14977 results for "cancer studies using rna-seq"

in 33.84 milliseconds.

• Identification of HER2-positive breast cancer molecular subtypes with potential clinical implications in the ALTTO clinical trial

  In HER2-positive breast cancer, clinical outcome and sensitivity to HER2-targeted therapies are influenced by both tumor and microenvironment features. However, we are currently unable to depict the molecular heterogeneity of this disease with sufficient granularity. Here, by performing gene expression profiling in HER2-positive breast cancers from patients receiving adjuvant trastuzumab in the ALTTO clinical trial, we identified and characterized five molecular subtypes associated with the risk of distant recurrence: immune-enriched (IM), proliferative/metabolic-enriched (P/Met), mesenchymal/stroma-enriched (Mes/S), luminal (LUM), and ERBB2-enrichedERBB2-dependent (ERBB2-EERBB2-D). We next validated the biological profiles of the subtypes and explored their prognostic/predictive value in external cohorts, namely the NeoALTTO trial, SCAN-B, I-SPY2, METABRIC and TCGA. IM tumors presented better survival outcomes, in contrast to Mes/S and P/Met tumors, while LUM tumors and ERBB2-EERBB2-D were characterized by low and high rates of pathological complete response, respectively. Of note, these molecular subtypes provide the rationale for treatment approaches leveraging the heterogeneous biology of HER2-positive breast cancer.

  Study EGAS50000000525

• High-coverage whole-genome sequencing reveals structural variations in triple-negative breast cancer

  Triple-negative breast cancer (TNBC) cells do not express estrogen receptors, progesterone receptors or human epidermal growth factor receptor 2 (HER2). Currently, apart from poly ADP-ribose polymerase (PARP) inhibitors, there are few effective therapeutic options for this cancer type. Here, we present a comprehensive characterization of genetic alterations in TNBC via high-coverage whole-genome sequencing along with transcriptomic and whole-exome sequencing. Silencing of BRCA1 gene impaired the homologous recombination (HR) pathway in a subset of TNBC, which exhibited similar phenotypes with tumors with BRCA1 mutations; they harbored many structural variations (SVs) with relative enrichment for tandem duplication. Clonal analysis suggested that TP53 mutations and methylation of CpG dinucleotides in the BRCA1 promoter were the early events of carcinogenesis. SVs were associated with driver oncogenic events such as amplification of MYC, NOTCH2 or NOTCH3 and impacted tumor suppressor genes including RB1, PTEN and KMT2C. We also identified a variety of oncogenes that could transform 3T3 mouse fibroblast cells, suggesting that individual TNBC tumors may undergo a unique driver event that can be targetable. Thus, we revealed several features of TNBC that had important clinical implications.

  Study JGAS000095

• Rucaparib in patients presenting a metastatic breast cancer with Homologous Recombination Deficiency, without germline BRCA1/2 mutation, pronostic value of high LOH genomic score and predictive value of HRDetect (microarray)

  Breast cancer may present genomic alterations leading to homologous recombination deficiency. PARP inhibitors have proved their efficacy in patients with HER2-negative metastatic breast cancer (mBC) harboring germline (g) BRCA1/2 mutations. We conducted the phase 2 RUBY trial to assess the efficacy of rucaparib in HER2-negative mBC with high genomic loss of heterozygosity (LOH) score or somatic, without gBRCA1/2 mutation. 220 of 711 patients with mBC screened for LOH presented high LOH score which was associated with a higher likelihood of death (HR = 1.39, 95% CI: 1.11-1.75, p = 0.005). The primary objective was not reached with a clinical benefit rate (objective response or SD>16 weeks) of 13.5%. Two LOH-high patients, without somatic BRCA1/2 mutation, presented a complete and durable response (14 and 32 months). HRDetect tended to be associated with response to rucaparib, whithout reaching statistical significance (median HRDetect responders versus non responders: 0.465 versus, 0.040, p = 0.2135). Our data suggests that a small subset of patients with high LOH score could derive benefit from PARP inhibitors.

