16624 results for "sec+and+unspecified+malignant+neoplasm"

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• McGill EMC Release 4 in tissue "venous blood" for cell type "T cell"

  McGill EMC Release 4 in tissue "venous blood" for cell type "T cell"

  Dataset EGAD00001001283

• scRNAseq of ovarian cancer patient derived organoids

  scRNAseq of ovarian cancer patient derived organoids with or without estradiol

  Dataset EGAD50000002058

• WGS of Multiple Myeloma/MGUS/SMM cases (germline) - VCF files (SNPs)

  WGS - PCR-free library preparation (whole blood gDNA), paired-end (2x100bp) sequencing on DNBseq sequencing platform (BGI) Number of samples: 26

  Dataset EGAD50000001800

• Transcriptomic characterization of the histopathological growth patterns in breast cancer liver metastases

  20 fastq files of RNA-sequencing of the 2 main histopathological grow patterns observed in liver metastases.

  Dataset EGAD50000000331

• Deep amplicon sequencing to infer malignant clonal populations for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  A total of 192 positions per patient were deeply sequenced in each corresponding tumor sample (including 4 experimental controls and SNVs predicted to originate at each node of the sample phylogeny, see Zhang et al. for details). Genomic DNA templates were used as starting material to generate PCR products. PCR was set up using Phusion DNA polymerase according to the manufacturer’s specifications. The standard PCR conditions used were an initial denaturation at 98C for 30 seconds, followed by 35 cycles of 98C for 10 seconds, 60C for 15 seconds and 72C for 8 seconds, and a final extension at 72C for 10 minutes. PCR products were cleaned up using PCRClean DX beads. Amplicons were pooled by template for sequencing sample preparation. Sample preparation involved a second round of amplification using Phusion DNA polymerase with 6 PCR cycles, with primers specified in Zhang et al. DNA quality was assessed using the Caliper LabChip GX HighSensitivity Assay and DNA quantity was measured using a Qubit dsDNA HS assay kit on a Qubit fluorometer. The indexed libraries were pooled together and sequenced on the Illumina NextSeq500 platform with paired-end 150bp reads using v2 chemistry reagents.

  Dataset EGAD00001003986

• The mutational landscape of skin tumours in CYLD cutaneous syndrome determined

  Patients with germline mutations in CYLD can develop hundreds of benign skin tumours called cylindromas. The development of multiple tumours within a single patient at sun-protected and sun-exposed sites, varying tumour histological patterns and grades of malignancy allow for the testing of several genetic hypothesis in relation to cutaneous carcinogenesis. By adopting the unprecedented approach of whole genome sequencing of multiple benign skin tumours within individuals in multigenerational families, we set out to study the impact of mutational diversity on models such as multistep carcinogenesis as well as non-sequential carcinogenesis. Using non-negative matrix factorisation (NMF) to discover mutational signatures, we found distinct mutational signatures in identical benign tumours (N=2 patients; n=11 tumours) at sun exposed and sun protected skin tumours within a mother and her daughter. We found recurrent mutations in epigenetic modifying genes in CCS tumours which are known to have an oncogenic dependency on Wnt signalling. We also demonstrate that cutaneous tumours that metastasize to the lung carry a a UV signature, supporting the origin from the skin. Distinct malignant tumours, such as BCC and malignant spiradenocarcinoma carried unique driver mutations. These findings add new dimensions to the existing paradigms of UV-induced skin cancer and highlight the utility of studying rare disease to gain novel insights into genetic mechanisms of tumour formation.

  Dataset EGAD00001004573

• Whole genome sequencing of GM09237 cells with and without folate depletion

  Two DNA samples extracted from GM09237 cell line cultured with either normal medium or medium with no folic acid for 5 days were sequenced using the BGISEQ500 platform (BGI whole genome 100 bp paired-end sequencing 60x) as well as PacBio Sequel long read sequencing.

  Dataset EGAD00001007732

• Targeted capture sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Targeted capture sequencing for 366 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study and 29 samples from a previously uploaded dataset.

  Dataset EGAD50000001364

• RNA sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  RNA-seq for 26 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study, and 32 samples from a previously uploaded dataset.

  Dataset EGAD50000001365

• Whole genome sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Whole genome sequencing for 10 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study, and 6 samples from a previously uploaded dataset.

  Dataset EGAD50000001366

• BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples (DLBCL-panel)

  This dataset contains BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples for cases 2, 3, 4 and 13. The sequencing panel used is a DLBCL-oriented panel containing 136 genes, described in Mozas P. et al., Hematol Oncol 2023.

  Dataset EGAD50000000802

• RNAseq and ATACseq data

  RNAseq and ATACseq data for the FMF patients and healthy control. The RNAseq data was sequenced on a BGI MGI G400 machine, with PE100 reads. ATAC-seq libraries were prepared with Illumina Nextera primers and sequenced on NovaSeq 6000 platform with 50bp paired-end sequencing, where each sample was sequenced to approximate 60 million reads.

