16461 results for "sec+and+unspecified+malignant+neoplasm"

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• EED inhibition of organoid development

  Transcriptomics and epigenomics after chemical inhibition of EED during early human brain organoid development. To investigate the role of H3K27me3 inhibition during neuroectoderm induction, we treated brain organoids with 3 concentrations of EED inhibitor (and control) during the transition of pluripotency to neuroepithelium. At the neuroepithelium stage, we profiled the organoids using scRNA-seq (transcriptome) and bulk Cut&Tag (H3K27me3, H3K27ac). Library preparation for scRNA-seq was carried out with the 10x genomics platform.

  Dataset EGAD50000000224

• A comprehensive DNA methylation landscape of human and mouse cell lines derived from hematological malignancies

  The dataset from Infinium Human MethylationEPIC v1.0 (IDAT files) includes 91 primary samples from patients with B-cell acute lymphoblastic leukemia (B-ALL) (n=34) and T-cell acute lymphoblastic leukemia (T-ALL) (n=57). This dataset was used in the article "A Comprehensive DNA Methylation Landscape of Human and Mouse Cell Lines Derived from Hematological Malignancies" to validate differentially methylated CpG sites, which were utilized to classify hematologic malignancies.

  Dataset EGAD50000000888

• RNA-sequencing from ALL patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL06 study.

  Dataset contains RNA-sequencing data (fastq files) from 45 patients treated on the the Australasian Leukaemia and Lymphoma Group (ALLG) ALL06 study, an MRD-stratified Paediatric Protocol. Patient samples (bone marrow or peripheral blood) were taken at diagnosis. mRNA was extracted from blast cells and underwent paired-end sequencing (75bp) using the illumina NextSeq platform. Genomic data was used for identification of genomic drivers of acute lymphoblastic leukaemia (ALL).

  Dataset EGAD50000001111

• Longitudinal cfDNA methylome and fragmentome profiles in health

  This dataset contains 432 plasma cfDNA samples from healthy individuals, comprising a diurnal cohort of 16 participants and a cross-sectional cohort of 144 participants. Samples underwent capture-based target enrichment using a custom probe set covering 4,991 genomic regions, followed by targeted enzymatic methyl-sequencing on Illumina instruments in 150 bp paired-end mode. The dataset consists of raw FASTQ files generated from the sequencing runs, accompanied by a metadata file containing individual demographic details and sampling information.

  Dataset EGAD50000001721

• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Tumor implantation and expansion were performed in two 6-week-old NOD/SCID mice. Once tumors reached an average volume of approximately 700 mm³, mice were randomly assigned to one of two treatment arms: vehicle (physiological saline, intraperitoneally, twice weekly) or cetuximab (20 mg/kg, intraperitoneally, twice weekly). After 1 week of treatment, mice were sacrificed, and tumors were harvested and preserved in sCelLiVE® Buffer for downstream single-cell RNA sequencing analysis.

  Dataset EGAD50000002103

• Discovery and validation of an ancillary genomic test of malignancy for primary melanocytic tumors

  Background:Pathological diagnosis of melanocytic tumors can be difficult and prone to error. More accurate and reliable ancillary investigations than those currently available are required to improve diagnostic accuracy. Goals: (1) to generate a genomic model for distinguishing benign (nevi) from malignant (melanoma) melanocytic skin tumors, developed from a customized gene panel evaluated on a cohort of 250 nevi and melanomas. (2) To evaluate the performance of the genomic model in melanocytic tumors of uncertain diagnosis/behavior. Details: The cohort of 250 melanomas and naevi was split into a discovery set and a validation set. Our genomic model obtained an area under the curve of 95% in the discovery cohort and 96% for the validation cohort. Based on a Youden index threshold, the resulting classifier shows high specificity (>95% in the discovery and validation cohorts), with sensitivities >80% in the discovery and validation cohorts. Evaluation of the genomic model on a cohort of 110 melanocytic tumors identifies key driver mutations in agreement with the likely pathway of origin of the tumors. The probability of melanoma (p=0.02) from the genomic model was significantly associated with pathology-based estimates of malignancy for melanocytic tumors lacking pathway-defining genomic aberrations (conventional tumors). The genomic model identified 8/36 (22%) conventional tumors with unresolved malignancy to have a high probability of melanoma, with 7/8 of these cases showing negative/non-aberrant results with either fluorescent in-situ hybridization, PRAME and/or p16 immunostains. Furthermore, no evidence of malignant behavior based on the genomic model was seen in 4 conventional borderline tumors with more than 1 year follow-up. Conclusion: This genomic model can become a clinically useful ancillary tool that is highly specific for differentiating melanomas from nevi.

  Study EGAS50000000887

• Development of Novel Chondrosarcoma Organoid Models for Drug Discovery

  Chondrosarcoma is a rare and aggressive malignant bone tumor characterized by resistance to conventional chemotherapy and radiotherapy. Its pathogenesis remains poorly understood, although recurrent mutations such as IDH1 have been implicated in tumor development. We treated patients with chondrosarcoma at the Osaka International Cancer Institute and established two organoid cultures from resected tumor specimens using a modified air-liquid interface method. After serial passaging, the organoids were successfully xenografted into NOD-scid IL2Rgnull (NSG) mice. The established organoids retained key histological features and genetic characteristics of the original tumors. These organoid models provide a novel and reliable platform for studying the biology of chondrosarcoma and may facilitate the development of effective therapeutic strategies for this treatment-resistant tumor.

  Study JGAS000834

• Single-cell RNA-seq data of the tumor microenvironment of lymphocyte-rich Hodgkin lymphoma and other Hodgkin lymphoma subtypes

  Lymphocyte-rich classic Hodgkin lymphoma (LR-CHL) is a rare subtype of Hodgkin lymphoma. Recent technical advances have allowed for the characterization of specific crosstalk mechanisms between malignant Hodgkin Reed-Sternberg (HRS) cells and different normal immune cells in the tumor microenvironment (TME) of CHL. However, the TME of LR-CHL has not yet been characterized at single cell resolution. Here, using single cell RNA sequencing, we examined the immune cell profile of 8 cell suspension samples of LR-CHL in comparison to 20 samples of the mixed cellularity (9 cases) and nodular sclerosis (11 cases) subtypes of CHL, as well as 5 reactive lymph node controls.

  Study EGAS00001005541

• The Normal Human Tissue Sequencing Project: Non-Diseased, Non-Malignant Tissues

  The Normal Human Tissue Sequencing Project provides RNA expression and DNA methylation data from normal (non-diseased) human tissues. This data set from a variety of source tissue is a valuable resource for human disease studies.

  Study phs000819

• Pre-clinical evolution of haematological malignancies_TGS

  Leukaemia and related blood cancers occur due to genetic changes that typically accumulate over many years. This study will employ targeted next-generation sequencing to retrace the preclinical evolution of several types of haematological malignancy. Investigating the progression of the earliest pre-malignant ancestral clones promises to offer valuable insights into early leukaemia evolution and therapeutic vulnerabilities of leukaemia stem cells.

  Dataset EGAD00001006424