  Study EGAS00001004755

• Immune and clinicopathological features predict HER2-positive breast cancer prognosis in the neoadjuvant NeoALTTO and CALGB 40601 trials

  The identification of prognostic drivers in patients receiving neoadjuvant therapy is crucial for treatment optimization in HER2-positive breast cancer, with the immune microenvironment being a key factor. Here, we investigated the complexity of B and T cell receptor (BCR and TCR) repertoires, reflecting antigen-specific immune response, in the context of two phase III trials, namely NeoALTTO and CALGB 40601, evaluating neoadjuvant paclitaxel with trastuzumab and/or lapatinib in women affected by HER2-positive breast cancer. BCR/TCR features were heterogeneous, and BCR measures describing clonal expansion demonstrated independent prognostic value. A model developed in NeoALTTO and validated in CALGB 40601 predicted event-free survival (EFS) by integrating hormone receptor and clinical nodal status, treatment response (breast pCR)breast pathological complete response (pCR) as well as tumor-infiltrating lymphocytes and BCR evenness, measuring the equality of BCR clonal distribution. The HER2-EveNT score derived from the model allows the identification of patients with 5-year EFS > 90%, and, in those not achieving pCR, of a subgroup of immune-enriched tumors with an excellent outcome despite residual disease.

  Study EGAS00001007563

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• EGAD00010000270

  Metabric breast cancer samples (Images)

  Dataset EGAD00010000270

• cfDNA dataset for cfDNA cohort

  Cell free DNA sequencing data for 233 samples across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000104

• Biomarker Data from KATHERINE: A Phase III Study of Adjuvant Trastuzumab Emtansine versus Trastuzumab in Patients with Residual Invasive Disease after Neoadjuvant Therapy for HER2-Positive Breast Cancer

  Study EGAS00001006229

• Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin

  Study EGAS00001004660

• FFPE_normals_v2_gbm_wtsi_panel

  Targeted pulldown of approx 60 ffpe normal samples to use as normal controls

  Study EGAS00001002124

• OT2_Illumina_WGS_MET

  Whole-genome sequencing on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003372

• OT2_Illumina_RNA_T

  RNAseq on Illumina HiSeq2000/2500 of colorectal cancer primary tumor sample (OT2_cohort)

  Dataset EGAD00001003367

• OT2_Solid_WXS_T

  Whole-exome sequencing on AB 5500xl Genetic Analyzer of colorectal cancer primary tumor sample (OT2_cohort)

  Dataset EGAD00001003386

• Prostate cancer datasets WES

  WES: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (HiSeq)

  Dataset EGAD00001004467

• Illumina_WGS_T

  Whole-genome sequencing on Illumina HiSeq2000/2500 of colorectal cancer primary tumor sample

  Dataset EGAD00001002088

• Hipo-032 Metastasome of Colorectal Cancer

  Whole genome sequencing of Control (blood), Tumor and metastasis triplets for 12 samples.

  Dataset EGAD00001003965

• BASIS Genome Validation Study

  Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing.

  Dataset EGAD00001000661

• Human_Developmental_Cell_Atlas_HDCA___WGS

  Single cell + bulk genomics study for immune and hematopoietic organs during human fetal development

  Study EGAS00001002929

• Childhood_arthritis_DNA

  The aim of this study is to describe the transcriptome of single arthritic cells.

  Study EGAS00001002652

• pilot

  Pilot study for genome-wide sequencing of cell-free DNA from nipple aspirate fluid and plasma of breast cancer patient

  Dataset EGAD00001010836

• Chromatin immunoprecipitation linked to next-generation whole genome sequencing (ChIP-Seq) for H3K36me3 in paediatric high grade glioma cell lines KKNS4 and SF188 with and without a G34V mutation in H3F3A

  Glioblastomas of children and young adults have a median survival of only 12-15months and are clinically and biologically distinct from histologically similar cancers in older adults1. They are defined by highly specific mutations in the gene encoding the histone H3.3 variant H3F3A2, occurring either at or close to key residues marked by methylation for regulation of transcription – K27 and G34. We performed chromatin immunoprecipitation linked to next-generation whole genome sequencing (ChIP-Seq) for H3K36me3 in order to test the hypothesis that, rather than total H3K36me3, the G34V mutation may instead result in differential binding of the trimethyl mark throughout the genome. Compared with H3F3A wild-type SF188 paediatric GBM cells, H3K36me3 was found to be significantly differentially bound in KNS42 cells at 5130 distinct regions of the genome corresponding to 156 genes. Concurrent whole genome DNA sequencing demonstrated that this was not confounded by copy number alterations. The cerebral hemispheric-specific G34 mutation drives a distinct expression signature through differential genomic binding of the K36 trimethylation mark (H3K36me3). The transcriptional program induced recapitulates that of the developing forebrain, and involves numerous markers of stem cell maintenance, cell fate decisions and self-renewal. Critically, H3F3A G34 mutations cause profound upregulation of MYCN, a potent oncogene which is causative of glioblastomas when expressed in the correct developmental context. This driving aberration is selectively targetable in this patient population by inhibiting kinases responsible for stabilisation of the protein.

