11762 results for "cancer rna-seq"

in 33.23 milliseconds.

• ETMR_Nanostring

  Total RNA (100ng) from 21 ETMRs with C19MC structural alterations and 28 other PBTs was prepared with nCounter miRNA Sample Prep Kit according to standard protocol. miRNA expression profiling was conducted with human v1, v2, or v3 miRNA panel on nCounter miRNA expression platform (NanoString Technologies, Seattle, WA) according to manufacturer’s protocol. Signal normalization was done using nSolver Analysis and batch corrected using ComBat (Johnson et al. Biostatistics. 2007). 565 miRNAs overlapped between all three versions and was used for further analyses. Fold change and supervised t-test with FDR correction was calculated between the ETMRs and other PBTs.

  Dataset EGAD00010001701

• Genetic investigation of 12q-amplified osteosarcomas

  Further investigation and characterisation of 12q-amplified low- and high-grade osteosarcomas with MDM2 and/or CDK4 amplification focusing on SV, copy number and gene fusion analyses. In total, 25 cases (33 samples total due to multi-sampling) were included, with some form of sequencing data available for 27 samples. Mate-pair whole genome sequencing (Illumina) is available for 19 samples, longread whole genome sequencing (PacBio HiFi) on 10 samples and RNA-sequencing (Illumina Truseq) on 21 samples. Data is available as BAM files.

  Dataset EGAD50000000707

• B cell transcriptome and repertoire data from patients with IBD and healthy controls

  This dataset contains transcriptome data generated from naive and memory B cells isolated from patients with inflammatory bowel disease and healthy controls. Data was generated from both patients with Crohn's disease and ulcerative colitis. In addition, it contains BCR repertoire data from patients with IBD and healthy controls. The repertoire data was generated using amplicon sequencing of RNA isolated from peripheral blood, lymph nodes from inflamed gut and gut associated lymphatic tissue.

  Dataset EGAD50000001335

• Single nucleus RNA sequencing of squamous cell carcinoma arising from mature teratoma of the ovary

  Squamous cell carcinoma arising from mature teratoma is one of the rare ovarian cancers. Therefore, the detailed molecular background of this disease has not been elucidated. The purpose of this study is to investigate the single-cell transcriptional landscape of this disease.

  Study JGAS000521

• Expression quantitative trait locus mapping in human pancreatic islets of Langerhans

  The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. To identify such effector transcripts for T2D and glycemic traits, we generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and high-density genotyping.

  Dataset EGAD00001001601

• Detection of Gene Fusions using Targeted Next-Generation Sequencing

  Five commercially available parallel sequencing assays were evaluated for their ability to detect gene fusions in eight cell lines and 18 FFPE tissue samples carrying a variety of known gene fusions. Four RNA-based assays and one DNA-based assay were compared; two were hybrid capture-based, TruSight Tumor 170 Assay (Illumina) and SureSelect XT HS Custom Panel (Agilent), and three were amplicon-based, Archer FusionPlex Lung Panel (ArcherDX), QIAseq RNAscan Custom Panel (Qiagen) and Oncomine Focus Assay (Thermo Fisher Scientific).

  Dataset EGAD00001006913

• Sequencing data for oesophageal and related samples - Scott et al (WGS, RNA)

  Data supporting: "Evidence that polyploidy in esophageal adenocarcinoma originates from mitotic slippage caused by defective chromosome attachments" Scott et al. WGS and RNAseq sequencing data Organoid, tumour and normal samples BAM files

  Dataset EGAD00001006738

• Next Generation Sequencing Characterization of Hematopoietic Stem and Progenitors Cells in Human Systemic Lupus Eryhtematosus (2)

  This dataset contains RNA-sequencing of Bone marrow-derived CD34+ cells from Healthy Controls (n=2) and SLE patients (n=10). SLE patients are divided into two categories based on severity: patients with moderate/mild disease (n=4) and patients with severe disease (n=6). Libraries were generated using the Illumina TruSeq Sample Preparation kit v2. Single-end 75-bp mRNA sequencing was performed on Illumina NextSeq 500. The raw fastq files are uploaded.

