4955 results for "*oma"

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• 10x Genomics Single Cell Gene Expression for SA1051AX1XB01452

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009124

• 10x Genomics Single Cell Gene Expression for SA1050FX1XB01446

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009125

• 10x Genomics Single Cell Gene Expression for SA1050DX1XB01437

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009126

• 10x Genomics Single Cell Gene Expression for SA1052BX1XB01516

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009127

• 10x Genomics Single Cell Gene Expression for SA1053FX1XB01611

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009128

• 10x Genomics Single Cell Gene Expression for SA1093CX1XB01917

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1093 passage 1

  Dataset EGAD00001009129

• 10x Genomics Single Cell Gene Expression for SA1091AX1XB01790

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1091 passage 1

  Dataset EGAD00001009130

• 10x Genomics Single Cell Gene Expression for SA1053BX1XB01603

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009131

• 10x Genomics Single Cell Gene Expression for SA1096AX1XB02034

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009132

• 10x Genomics Single Cell Gene Expression for SA1051DX1XB01482

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009133

• 10x Genomics Single Cell Gene Expression for SA1052JX1XB01535

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009134

• 10x Genomics Single Cell Gene Expression for SA1181AX1XB02700

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1181 passage 1

  Dataset EGAD00001009135

• 10x Genomics Single Cell Gene Expression for SA1096CX1XB02039

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009136

• 10x Genomics Single Cell Gene Expression for SA1096BX1XB02037

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009137

• 10x Genomics Single Cell Gene Expression for SA1162BX1XB03004

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1162 passage 1

  Dataset EGAD00001009138

• 10x Genomics Single Cell Gene Expression for SA1096A

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1096

  Dataset EGAD00001009139

• 10x Genomics Single Cell Gene Expression for SA1049CX1XB01422

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

  Dataset EGAD00001009140

• 10x Genomics Single Cell Gene Expression for SA1050EX1XB01442

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009141

• 10x Genomics Single Cell Gene Expression for OV2295

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295

  Dataset EGAD00001009143

• 10x Genomics Single Cell Gene Expression for OV2295(R2)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295(R2)

  Dataset EGAD00001009144

• 10x Genomics Single Cell Gene Expression for SA1184SA

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1184

  Dataset EGAD00001009145

• 10x Genomics Single Cell Gene Expression for SA1047BX1XB01022

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1047 passage 1

  Dataset EGAD00001009146

• Exome-sequencing of H3-K27M glioma.

  Fastq or bam files are deposited for 28 patient H3-K27M diffuse midline gliomas. UMPEDD65 was profiled by targeted exome-sequencing using the TSO500 Illumina assay, while all other samples were sequenced by whole-exome sequencing.

  Dataset EGAD00001009269

• Bone marrow microenvironment of 6 newly diagnosed myeloma patients using 10X Genomics scRNA- and TCR-sequencing

  10X Genomics scRNA- and TCR-sequencing (Chromium Next GEM Single Cell 5’ Reagent Kit v1.1) was performed on the plasma cell depleted mononuclear fraction of bone marrow aspirates from 6 patients with newly diagnosed multiple myeloma. Generated gene expression libraries were paired-end sequenced on the NovaSeq 6000 S2. Generated V(D)J libraries were paired-end sequenced on the NextSeq 550.

  Dataset EGAD00001009270

• Neuroblastoma WGS samples used for analysis of telomeric sequences

  Paired-end WGS data of 10 neuroblastoma patient samples (5 obtained at diagnosis and 5 matched blood samples as controls) used for analysis of telomeric content and sequence composition. Mean coverage is 11-65x per sample. The remaining patient samples of the dataset can be found under accession numbers EGAS00001001308 and EGAS00001005424 and mappings of the patients IDs in the supplementary material of the publication.

  Dataset EGAD00001009289

• SPECIAL: scRNA-seq

  Tumour biopsies were collected from twenty-three patients (46 samples) (of which 20 were matched) with locally advanced or metastatic melanoma (stage IIIB – stage IV). Library construction was done either with the Chromium Single Cell 3ʹ GEM, Library & Gel Bead Kit v3 (n = 16; 10x genomics, Cat#1000092) or the Chromium Single Cell A Chip Kit and 5’ Library & Gel Bead Kit (10x genomics, Cat#1000014). All libraries were sequenced on Illumina NextSeq, HiSeq4000 or NovaSeq6000 until sufficient saturation was reached (60% on average). The reference genome used in this study was GRCh38.

