14995 results for "cancer studies using rna-seq"

in 23.73 milliseconds.

• BELLINI clinical trial bulk WES data: cohorts A & B

  WES data of 30 breast cancer primary tumors obtained from 30 unique patients from BELLINI clinical trial (cohorts A & B) and 30 matched blood samples. The data includes pretreatment samples. The included raw WES sequencing data in fastq format was generated using Illumina NovaSeq 6000.

  Dataset EGAD50000000809

• Dataset for "HPV integration induces gene fusions" (Illumina)

  Illumina whole-genome sequencing data for "HPV integration induces gene fusions" We performed short read whole-genome sequencing of five HPV+ head and neck cancer samples using Illumina. The reads are submitted in bam or fastq file format.

  Dataset EGAD50000001305

• Targeted sequencing data on sequential liquid biopsy samples from mCRPC patients receiving cabazitaxel

  Sequencing data from mCRPC patients receiving cabazitaxel. Targeted sequencing data of prostate cancer relevant genes using the PCF-SELECT capture panel. cfDNA from baseline, on-treatment and progression samples taken on cabazitaxel were sequenced as well as patient match WBC DNA

  Dataset EGAD50000001840

• Nurminen et al ("GP2Men") Study Primary and Metastatic Prostate Cancer Whole Genome Sequence Data

  We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

  Dataset EGAD50000000005

• Non-ADT METs ICGC Prostate UK

  To characterize the subclonal genomic architecture of non-androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of pelvic lymph node metastases and matching noncancerous blood from 10 patients to an average sequencing depth of 55x. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, study using these data is: Wedge et al, Nature Genetics 2018 (PMID: 29662167)

  Dataset EGAD00001002002

• Impaired HLA Class I Antigen Processing and Presentation as a Mechanism of Acquired Resistance to Immune Checkpoint Inhibitors in Lung Cancer

  Mechanisms of acquired resistance to immune checkpoint inhibitors (ICIs) are poorly understood. The purpose of this study was to investigate whether alterations in genes encoding components of the HLA Class I antigen processing and presentation machinery or interferon signaling pathways play a role in acquired resistance to PD-1 or PD-L1 antagonistic antibodies. Whole exome sequencing was performed on tumor samples collected from patients with advanced non-small cell lung cancer at the time of resistance to PD-1 axis inhibitors and on available matched pre-treatment and normal samples. Patient-derived xenografts successfully established from the ICI-resistant samples were also exome sequenced. Additionally, RNA sequencing was performed on cases with sufficient tissue.

  Study phs001464

• Clinical validity of post-surgery circulating tumor DNA (ctDNA) in stage III colon cancer patients treated with adjuvant chemotherapy: the PROVENC3 study

  The PROVENC3 study aimed to determine the clinical validity of post-surgery ctDNA testing in patients with stage III colon cancer treated with adjuvant chemotherapy (ACT). Blood was collected pre-surgery, post-surgery and post-adjuvant chemotherapy. Tumor-informed plasma ctDNA detection was performed through integrated whole genome sequencing (WGS) analyses of formalin-fixed paraffin-embedded tumor tissue DNA (80x), white blood cell germline DNA (40x) and plasma cell-free DNA (30x). These raw WGS data for 209 patients are shared in .cram format in this EGA submission. For 196/209 of these patients there is overlapping FFPE tumor RNA sequencing data available, shared in .fastq format in this EGA submission.

  Study EGAS50000000804

• Mutational signatures in normal tissues of patients treated with clinical stage G-quadruplex binder CX5461

  Drug induced photoreactions following exposure to UVA have been documented for several therapeutic compound classes, including psoralens and fluoroquinolones. CX5461, a quinolone-derived small molecule currently in phase 1 studies for cancer treatment, has been shown to be a clinically significant UV photosensitizer. Here we examined the mutagenic spectrum of CX5461 in normal tissues of patients undergoing treatment, by comparing deep whole genome sequencing (WGS) from skin biopsies taken from non-sun exposed areas pre and post drug exposure of patients in the Canadian Cancer Clinical Trials Group (CCTG) IND.231 trial (NCT02719977). We show that a low burden of SNVs (<100) and indels (<40) mutations was detected in post CX5461 skin biopsies, with a pattern resembling background or sequencing artefact signatures. To further characterize the mutational pattern of CX5461 photoreactivity, we compared mutational profiles of human retinal pigment epithelial cells exposed to UVA, CX5461, or a combination of both UV and CX5461. Treatment with CX5461 or UVA alone, resulted in a low SNV burden. In contrast, human cells exposed to UVA and CX5461 had a two to four orders higher mutational burden, with a distinct mutational pattern characterized by T>A, T>C mutations, dissimilar to that of UV alone or CX5461 alone. Our results suggest that human exposure to CX5461 alone is not associated with high levels of single base mutagenesis. However, CX5461 is a very potent UV photosensitizer, underscoring the need for adequate UV screening and controls when studying the effects of photosensitizing small molecules on single base DNA variation.

  Study EGAS50000001145

• Clonal Lineage Tracing of Primary Human Cortical Progenitors, Cell Type Profiles in the Brain Vasculature and Genotyping Data for 22q11DS and Control iPS Lines

  We sought to characterize the cell types produced by individual human cortical progenitors and describe their lineage relationships. We labeled individual human cortical cells with a massively complex lentivirus library encoding a GFP reporter gene and a molecular barcode that could be captured by standard 3' scRNA-seq methodologies. We then cultured the labeled human cells for 6 weeks in either a 1) mouse cortical astrocyte co-culture system or 2) in the mouse cortex as a xenograft. In a separate experiment, we maintained human cortical tissue slices in organotypic slice culture for 12 days. GFP+ cells were then isolated by FACS and then captured on the 10x chromium scRNA-seq platform. An additional sample was labeled by lentivirus and briefly cultured for 3 days prior to being mixed with mouse 3T3 cells in order to perform a cell mixing experiment ("barnyard") to benchmark our methodologies. We found that human individual cortical progenitors gave rise to both excitatory and inhibitory neurons as well as glia.We also sought to characterize the adult brain vasculature in both vascular malformations and non-malformed tissue. We use the 10x chromium scRNA-seq platform across 10 individuals (5 control and 5 arteriovenous malformations). We find broad disregulation across multiple cell types including the immune cells and find a specific monocyte subtype to contribute to a rupture phenotype. We also find a novel population of fibromyocytes in both conditions.Finally, we confirmed the genotype status of iPS lines that were derived from either karyotypically normal control individuals or from DiGeorge Syndrome patients carrying the 22q11.2 deletion using the Illumina Infinium Global Screening Array v3.0.

  Study phs002624

• 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

• 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

• 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

• 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

• 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

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

  This dataset contains RNA-sequencing of Bone marrow-derived CD34+ cells from Healthy Controls (n=2) and SLE patients (n=8). SLE patients are divided into two categories based on severity: patients with moderate/mild disease (n=3) and patients with severe disease (n=5). 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 EGAD00001005052

• Target sequencing of 27 cancer-predisposing genes in Japanese colorectal cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000346

• Target sequencing of 27 cancer-predisposing genes in Japanese pancreatic cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000327