3798 results for "*oma"

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• Epigenetic subtypes of neuroblastoma - ChIPseq

  In the absence of recurrent gene mutations, evidence accumulates that epigenetic deregulation plays a prominent role in neuroblastoma biology. Here we provide genome wide H3K27ac profiles in 60 primary neuroblastoma samples.

  Dataset EGAD00001006285

• Epigenetic subtypes of neuroblastoma - RNAseq

  In the absence of recurrent gene mutations, evidence accumulates that epigenetic deregulation plays a prominent role in neuroblastoma biology. Here we provide RNAseq profiles in 71 primary and relapse neuroblastoma samples.

  Dataset EGAD00001006286

• Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

  NGS data of 12 patients enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017.

  Dataset EGAD00001006287

• SF10679

  SF10679 snATAC Seq. Oligodendroglioma, Anaplastic (WHO gr. 3). Tumor Location: Frontal Age: 43. Sex: Male.

  Dataset EGAD00001006312

• SF10619

  SF10619 snATAC Oligodendroglioma (WHO gr. 2).Tumor Location: Parietal. Age: 52. Sex: Male

  Dataset EGAD00001006316

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Dataset EGAD00001006293

• Therapeutic vulnerabilities in the DNA damage response for the treatment of ATRX mutant neuroblastoma

  Whole genome sequencing data of isogenic ATRX/TP53 knockout clones of the neuroblastoma cell line SK-N-SH

  Dataset EGAD00001006294

• Genomic characterization (through whole-exome sequencing) of bone marrow clonal plasma cells before and after VRD treatment from multiple myeloma patients.

  WES data from clonal pahtologic bone marrow plasma cells of multiple myeloma patients. From each patient there are three samples, pathologyc bone marrow plasma cells at diagnosis, pathologyc bone marrow plasma cells after VRD treatment and T lymphocytes as germline control. There are 14 patients in total

  Dataset EGAD00001006302

• SF4007

  SF4007 snATAC Seq. Oligodendroglioma (WHO gr. 2) Tumor Location: Left frontotemporal. Age:33. Sex: Female.

  Dataset EGAD00001006317

• SF10207

  SF10207 snATAC Seq. Oligodendroglioma, Anaplastic (WHO gr. 3). Tumor Location:Frontal. Age:43. Sex: Male

  Dataset EGAD00001006319

• The Transcriptional Landscape of SHH Medulloblastoma

  To further understand the biology of Sonic hedgehog medulloblastoma and its molecular subtypes, we studied 250 human Shh-MB using strand-specific RNA sequencing. We identified novel alterations within the cAMP dependent pathway and found that 18% of tumors have genetic events that directly target the abundance and/or stability of MYCN. We also discovered an extensive network of fusions in focally amplified regions, and several loss-of-function fusions in tumor suppressor genes PTCH, SUFU and NCOR1. Molecular convergence on a core of specific genes by nucleotide variants, copy number aberrations, and gene fusions highlights key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma.

  Dataset EGAD00001006305

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma_CM67-RNASeq

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006306

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006309

• SF11940

  SF11940 snATAC Sequencing.Anaplastic Astrocytoma, IDH-mutant. Tumor location: Left Frontal. Age: 29. Sex: Male .

  Dataset EGAD00001006311

• SF11310

  SF11310 Oligodendroglioma, IDH-mutant.Tumor Location: Frontal. Age:22. Sex: Female

  Dataset EGAD00001006313

• SF12374

  SF12374 snATAC Oligodendroglioma. Tumor Location: Right frontal. Age: 33. Sex: Male.

  Dataset EGAD00001006315

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006325

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  Dataset EGAD00001006329

• Analysis of the Patient derived cells that model the intratumoral heterogeneity of hypermutated IDH1 mutant glioma

  Dataset contains paired-end Whole Exome sequencing data from 2 glioma patients (1 oligodendroglioma and 1 astrocytoma) , derived cultured cells, and derived murine xenografts.

  Dataset EGAD00001006340

• Additional Neuroblastoma whole genome sequencing data (Part 2)

  Additional Neuroblastoma whole genome sequencing data

  Dataset EGAD00001006344

• Whole Exome Sequences IberianRoma

  Dataset with 81 whole exome sequences from Iberian Roma samples.

  Dataset EGAD00001006357

• Genome-wide data Iberian Roma

  VCF file with genome-wide data for 62 Iberian Roma samples.

  Dataset EGAD00001006358

• Genomic characterisation of MGUS

  The hematological malignancy multiple myeloma (MM), also called Kahler's disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Dataset EGAD00001006363

• RRBS profiling for a cohort including 88 precancer specimens from 62 resected lung nodules from 39 patients including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) and 39 matched normal lung tissues.

  To study the evolution of DNA methylation at genome level and methylation intra-tumor heterogeneity (ITH) during early lung carcinogenesis, we performed multiregional reduced representation bisulfite sequencing (RRBS) of 127 resected lung samples from 39 patients using single end library Hiseq3000.

  Dataset EGAD00001006367