  Dataset EGAD00001009744

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• PIVUS study - Longitudinal transcriptomics - Advanced aging

  We performed RNA sequencing in whole-blood from the same 65 individuals from the PIVUS study at ages 70 and 80 (130 samples) to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging. Each individual has four fastq files, two for each age. Consecutive sample IDs refer to the sample individual, e.g. PIVUS003 and PIVUS004 are the age 70 and age 80 samples of the first individual.

  Dataset EGAD00001004965

• Single cell study of infant leukemias

  We have performed single cell RNA-sequencing for infant and childhood B-cell acute lymphoblastic leukemias as well as infant acute myeloid leukemias at diagnosis. The sequencing was performed with 10X Chromium single cell 3’ and 5’ chemistry.

  Dataset EGAD00001007854

• Neuroblastoma patient WGS data

  Paired tumor and normal WGS of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008123

• DCM-controls

  DCM-controls (113 human non-DCM samples) human heart biopsies from 113 non-diseased controls were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

  Dataset EGAD00001003391

• Sequencing data for oesophageal and related samples - Izadi et al (WGS, RNA)

  Data supporting: "Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma" Izadi et al. WGS for tumour and normal samples. RNAseq for tumour samples.

  Dataset EGAD00001007493

• Patient-derived gene and protein expression signatures of NGLY1 deficiency

  Single-end bulk RNA sequencing results of cell lines derived from patients described with NGLY1 deficiency as well as parent and CRISPR edited controls. The cell lines represent 4 different cell types: fibroblasts, lymphoblastoid cells, induced pluripotent stem cells (iPSCs) and neural progenitor cells (NPCs.).

  Dataset EGAD00001008094

• DCM-cases

  DCM-cases (149 human DCM samples) human heart biopsies from 149 patients with dilated cardiomyopathy (DCM) were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

  Dataset EGAD00001003390

• Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets (2020-05-12)

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2020-05-12.

  Dataset EGAD00001006139

• Single-cell GoT sequencing from CH, MDS and AML patients with CH mutations

  Single-cell targeted amplicon RNA sequencing from CH (n = 3), MDS (n = 6, MDS02 in 2 replicates) and AML (n =1, in 2 replicates) samples with mutations in splicing factors (SF3B1 - n = 8 [2 -CH, 6 MDS], U2AF1 n = 1) or transcription regulators (DNMT3A - CH04). The transcripts are targeted to detect a particular CH mutation in the listed genes. U2AF1 GoT are full-length cDNA, while the rest follow the 10x 3' V3 protocol.

  Dataset EGAD00001011284

• Whole-genome sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumoroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015707

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015709

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Targeted gene panel sequencing of matched diagnosis-remission-relapse B cell precursor acute lymphoblastic leukemia samples

  Bone marrow mononuclear cells from patients diagnosed with B cell precursor acute lymphoblastic leukemia were obtained at three sequential time points: first diagnosis, remission after chemotherapy and relapse. Genomic DNA was isolated and targeted gene panel sequencing was performed using a customized biotinylated RNA oligo pool (SureSelect, Agilent, Santa Clara, California) to hybridize the target regions comprising 362 kbp on a HiSeq2000. Target regions were selected to validate mutations previously identified in these samples using whole exome sequencing.

  Dataset EGAD00001004977

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (bulk RNA)

  Data supporting: “Deep molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition.” Nowicki-Osuch, Zhuang et al. RNAseq (BAM files) 12 Barrett's samples 12 normal oesophageal samples 11 normal gastric cardia samples

  Dataset EGAD00001006882

• Memorial Sloan Kettering Cancer Center - Human Oncology & Pathogenesis Program (HOOP) - Data Access Committee

  Dac EGAC00001000305

• Functional Genomics Laboratory, Kolling Institute of Medical Research DAC - TP53 mutation data in ovarian cancer

  Dac EGAC00001000589

• The data access committee for genome-wide cell-free DNA fragmentation in patients with cancer

  Dac EGAC00001001180

• Somatic pathogenic variants in the normal mammary gland of sporadic breast cancer patients.

