4836 results for "*oma"

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• Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

  This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

  Dataset EGAD00001010073

• CTCF ChIP-sequencing data for Oncogenic 3D genome conformations identify novel therapeutic targets in ependymoma

  This dataset contains CTCF ChIP-sequencing data from seven samples (six tumor samples and one tumor derived cell line). Following library amplification, DNA fragments were sequenced using Illumina HiSeq 2000 paired-end sequencing resulting in 14 FASTQ files.

  Dataset EGAD00001008806

• Genome and transcriptome sequence data from a uveal melanoma patient

  Genome and transcriptome sequence data from a uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010956

• Single-cell study of 14 childhood medulloblastoma patients

  Medulloblastoma intra-tumoural genetic heterogeneity and clonal evolution, and their role in disease pathogenesis and clinical behaviour, are poorly understood. We used single-cell whole-genome sequencing (sc-WGS) to reconstruct the natural history and temporal evolution of 14 medulloblastomas, representing its major clinico-molecular sub-classes. We identified wholly-clonal tumours which displayed single-clone expansion (i.e. linear evolution); all were observed in favourable-outcome sub-classes (i.e. MBWNT and infant MBSHH). In contrast, remaining tumours harboured sub-clonal structures which displayed punctuated or gradual trajectories; highest-risk sub-classes, typically characterised by MYC-amplification (MBGroup3) or TP53-mutation (MBSHH), and linked to genomic instability and LCA pathology, were most clonally-diverse. Clinically-adopted biomarkers were typically early-clonal/initiating events, representing exploitable targets for early-disease detection; in analyses of spatially-distinct tumour regions, a single biopsy was sufficient to assess their status. sc-WGS revealed events not previously appreciated in bulk tumour analysis, which arose later and/or sub-clonally and more commonly displayed spatial diversity; their clinical significance and role in disease evolution post-diagnosis now require establishment. In summary, our findings reveal diverse modes of tumour initiation and clonal evolution in the major medulloblastoma sub-classes, highlighting their pathogenic relevance and clinical potential.

  Dataset EGAD00001009057

• WES normal samples

  Raw FASTQ files obtained from whole exome sequencing (WES) of normal samples from patients with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008405

• Whole exome sequencing data of Hispanic hepatocellular carcinoma

  The paired-end reads were aligned to the human reference genome (hg19) with decoy sequences (as used in the 1000 Genomes Project) using BWA (v0.7.5a) software. The duplicate reads were marked and subsequently removed using Picard (v1.140) (https://broadinstitute.github.io/picard/) and SAMtools (v0.1.19), respectively. Local realignment around insertions/deletions (indels) and base quality recalibration were performed using GATK (v3.6).

  Dataset EGAD00001011158

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• Immune profiling reveals enrichment of distinct immune signatures in oral epithelial dysplasia

  The dataset contains transcriptomic information of 36 oral potentially malignant disorders (OPMD), 14 fibroepithelial polyps (FEP), and 6 early stage oral squamous cell carcinoma (OSCC) from the Asian population. Total RNA was extracted from formalin-fixed paraffin embedded (FFPE) tissue sections. RNA libraries were prepared using the NEB NextUltra RNA kit with Illumina Ribo-Zero rRNA removal as per manufacturer’s instructions. RNA sequencing was performed on the HiSeq2500 platform to generate paired-end 150 nucleotides reads and with a coverage of 50 million reads per sample. Uploaded bam files have been mapped to the GRCh38 human genome using TopHat2. Clinical and demographic data for these patients are available from the associated publications or by request.

  Dataset EGAD00001007970

• Whole transcriptome profiling of osteosarcoma

  This dataset contains 86 osteosarcoma samples and their matched normals that underwent RNA sequencing using size fractionation, NuGEN Ovation Ultralow Library System V2 preparation, and paired-end sequencing on Illumina HiSeq 2000.

  Dataset EGAD00001008436

• Single-cell RNA-sequencing of a multi-region pleural mesothelioma case

  Single-cell RNA-seq (Smart-Seq2) from 3 distant biopsies (costal, mediastinal, diaphragmatic) of a pleural mesothelioma case.