  Study EGAS00001001437

• HuBMAP: KULMAP - Human Kidney, Urinary Tract, and Lung Mapping Center

  The major goal of the Human Kidney, Urinary Tract, and Lung Mapping Center (KULMAP) is to generate multi-omic and spatially resolved molecular anatomical maps of the human bladder, ureter and kidneys (BUKMAP) and the lung airways and parenchyma (LAPMAP) at a single cell resolution. This entails sequencing of the transcriptomes and epigenomes of dissociated single cells in a massively parallel manner. These profiles will then inform on highly multiplexed RNA in situ imaging for spatial mapping of hundreds of molecular targets in the tissue sections, at a subcellular resolution. These spatial molecular maps will serve as scaffolds for computational registration of cell types and the associated transcriptome/chromatin maps to the tissue space. The combination of sequencing single dissociated cells and multiplexed in situ mapping will allow the construction of detailed spatial maps for these large organs.

  Study phs002249

• University of Texas at Austin (UTA) Histone Modification and Gene Expression Profiling in 9 Primary Glioblastoma Multiforme, 2 Anaplastic Astrocytomas and Two Meningiomas

  The primary goal of this study was to collect and analyze genomic data from primary glioblastoma multiforme tumors. Our collaborators at St David's Medical Center (SDMC) obtained informed consent from patients undergoing surgery to remove a tumor in the brain. After consent was obtained, specimens were removed from the operating suite and flash frozen in liquid nitrogen. Tumors were analyzed if they were a grade III (anaplastic astrocytoma) or grade IV glioma (glioblastoma multiforme). Tumors were transported from SDMC to UT Austin, then weighed and homogenized. Chromatin immunoprecipitation was performed for 7 proteins in each tumor (histone modifications H3K4me3, H3K4me1, H3K9ac, H3K9me3, H3K27ac, H3K27me3, and the multifunctional insulator binding protein CTCF) and no-antibody input was also sequenced. An aliquot of tumor material was set aside for isolation of total RNA.

  Study phs001389

• Modeling Malignant Progression in Glioma

  Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.

  Study phs002607

• A Human Lymphoma Organoid Model for Evaluating and Targeting the Follicular Lymphoma Tumor Immune Microenvironment

  Heterogeneity in the tumor microenvironment (TME) of follicular lymphoma (FL) can affect clinical outcomes. We developed a new organoid culture method for cultivating patient-derived lymphoma organoids (PDLOs), which include cells from the native FL TME. We generated organoids from 12 FL patients at diagnosis, clinical progression, or relapse. These organoids were profiled with targeted DNA sequencing and mRNA sequencing. We evaluated the stability of organoids in culture at serial weekly timepoints (D0, D7, D14, D21). We treated organoids with CD19:CD3 or CD20:CD3 bispecific antibodies or unconjugated anti-CD20, anti-CD19, and anti-CD3 as a control, and profiled DNA/RNA at D11 to evaluate treatment response. This system is intended as a platform for advancing precision medicine efforts in FL through patient-specific modeling, high-throughput screening, TME signature identification, and treatment response evaluation.

  Study phs003410

• Pediatric Preclinical Testing Consortium (PPTC)

  The Pediatric Preclinical Testing Consortium (PPTC) is addressing the unmet need of streamlining the development of new therapies for childhood cancers. The PPTC seeks to develop robust biomarkers of anticancer drug activity, and the majority of these are predicted to be genetic mutations that can be detected in tumor DNA and/or RNA. In order to design the most impactful experiments that can be rapidly translated to the clinic, PPTC investigators require a complete genomic characterization of the patient-derived xenograft tumor models that are utilized across the consortium. This will not only allow for the most robust experimental design, but also will increase the engagement of industry partners who seek collaborators poised to provide the proof-of-concept necessary for drugs in their development pipelines. All data and models will be made available to academically qualified investigators.