  Dataset EGAD00001010304

• Transcriptional profiles of Kleefstra syndrome (EHMT1 and EHMT2) and healthy fibroblasts

  This dataset contains FASTQ files from RNA sequencing (RNA-seq) of fibroblasts derived from a healthy donor (control), a patient with Kleefstra syndrome (KSP), and a patient carrying a pathogenic variant in EHMT2 (P2). Ribosomal RNA was removed using an RNase H–based depletion method, and strand-specific libraries were prepared for paired-end sequencing on the MGI DNBSEQ PE100 platform.

  Dataset EGAD50000002343

• 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

• Pre-clinical evolution of haematological malignancies_WGS

  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 EGAD00001006423

• The University of Hong Kong Gastric Cancer Organoids RHO Signaling Study

  Objective: Cell-cell (CC) and cell-matrix (CM) adhesions are essential for epithelial cell survival, yet dissociation-induced apoptosis is frequently circumvented in malignant cells. Design: We explored CC and CM dependence in 58 gastric cancer (GC) organoids by withdrawing either ROCK inhibitor, matrix, or both, to evaluate their tumorigenic potential in terms of apoptosis resistance, correlation with oncogenic driver mutations and clinical behaviour. We performed mechanistic studies to determine the role of diffuse-type GC drivers: ARHGAP fusions, RHOA, and CDH1, in modulating CC (CCi) or CM (CMi) adhesion independence. Results: 97% of the tumour organoids were CMi, 66% were CCi and 52% were resistant to double withdrawal (CCi/CMi), while normal organoids were neither CMi nor CCi. Clinically, the CCi/CMi phenotype was associated with an infiltrative tumour edge and advanced tumour stage. Moreover, the CCi/CMi transcriptome signature was associated with poor patient survival when applied to 3 public GC datasets. CCi/CMi and CCi phenotypes were enriched in diffuse-type GC organoids, especially in those with oncogenic driver perturbation of RHO signalling via RHOA mutation or ARHGAP fusions. Inducible knockout of ARHGAP fusions in CCi/CMi tumour organoids led to re-sensitization to CC/CM dissociation-induced apoptosis, upregulation of focal adhesion and tight junction genes, partial reversion to a more normal cystic phenotype, and inhibited xenograft formation. Normal gastric organoids engineered with CDH1 or RHOA mutations became CMi or CCi, respectively. Conclusions: The CCi/CMi phenotype has a critical role in malignant transformation and tumour progression, offering new mechanistic information on RHO-ROCK pathway inhibition that contributes to GC pathogenicity.

  Study EGAS00001006252

• GBM-Space: Spatial Transcriptomic Profiling of Glioblastoma (10x Genomics - Visium)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. The datasets in this study include sequencing data from Visium spatial transcriptomic (10x Genomics) profiling of these tumours.

  Dataset EGAD00001015527

• FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003508

• FASTQ files of total RNA-Seq data from the POPS SGA (Small for Gestational Age) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003507

• 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

• MPNST - DLPplus single nucleus DNAseq

  Understanding the spatial and temporal dynamics of tumour evolution is crucial for determining the drivers of cancer progression. Here, we comprehensively profile a primary malignant peripheral nerve sheath tumour (MPNST) and its recurrence with a multi-omic and spatial approach at single-cell resolution. Leveraging the extensive heterogeneity in copy number aberrations (CNAs) as a native barcoding system, we fully resolve the evolutionary tree of this tumour revealing multi-furcations suggestive of ongoing chromosomal instability. We show gene dosage effects contribute to phenotypic diversity and are predominantly linear with the exception of FOS in a specific subclone. Using laser capture microdissection, we performed spatial lineage tracing in a human tumour, elucidating the relationship between local expansions and interactions between tumour cells and the microenvironment.

  Study EGAS50000001788

• MPNST - 10X Visium spatial transcriptomics

  Understanding the spatial and temporal dynamics of tumour evolution is crucial for determining the drivers of cancer progression. Here, we comprehensively profile a primary malignant peripheral nerve sheath tumour (MPNST) and its recurrence with a multi-omic and spatial approach at single-cell resolution. Leveraging the extensive heterogeneity in copy number aberrations (CNAs) as a native barcoding system, we fully resolve the evolutionary tree of this tumour revealing multi-furcations suggestive of ongoing chromosomal instability. We show gene dosage effects contribute to phenotypic diversity and are predominantly linear with the exception of FOS in a specific subclone. Using laser capture microdissection, we performed spatial lineage tracing in a human tumour, elucidating the relationship between local expansions and interactions between tumour cells and the microenvironment.

  Study EGAS50000001791

• MPNST - 10X single nucleus DNAseq

  Understanding the spatial and temporal dynamics of tumour evolution is crucial for determining the drivers of cancer progression. Here, we comprehensively profile a primary malignant peripheral nerve sheath tumour (MPNST) and its recurrence with a multi-omic and spatial approach at single-cell resolution. Leveraging the extensive heterogeneity in copy number aberrations (CNAs) as a native barcoding system, we fully resolve the evolutionary tree of this tumour revealing multi-furcations suggestive of ongoing chromosomal instability. We show gene dosage effects contribute to phenotypic diversity and are predominantly linear with the exception of FOS in a specific subclone. Using laser capture microdissection, we performed spatial lineage tracing in a human tumour, elucidating the relationship between local expansions and interactions between tumour cells and the microenvironment.

  Study EGAS50000001790