  Dac EGAC00001002391

• DAC Molecular heterogeneity and commonalities in pancreatic cancer precursors with gastric and intestinal phenotype

  Dac EGAC00001002978

• NPY methylated ctDNA is a promising biomarker for treatment response monitoring in metastatic colorectal cancer

  Dac EGAC00001003001

• EGAD00010000526

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000526

• Microbiome confounders and quantitative profiling challenge established microbial targets in colorectal cancer developmental stages

  Study EGAS00001007413

• Genomic validation of the revised Bethesda criteria in terms of pathogenesis and oncologic significance

  Study EGAS00001003959

• Accurate mutation detection in leukemia by re-sequencing a cancer gene set

  Study EGAS00001000268

• Activation of IL7RA signalling in human B-lymphoid precursors induces pre-leukemia

  Study EGAS00001003979

• Biological and Therapeutic Implications of a Unique Subtype of NPM1 Mutated AML

  Study EGAS00001004872

• A renal cell carcinoma tumorgraft platform to advance precision medicine

  Study EGAS00001005516

• Minor intron splicing efficiency increases with the development of lethal prostate cancer

  Study EGAS00001005546

• Serum Proteome Profiling Identifies Early Markers of Therapeutic Response to Neoadjuvant Chemotherapy of Breast Cancer

  Study EGAS00001006228

• Genomics characterization of BRAF-V600E colorectal cancer patients treated with anti-BRAF/EGFR

  Study EGAS00001006247

• PCF SELECT data on liquid biopsy samples from 3 clinical studies on prostate cancer patients

  Dac EGAC50000000758

• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  Study EGAS00001006411

• PPCG UK BAMs

  Pan Prostate Cancer Group UK BAM files

  Dataset EGAD00001006742

• Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE)

  The goal of this study was to identify SNPs and CNPs that are associated with development of normal tissue toxicities resulting from radiotherapy for prostate cancer. The study population includes approximately 1,400 men treated with brachytherapy, external beam radiation therapy, or a combination of the two treatments, and assessed for adverse effects at baseline and following radiotherapy. Three toxicity endpoints were investigated using a two-stage GWAS approach: urinary morbidity, rectal bleeding and erectile dysfunction. The study sample was split into a discovery set (N=367) and a replication set (N=417), and an additional 647 samples, which were not part of this original cohort, were also included as an independent replication set. The replication set was developed via collaboration developed under the framework of the Radiogenomics Consortium (RGC). The long-term goal of this project, and other radiogenomics projects lead by the RGC, is two-fold: 1) Develop an assay capable of predicting which cancer patients are most likely to develop radiation injuries resulting from treatment with a standard RT protocol, and 2) Obtain information to assist with the elucidation of the molecular pathways responsible for radiation-induced normal tissue toxicities. These studies focus on multiple cancer types including prostate, breast, lung, and head and neck cancers.

  Study phs000772

• Genomic Sequencing of Cervical Cancers

  Cervical cancer is responsible for 10-15% of cancer related deaths in women worldwide. The etiological role of infection with high-risk human papilloma viruses (HPV) in carcinomas of the cervix is well established. In general, the development of cervical carcinomas follows a progression from persistent HPV infection through precancerous lesions to invasive cancer. Previous studies have implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS as well as chromosome-arm level copy number alterations in the pathogenesis of cervical carcinomas. Here, we report whole exome sequencing analysis of 118 cervical carcinoma-normal paired samples from patients in Norway and Mexico, as well as transcriptome sequencing of 80 cases and whole genome sequencing of 13 tumor-normal pairs. Novel somatic mutations include recurrent E322K substitutions in the MAPK1 gene encoding the ERK2 kinase and inactivating mutations in the HLA-B gene. In addition, recurrent somatic mutations in FBXW7, EP300, and NFE2L2 are novel in the context of primary cervical carcinomas. Analysis of HPV integration sites revealed recurrent integration into the RAD51B locus as well as co-occurrence of HPV genome integration and copy number gains within several genomic loci. These findings shed new light on the pathogenesis of cervical carcinomas and suggest potential novel therapeutic targets.