  Study phs001437

• Recurrent CLTC::SYK fusions and CSF1R mutations in juvenile xanthogranuloma of soft tissue

  In this study, the genomic landscape of extracutaneous juvenile xanthogranuloma (JXG) was analyzed. By leveraging the Dutch Nationwide Pathology Databank (Palga), tumor samples were obtained from different academic medical centers in the Netherlands. The study was approved by the Palga Scientific Council and Privacy Committee (LZV-2016-183) and the Institutional Review Board of Leiden University Medical Center (B19.074). In addition, the study was approved by the Biobank and Data Access Committee of the Princess Máxima Center for Pediatric Oncology (PMCLAB2024.0512). Provided are whole transcriptome sequencing (WTS) data of 3 histiocytic tumors with CLTC::SYK fusions. WTS was performed in the routine workflow of the Princess Máxima Center for Pediatric Oncology (as described in Hehir-Kwa, et al. JCO Precis Oncol 2022). RNA was derived from formalin-fixed paraffin-embedded tumor tissue (n=1) or from frozen tumor tissue (n=2).

  Study EGAS50000000584

• Genetic and transcriptional landscape of plasma cells in POEMS syndrome

  POEMS syndrome is a rare paraneoplastic disease, associated with monoclonal plasma cells whose pathogenic importance remains unclear. We performed comprehensive genetic analyses of plasma cells in 20 patients with POEMS syndrome. Whole exome sequencing and targeted sequencing identified 7 recurrently mutated genes: KLHL6, LTB, EHD1, EML4, HEPHL1, HIPK1, and PCDH10. None of the driver gene mutations frequently found in multiple myeloma (MM) such as NRAS, KRAS, BRAF, and TP53 was detected. Copy number analysis showed chromosomal abnormalities shared with monoclonal gammopathy of undetermined significance (MGUS). RNA sequencing revealed a transcription profile specific to POEMS syndrome, especially in terms of tumorigenesis. Unexpectedly, disease-specific VEGFA expression was not increased in POEMS syndrome. Our study illustrates that the genetic and transcriptional profiles of plasma cells in POEMS syndrome are distinct from MM and MGUS, indicating its unique pathogenesis.

  Study JGAS000150

• Raw human sequencing data for “Characterization of intestinal immune responses in generalized human and murine lipodystrophy”

  This dataset contains raw FASTQ files generated from peripheral blood and intestinal biopsy samples collected for the study “Characterization of intestinal immune responses in generalized human and murine lipodystrophy.” Peripheral blood sequencing was performed on samples from three healthy donors as controls and from a patient with acquired generalized lipodystrophy and Crohn’s disease (AGLCD) at two distinct timepoints. Intestinal biopsy–derived immune cells were sequenced from three individuals with Crohn’s disease as disease controls, as well as from the AGLCD patient (single timepoint). The data include paired-end FASTQ files derived from single-cell RNA sequencing and T-cell receptor repertoire profiling, enabling analyses of immune composition, transcriptional states, and clonal T-cell expansion. All data are controlled-access human genomic datasets and require appropriate authorization for secondary use.

  Study EGAS50000001517

• Measuring the level of relatedness between NGS datasets

  Sequencing technologies are providing increasingly detailed insight in genetic makeup are paving their way into molecular diagnostics. The field will benefit from rigorous and bias-free measures for the quality of sequence data and for the proper representation of the complexity of the original samples. While current methodologies rely on the availability of a well-characterized reference genome, we propose kMer profiling for alignment-free assessment of the quality, comparability, and complexity of sequencing datasets. We show that kMer detects technical artefacts such as high duplication rates, library chimaeras, and differences in library preparation protocols in whole-genome, whole-exome, and RNA sequencing data. Additionally, it successfully captures the complexity and diversity of microbiomes. Thus, kMer allows for a robust evaluation of the quality and complexity of sequencing data without relying on any prior information and opens the way to a more reliable biological reasoning.

  Study EGAS00001000600