  Dataset EGAD00001015519

• Mesothelioma of the peritoneum and Pseudomyxoma peritonei

  Mesothelioma of the peritoneum (n=21) and Pseudomyxoma peritonei/mucinous adenocarcinoma of the appendix (n=11)

  Dataset EGAD00001008826

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• Whole exome sequencing (bam files) of 55 samples of myxofibrosarcoma and 44 matched pairs

  Whole exome sequencing data (bam files) of 55 samples of myxofibrosarcoma and 44 matched pairs.

  Dataset EGAD00001007824

• DLP+ Single Cell Genomic Library 98211

  DLP+ Single Cell Genomic Library 98211 for Diffuse large B-cell lymphoma patient sample TFRIPAIR11_DLBCL

  Dataset EGAD00001010239

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  38 PPTCs were sequenced using RNASeq to identify oncogenic variants in driver-unknown tumors and to explore gene expression patterns. RNA libraries were quantified by qPCR using the Kapa Library Quantification Illumina/ABI Prism Kit protocol (KAPA Biosystems). Libraries were pooled in equimolar quantities and paired-end sequenced on 2 lanes of a High Throughput Run Mode flowcell with the V4 sequencing chemistry on an Illumina HiSeq 2500 platform following Illumina’s recommended protocol to generate paired-end reads of 126-bases in length.

  Dataset EGAD00001007499

• Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

  Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN >=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

  Dataset EGAD00001010876

• A Proteogenomic Analysis of Clear Cell Renal Cell Carcinoma in a Chinese Population

  Whole exome sequecing data of 224 Chinese Clear Cell Renal Cell Carcinoma patients.

  Dataset EGAD00001008556

• Berlin Neuroblastoma Patient Genomic Data from Targeted Sequencing

  Targeted DNA sequencing data of paired primary and relapse tumor material taken from a pediatric patient with neuroblastoma.

  Dataset EGAD00001008564

• Ampliseq library database

  This database contains 46 samples for early stage ovarian high grade serous carcinoma project. Amplicon sequencing on 37 tumour samples from early stage ovarian high grade serous carcinoma as well as 5 adjacent normal tissue samples and 4 whole blood samples.

  Dataset EGAD00001008587

• Whole genome sequencing of Multiple Myeloma CD138positive bone marrow plasma cells and saliva control samples

  Whole genome paired sequencing of Multiple Myeloma CD138positive bone marrow plasma cells and saliva control samples (6 tripletts, tumor1, tumor2, saliva control) from 6 patients. WGS was done on HiSeq X-Ten or Novaseq 6000 with Illumina TruSeq Nano DNA.

  Dataset EGAD00001008618

• shallow whole genome sequencing dataset

  shallow whole genome sequencing dataset contains 44 samples. all the samples are early stage high ovarian high grade serous carcinoma.

  Dataset EGAD00001008588

• EPICC: Evolutionary Predictions in Colorectal Cancer WGS-3

  WGS profiling bam files from colorectal carcinoma and adenoma.

  Dataset EGAD00001008642

• Targetable NOTCH1 rearrangements in reninoma - RNA

  Reninomas are exceedingly rare renin-secreting kidney tumours that derive from juxtaglomerular cells, specialised smooth muscle cells that reside at the vascular inlet of glomeruli. They are the central component of the juxtaglomerular apparatus which controls systemic blood pressure through the secretion of renin. We assessed somatic changes in reninoma and found structural variants that generate canonical activating rearrangements of NOTCH1, whilst removing its negative regulator, NRARP. Accordingly, in single reninoma nuclei we observed excessive renin and NOTCH1 signalling mRNAs, with a concomitant non-excess of NRARP expression. Re-analysis of previously published reninoma bulk transcriptomes further corroborates our observation of dysregulated Notch pathway signalling in reninoma. Our findings reveal NOTCH1 rearrangements in reninoma, therapeutically targetable through existing NOTCH1 inhibitors, and indicate that unscheduled Notch signalling may be a disease-defining feature of reninoma.

  Dataset EGAD00001010889

• RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  Dataset EGAD00001008656

• Genome and transcriptome sequence data from a hepatocellular carcinoma patient

  Genome and transcriptome sequence data from a hepatocellular carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008929