissue Optimization Slide and Reagent Kit” (10X Genomics; #PN-1000193) was then used to optimize permeabilization conditions for BC tissues. Briefly, sections were fixed, stained and then permeabilized at different time points to capture mRNA, and the reverse transcription was performed to generate fluorescently labeled cDNA. The permeabilization time that resulted in the highest fluorescence signal with the lowest background diffusion was chosen. The best permeabilization time for BC tissue was 18 min. Cryostat sections of 10 μm of thickness were cut and placed on Visium Spatial Gene Expression slides (10X Genomics, PN-1000184). The slide was incubated for 1 min at 37°C, then fixed with methanol for 30 min at -20°C followed by Hematoxylin and Eosin (H&E) staining and images were taken under a high-resolution microscope. After imaging, the coverslip was detached by holding the slide in water and the slide was mounted in a plastic slide cassette. The spatial gene expression process, including tissue permeabilization, second strand synthesis and cDNA amplification, was performed according to the manufacturer’s instructions (10X Genomics; #CG000239). cDNA quality was next assessed using Agilent High sensitivity DNA Kit (Agilent, #5067-4626). The spatial gene libraries were constructed using Visium Spatial Library Construction Kit (10X Genomics, PN-1000184).

  Dataset EGAD50000000322

• RNA sequencing of Ewing sarcoma and CIC-DUX4 sarcoma

  RNA sequencing of a collection of 6 Ewing sarcoma and 3 CIC-DUX4 sarcoma tumoroids plus 3 matched patient tumors. Tumoroids were established from digested patient tumor material as 3D culture in Matrigel. After 2-3 month of growth, RNA was isolated from individual tumoroid models using the RNeasy Kit (Qiagen) and used for whole exome sequencing. RNA from corresponding patient tumors was tested in parallel, if available.

  Dataset EGAD50000000557

• MiRNome_pituitary_adenoma

  Small RNA (<100 bases in length) were purified from total RNA using miRNeasy kit (Qiagen), then sequenced. Libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq small RNA protocol (Illumina), starting from 1 µg of high quality total RNA. Single read (1 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on miRBase v.2052, then counted with STAR (v.2.5.2a).

  Dataset EGAD00001004998

• Genome-wide association study identifies common variants associated with breast cancer in South African Black women

  Genome-wide association studies (GWAS) have characterized the contribution of common variants to the development of breast cancer (BC) in populations of European descent, however no GWAS have been reported in resident African populations. This GWAS included 2,485 resident African BC cases and 1,101 population matched controls. Two risk loci were identified, one on chromosome 15, located between UNC13C and RAB27A (rs7181788, p = 1.01x10-08) and a second in an intron of USP22 on chromosome 17 (rs899342, p = 4.62x10-08). RAB27A is a member of the RAS oncogene family associated with invasive growth and metastasis, and UNC13C is involved in tumor progression. The rs899342 SNP is an eQTL for expression of USP22 in a wide range of tissues. Several genome-wide significant signals were detected in a hormone receptor subtype analysis. Comparison of a meta-analysis of other African ancestry BC GWAS datasets predominantly of West African ancestry with our South African data showed limited evidence of shared risk loci, suggesting potential heterogeneity in genetic risk factors for breast cancer in different African populations. A European ancestry derived polygenic risk model for BC was applied to our data, explaining only 0.79% of variance, with an area under the curve of 0.56. This study identified genetic risk factors for BC in a resident African population, but larger studies in this and other African populations are needed to further define the contribution of common variants to BC risk.

  Study EGAS00001008032

• Dataset for urologic_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 36 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008903