  Dataset EGAD00001009291

• WTS and WES of Renal Cell Carcinoma Tumors From a Phase III Anti-Angiogenic Adjuvant Therapy Trial

  Archival de-identified formalin-fixed paraffin-embedded RCC tumor tissue blocks from nephrectomy or tumor biopsy were processed as per below and the same sections were used for both DNA and RNA extractions. For WES (ACE version 3; Illumina NovaSeq), samples were profiled using Personalis ACE Cancer Exome (Personalis, Inc, Menlo Park, CA) Whole-transcriptome profiles were generated by RNA-seq (Accuracy and Content Enhanced (ACE) version 3; Illumina NovaSeq) using Personalis ACE Cancer Transcriptome (Personalis, Inc, Menlo Park, CA ) Of the 615 patients in the intent-to-treat population in S-TRAC trial, 193 individual specimens were available for molecular profiling, of which 171 (27.8%) (sunitinib, n = 91; placebo, n = 80) returned results for the WES analysis, and 133 (21.6%) (sunitinib, n = 72; placebo, n = 61) returned results for the GES analysis. Of the 138 WTS samples with data, replicates for two patients were summarized by median expression, and three samples were excluded from the final analysis due to low counts.

  Dataset EGAD00001009294

• extended cohort of single cell RNAseq data of lung adenocarcinoma

  extended cohort of single cell RNAseq data of lung adenocarcinoma

  Dataset EGAD00001009300

• 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

• 10x Genomics Single Cell Gene Expression for TOV2295(R)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line TOV2295(R)

  Dataset EGAD00001009158

• Oropharyngeal Squamous Cell Carcinoma Mutanome

  This dataset comprises genetic variation data (as somatic indels and snvs VCFs) of 38 OPSCC tumors. WES was done using NextSeq 500 System running in 150 cycles (2x 75bp paired-end) mode. Sequence information was converted to FASTQ format using bcl2fastq v2.20.0.422. VCFs were generated using the Strelka package.

  Dataset EGAD00001009167

• Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma consisting of 123 samples with FASTQs with hg19 aligned BAM/BAI files.

  Dataset EGAD00001009175

• Single-cell mRNA-sequencing to generate a transcriptomic atlas of RMS

  Single-cell mRNA-sequencing to generate a transcriptomic atlas of soft tissue sarcoma tumors

  Dataset EGAD00001009385

• Somatic mutations predict an aggressive phenotype in meningioma but do not drive grade progression

  A subset of meningiomas progress in histopathological grade and drivers of progression are poorly understood. We aimed to identify somatic mutations and copy number alterations (CNAs) associated with grade progression in a unique matched tumour dataset. This dataset consists of DNA sequencing from 10 individuals with meningiomas, where the meningiomas have underdone grade progression. 50 meningiomas were sequenced from the 10 individuals using the hybrid capture-based TruSight Oncology 500 (TSO500) Library Preparation Kit, and 13 of those meningiomas were also sequenced using Agilent SureSelect Clinical Research Exome V2. BAM files for the sequencing data are included in the dataset.

  Dataset EGAD00001009391

• Additional RNASeq files for Roussel MBPRP

  Additional RNASeq files for Roussel paper titled "Combination of CDK4/6 with BET-bromodomain and PI3K/mTOR inhibitors in medulloblastoma in vitro and in vivo"

  Dataset EGAD00001009394

• Targeted DNA sequencing dataset for the study "Molecular profiling of EBV associated diffuse large B-cell lymphoma"

  We performed deep targeted DNA sequencing with a panel of 74 selected cancer-related genes previously identified to be recurrently mutated in EBV associated DLBCL. Sequencing was performed on a HiSeq platform (Illumina) with 250 bp paired-end reads. There are 68 FFPE samples in this targetedDNAseq-dataset with 46 unpaired tumors and 22 normals used as a panel of normals.