  Study phs000600

• WGS of 32 paired SRCC samples

  Signet-ring cell carcinoma (SRCC) has specific epidemiology and oncogenesis in gastric cancer, however with no systematical investigation for prognostic genomic features. We systematically investigated the clinical characteristics of 1,868 Chinese gastric cancer patients, and found that signet-ring cell content was significantly related to multiple clinical characteristics and treatment outcomes. Next, we performed whole genome sequencing for 32 SRCC patients with > 80% signet-ring cells in tumor, and identified frequent5 CLDN18-ARHGAP26/6 fusion (25%). With additional 797 patients for validation, we notice that prevalence of CLDN18-ARHGAP26/6 fusion is positively associated with signet-ring cell content (P = 4.1 x 10 -9 ), younger age at diagnosis (P = 4.2 x 10 -10 ), female/male ratio (P = 1.7 x 10 -9 ), and advanced TNM stage (P = 1.7 x 10 -5 ). Importantly, patients with CLDN18-ARHGAP26/6 fusion had a worse survival outcomes (P = 0.03), and got no benefit0 from platinum/fluoropyrimidines based chemotherapy (P = 0.92) compared to fusion-free patients (P = 0.001), which is consistent with the fact of oxaliplatin/fluoropyrimidine resistance acquired in CLDN18-ARHGAP26 introduced gastric cancer cell lines. Overall, this study provides new insights into the clinical and genomic features of SRCC, and highlights the importance of frequent CLDN18-ARHGAP26/6 fusions in chemotherapy response for SRCC.

  Study EGAS00001002668

• Whole-Genome sequencing of hepatocellular carcinomas

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome and whole exome sequencing together with CGH-SNP, methylome and transcriptomic profiling. For this purpose, a series of 500 liver tumors are collected through the French National Liver Collection and these samples will be analyzed using the different omics technologies. The data will be deposited in the ICGC and EGA database to be publically available for the scientific community. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before. The dataset will include 50 whole genome sequencing tumor/germline pairs, of which 6 are deposited in February 2014.

  Study EGAS00001000706

• The evolutionary steps from primary to metastatic prostate cancer are largely uncharted, and the ability to use DNA present in body fluids as correlates of aggregate metastatic status is under-examined. We reconstructed phylogenies in ten prostate cancer patients with fatal disease using deep targeted sequencing of the prostate, adjacent and distant organs, as well as plasma, serum, and cerebrospinal fluid at various time points. A total of 163 samples are studied.

  The evolutionary steps from primary tumor to metastasis in prostate cancer are largely uncharted, and the ability to use serum, plasma, and cerebrospinal fluid as a correlate of aggregate metastatic tumor genomic status has not been tested. We used deep targeted sequencing to reconstruct tumor evolution in ten prostate cancer patients with fatal disease encompassing examination of the prostate and adjacent and distant organs, as well as plasma, serum, and cerebrospinal fluid at various time points. We show that there is substantial evolution from a common ancestor within the prostate that results in branching to multiple lineages which form an intermixed multi-clonal primary tumor mass. After the occurrence of key driver aberrations, one of these lineages will metastasize to multiple sites in a sequential fashion. These metastatic sites are then susceptible to being populated by cells from other intra-prostatic lineages or from other metastases. Genomic representation of metastases in body fluids is not uniform. Cerebrospinal fluid analysis can detect lineages not detected in circulating DNA, suggesting possible clinical utility.

  Study EGAS00001003848

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Immune checkpoint inhibitors (ICI), which target immune regulatory pathways to unleash antitumor responses, have revolutionized cancer immunotherapy. Despite the remarkable success of ICI immunotherapy, a significant proportion of patients whose tumors respond to these treatments develop immune-related adverse events (irAEs) resembling autoimmune diseases. Although the clinical spectrum of irAEs is well characterized, their successful management remains empiric. This is in part because the pathogenic mechanisms involved in the break-down of peripheral tolerance and induction of irAEs remain elusive. Herein, we focused on regulatory T cells (Tregs) in individuals with irAEs because these cells are vital for maintenance of peripheral tolerance, appear expanded in the peripheral blood of individuals with cancer and abundantly express checkpoint molecules, hence representing direct targets of ICI immunotherapy. Our data demonstrate an intense transcriptomic reprogramming of CD4+CD25+CD127– Tregs in the blood of individuals with advanced metastatic melanoma who develop irAEs following ICI immunotherapy, with a characteristic inflammatory, apoptotic and metabolic signature. This inflammatory signature was shared by Tregs from individuals with different types of cancer developing irAEs and individuals with autoimmune diseases. Our findings propose an inflammatory Treg reprogramming as a feature of immunotherapy-induced irAEs, that may facilitate translational approaches aiming to induce robust antitumor immunity without disturbing peripheral tolerance.

  Study EGAS00001004694

• Proteogenomics of chronic lymphocytic leukemia

  Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. This is the transcriptomics data of the discovery cohort.

  Study EGAS00001005746

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068