  Dataset EGAD00001009396

• Oesophageal adenocarcinoma RNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains bulk transcriptomes from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). Transcriptomes were prepared from pre-treatment oesophageal tumour biopsies using a ribodepletion approach in order to assess both previously reported (e.g. PD-L1 expression) and novel predictive expression-based biomarkers for immunochemotherapy treatment in this setting. On-treatment and post-treatment biopsies were generated as well to characterize response to therapy, and samples were also prepared from paired normal GI tissues for a subset of patients. scRNA-seq based deconvolution was also applied to bulk transcriptomes in this study to estimate the cell composition of tumour biopsies and assess the link between the presence of specific cell types with immunochemotherapy outcomes.

  Dataset EGAD00001009399

• Oesophageal adenocarcinoma WGS from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains whole genome sequencing (WGS) generated from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). WGS data were generated with the aim to assess previously reported (e.g. tumour mutational burden) and novel predictive genomic markers for immunochemotherapy treatment in this setting. Using these data, mutation and copy number profiles were generated for the LUD2015-005 study, which were assessed for correlation with patient outcomes from this trial.

  Dataset EGAD00001009400

• An aggregated vcf file

  Germline variants calls were defined using the sequenced reads derived from 230 patients with hepatocellular carcinoma. This dataset is comprised of one aggregated vcf file.

  Dataset EGAD00001009410

• Medulloblastoma Nanopore whole genome sequencing 3 samples

  ONT (PromethION) sequencing of chromothriptic medulloblastoma. Three samples: blood, primary tumor, and relapse tumor. Includes a fourth low-coverage run that multiplexes blood and primary tumor.

  Dataset EGAD00001009411

• Tapestri snDNA-seq data along with matched bulk data for validation

  Files from Tapestri snDNA-seq of archival tissue samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients. Matched bulk sequencing (whole-exome, whole-genome, MSK-IMPACT) data are attached for a subset of the patients.

  Dataset EGAD00001009735

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 0)

  Whole genome sequencing data of 5 High-grade serous carcinoma (HGSC) patients (6 samples) sequenced with BGI.

  Dataset EGAD00001009738

• Single-cell mRNA-sequencing of neuroblastoma

  Profiling of childhood neuroblastoma by single-cell RNA sequencing

  Dataset EGAD00001009766

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• Single cell RNA sequencing of bone marrow mononuclear cells from healthy donors and B-cell lymphoma patients following CD19 CAR T-cell therapy

  Bone marrow aspirates were obtained from patients with relapsed/refractory large B cell lymphoma (rrLBCL), mononuclear cells isolated by ficoll density-gradient centrifugation, and loaded onto a 10X Chromium for single cell RNA-sequencing using 5’ chemistry without prior cryopreservation. Healthy donor bone marrow mononuclear cells were obtained from healthy allogeneic stem cell transplant donors and analyzed following viable cryopreservation.

  Dataset EGAD00001009774

• Dataset HCV positive lymphoma whole exome sequencing

  This dataset contains 68 BAM files from matched normal-tumor pairs of HCV positive lymphoma analyzed by exome sequencing on Ilumina platform.

  Dataset EGAD00001009786

• WGS files for CIC paper data

  WGS files for CIC paper titled "Malignant progression of an ancestral bone marrow clone harboring a CIC-NUTM2A fusion in isolated myeloid sarcoma"

  Dataset EGAD00001009787

• RNASeq files for CIC paper data

  RNASeq files for CIC paper titled "Malignant progression of an ancestral bone marrow clone harboring a CIC-NUTM2A fusion in isolated myeloid sarcoma"

  Dataset EGAD00001009788

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 2)

  Whole genome sequencing data of 8 High-grade serous carcinoma (HGSC) patients (20 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001009791

• WGS of tumor and blood control samples of neuroblastoma

  high coverage whole genome sequencing of 38 samples was done on a patterned flowcell v.2.5 (150 bp paired end, HiSeq X Ten) with coverage of about 60x for the tumor and whole blood control samples. All tumors had a tumor cell content of ≥60%. Sequencing libraries were prepared using the Truseq DNA Nano kit (Illumina) according to the manufacturers’ instructions and size selected using SPRI beads (Beckman Coulter Genomics).

  Dataset EGAD00001009624